**Supercapacitor Applications**

[11] H.R. Yu, S. Cho, M.J. Jung and Y.S. Lee, Microporous and Mesoporous Materials, 2013,

[12] J.J. Rueda‐Márquez, M. Sillanpää, P. Pocostales, A. Acevedo and M.A. Manzano, Water

[13] Y.W. Wang, Y.S. Wei and J.X. Liu, Journal of Hazardous Materials, 2009, 169, 680‐684. [14] Y. Xiao, C. Long, M.T. Zheng, H.W. Dong, B.F. Lei, H.R. Zhang and Y.L. Liu, Chinese

[15] X.J. He, P.H. Ling, M.X. Yu, X.T. Wang, X.Y. Zhang and M.D. Zheng, Electrochimica

[16] S.J. Han, Y.H. Kim, K.S. Kim and S.J. Park, Current Applied Physics, 2012, 12, 1039‐1044. [17] N.D. Kim, W. Kim, J.B. Joo, S. Oh, P. Kim, Y. Kim and J. Yi, Journal of Power Sources,

[19] M.X. Wang, C.Y. Wang, M.M. Chen, Y.S. Wang, Z.Q. Shi, X. Du, T.Q. Li and Z.J. Hu,

[20] X. Du, C.Y. Wang, M.M. Chen, Y. Jiao and J. Wang, Journal of Physical Chemistry C,

[21] H.J. Shen, E.H. Liu, X.X. Xiang, Z.Z. Huang, Y.Y. Tian, Y.H. Wu, Z.L. Wu and H. Xie,

[22] M.B. Wu, R.C. Li, X.J. He, H.B. Zhang, W.B. Sui and M.H. Tan, New Carbon Materials,

[23] X.X. Xiang, E.H. Liu, Z.Z. Huang, H.J. Shen, Y.Y. Tian, C.Y. Xiao, J.J. Yang and Z.H. Mao,

[24] D.S. Patil, S.A. Pawar, R.S. Devan, Y.R. Ma, W.R. Bae, J.H. Kim and P.S. Patil, Materials

[25] A. Davies and A. Yu, Canadian Journal of Chemical Engineering, 2011, 89, 1342‐1357. [26] M.B. Wu, P.P. Ai, M.H. Tan, B. Jiang, Y.P. Li, J.T. Zhang, W.T. Wu, Z.T. Li, Q.H. Zhang

[27] J.L. Chang, Z.Y. Gao, X.R. Wang, D.P. Wu, F. Xu, X. Wang, Y.M. Guo and K. Jiang,

172, 131‐135.

118 Supercapacitor Design and Applications

Research, 2015, 71, 85‐96.

Acta, 2013, 105, 635‐641.

2008, 180, 671‐675.

2009, 113, 2643‐2646.

2015, 30, 86‐91.

Letters, 2014, 117, 248‐251.

Electrochimica Acta, 2015, 157, 290‐298.

Chemical Letters, 2014, 25, 865‐868.

[18] L. Wei and G. Yushin, Carbon, 2011, 49, 4830‐4838.

Materials Research Bulletin, 2012, 47, 662‐666.

Journal of Solid State Electrochemistry, 2011, 15, 2667‐2674.

and X.J. He, Chemical Engineering Journal, 2014, 245, 166‐172.

[28] I. Oh, M. Kim and J. Kim, Microelectronics Reliability, 2015, 55, 114‐122.

New Carbon Materials, 2010, 25, 285‐290.

**Chapter 7 Provisional chapter**

#### **Development and On‐Orbit Demonstration of Lithium‐ Ion Capacitor‐Based Power System for Small Spacecraft Development and On**‐**Orbit Demonstration of Lithium**‐**Ion Capacitor**‐**Based Power System for Small Spacecraft**

Masatoshi Uno and Akio Kukita Masatoshi Uno and Akio Kukita

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64966

#### **Abstract**

Lithium‐ion capacitors (LICs) offer higher energy density and specific energy than do traditional electric double‐layer capacitors (EDLCs). In spacecraft power systems where traditional lithium‐ion batteries (LIBs) have been used with shallow depth of discharge (DoD) in order to achieve long‐cycle life, LICs would potentially be an alternative to secondary batteries. Firstly, this chapter presents the quantitative comparison between the LIB‐ and LIC‐based spacecraft power system from the viewpoint of system mass. On the basis of the potential suggested by the comparison, we have been developing the technology demonstration platform named "NESSIE" that contains the LIC pouch cell as one of its major demonstration missions. NESSIE was successfully launched with the main satellite HISAKI on September 2013. This chapter also presents the development of the LIC pouch cell for NESSIE and its experimental (or ground test) and on‐orbit operation data.

**Keywords:** cycle life testing, lithium‐ion capacitor, pouch cell, spacecraft power sys‐ tem, vacuum tolerance

### **1. Introduction**

Applications of secondary battery‐based energy storage are rapidly expanding from portable electronic devices to large‐scale systems, including electric vehicles and grid‐connected applications. Among various secondary battery chemistries, lithium‐ion batteries (LIBs) are the most promising and viable for portable and vehicular applications thanks to their highest energy density and specific energy. Vigorous research and development efforts for increased energy density and extended service life are underway.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Meanwhile, supercapacitors (SCs), formally known as electric double‐layer capacitors (EDLCs), are also an attractive energy storage device that plays an important role in various scenes. Thanks to their energy storage mechanism utilizing the double‐layer capacitance on porous‐activated carbon electrodes, EDLCs offer remarkable advantages over traditional secondary batteries in terms of cycle life, power capability, safety, and allowable temperature range. However, their low‐energy density property is generally considered as a major drawback to be used as an alternative energy storage source to traditional secondary batteries. Hence, applications of EDLCs are chiefly limited to hybrid energy storage applications where EDLCs play a role of the high‐power energy buffer that complements the main energy sources, such as secondary batteries and fuel cells.

To cope with the drawback of the low‐energy density of EDLCs, lithium‐ion capacitors (LICs) have been developed and commercialized by several manufacturers. LICs are basically a hybrid electrochemical capacitor combining double‐layer capacitance and lithium intercala‐ tion for energy storage mechanism, and they offer the higher specific energy than EDLC without sacrificing the major benefits of EDLCs. LICs have been drawing significant attentions in vehicular and industry applications where high‐power energy buffers are indispensable. Despite the increased energy density property, there is still a huge gap between LICs and secondary batteries.

**Figure 1.** EDLC‐based uninterruptible power supplies (UPSs).

However, once the excellent long‐cycle life performance of EDLCs and LICs is factored in, it drives expectation that EDLCs and LICs would be an alternative energy storage source to traditional secondary batteries in certain applications. For example, EDLC‐based uninterrup‐ tible power supplies (UPSs) have been commercialized [1], as shown in **Figure 1**, as mainte‐ nance‐free alternatives aiming for infrastructure applications where traditional lead‐acid batteries need to be replaced with new ones for every few years. Another potential application is a spacecraft power system where long‐life energy storage sources are essential. In the previous study [2, 3], systematic cycle life testing emulating low‐Earth‐orbit (LEO) satellite conditions has been performed for EDLCs and LICs, and the results demonstrated that excellent cycle life performance can be expected for cycling conditions for LEO satellites.

For spacecraft applications where specific energy is of great importance, LICs are undoubtedly superior to EDLCs. Despite the great potential suggested in the laboratory cycle life testing, LICs had not been used in practical space applications. In order to demonstrate the LIC performance in practical on‐orbit conditions, we developed the technology demonstration platform named 'NESSIE (NExt‐generation Small Satellite Instrument for Electric power systems)' containing an LIC pouch cell as one of its major components to be demonstrated on orbit; NESSIE's major missions are (1) on‐orbit demonstration for the LIC cells and (2) on‐orbit demonstration for high‐efficiency thin‐film solar cells. NESSIE was embedded in the main satellite named "HISAKI", the Spectroscopic Planet Observatory for Recognition of Interaction of Atmosphere (see **Figure 2**) and was launched on September 14, 2013.

**Figure 2.** An image of HISAKI.

Meanwhile, supercapacitors (SCs), formally known as electric double‐layer capacitors (EDLCs), are also an attractive energy storage device that plays an important role in various scenes. Thanks to their energy storage mechanism utilizing the double‐layer capacitance on porous‐activated carbon electrodes, EDLCs offer remarkable advantages over traditional secondary batteries in terms of cycle life, power capability, safety, and allowable temperature range. However, their low‐energy density property is generally considered as a major drawback to be used as an alternative energy storage source to traditional secondary batteries. Hence, applications of EDLCs are chiefly limited to hybrid energy storage applications where EDLCs play a role of the high‐power energy buffer that complements the main energy sources,

To cope with the drawback of the low‐energy density of EDLCs, lithium‐ion capacitors (LICs) have been developed and commercialized by several manufacturers. LICs are basically a hybrid electrochemical capacitor combining double‐layer capacitance and lithium intercala‐ tion for energy storage mechanism, and they offer the higher specific energy than EDLC without sacrificing the major benefits of EDLCs. LICs have been drawing significant attentions in vehicular and industry applications where high‐power energy buffers are indispensable. Despite the increased energy density property, there is still a huge gap between LICs and

However, once the excellent long‐cycle life performance of EDLCs and LICs is factored in, it drives expectation that EDLCs and LICs would be an alternative energy storage source to traditional secondary batteries in certain applications. For example, EDLC‐based uninterrup‐ tible power supplies (UPSs) have been commercialized [1], as shown in **Figure 1**, as mainte‐ nance‐free alternatives aiming for infrastructure applications where traditional lead‐acid

such as secondary batteries and fuel cells.

122 Supercapacitor Design and Applications

**Figure 1.** EDLC‐based uninterruptible power supplies (UPSs).

secondary batteries.

In this chapter, the quantitative comparison between LIB‐ and LIC‐based spacecraft power systems is performed in terms of system mass. This chapter also presents the development of the LIC pouch cell for NESSIE and its experimental (or ground test) and on‐orbit operation data.

## **2. Cycle life of LICs**

In the previous study [4], cycle life testing emulating LEO spacecraft conditions was per‐ formed for LICs, and capacitance retentions of LICs were compared to those of LIBs under the same temperature conditions, as shown in **Figure 3**. The capacitance retention of the LIB with the shallow DoD of 20% dropped to approximately 70% at 10,000 cycles, which is equivalent to approximately 2‐year operation, while that of LICs was still greater than 95%. Furthermore, different from LIBs whose retention trends were dependent on DoD, the LICs showed DoD‐independent trends.

**Figure 3.** Capacitance retention trends of LIBs and LICs [4].

The accelerated ageing testing and the cycle life prediction model for LICs were also investi‐ gated in the previous study [3]. LIC cells were cycled at various temperatures in the system‐ atically designed cycle test matrix. The activation energies of degradation ratios of LIC cells were calculated using the Arrhenius equation, whereupon ageing acceleration factors were determined. The experimental and predicted capacitance retention trends matched satisfac‐ torily, and hence, the established cycle life prediction model was verified. According to the reported results in [3], LICs are expected to operate even longer than millions of cycles at temperature lower than 10°C.

The mission life of the main satellite HISAKI was 1 year, and therefore, the cycle life of LICs reported in the previous studies was adequate for NESSIE. However, the cycle life testing reported in the previous study was performed under laboratory conditions, leaving the investigation of tolerance against space environment, such as vacuum, vibration, and radia‐ tion, as issues to be cleared. Section 4 discusses these issues in detail.

### **3. LIC‐ and LIB‐based power system comparison**

#### **3.1. Specific energy**

Cycle life performance of traditional secondary batteries is greatly dependent on DoD. In general, secondary batteries for LEO satellites are operated with DoD shallower than 40% in order to meet the typical cycle life requirement of 30,000 cycles that is equivalent to approxi‐ mately 5.7 years on‐orbit operation. In other words, the net specific energy of secondary batteries is far lower than their rated specific energy because of the shallow DoD operation. Specific energies as well as net specific energies of various energy storage devices are com‐ pared in **Table 1**. Although LIBs offer the highest specific energy of 150 Wh/kg, their net specific energy drops to as low as 60 Wh/kg with DoD of <40%.


**Table 1.** Specific energy and net specific energy of energy storage devices.

Furthermore, different from LIBs whose retention trends were dependent on DoD, the LICs

The accelerated ageing testing and the cycle life prediction model for LICs were also investi‐ gated in the previous study [3]. LIC cells were cycled at various temperatures in the system‐ atically designed cycle test matrix. The activation energies of degradation ratios of LIC cells were calculated using the Arrhenius equation, whereupon ageing acceleration factors were determined. The experimental and predicted capacitance retention trends matched satisfac‐ torily, and hence, the established cycle life prediction model was verified. According to the reported results in [3], LICs are expected to operate even longer than millions of cycles at

The mission life of the main satellite HISAKI was 1 year, and therefore, the cycle life of LICs reported in the previous studies was adequate for NESSIE. However, the cycle life testing reported in the previous study was performed under laboratory conditions, leaving the investigation of tolerance against space environment, such as vacuum, vibration, and radia‐

Cycle life performance of traditional secondary batteries is greatly dependent on DoD. In general, secondary batteries for LEO satellites are operated with DoD shallower than 40% in

tion, as issues to be cleared. Section 4 discusses these issues in detail.

**3. LIC‐ and LIB‐based power system comparison**

showed DoD‐independent trends.

124 Supercapacitor Design and Applications

**Figure 3.** Capacitance retention trends of LIBs and LICs [4].

temperature lower than 10°C.

**3.1. Specific energy**

EDLCs and LICs, on the other hand, offer excellent cycle life performance that is insensitive to DoD conditions, allowing deep DoD operations. In the case of the 80% DoD operation for EDLCs and LICs, for example, their net specific energies are <8 Wh/kg and <24 Wh/kg, respectively, greatly bridging the gap in terms of net specific energy.

#### **3.2. Photovoltaic array reduction by constant power charging scheme**

A charging profiles of a 10‐Wh LIB cell with a constant‐current‐constant‐voltage (CC‐CV) charging scheme are shown in **Figure 4(a)** as typical characteristics. The charging power peaks at the end of the CC charging period (or at the beginning of the CV charging period), when both the current and voltage become maximum. The chargeable state of charge (SoC) in the CC charging period is merely 60%, and the rest 40% is charged with CV charging. This characteristic indicates that the CV charging is indispensable for LIBs to reach high SoC. In typical LEO satellites, photovoltaic (PV) arrays are designed to be capable of supplying not only load power but also this peak charging power.

Different from LIBs mentioned above, LICs and EDLCs can be charged to nearly 100% SoC without CV charging because of their low‐impedance properties. A charging profiles of a 10‐ Wh LIC cell with the constant‐power (CP) charging scheme, instead of CC‐CV charging scheme, are shown in **Figure 4(b)**. The charging power with the CP charging scheme is constant, and its peak value is substantially lower than that with the CC‐CV charging scheme. This reduction in peak charging power contributes to the reduction in area and mass of PV arrays, as will be exemplified in Section 3.6.

**Figure 4.** Comparison between (a) CC‐CV charging and (b) CP charging schemes.

#### **3.3. Power system using LIC**

An unregulated bus system using an array power regulator (APR), as shown in **Figure 5(a)**, is mainstream for low‐ to medium‐scale spacecraft power systems using an LIB‐based energy storage. The LIB can be directory connected to the load (or bus) because of the relatively float voltage characteristics. The APR plays a role of battery charging, and a load power is supplied by the LIB and/or APR.

**Figure 5.** Spacecraft power system architectures for (a) LIB‐ and (b) LIC‐based systems.

On the other hand, an LIC cannot be directory connected to the bus because of the relatively large‐voltage variation (see **Figure 4(b)**), and therefore, a charge‐discharge regulator (CDR) is necessary. An LIC‐based power system using a shunt dissipator as a bus voltage regulator is shown in **Figure 5(b)**. In the following subsections, power systems shown in **Figure 5** are compared from the viewpoint of mass.

#### **3.4. Mass of LIB‐based power system**

(a)

126 Supercapacitor Design and Applications

(b)

**Figure 4.** Comparison between (a) CC‐CV charging and (b) CP charging schemes.

An unregulated bus system using an array power regulator (APR), as shown in **Figure 5(a)**, is mainstream for low‐ to medium‐scale spacecraft power systems using an LIB‐based energy storage. The LIB can be directory connected to the load (or bus) because of the relatively float

**3.3. Power system using LIC**

A single charge‐discharge cycle consists of the sun and eclipse periods *T*sun and *T*eclipse, respec‐ tively. The discharged energy during the eclipse period *Edis\_LIB* is

$$E\_{\rm dis\_{\rm dis\_{\rm \\_LIB}}} = P\_{\rm load} T\_{\rm collapses} \tag{1}$$

where *Pload* is the load power.

Batteries contain not only cells but also mechanical structural support that represents nearly 20% increase in mass over that of cells. Now, the ratio of the mechanical support to cells is defined as *A*. The mass of the LIB, *MLIB*, is expressed as

$$M\_{LIB} = \frac{E\_{dis\\_LIB} \left(1 + A\right)}{DS\_{LIB\\_cell}} \tag{2}$$

where *D* is the DoD, and *SLIB\_cell* is the specific energy of LIB cells.

Let *Vave* be the average voltage of the LIB during discharging. The capacity of the LIB, *CLIB*, can be determined as

$$\mathbf{C}\_{LIB} = \frac{E\_{dis\\_LIB}}{DV\_{ave}} \tag{3}$$

Introducing the charge rate (also known as C‐rate) as *Rcha*, the charge current for the LIB, *Icha*, is yielded as

$$I\_{cha} = \mathbb{C}\_{LIB} \mathbb{R}\_{cha} \tag{4}$$

The value of *Rcha* can be determined from the charge‐discharge ratio that is defined as

$$R\_{C/D} = \frac{R\_{cha} T\_{sun}}{D} \tag{5}$$

Generally, a typical value of *RC/D* for LEO spacecraft is 1.25 [5].

The maximum charging power (*Pcha\_LIB*) at the end of the CC charging or at the beginning of the CV charging, at which the LIB voltage is as high as *Vcha*, is

$$P\_{\text{cha\\_LIB}} = V\_{\text{cha}} I\_{\text{cha}} \tag{6}$$

The mass of the PV arrays in the LIB‐based power system, *MPV\_LIB*, can be determined to be

$$M\_{PV\\_LIB} = \frac{P\_{load} + P\_{cla\\_LIB}}{\eta\_{APR}\rho\_{PV}}\tag{7}$$

where *ηAPR* is the power conversion efficiency of the APR and *ρPV* is the specific power of the PV array.

The mass of the power conditioning system *MPCS\_LIB*, which is equal to the mass of the APR in the LIB‐based power system, is expressed as

$$M\_{\rm{PCS\\_LIB}} = m\_{\rm{APR}} \left( P\_{\rm{cha\\_LIB}} + P\_{\rm{load}} \right) \tag{8}$$

where *mAPR* is the mass/watt coefficient of the APR.

From Eqs. (2), (7), and (8), the total mass of the LIB‐based power system *MLIB\_system* is obtained as

Development and On‐Orbit Demonstration of Lithium‐Ion Capacitor‐Based Power System for Small Spacecraft http://dx.doi.org/10.5772/64966 129

$$M\_{\rm LIB\\_system} = M\_{\rm LIB} + M\_{\rm PV\\_L\&B} + M\_{\rm PCS\\_L\&B} \tag{9}$$

#### **3.5. Mass of LIC‐based power system**

Let *Vave* be the average voltage of the LIB during discharging. The capacity of the LIB, *CLIB*, can

*dis LIB* \_

Introducing the charge rate (also known as C‐rate) as *Rcha*, the charge current for the LIB, *Icha*,

*cha sun*

The maximum charging power (*Pcha\_LIB*) at the end of the CC charging or at the beginning of

The mass of the PV arrays in the LIB‐based power system, *MPV\_LIB*, can be determined to be

*P P*

where *ηAPR* is the power conversion efficiency of the APR and *ρPV* is the specific power of the

The mass of the power conditioning system *MPCS\_LIB*, which is equal to the mass of the APR in

From Eqs. (2), (7), and (8), the total mass of the LIB‐based power system *MLIB\_system* is obtained

h r \_

*load cha LIB*

*APR PV*

*E*

The value of *Rcha* can be determined from the charge‐discharge ratio that is defined as

/

Generally, a typical value of *RC/D* for LEO spacecraft is 1.25 [5].

the CV charging, at which the LIB voltage is as high as *Vcha*, is

\_

*M*

the LIB‐based power system, is expressed as

where *mAPR* is the mass/watt coefficient of the APR.

*PV LIB*

*C D R T <sup>R</sup>*

*ave*

*DV* <sup>=</sup> (3)

*cha LIB cha I CR* = (4)

*<sup>D</sup>* <sup>=</sup> (5)

*P VI cha LIB cha cha* \_ = (6)

<sup>+</sup> <sup>=</sup> (7)

*M mP P PCS LIB APR cha LIB load* \_ \_ = + ( ) (8)

*LIB*

*C*

be determined as

128 Supercapacitor Design and Applications

is yielded as

PV array.

as

Let *ηCDR* be the power conversion efficiency of the CDR. The discharged energy of the LIC *Edis\_LIC* can be expressed as

$$E\_{dis\\_LIC} = \frac{P\_{load}T\_{cellps}}{\eta\_{CDR}}\tag{10}$$

With the specific energy of the LIC cells *SLIC\_cell*, the mass of the LIC, *MLIC*, can be represented as

$$\mathcal{M}\_{\text{LIC}} = \frac{E\_{\text{dis\\_LIC}} \left(1 + A\right)}{D \mathcal{S}\_{\text{LIC\\_coll}}} \tag{11}$$

Assuming that the LIC is fully charged at the end of the sun period, the power demanded for the PV array from the LIC, *Pcha\_LIC*, is expressed as

$$P\_{chu\\_LIC} = \frac{E\_{dis\\_LIC}}{\eta\_{CDR}T\_{sun}}\tag{12}$$

The mass of the PV arrays in the LIC‐based power system, *MPV\_LIC*, is

$$\mathcal{M}\_{\text{PV\\_LIC}} = \frac{P\_{\text{load}} + P\_{\text{char\\_LIC}}}{\mathcal{P}\_{\text{PV}}} \tag{13}$$

Assuming the shunt dissipator is designed to be capable of the sum of *Pload* and *Pcha\_LIC*, the mass of the PCS in the LIC‐based power system, *MPCS\_LIC*, is given by

$$M\_{PCS\\_LIC} = P\_{load}m\_{CDR} + m\_{shunt} \left( P\_{cha\\_LIC} + P\_{load} \right) \tag{14}$$

where *mCDR* and *mshunt* are the mass/watt coefficient of the CDR and shunt dissipator, respec‐ tively.

From Eqs. (11), (13), and (14), the total mass of the LIC‐based power system *MLIC\_system* is determined as

$$M\_{L\text{C\\_system}} = M\_{L\text{C}} + M\_{PV\\_L\text{C}} + M\_{P\text{CS\\_L\text{C}}} \tag{15}$$

#### **3.6. System mass comparison**

The LIB‐ and LIC‐based power systems, shown in **Figure 5**, are quantitatively compared using the parameters listed in **Table 2**. These values were determined according to the literature [6].


**Table 2.** Parameters used for mass comparison.

**Figure 6** depicts the system mass of 1‐kW LIB‐ and LIC‐based power systems, with nominal specific energies (*SLIB\_cell* = 150 Wh/kg and *SLIC\_cell* = 30 Wh/kg) ±20% variation, as a function of DoD. As mentioned earlier, in order for LIBs to meet the typical cycle life requirement of 30,000 cycles, DoD should be set as shallow as 40% to mitigate cycling‐induced degradation. The mass of the LIB‐based power system with 40% DoD is around 50 kg and lighter than the LIC‐based system, indicating the traditional LIB‐based power system is superior for the typical 30,000‐ cycle life requirement from the viewpoint of system mass. For longer cycle life requirement, on the other hand, LIBs have to be cycled with even shallower DoD, and therefore, the mass of the LIB‐based power system is prone to sharp increase, as can be found around 20% DoD in **Figure 6**. Hence, the LIB‐based system with shallow DoD competes with the LIC‐based system. The mass of the LIB‐based system with DoD of 15%, for example, is around 70 kg and is comparable with that of the LIC‐based system with 60% DoD.

Development and On‐Orbit Demonstration of Lithium‐Ion Capacitor‐Based Power System for Small Spacecraft http://dx.doi.org/10.5772/64966 131

**Figure 6.** Mass of LIB‐ and LIC‐based power systems as a function of DoD.

=+ + *M MM M LIC system LIC PV LIC PCS LIC* \_ \_ \_ (15)

The LIB‐ and LIC‐based power systems, shown in **Figure 5**, are quantitatively compared using the parameters listed in **Table 2**. These values were determined according to the literature [6].

**Parameter Symbol Value** Load power *Pload* 1000 W

Sun period *Tsun* 1 h Eclipse period *Teclipse* 0.5 h C/D ratio (for LIB only) *RC/D* 1.25 Charge voltage (LIB only) *Vcha* 28.7 V Average discharge voltage (LIB only) *Vave* 25.9 V Mass ratio of mechanical structural supports to cells *A* 20%

Specific power of PV array *ρPV* 60 W/kg

Mass/watt coefficient of array power regulator *mAPR* 4 kg/kW Mass/watt coefficient of charge/discharge regulator *mCDR* 4 kg/kW Mass/watt coefficient of shunt dissipator *mShunt* 2 kg/kW

**Figure 6** depicts the system mass of 1‐kW LIB‐ and LIC‐based power systems, with nominal specific energies (*SLIB\_cell* = 150 Wh/kg and *SLIC\_cell* = 30 Wh/kg) ±20% variation, as a function of DoD. As mentioned earlier, in order for LIBs to meet the typical cycle life requirement of 30,000 cycles, DoD should be set as shallow as 40% to mitigate cycling‐induced degradation. The mass of the LIB‐based power system with 40% DoD is around 50 kg and lighter than the LIC‐based system, indicating the traditional LIB‐based power system is superior for the typical 30,000‐ cycle life requirement from the viewpoint of system mass. For longer cycle life requirement, on the other hand, LIBs have to be cycled with even shallower DoD, and therefore, the mass of the LIB‐based power system is prone to sharp increase, as can be found around 20% DoD in **Figure 6**. Hence, the LIB‐based system with shallow DoD competes with the LIC‐based system. The mass of the LIB‐based system with DoD of 15%, for example, is around 70 kg and

is comparable with that of the LIC‐based system with 60% DoD.

Efficiency of array power regulator *ηAPR* 90% Efficiency of charge/discharge regulator *ηCDR* 90%

**3.6. System mass comparison**

130 Supercapacitor Design and Applications

**Table 2.** Parameters used for mass comparison.

**Figure 7.** Mass breakdown of LIB‐ and LIC‐based power systems.

The mass breakdown of the LIB‐ and LIC‐based power systems with the nominal specific energies of *SLIB\_cell* = 150 Wh/kg and *SLIC\_cell* = 30 Wh/kg are compared in **Figure 7**. In the LIC‐ based power systems, the LIC accounted for greater than half the total mass of the systems. Meanwhile, thanks to the CP charging scheme introduced in Section 3.2, the mass of the PV array in the LIC‐based system can be reduced compared to that in the LIB‐based system. The total mass of the LIC‐based system with DoD of 60–80% is comparable with that of LIB‐based system with DoD of 15–20%, suggesting that LICs would be an alternative energy storage source to LIBs for applications needing long‐cycle life. Other benefits, such as wider opera‐ tional temperature range of LICs, would further improve the likelihood of LICs being an alternative to traditional LIBs.

## **4. Development of LIC for NESSIE**

#### **4.1. Vacuum tolerance of LIC pouch cell**

Needless to say, there is no air in the space, and therefore, components for spacecraft must be vacuum‐tolerant. In general, secondary batteries for spacecraft power systems are reinforced by metal‐housing so as to increase the ruggedness for shock and vibration during launch and tolerance against vacuum in space. In the previous developmental work, electrical character‐ istics of lithium‐ion pouch cells were investigated [7]. The cells swelled in vacuum, and the performance of LIB pouch cells significantly deteriorated. In order to improve the vacuum tolerance, LIB pouch cells were potted with epoxy resin in an aluminium‐housing. However, this reinforcement adversely increases the mass and volume of the battery, resulting in decreased specific energy, and it neutralizes the benefit of pouch cells of high specific energy.

**Figure 8.** LIC pouch cells under (a) normal pressure and (b) vacuum.

Although both the resin‐ and metal‐housing‐based reinforcement were reportedly necessary for LIB pouch cells, we considered it was worth investigating whether LIC pouch cells work well in vacuum. To investigate vacuum tolerance of LIC pouch cells, we performed short‐term cycle life testing for two LIC pouch cells in a vacuum chamber. In the vacuum chamber, LIC pouch cells were placed on a thermostatic plate that was controlled to be 25°C by a coolant circulator (see **Figure 8**). As reference data, the same cycling test under a normal pressure condition was also carried out for other two LIC pouch cells. A single charge‐discharge cycle consists of 65‐min CP charging and 35‐min CC discharging with 80% DoD.

source to LIBs for applications needing long‐cycle life. Other benefits, such as wider opera‐ tional temperature range of LICs, would further improve the likelihood of LICs being an

Needless to say, there is no air in the space, and therefore, components for spacecraft must be vacuum‐tolerant. In general, secondary batteries for spacecraft power systems are reinforced by metal‐housing so as to increase the ruggedness for shock and vibration during launch and tolerance against vacuum in space. In the previous developmental work, electrical character‐ istics of lithium‐ion pouch cells were investigated [7]. The cells swelled in vacuum, and the performance of LIB pouch cells significantly deteriorated. In order to improve the vacuum tolerance, LIB pouch cells were potted with epoxy resin in an aluminium‐housing. However, this reinforcement adversely increases the mass and volume of the battery, resulting in decreased specific energy, and it neutralizes the benefit of pouch cells of high specific energy.

alternative to traditional LIBs.

132 Supercapacitor Design and Applications

**4. Development of LIC for NESSIE**

(a)

(b)

**Figure 8.** LIC pouch cells under (a) normal pressure and (b) vacuum.

**4.1. Vacuum tolerance of LIC pouch cell**

**Figure 9.** Capacitance retention trends of LICs cycled under normal pressure and vacuum conditions.

The pouch cells under normal pressure and vacuum are shown in **Figure 8(a)** and **(b)**, respectively. The LIC pouch cells swelled similarly to the LIB pouch cells reported in [7]. In spite of the significant shape deformation, the observed deterioration of cells in a vacuum was merely around 2%, compared to those under normal pressure, as shown in **Figure 9**. The capacitance retentions of cells dropped as the vacuum chamber was evacuated at the beginning of the testing (i.e., at an initial cycle). After this initial drop in capacitance retention, all cells exhibited the similar degradation trends. The measured capacitance retentions of cells in vacuum and under normal pressure at 5000th cycle (equivalent to 1‐year on‐orbit operation) were approximately 94 and 96%, respectively. **Figure 10** shows the discharge curve trends of LICs during capacitance measurement. The dischargeable time gradually shortened as cells deteriorated. However, no significant voltage decline due to an increase in internal resistance was observed, indicating that the vacuum condition did not increase an internal resistance of LIC pouch cells. The results shown in **Figures 9** and **10** suggested that bulky and heavy reinforcement using resin and/or metal‐housing would not be mandatory even though pouch cells swelled.

**Figure 10.** Discharge curve trends of LICs cycled under (a) normal pressure and (b) vacuum.

#### **4.2. LIC pouch cell for NESSIE**

NESSIE is a small demonstration platform, in which only one single LIC cell is allowed to be equipped. In general, for practical use, a plastic or metal container is used for pouch cells to be stacked and bundled to form a module. However, to reduce the mass of NESSIE, a container for the LIC pouch cell should be as simple and light as possible. In addition, although the results shown in **Figures 9** and **10** implied that LIC cells might be used without reinforcement, the swelling should be avoided because it might cause unexpected interference with other components in NESSIE. To prevent the swelling at the lightest possible measure, we developed a dedicated metal‐bracket that looks 'III‐shape', as shown in **Figure 11**. This metal bracket can suppress the swelling at a light mass. This LIC pouch cell with the metal bracket successfully passed the vibration test. The specification of the LIC cell for NESSIE is shown in **Table 3**.

Development and On‐Orbit Demonstration of Lithium‐Ion Capacitor‐Based Power System for Small Spacecraft http://dx.doi.org/10.5772/64966 135

**Figure 11.** LIC cell with metal bracket.


**Table 3.** Specification of LIC cell.

(b)

134 Supercapacitor Design and Applications

**4.2. LIC pouch cell for NESSIE**

**Figure 10.** Discharge curve trends of LICs cycled under (a) normal pressure and (b) vacuum.

NESSIE is a small demonstration platform, in which only one single LIC cell is allowed to be equipped. In general, for practical use, a plastic or metal container is used for pouch cells to be stacked and bundled to form a module. However, to reduce the mass of NESSIE, a container for the LIC pouch cell should be as simple and light as possible. In addition, although the results shown in **Figures 9** and **10** implied that LIC cells might be used without reinforcement, the swelling should be avoided because it might cause unexpected interference with other components in NESSIE. To prevent the swelling at the lightest possible measure, we developed a dedicated metal‐bracket that looks 'III‐shape', as shown in **Figure 11**. This metal bracket can suppress the swelling at a light mass. This LIC pouch cell with the metal bracket successfully passed the vibration test. The specification of the LIC cell for NESSIE is shown in **Table 3**.

## **5. Development of NESSIE**

#### **5.1. Charge‐discharge regulator for LIC**

The LIC cell is charged and discharged by a CDR that is basically a bidirectional dc‐dc converter. As explained in the previous section, LIC cells for the short‐term cycle life testing in the vacuum chamber were charged and discharged with the CP charging and CC discharg‐ ing schemes, respectively. In practical use, the bidirectional dc‐dc converter plays the role of these charging and discharging schemes.

In general, a discharging power is simply determined by loads, and the bidirectional converter operates to regulate a load voltage at a constant value (e.g., 5 V in the NESSIE's power system). On the other hand, a charging power is controlled by the bidirectional converter based on measured voltage and current. To this end, a feedback control loop including current and voltage sensors is necessary. Furthermore, the measured current and voltage values need to be multiplied to determine the charging power. In general, for small‐scale systems such as NESSIE, both circuit‐ and system‐level simplifications are of great importance to realize the miniaturized circuit and system. In other words, the current and voltage sensors as well as computational circuit for determining the charging power are desirably be eliminated from the system.

**Figure 12.** Bidirectional buck‐boost converter as charge‐discharge regulator for LIC.

**Figure 13.** Key operation waveforms and current flow directions in DCM operation.

As a simplest possible solution, we employed a bidirectional buck‐boost converter operating in the discontinuous conduction mode (DCM), with which the charging power can be automatically constant even without feedback control nor calculation of product of current and voltage. The bidirectional buck‐boost converter and its key operation waveforms as well as current flow directions in DCM are shown in **Figures 12** and **13**, respectively. Switches Q1 and Q2 are driven so that an LIC is charged and discharged, respectively. The fundamental operation of the buck‐boost converter is well known and can be found in basic textbooks, and hence, this subsection focuses on the mechanism of the CP charging. One switching cycle contains three modes, and *Toff\_b* period, during which no current flows in the converter, is unique to DCM operation; the inductor current *iL* reaches zero in the *Toff\_b* period for every switching cycle. In this chapter, the operation for charging only is explained to save page length. To charge an LIC with the buck‐boost converter shown in **Figure 12**, the switch Q1 is driven while Q2 is always off. For discharging, on the other hand, the operation is vice versa —Q2 is driven, and Q1 is always off.

In the first mode, *Ton* period, *iL* increases linearly from zero, and its inclination is equal to *Vin*/*L*. At the end of this mode, *iL* reaches its peak value of *Ipeak* expressed as

$$I\_{peak} = \frac{V\_{in} T\_{on}}{L} = \frac{V\_{in} D T\_S}{L} \tag{16}$$

where *TS* is the switching period and *D* is the duty cycle defined as *Ton*/*TS*.

**Figure 12.** Bidirectional buck‐boost converter as charge‐discharge regulator for LIC.

136 Supercapacitor Design and Applications

**Figure 13.** Key operation waveforms and current flow directions in DCM operation.

As a simplest possible solution, we employed a bidirectional buck‐boost converter operating in the discontinuous conduction mode (DCM), with which the charging power can be automatically constant even without feedback control nor calculation of product of current and voltage. The bidirectional buck‐boost converter and its key operation waveforms as well as current flow directions in DCM are shown in **Figures 12** and **13**, respectively. Switches Q1 and Q2 are driven so that an LIC is charged and discharged, respectively. The fundamental operation of the buck‐boost converter is well known and can be found in basic textbooks, and hence, this subsection focuses on the mechanism of the CP charging. One switching cycle contains three modes, and *Toff\_b* period, during which no current flows in the converter, is unique to DCM operation; the inductor current *iL* reaches zero in the *Toff\_b* period for every switching cycle. In this chapter, the operation for charging only is explained to save page length. To charge an LIC with the buck‐boost converter shown in **Figure 12**, the switch Q1 is As Q1 is turned off, the operation moves to *Toff\_a* period, during which *iL* linearly decreases from *Ipeak* with the slope of –*Vcell*/*L*. *iL* starts flowing through diode D2 that is connected in parallel with Q2. The time length of this period, *Toff\_a*, can be determined to be

$$T\_{\text{ogf\\_a}} = I\_{\text{peak}} \frac{L}{V\_{cell}} = \frac{V\_{\text{ln}} D T\_{\text{S}}}{V\_{cell}} \tag{17}$$

As *iL* reaches zero, the final mode of *Toff\_b* period begins. In this mode, except for the current of the smoothing capacitor Cout, no current flows in the converter.

In order for *Toff\_b* period to exist, *Toff\_a* must be shorter than *TS* ‐ *Ton*, meaning *Toff\_a* < *TS* ‐ *Ton*. It leads to the operation criterion given by

$$D < \frac{V\_{\text{coll}}}{V\_{\text{in}} + V\_{\text{coll}}} \tag{18}$$

The input current for the buck‐boost converter is supplied only during *Ton* period, and hence, the input power (or charging power) can be expressed as

$$P\_{in} = V\_{in} \frac{I\_{peak}}{2} \frac{T\_{on}}{T\_s} \tag{19}$$

This equation indicates that, with a constant on‐time of *Ton*, the charging power for the LIC cell or *Pin* for the buck‐boost converter can be automatically constant even without feedback control. In other words, open‐loop control is feasible, hence allowing simplified control circuit.

The photograph of a power control unit (PCU) that contains the buck‐boost converter is shown in **Figure 14**. The converter operated with a fixed *D* of 0.35 at a switching frequency of 100 kHz for the charging power to be approximately 3.8 W. For discharging periods, on the other hand, *D* was adjusted so that the load voltage was controlled to be 5.0 V.

**Figure 14.** Photograph of power control unit (PCU) containing charge‐discharge regulator.

**Figure 15.** (a) Measured key operation waveforms of the buck‐boost converter and (b) cycling profiles of an LIC cycled by the buck‐boost converter.

The measured key operation waveforms during charging are shown in **Figure 15(a)**. The inductor current *iL* swung as the gate signal for Q1 was applied. The measured *iL* was discon‐ tinuous triangular wave—the displayed *iL* is inverted—and the good agreement with the theoretical ones was observed. A single charge‐discharge cycling profile of an LIC cell with the buck‐boost converter operating in DCM is shown in **Figure 15(b)**. The measured power during charging was nearly constant, verifying the automatic CP charging property.

#### **5.2. NESSIE**

**Figure 14.** Photograph of power control unit (PCU) containing charge‐discharge regulator.

**Figure 15.** (a) Measured key operation waveforms of the buck‐boost converter and (b) cycling profiles of an LIC cycled

(a)

138 Supercapacitor Design and Applications

(b)

by the buck‐boost converter.

The specification of NESSIE is listed in **Table 4**. The photographs of NESSIE installed in the main satellite HISAKI are shown in **Figure 16**. The high‐efficiency thin‐film solar cells were mounted on the main panel that was used as a lid for the interior components, including the LIC pouch cell and charge‐discharge regulator. NESSIE was installed in the side panel of the main satellite HISAKI.


**Table 4.** Specification of NESSIE.

**Figure 16.** Photographs of NESSIE installed in HISAKI.

## **6. On‐orbit operation**

The main satellite HISAKI was launched by Epsilon‐1 rocket on September 14, 2013, and NESSIE was turned on for the first time on October 12, 2013, and the LIC was cycled in the first check‐up operation, as shown in **Figure 17**. During the first eclipse period, the LIC was nearly fully discharged to 2.2 V, followed by a CP charging during the subsequent sun period. The data at the beginning of the charging were temporarily not available because of an operation with low communication rate, with which essential housekeeping data for HISAKI only was acquired. The short‐term pulsating discharges during charging periods were due to the measurement operation for the thin‐film solar cells, during which the PV panel was short‐ circuited and the LIC supplied power to the loads. The first check‐up results demonstrated the LIC as well as the charge‐discharge regulator performed well.

**Figure 17.** On‐orbit cycling profiles during the first check‐up.

Since approximately 1 month after the first check‐up, the voltage of the PV panel of NESSIE has unexpectedly dropped. The decreased PV panel voltage was lower than the threshold voltage of the charge‐discharge regulator. In other words, the voltage of the PV panel was not high enough for the charge‐discharge regulator to operate, meaning the LIC has no longer been charged since then.

As the best effort we could do with the malfunctioning PV panel, we determined to turn on NESSIE only for a few minutes in every few months to observe the LIC pouch cell under the float condition. This is rather different from the originally planned cycling condition that was used for laboratory testing. But we consider that this floating operation of the LIC pouch cell would still be meaningful to demonstrate the on‐orbit vacuum tolerance and to investigate whether unexpected malfunctions would happen to the LIC after long‐term exposure to space environment.

Development and On‐Orbit Demonstration of Lithium‐Ion Capacitor‐Based Power System for Small Spacecraft http://dx.doi.org/10.5772/64966 141

**Figure 18.** On‐orbit trend of LIC voltage.

**6. On‐orbit operation**

140 Supercapacitor Design and Applications

The main satellite HISAKI was launched by Epsilon‐1 rocket on September 14, 2013, and NESSIE was turned on for the first time on October 12, 2013, and the LIC was cycled in the first check‐up operation, as shown in **Figure 17**. During the first eclipse period, the LIC was nearly fully discharged to 2.2 V, followed by a CP charging during the subsequent sun period. The data at the beginning of the charging were temporarily not available because of an operation with low communication rate, with which essential housekeeping data for HISAKI only was acquired. The short‐term pulsating discharges during charging periods were due to the measurement operation for the thin‐film solar cells, during which the PV panel was short‐ circuited and the LIC supplied power to the loads. The first check‐up results demonstrated the

Since approximately 1 month after the first check‐up, the voltage of the PV panel of NESSIE has unexpectedly dropped. The decreased PV panel voltage was lower than the threshold voltage of the charge‐discharge regulator. In other words, the voltage of the PV panel was not high enough for the charge‐discharge regulator to operate, meaning the LIC has no longer

As the best effort we could do with the malfunctioning PV panel, we determined to turn on NESSIE only for a few minutes in every few months to observe the LIC pouch cell under the float condition. This is rather different from the originally planned cycling condition that was used for laboratory testing. But we consider that this floating operation of the LIC pouch cell would still be meaningful to demonstrate the on‐orbit vacuum tolerance and to investigate whether unexpected malfunctions would happen to the LIC after long‐term exposure to space

LIC as well as the charge‐discharge regulator performed well.

**Figure 17.** On‐orbit cycling profiles during the first check‐up.

been charged since then.

environment.

The trend of the LIC voltage is shown in **Figure 18**. As aforementioned, NESSIE was turned on for a few minutes in every few months, and the LIC‐powered NESSIE and its voltage gradually decreased during the turn‐on periods. During the turn‐off periods, on the other hand, the voltage of the LIC unchanged as the voltages at the beginning and end of turn‐off periods were nearly identical, indicating the insignificant self‐discharge.

**Figure 19.** On‐orbit trend of LIC voltage as a function of discharged ampere‐hour capacity.

The on‐orbit LIC's voltage trend shown in **Figure 18** is redrawn as a function of discharged capacity in ampere‐hour and is compared to that of a cell tested in the laboratory, as shown in **Figure 19**. The on‐orbit and laboratory data matched very well, suggesting the LIC has been performing well.

## **7. Conclusions**

Although the specific energy of LICs is far lower than that of traditional LIBs, the gap be‐ tween LICs and LIBs can be greatly bridged once long‐cycle life performance with deep DoD conditions is factored in. In addition, LICs allow the CP charging scheme, with which the mass of the PV panel can be reduced compared to that with a traditional CC‐CV charg‐ ing scheme. The mass of an LIC‐based power system was compared to that of a LIB‐based system. The results of the quantitative comparison suggested that, for applications requiring very long‐cycle life, for which LIBs need to be cycled with DoD shallower than 20% to ach‐ ieve long‐cycle life, the LIC‐based power system would be comparable to the LIB‐based one, driving expectation that LIC would potentially be an alternative energy storage source.

We developed the technology demonstration platform named NESSIE whose one of the missions is the on‐orbit demonstration of the LIC pouch cell. Short‐term cycle life testing in vacuum was performed to investigate the vacuum tolerance of LIC pouch cells. The results of the 1‐year testing suggested the deterioration in capacitance retention due to the vacuum condition was insignificant. The dedicated charge‐discharge regulator, with which the LIC can be charged with the CP charging scheme even without feedback control, was also developed to realize simplified circuit.

NESSIE was launched with the main satellite HISAKI on September 14, 2013, and the first check‐up data showed the successful charge‐discharge cycling profiles of the LIC. However, the LIC has no longer been charged due to the malfunction of the PV panel since 1 month after the launch. Since then, as the best effort, the voltage trend of the LIC has been monitored to see whether long‐term exposure to space environment has negative influence on the LIC. As of this writing, no malfunctioning trend has been observed, suggesting the LIC has still been performing well.

## **Author details**

Masatoshi Uno1\* and Akio Kukita2

\*Address all correspondence to: masatoshi.uno.ee@vc.ibaraki.ac.jp

1 Ibaraki University, Hitachi, Japan

2 Japan Aerospace Exploration Agency, Sagamihara, Japan

## **References**


[3] M. Uno and A. Kukita. Cycle life evaluation based on accelerated aging testing for lithium‐ion capacitors as alternative to rechargeable batteries. IEEE Transactions on Industry Electronics. 2016;63(3):1607–1617.

DoD conditions is factored in. In addition, LICs allow the CP charging scheme, with which the mass of the PV panel can be reduced compared to that with a traditional CC‐CV charg‐ ing scheme. The mass of an LIC‐based power system was compared to that of a LIB‐based system. The results of the quantitative comparison suggested that, for applications requiring very long‐cycle life, for which LIBs need to be cycled with DoD shallower than 20% to ach‐ ieve long‐cycle life, the LIC‐based power system would be comparable to the LIB‐based one, driving expectation that LIC would potentially be an alternative energy storage source.

We developed the technology demonstration platform named NESSIE whose one of the missions is the on‐orbit demonstration of the LIC pouch cell. Short‐term cycle life testing in vacuum was performed to investigate the vacuum tolerance of LIC pouch cells. The results of the 1‐year testing suggested the deterioration in capacitance retention due to the vacuum condition was insignificant. The dedicated charge‐discharge regulator, with which the LIC can be charged with the CP charging scheme even without feedback control, was also developed

NESSIE was launched with the main satellite HISAKI on September 14, 2013, and the first check‐up data showed the successful charge‐discharge cycling profiles of the LIC. However, the LIC has no longer been charged due to the malfunction of the PV panel since 1 month after the launch. Since then, as the best effort, the voltage trend of the LIC has been monitored to see whether long‐term exposure to space environment has negative influence on the LIC. As of this writing, no malfunctioning trend has been observed, suggesting the LIC has still been

[1] JCC. UPS‐J EDLC Module [Internet]. Available from: http://www.jcc‐foil.co.jp/cdg/

[2] M. Uno and K. Tanaka. Accelerated charge‐discharge cycling test and cycle life prediction model for supercapacitors in alternative battery applications. IEEE Trans‐

to realize simplified circuit.

142 Supercapacitor Design and Applications

performing well.

**Author details**

**References**

Masatoshi Uno1\* and Akio Kukita2

1 Ibaraki University, Hitachi, Japan

products/index.html

\*Address all correspondence to: masatoshi.uno.ee@vc.ibaraki.ac.jp

actions on Industry Electronics. 2012;59(12):4704–4712.

2 Japan Aerospace Exploration Agency, Sagamihara, Japan


#### **Interdigitated MEMS Supercapacitor for Powering Heart Pacemaker Interdigitated MEMS Supercapacitor for Powering Heart Pacemaker**

Hafzaliza Erny Zainal Abidin, Azrul Azlan Hamzah, Jumril Yunas, Mohd Ambri Mohamed and Burhanuddin Yeop Majlis Hafzaliza Erny Zainal Abidin, Azrul Azlan Hamzah, Jumril Yunas, Mohd Ambri Mohamed and Burhanuddin Yeop Majlis

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/65127

#### **Abstract**

Power MEMS can be defined as microelectromechanical systems for power generation and energy conversion. Energy harvesting has become an increasingly popular option for powering electronic devices as a long-lasting power source. Energy scavenging is defined as the process by which the energy is derived such as vibration, solar, wind, and thermal. Energy harvesting from the environment can prolong the life cycle and reduce the maintenance costs of electronic devices. Among the various sources of energy storage, Among the various of energy storage, supercapacitor has recently gained much interest in fields such as bioMEMS, biomedical implants and power electronic devices due to its advantages such as high power density, rapid charge and discharge and unlimited number of recharge cycles. In biomedical and bioMEMS systems, an energy storage device is needed to power other active biomedical devices within the system. For implantable devices such as a heart pacemaker, the power requirement is in the range of 30–100 μW. Microsupercapacitors play an important role in energy harvesting system, such as collecting energy from ambient energy sources. Human body is very resourceful in generating micropower in the form of heat dissipation, deformation of elastic tissue, and motion. Due to the advantages of MEMS energy harvesting system, the system can be use widely for biomedical implant devices, such as heart pacemakers and hearing aids, and can be used for a long time and without the need for battery replacement. In this work, planar and double-stacked interdigital electrode supercapacitor designs were modeled using Coventorware software. From simulation, it is observed that for planar structure, the specific capacitance is 0.22 mF/cm−2, and for double-stacked structure specific capacitance can be increased to 0.48 mF/cm−2. In terms of specific power, the planar structure produces 0.99 mW/cm−2, and the double-stacked structure produces 2.18 mW/cm−2. These results highlight the superiority of the doublestacked MEMS interdigital supercapacitor design compared with its planar counterpart

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

in terms of charging capacity and electrical performance, thus making it favorable for powering heart pacemaker.

**Keywords:** energy scavenging, interdigital electrode microsupercapacitor, heart pacemaker, Coventorware

### **1. Introduction**

Biomedical implantable devices usually required micro power sources with smaller dimensions and higher power density. The output power generated is in the range of nanowatt to microwatt. Power requirement for implantable devices for heart pacemaker is 30-100 μW [1, 2]. An energy generation system producing power within that range would qualify as a probable candidate to replace the conventional battery system. Typically, a Lithium-ion battery is widely used in biomedical implants such as pacemakers. However, batteries have many disadvantages such as short lifetime and contain a finite amount of depletable chemical energy [3]. Thus, patients using biomedical implants devices such as cardiac pacemakers have to replace the battery once every 5 years to 10 years. To avoid frequent battery replacement, a renewable energy generation and storage system could become a vital solution to infinitely empower biomedical devices, without the need for any powering unit replacement [4, 5].

**Figure 1.** 2D view of planar interdigital electrode supercapacitor [23].

MEMS is one of the fundamental area that consists of mechanical, electrical, chemical, optical, and fluids engineering and integrated to the MEMS such as micropump,microvalve,microneedles and micronozzles [6–8]. Supercapacitor has high potential to replace conventional battery usage due to its high power density, rapid charge and discharge, long cycle life, high energy densities and unlimited number of recharge cycles. Miniaturized electrochemical capacitor or micro supercapacitor has promising capability to power small electronic devices. [9–11]. Supercapacitors have the capability to store up to 10,000 times more energy compared with its conventional counterparts [12, 13]. For electrode structure design of a supercapacitor, it can be classified into interdigital, sandwich, and roll structure [14]. Interdigital electrodes structure has their advantages such as low charging current, reduced solution resistance effects, and diffusion controllable current [15].

in terms of charging capacity and electrical performance, thus making it favorable for

**Keywords:** energy scavenging, interdigital electrode microsupercapacitor, heart pace-

Biomedical implantable devices usually required micro power sources with smaller dimensions and higher power density. The output power generated is in the range of nanowatt to microwatt. Power requirement for implantable devices for heart pacemaker is 30-100 μW [1, 2]. An energy generation system producing power within that range would qualify as a probable candidate to replace the conventional battery system. Typically, a Lithium-ion battery is widely used in biomedical implants such as pacemakers. However, batteries have many disadvantages such as short lifetime and contain a finite amount of depletable chemical energy [3]. Thus, patients using biomedical implants devices such as cardiac pacemakers have to replace the battery once every 5 years to 10 years. To avoid frequent battery replacement, a renewable energy generation and storage system could become a vital solution to infinitely empower biomedical devices, without the need for any powering unit replacement [4, 5].

MEMS is one of the fundamental area that consists of mechanical, electrical, chemical, optical, and fluids engineering and integrated to the MEMS such as micropump,microvalve,microneedles and micronozzles [6–8]. Supercapacitor has high potential to replace conventional

powering heart pacemaker.

**Figure 1.** 2D view of planar interdigital electrode supercapacitor [23].

maker, Coventorware

146 Supercapacitor Design and Applications

**1. Introduction**

Conducting polymers have high capacitance and high conductivity with low cost compared to carbon as the electrode material for supercapacitor [16, 17]. Conducting polymers such as Polypyrrole (PPY), Polyaniline (PANI), and Polythiophene are mostly used as the electrode material in supercapacitors due to its advantages such as easy fabrication, low cost, high charge density, good conductivity, and more flexible [18–21]. In terms of electrolyte, Polyvinyl Alcohol (PVA) has been chosen due to its high charging density and low cost [22].

Planar interdigital electrode supercapacitor with polypyrrole (Ppy) – polyvinyl alcohol (PVA) as electrodes coating and electrolyte material respectively was first introduced by Wei Sun and Xuyuan Chen, having the advantage of high charging capacity due to its interdigital structure. In this structure, the supercapacitor consists of two Ppy coated nickel electrodes as current collectors and PVA as a solid-state electrolyte (**Figure 1**) [23].

In addition, carbon nano tube (CNT) can also be used as electrodes for the supercapacitor. In 2009, Jiang et al. [24] used carbon nano tube as supercapacitor electrodes and produced a specific capacitance of 428 μF/cm2 and a power density of 0.28 mW/cm2 . In 2011, Shen et al. have used an activated carbon as part of a supercapacitor material to obtain a larger surface area. Beidaghi and Wang 2011 [25] also used carbon as supercapacitor electrodes to increase the surface area to be more effective but had to be improved in terms of ion diffusion through the thickness of the dielectric film for the electrodes.

**Figure 2.** (a) Current pacemaker; (b) Future pacemaker using energy harvesting. Source: http://www.eetimes.com [26].

Microsupercapacitors play an important role in the energy harvesting system such ascollecting energy from ambient energy sources. In energy harvesting systems, it does not require any chemicals. In fact, the human body is very flexible in generating power from heat dissipation, deformation of elastic tissue, and the others. Due to its advantages as a energy harvesting system, it can be used widely for biomedical implant devices such as pacemakers and hearing aids and can be used for a long time and recharge without any replacement. **Figures 2** and **3** show examples of supercapacitor applications in MEMS devices. For a current pacemaker as depicted in **Figure 2**, the batteries are frequently changed and required a high cost for surgical operations compared with a pacemaker using energy harvesting that is more reliable and comfortable to the patients. For a normal pacemaker as shown in **Figure 2(a)**, it consists of two elements which are first, a pulse generator, placed under the skin in the chest, a battery, and the impulse control system, and second, a lead inserted directly in the heart through a vein, delivering the impulses [26]. **Figure 3** shows a small chip in the middle-ear cavity. The main components are the surgical implant, which is placed underneath the skin, and externally the audio processor that converts sound into electrical signals [26].

**Figure 3.** Small chip in the middle-ear cavity. Source: http://www.eetimes.com [26].

### **2. Design of planar interdigital electrode MEMS supercapacitor**

In this research, planar interdigital electrode supercapacitor design was modeled using Coventorware ver.2008 via its process simulator tool. The software uses finite element analysis [27]. The planar supercapacitor structure consists of silicon (Si), silicon oxide (SiO2), nickel (Ni), Polypyrrole (Ppy), and Polyvinyl Alcohol (PVA) layers. The structure was initiated by setting silicon as substrate 200 nm SiO2 that was deposited on the silicon layer. Interdigital electrode structure was patterned using Ni on the SiO2 layer. After that, the seed nickel layer was electroplated to construct high aspect ratio of nickel [28, 29]. The Ni electrodes were coated with Ppy to create the dielectric layer. PVA layer was fill deposited between the fingers to function as solid-state electrolyte. The process flow for modeling the structure of planar interdigital electrode supercapacitor is as shown in **Figure 4** and three-dimension structure of planar interdigital electrode supercapacitor is as shown in **Figure 5**.

Interdigitated MEMS Supercapacitor for Powering Heart Pacemaker http://dx.doi.org/10.5772/65127 149

**Figure 4.** Process flow for modeling the double-stacked supercapacitor. (a) SiO2 deposition, (b) Seed Ni deposition and patterning of 2D layout interdigital structure, (c) Ni growth of the interdigital structure, (d) Ppy coating on Ni, (e) PVA filling.

**Figure 5.** Structure of planar interdigital electrode supercapacitor.

Microsupercapacitors play an important role in the energy harvesting system such ascollecting energy from ambient energy sources. In energy harvesting systems, it does not require any chemicals. In fact, the human body is very flexible in generating power from heat dissipation, deformation of elastic tissue, and the others. Due to its advantages as a energy harvesting system, it can be used widely for biomedical implant devices such as pacemakers and hearing aids and can be used for a long time and recharge without any replacement. **Figures 2** and **3** show examples of supercapacitor applications in MEMS devices. For a current pacemaker as depicted in **Figure 2**, the batteries are frequently changed and required a high cost for surgical operations compared with a pacemaker using energy harvesting that is more reliable and comfortable to the patients. For a normal pacemaker as shown in **Figure 2(a)**, it consists of two elements which are first, a pulse generator, placed under the skin in the chest, a battery, and the impulse control system, and second, a lead inserted directly in the heart through a vein, delivering the impulses [26]. **Figure 3** shows a small chip in the middle-ear cavity. The main components are the surgical implant, which is placed underneath the skin, and externally the

audio processor that converts sound into electrical signals [26].

148 Supercapacitor Design and Applications

**Figure 3.** Small chip in the middle-ear cavity. Source: http://www.eetimes.com [26].

planar interdigital electrode supercapacitor is as shown in **Figure 5**.

**2. Design of planar interdigital electrode MEMS supercapacitor**

In this research, planar interdigital electrode supercapacitor design was modeled using Coventorware ver.2008 via its process simulator tool. The software uses finite element analysis [27]. The planar supercapacitor structure consists of silicon (Si), silicon oxide (SiO2), nickel (Ni), Polypyrrole (Ppy), and Polyvinyl Alcohol (PVA) layers. The structure was initiated by setting silicon as substrate 200 nm SiO2 that was deposited on the silicon layer. Interdigital electrode structure was patterned using Ni on the SiO2 layer. After that, the seed nickel layer was electroplated to construct high aspect ratio of nickel [28, 29]. The Ni electrodes were coated with Ppy to create the dielectric layer. PVA layer was fill deposited between the fingers to function as solid-state electrolyte. The process flow for modeling the structure of planar interdigital electrode supercapacitor is as shown in **Figure 4** and three-dimension structure of

## **3. Design of double-stacked interdigital electrode MEMS supercapacitor**

Double-stacked supercapacitor design was modeled using Coventorware ver.2008 via its process simulator tool. The double-stacked supercapacitor structure consists of Si, SiO2, Ni,

**Figure 6.** Meshing structure of planar interdigital electrode supercapacitor.

Ppy, and PVA layers. For a double-stacked structure, the mirrored cell from initial cell was developed by similar process steps. The electrodes would lie next to and atop of each other when the two cells are sandwiched together. The structure was initiated by setting silicon as substrate. 200 nm SiO2 was stack deposited on the silicon layer. Interdigital electrode structure was patterned using Ni on the SiO2 layer. The Ni electrodes were coated with Ppy to create the dielectric layer. PVA layer was deposited between the fingers to function as a solid-state electrolyte (**Figures 6**–**9**).

**Figure 7.** Process flow for modeling the double-stacked supercapacitor. (a) SiO2 deposition, (b) Seed Ni deposition and patterning of 2D layout interdigital structure, (c) Ni growth of the interdigital structure, (d) Ppy coating on Ni, (e) PVA filling and (f) Double-stack attachment.

**Figure 8.** Structure of double-stacked interdigital supercapacitor with interwoven electrodes. Note that anode and cathode are always next to each other in bottom–bottom, top–top, and top–bottom electrode pairing configurations for the double-stacked design.

**Figure 9.** Meshing structure double-stacked interdigital electrode supercapacitor.

Ppy, and PVA layers. For a double-stacked structure, the mirrored cell from initial cell was developed by similar process steps. The electrodes would lie next to and atop of each other when the two cells are sandwiched together. The structure was initiated by setting silicon as substrate. 200 nm SiO2 was stack deposited on the silicon layer. Interdigital electrode structure was patterned using Ni on the SiO2 layer. The Ni electrodes were coated with Ppy to create the dielectric layer. PVA layer was deposited between the fingers to function as a solid-state

**Figure 7.** Process flow for modeling the double-stacked supercapacitor. (a) SiO2 deposition, (b) Seed Ni deposition and patterning of 2D layout interdigital structure, (c) Ni growth of the interdigital structure, (d) Ppy coating on Ni, (e) PVA

**Figure 8.** Structure of double-stacked interdigital supercapacitor with interwoven electrodes. Note that anode and cathode are always next to each other in bottom–bottom, top–top, and top–bottom electrode pairing configurations for

electrolyte (**Figures 6**–**9**).

150 Supercapacitor Design and Applications

filling and (f) Double-stack attachment.

the double-stacked design.

### **4. Electrical characteristics for planar interdigital electrode supercapacitor**

Comsol Multiphysics ver.4.2 simulation tool was used to simulate the electrical characteristic of planar interdigital electrode design. Secondary current distribution and transport of diluted are chosen as the application modules [30]. Two dimensional time dependent cyclic voltammetry model was developed for the interdigital structure. Cyclic voltammetry measures current response when potential is applied to the working electrodes. For interdigital structure, the boundary conditions define the interface between the electrode and the electrolyte. The applied voltage range is set to −0.5 V to 0.5 V at the working electrode, and the current response at the working electrode can be measured. In the structure, Ppy-coated nickel is the current collector and PVA is the solid-state electrolyte. For the interdigital electrode, it consists of two electrode which is working electrode and counter electrode. The boundary conditions can be identify the interface between electrode and electrolyte. We set the boundaries at the counter electrode as ground and the electrode potential was applied at the working electrode boundaries based on 1[V]/Scan (t/1[s])-0.5[V] function [31, 32].

For cyclic voltammetry simulation, the bidirectional reaction can be formulated as in Ref. [3]:

$$A + e \xrightarrow{\rightarrow}\_{B} B$$

According to Eq. (2), for mass flow density of forward reaction *Nf* , it can be expressed as the rate constant *kf* multiplied by concentration species during oxidation process C*O*. For backward reaction, according to Eq. (3), for mass flow density of backward reaction *Nb*, it can be expressed as the rate constant *kb* multiplied by concentration species during reduction process C*R*.

$$N\gamma = k\gamma.Co\tag{2}$$

$$N\_b = k\_b C\_R \tag{3}$$

The rate constants of forward and backward reaction at the electrodes are described by the Butler-Volmer reaction kinetics

$$k\_{\ell} = k\_{\ell}e = \alpha \left(E - E\_{\ell}\right) \frac{F}{RT} \tag{4}$$

$$k\_{\circ} = k\_{\circ}e(1 - \alpha)(E - E\_{\circ})\frac{F}{RT} \tag{5}$$

where *ks* is the standard rate constant and *α* is the transfer coefficient. In symmetrical reactions, *α* has a value 0.5. *E* is the applied voltage on the electrode interface and *E*<sup>0</sup> has a value 0 V. For *F*, *R*, and *T*, it is a Faraday constant (96485 C/mol), molar gas constant (8.3144 J mol−1 K−1), and temperature (298 K), respectively.

Additionally, the relationship for current, potential, and concentration can be summarized as follows:

$$\frac{i}{nFA} = k0 \left\{ c\nu e[-\alpha\theta] \text{--} c\kappa \text{e}[(1-\alpha)\theta] \right\} \tag{6}$$

where *θ* = *nF*(*E* − *E*0)/*RT*.

Initially, the Comsol simulation is simplified and performed on planar interdigital electrode structure as depicted in **Figure 8(a)**. It is observed that surface charge density is evenly distributed throughout the interdigital structures. As applied voltage between anode and cathode is slowly increased from 0 to 3 V, the charge density increases as more and more ions accumulate between the electrodes. A closer observation into the structure reveals that maximum charge density often occurs at the intersection of electrodes and its anchor, as depicted in **Figure 8(b)**. This is due to the proximity of the intersection point with the adjacent electrode, causing the charge to concentrate at the sharp edged points. The maximum charge density is as shown in **Figure 10(b)**.

Cyclic voltammetry portrays current response when potential is applied to the electrodes. In our case, the potential is applied at working electrode is between -0.5 V and 0.5 V, with the other electrode set as ground. The increasing voltage increases oxidation and reduction processes between the electrodes, driving current flow between working and counter electrodes. **Figure 11** shows that the oxidation and reductions occur within a voltage range of −0.5 and 0.5 V. For our design, ion flux reaches a peak within that region, resulting in maximum peak current (ip) of 6.0 A/m.

Interdigitated MEMS Supercapacitor for Powering Heart Pacemaker http://dx.doi.org/10.5772/65127 153

(3)

(4)

(5)

(6)

The rate constants of forward and backward reaction at the electrodes are described by the

where *ks* is the standard rate constant and *α* is the transfer coefficient. In symmetrical reactions, *α* has a value 0.5. *E* is the applied voltage on the electrode interface and *E*<sup>0</sup> has a value 0 V. For *F*, *R*, and *T*, it is a Faraday constant (96485 C/mol), molar gas constant (8.3144 J mol−1 K−1), and

Additionally, the relationship for current, potential, and concentration can be summarized as

Initially, the Comsol simulation is simplified and performed on planar interdigital electrode structure as depicted in **Figure 8(a)**. It is observed that surface charge density is evenly distributed throughout the interdigital structures. As applied voltage between anode and cathode is slowly increased from 0 to 3 V, the charge density increases as more and more ions accumulate between the electrodes. A closer observation into the structure reveals that maximum charge density often occurs at the intersection of electrodes and its anchor, as depicted in **Figure 8(b)**. This is due to the proximity of the intersection point with the adjacent electrode, causing the charge to concentrate at the sharp edged points. The maximum charge

Cyclic voltammetry portrays current response when potential is applied to the electrodes. In our case, the potential is applied at working electrode is between -0.5 V and 0.5 V, with the other electrode set as ground. The increasing voltage increases oxidation and reduction processes between the electrodes, driving current flow between working and counter electrodes. **Figure 11** shows that the oxidation and reductions occur within a voltage range of −0.5 and 0.5 V. For our design, ion flux reaches a peak within that region, resulting in maximum

Butler-Volmer reaction kinetics

152 Supercapacitor Design and Applications

temperature (298 K), respectively.

where *θ* = *nF*(*E* − *E*0)/*RT*.

density is as shown in **Figure 10(b)**.

peak current (ip) of 6.0 A/m.

follows:

**Figure 10.** (a) Structure surface charge density; (b) Maximum surface charge density distributions of a planar supercapacitor with 20 finger pairs at an applied voltage of 3 V.

**Figure 11.** Cyclic voltammetry for planar interdigital electrode supercapacitor.

For a charge discharge of a microsupercapacitor, there are two techniques. One is the charging and discharging at a constant voltage to record current response with time, and the other is the charging discharging at a constant current to record the voltage response with time. In **Figure 12**, it is shown that when time is zero, the value of voltage is also zero. Discharging process for planar interdigital electrode occurred when the value of voltage decreased and was back to zero at 1 s.

**Figure 12.** Charge discharge curve of planar electrode supercapacitor.

**Figure 13.** Cyclic voltammetry for various values of the length interdigital electrode.

Interdigitated MEMS Supercapacitor for Powering Heart Pacemaker http://dx.doi.org/10.5772/65127 155

**Figure 14.** Cyclic voltammetry for various values of the width interdigital electrode.

For a charge discharge of a microsupercapacitor, there are two techniques. One is the charging and discharging at a constant voltage to record current response with time, and the other is the charging discharging at a constant current to record the voltage response with time. In **Figure 12**, it is shown that when time is zero, the value of voltage is also zero. Discharging process for planar interdigital electrode occurred when the value of voltage decreased and was

back to zero at 1 s.

154 Supercapacitor Design and Applications

**Figure 12.** Charge discharge curve of planar electrode supercapacitor.

**Figure 13.** Cyclic voltammetry for various values of the length interdigital electrode.

**Figure 15.** Cyclic voltammetry for various values of the gap interdigital electrode.

For the purposes of studying effects of design parameter changes, Comsol simulations were performed on the planar design with varying electrode length, width, and gap between the electrodes. Length of the interdigital electrodes are varied between 500 μm and 700 μm, with 700 μm being the maximum allowable length due to design limitation. From **Figure 13**, we can see the longer the electrode, the higher the current response. The maximum current response achieved is 1.6 A/m corresponding to electrode length of 700 μm. Increasing electrode length increases active surface area, which in turn enable a higher redox activity between the electrodes. Thus, increasing electrode length increases current generating mass transport activity on the cyclic voltammetry. Adversely, increasing electrode width from 50 μm to 250 μm produces the opposite effect as shown in **Figure 14**. From the figure, we can see that the smaller the width, the higher the current response. The maximum value of current response is 0.9 A/m, which occurs at electrode width of 50 μm. The reactions occurs at working electrode per depth of electrode data because the modelling is done in 2-D. The increasing value of gap increases space between the electrodes. This allows higher amount of active species to be present at the active interface. At the working electrode, the reduction and oxidation occurs more and more rapidly as more electrolyte are available with the increasing gap (**Figure 15**).

## **5. Electrical characteristics for double-stacked interdigital electrode supercapacitor**

Cyclic voltammetry for the determination of a plane design double-digit supercapacitor between MEMS is the same as determining the design for cycle voltammetry for a coplanar. But there is a slight difference compared with the maximum current value for the design of the plane. **Figure 16** shows that the maximum flow for the cycle voltammetry multiple planar design is 13.2 A/m, which is more than twice the maximum current value relative to the plane designs. In the process of oxidation and reduction, equilibrium is reached and is limited by the voltage on the electrode surface. In the redox cycle, a decrease in current flow is from the effects of depletion. To complete the cycle, the voltage is not only directed to the front but also, on the other hand, within the range specified above. The curved shape also depends on the scan rate. Scan rate can be described as the speed at which the potential is varied. In addition,

**Figure 16.** Cyclic voltammetry for double-stacked interdigital electrode supercapacitor.

**Figure 17** shows the voltage response to the time indicated at 0.5 s, and the voltage reaches 1 V.

**Figure 17.** Charge discharge curve of double-stacked electrode supercapacitor.

see the longer the electrode, the higher the current response. The maximum current response achieved is 1.6 A/m corresponding to electrode length of 700 μm. Increasing electrode length increases active surface area, which in turn enable a higher redox activity between the electrodes. Thus, increasing electrode length increases current generating mass transport activity on the cyclic voltammetry. Adversely, increasing electrode width from 50 μm to 250 μm produces the opposite effect as shown in **Figure 14**. From the figure, we can see that the smaller the width, the higher the current response. The maximum value of current response is 0.9 A/m, which occurs at electrode width of 50 μm. The reactions occurs at working electrode per depth of electrode data because the modelling is done in 2-D. The increasing value of gap increases space between the electrodes. This allows higher amount of active species to be present at the active interface. At the working electrode, the reduction and oxidation occurs more and more rapidly as more electrolyte are available with the increasing gap (**Figure 15**).

**5. Electrical characteristics for double-stacked interdigital electrode**

**Figure 16.** Cyclic voltammetry for double-stacked interdigital electrode supercapacitor.

Cyclic voltammetry for the determination of a plane design double-digit supercapacitor between MEMS is the same as determining the design for cycle voltammetry for a coplanar. But there is a slight difference compared with the maximum current value for the design of the plane. **Figure 16** shows that the maximum flow for the cycle voltammetry multiple planar design is 13.2 A/m, which is more than twice the maximum current value relative to the plane designs. In the process of oxidation and reduction, equilibrium is reached and is limited by the voltage on the electrode surface. In the redox cycle, a decrease in current flow is from the effects of depletion. To complete the cycle, the voltage is not only directed to the front but also, on the other hand, within the range specified above. The curved shape also depends on the scan rate. Scan rate can be described as the speed at which the potential is varied. In addition,

**supercapacitor**

156 Supercapacitor Design and Applications

**Figure 18.** Cyclic voltammetry for various values of the length interdigital electrode.

Voltage is still in negative values until at *t* = 0.25 s. After that, the voltage increases until it reaches a maximum of 1.0 V at a value that is twice the value of the design of the plane at the time, *t* = 0.5 s, where the charging process occurs so as to achieve the maximum voltage. After reaching the maximum voltage, the discharge process occurs, whereby the voltage drop causes the charging rate to reduce back to a negative value of −1.0 V at a time *t* = 1 s.

For the purpose of studying the effects of changes in response to the current design of the multiple-plane and the plane, the value for the electrode length, width, and the gap between the electrodes was varied as the design of the plane. The length of the electrode between the digits are 500 and 900 m, where the length of the electrode between the digit at 900 m is the maximum length allowed for the design limits. According to **Figure 18**, it can be seen that the more the length of the electrode, the higher the reaction flow. The maximum current response was obtained at 37.4 A/m to 900 m-long electrode. Increasing the length of the electrode leads to an increase in active surface area, which in turn allows a higher redox activity to occur between the electrodes. Therefore, increasing the length of the electrodes improves the mass transport activity generated during the cycle voltammetry. High flow shows the life cycle of a higher supercapacitor.

**Figure 19.** Cyclic voltammetry for various values of the width interdigital electrode.

According to **Figure 19**, we can see that the smaller the width of the electrode, the higher is the current response. The situation is similar to the design of the plane, and there is a difference in the maximum response current that is 13.2 A/m compared with 6.0 A/m for the design of the plane, which took place on the electrode width of 50 m. This phenomenon occurs because there is a balance between the surface area of the electrodes and the electrolyte. When the electrode width is increased, it will reduce the surface area of the electrolyte and also the amount of active species produced also decreasing.

For the gap between the electrodes to design multiple planes, the same value is used as in the design of the plane that is between 50 and 250 μm. In response to the voltage, resulting flows are plotted in **Figure 20**. Based on these figures, we can see that the greater the gap between the electrodes, the higher the current response. On the sidelines of the electrode 250 μm, the reaction flow reaches a maximum value of 26.4 A/m,which is doubled in value compared the design of the plane. This is because the number of cells for multiple planar design is twice that of the coplanar design that has 40 pairs of cells, so, with the increase in the number of cells, allowing for a number of active species of a higher existence on the active surface **Table 1** shows the comparison of parameters between planar and interdigital electrode supercapacitor design.

**Figure 20.** Cyclic voltammetry for various values of the width interdigital electrode.


**Table 1.** Comparison of parameters between planar and interdigital electrode supercapacitor design.

## **6. Conclusions**

reaching the maximum voltage, the discharge process occurs, whereby the voltage drop causes

For the purpose of studying the effects of changes in response to the current design of the multiple-plane and the plane, the value for the electrode length, width, and the gap between the electrodes was varied as the design of the plane. The length of the electrode between the digits are 500 and 900 m, where the length of the electrode between the digit at 900 m is the maximum length allowed for the design limits. According to **Figure 18**, it can be seen that the more the length of the electrode, the higher the reaction flow. The maximum current response was obtained at 37.4 A/m to 900 m-long electrode. Increasing the length of the electrode leads to an increase in active surface area, which in turn allows a higher redox activity to occur between the electrodes. Therefore, increasing the length of the electrodes improves the mass transport activity generated during the cycle voltammetry. High flow shows the life cycle of a

the charging rate to reduce back to a negative value of −1.0 V at a time *t* = 1 s.

**Figure 19.** Cyclic voltammetry for various values of the width interdigital electrode.

amount of active species produced also decreasing.

According to **Figure 19**, we can see that the smaller the width of the electrode, the higher is the current response. The situation is similar to the design of the plane, and there is a difference in the maximum response current that is 13.2 A/m compared with 6.0 A/m for the design of the plane, which took place on the electrode width of 50 m. This phenomenon occurs because there is a balance between the surface area of the electrodes and the electrolyte. When the electrode width is increased, it will reduce the surface area of the electrolyte and also the

For the gap between the electrodes to design multiple planes, the same value is used as in the design of the plane that is between 50 and 250 μm. In response to the voltage, resulting flows

higher supercapacitor.

158 Supercapacitor Design and Applications

Energy harvesting system has a high potential as an alternative power especially in biomedical implant devices such as pacemakers. Due to the disadvantages such as short lifetime and containing a finite amount of depletable chemical energy of lithium-ion batteries, the patients using heart pacemaker have to replace the battery once every 5–10 years. To avoid any powering unit replacement, a renewable energy generation and storage system could become a vital solution. From this research, it can be concluded that double-stacked MEMS interdigital supercapacitor has same layout, only slightly thicker compared with the planar structure due to double stacking, but with much superior charging capacity. For both planar and doublestacked MEMS interdigital supercapacitor designs, the electrodes width, length, and gap between electrode fingers were fixed at 50, 500, and 50 μm, respectively. Furthermore, the planar and double-stacked MEMS interdigital supercapacitor designs were simulated using COMSOL ver.4.2a for electrical performance verification such as cyclic voltammetry and charge discharge performance. For cyclic voltammetry performance, applied voltage range is set to −0.5 to 0.5 V. For capacitance performance, it is observed that capacitance increases linearly with increasing number of cell, length of fingers, and width of fingers due to charge interactions among adjacent cells. The simulation results show that the planar structure has a charging capacity of 6.77 pC and the double-stacked structure has a charging capacity of 15.5 pC. Furthermore, for specific capacitance, it is observed that for planar structure is 0.22 mF/cm−2 and for double-stacked structure is 0.48 mF/cm−2, while for specific power, the planar structure is 0.99 mW/cm−2 and for double-stacked structure is 2.18 mW/cm−2. For charge discharge curve, it is observed that the curves are almost linear in the potential range. These results highlight the superiority of the double-stacked MEMS interdigital supercapacitor design compared with its planar counterpart in terms of charging capacity and electrical performance, thus making it favorable for powering heart pacemakers.

## **Author details**

Hafzaliza Erny Zainal Abidin, Azrul Azlan Hamzah\* , Jumril Yunas, Mohd Ambri Mohamed and Burhanuddin Yeop Majlis

\*Address all correspondence to: azlanhamzah@ukm.edu.my

Institute of Microengineering and Nanoelectronics (IMEN), The National University of Malaysia, Bangi, Selangor, Malaysia

## **References**


[3] Pei Hong Wang, Xu Hu Dai, Dong Ming Fang and Xiao Lin Zhao. Design, fabrication and performances of a new vibration based electromagnetic micro power generator. Microelectronics Journal. 2007;38(12):1175–1180.

containing a finite amount of depletable chemical energy of lithium-ion batteries, the patients using heart pacemaker have to replace the battery once every 5–10 years. To avoid any powering unit replacement, a renewable energy generation and storage system could become a vital solution. From this research, it can be concluded that double-stacked MEMS interdigital supercapacitor has same layout, only slightly thicker compared with the planar structure due to double stacking, but with much superior charging capacity. For both planar and doublestacked MEMS interdigital supercapacitor designs, the electrodes width, length, and gap between electrode fingers were fixed at 50, 500, and 50 μm, respectively. Furthermore, the planar and double-stacked MEMS interdigital supercapacitor designs were simulated using COMSOL ver.4.2a for electrical performance verification such as cyclic voltammetry and charge discharge performance. For cyclic voltammetry performance, applied voltage range is set to −0.5 to 0.5 V. For capacitance performance, it is observed that capacitance increases linearly with increasing number of cell, length of fingers, and width of fingers due to charge interactions among adjacent cells. The simulation results show that the planar structure has a charging capacity of 6.77 pC and the double-stacked structure has a charging capacity of 15.5 pC. Furthermore, for specific capacitance, it is observed that for planar structure is 0.22 mF/cm−2 and for double-stacked structure is 0.48 mF/cm−2, while for specific power, the planar structure is 0.99 mW/cm−2 and for double-stacked structure is 2.18 mW/cm−2. For charge discharge curve, it is observed that the curves are almost linear in the potential range. These results highlight the superiority of the double-stacked MEMS interdigital supercapacitor design compared with its planar counterpart in terms of charging capacity and electrical

performance, thus making it favorable for powering heart pacemakers.

, Jumril Yunas,

Hafzaliza Erny Zainal Abidin, Azrul Azlan Hamzah\*

Malaysia, Bangi, Selangor, Malaysia

Mohd Ambri Mohamed and Burhanuddin Yeop Majlis

\*Address all correspondence to: azlanhamzah@ukm.edu.my

Institute of Microengineering and Nanoelectronics (IMEN), The National University of

ical microcapacitors. Journal of Power Sources. 2004;133(2):312–319.

pacemaker. Indian Pacing & Electrophysiology Journal. 4(4):201–212.

[1] Joo Hwan Sung, Se Joon Kim and Kun Hong. Fabrication of all solid state electrochem-

[2] Venkateswara Sarma Mallela, V Ilankumaran and N Srinivasa Rao. Trends of cardiac

**Author details**

160 Supercapacitor Design and Applications

**References**


editor. IEEE International Conference Semiconductor Electronics; Kuala Lumpur, Malaysia. 7–9 September 2004; 2004.

[28] Norazreen Abdul Aziz, B Bais, A A Hamzah and B Y Majlis. Characterization of HNA etchant for silicon microneedles array fabrication. In: IEEE 8th International Conference on Semiconductor Electronics; IEEE; Johor Bharu, Malaysia, 2008. pp. 203–206.

[15] M Paeschke, U Wollenberger, C Kohler, T Lisec, U Schnakenberg and R Hintsche. Properties of interdigital electrode arrays with different geometries. Analytica Chimica

[16] Meng Deng, Xi Yang, Musa Silke, Weiming Qiu, MingSheng Xu, Gustaaf Borghs et al. Electrochemical deposition of polypyrrole/graphene oxide composition on microelectrodes towards tuning the electrochemical properties of neural probes. Sensors and

[17] Marin S. Halper and James C Ellenbogen. Supercapacitor: A brief overviews. 2006:1–

[18] Hyuck Lee, Hyeongkeun Kim, Mi Suk Cho,Jaeboong Choi and Youngkwan Lee. Fabrication of polypyrrole (Ppy)/carbon nano tube (CNT) composite electrode on ceramic fabric for supercapacitor applications. Electrochimica Acta. 2011;56(22):7460–

[19] R Ramya, R Sivasubramanian and M V Sangaranarayanan. Conducting polymers based electrochemical supercapacitor-progress and prospects. Electrochimica Acta.

[20] Farah Alvi, Manoj K Ram, Punya A Basnayaka, Elias Stefanakes, Yogi Goswami and Ashok Kumar. Graphene polyethylenedioxythiophene conducting polymer nanocom-

[21] Mustafa Gullu and Deniz Yigit. A novel asymmetric pseudocapacitor based on poly (5,12-dihydrothieno[3,4:2,3] [1, 4] dioxocino[6,7-b] auinoxaline) coated graphite anode and poly(ethylenedioxythiophene)coated graphite cathodes. Electrochimica Acta.

[22] Graeme A Snook, Pon Kao and Adam S Best. Conducting polymer based supercapa-

[23] Wei Sun and Xuyuan Chen. Fabrication and tests of a novel three dimensional micro-

[24] Y Q Jiang, Q Zhou and L Lin. Planar MEMS supercapacitor using CNT forests. In: 2009 IEEE 22nd International Conference on Micro Electromechanical Systems; IEEE;

[25] Majid Beidaghi and Chunlei Wang. Micro supercapacitor based on three dimensional interdigital polypyrrole/C-MEMS electrodes. Electrochimica Acta. 2011;56(25):9508–

[26] Available from: http://www.embedded.com/print/4403423. 10 energy Harvesting

[27] Azrul Azlan Hamzah, Burhanuddin Yeop Majlis and Ibrahim Ahmad. Deflection analysis of epitaxially deposited polysilicon encapsulation for MEMS devices. In: IEEE,

posite based supercapacitor. Electrochimica Acta. 2011;56(25):9406–9412.

citor devices and electrodes. Journal of Power Sources. 2011;196(1):1–12.

supercapacitor. Microelectronic Engineering. 2009;86(4–6):1307–1310.

Acta. 1995;2670(136):126–136.

162 Supercapacitor Design and Applications

Actuators B. 2011;158(1):176–184.

41.

7466.

9514.

solutions for 2012.

2013;101:101–129.

2012;162(15–16):1434–1442.

Sorrento, Italy. 2009. pp. 587–590.


#### **Power Management in Supercapacitor-Based Wireless Sensor Nodes Power Management in Supercapacitor-Based Wireless Sensor Nodes**

Hengzhao Yang and Ying Zhang Hengzhao Yang and Ying Zhang

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64987

#### **Abstract**

This chapter studies a power management problem for supercapacitor-based wireless sensor nodes with energy harvesting capabilities. A dependent task scheduling algorithm for nonpreemptable tasks with precedence constraints is developed. The modified first in first out (MFIFO) algorithm takes into account supercapacitor state and energy harvesting. Task precedence constraints are handled by defining a variable called task effective release time. Results show that the MFIFO algorithm improves the energy performance of the first in first out (FIFO) algorithm and maintains the timing performance at the same time.

**Keywords:** algorithm, energy harvesting, power management, supercapacitor charge redistribution, dependent task scheduling, wireless sensor network

## **1. Introduction**

Wireless sensor networks have been developed for many applications. A wireless sensor network is composed of a large number of spatially distributed wireless sensor nodes. Wireless sensor nodes are usually powered by nonrechargeable batteries with limited capacity. Therefore, energy efficiency is a major concern. To maximize the network lifetime, various power management strategies have been proposed to minimize the energy consumption. In the meantime, numerous energy harvesting technologies have been developed to increase the energy income. Environmentally powered wireless sensor nodes usually need energy storage systems [1] to buffer the harvested energy. Typical energy storage systems include rechargeable batteries [2], supercapacitors [3–5], and hybrid systems [6, 7]. In general, rechargeable batteries have a larger capacity while supercapacitors have a much longer cycle

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

life. The major drawback of supercapacitors is their high self-discharge rate. Supercapacitor characteristics must be taken into account to develop effective power management solutions. For instance, supercapacitor self-discharge is considered in Refs. [3, 6]. This is because the supercapacitor terminal voltage is a critical parameter in analyzing the power behavior of supercapacitor-based energy storage systems, and self-discharge results in voltage drop. Because of the significance of the voltage drop during self-discharge, this characteristic has been extensively examined [8–14].

While supercapacitor self-discharge leads to voltage drop, this characteristic cannot completely characterize the supercapacitor voltage behavior. In fact, the supercapacitor voltage may increase under the open circuit condition [15], which is due to the charge redistribution characteristic. A mechanism of the low ionic mobility in supercapacitor micropores is identified in Ref. [16]. The impact of charge redistribution on power management is qualitatively investigated in Ref. [17]. A detailed analysis of the voltage change during charge redistribution is performed in Ref. [18]. In Ref. [19], the modified earliest deadline first (MEDF) algorithm is developed for scheduling independent tasks.

This chapter extends the results in Refs. [17–19] and studies a new power management problem. Specifically, this chapter develops a modified first in first out (MFIFO) algorithm for scheduling tasks with precedence constraints in environmentally powered wireless sensor nodes that use supercapacitor-based energy storage systems. The MFIFO algorithm takes into account supercapacitor charge redistribution and energy harvesting. Task precedence constraints are handled by defining a variable called task effective release time. While the first in first out (FIFO) algorithm only considers the timing constraints of tasks, the MFIFO algorithm also considers the energy constraints.

The remainder of this chapter is organized as follows. Section 2 describes a system model for analyzing the power flow in wireless sensor nodes. Section 3 develops the MFIFO algorithm. Section 4 illustrates the implementation setup. A case study and extensive simulations are performed to evaluate the algorithm performance. These qualitative and quantitative results demonstrate that the MFIFO algorithm improves the energy performance of the FIFO algorithm while maintaining its timing performance. Section 5 concludes this chapter.

## **2. A power model for wireless sensor nodes**

#### **2.1. System model**

This chapter adopts the wireless sensor node power model used in Ref. [19]. As shown in **Figure 1**, this model is composed of five modules: energy harvester, input power conditioning unit, energy buffer, output power conditioning unit, and energy user. Energy harvesters such as solar cells and piezoelectric films convert energy in other forms to electricity. Typically, an input power conditioning unit is needed to bridge the energy harvester and the energy buffer. For example, a solar-powered wireless sensor node usually includes a maximum power point tracker (MPPT). Energy buffers such as rechargeable batteries and supercapacitors are devices that store the harvested energy. An output power conditioning unit is often necessary to generate a suitable power supply for the energy user. DC-DC converters are commonly used modules to bridge the energy buffer and the energy user. Energy users are mainly RF transceivers, microcontrollers, and sensors.

**Figure 1.** A power model for wireless sensor nodes.

life. The major drawback of supercapacitors is their high self-discharge rate. Supercapacitor characteristics must be taken into account to develop effective power management solutions. For instance, supercapacitor self-discharge is considered in Refs. [3, 6]. This is because the supercapacitor terminal voltage is a critical parameter in analyzing the power behavior of supercapacitor-based energy storage systems, and self-discharge results in voltage drop. Because of the significance of the voltage drop during self-discharge, this characteristic has

While supercapacitor self-discharge leads to voltage drop, this characteristic cannot completely characterize the supercapacitor voltage behavior. In fact, the supercapacitor voltage may increase under the open circuit condition [15], which is due to the charge redistribution characteristic. A mechanism of the low ionic mobility in supercapacitor micropores is identified in Ref. [16]. The impact of charge redistribution on power management is qualitatively investigated in Ref. [17]. A detailed analysis of the voltage change during charge redistribution is performed in Ref. [18]. In Ref. [19], the modified earliest deadline first (MEDF)

This chapter extends the results in Refs. [17–19] and studies a new power management problem. Specifically, this chapter develops a modified first in first out (MFIFO) algorithm for scheduling tasks with precedence constraints in environmentally powered wireless sensor nodes that use supercapacitor-based energy storage systems. The MFIFO algorithm takes into account supercapacitor charge redistribution and energy harvesting. Task precedence constraints are handled by defining a variable called task effective release time. While the first in first out (FIFO) algorithm only considers the timing constraints of tasks, the MFIFO algorithm

The remainder of this chapter is organized as follows. Section 2 describes a system model for analyzing the power flow in wireless sensor nodes. Section 3 develops the MFIFO algorithm. Section 4 illustrates the implementation setup. A case study and extensive simulations are performed to evaluate the algorithm performance. These qualitative and quantitative results demonstrate that the MFIFO algorithm improves the energy performance of the FIFO algo-

This chapter adopts the wireless sensor node power model used in Ref. [19]. As shown in **Figure 1**, this model is composed of five modules: energy harvester, input power conditioning unit, energy buffer, output power conditioning unit, and energy user. Energy harvesters such as solar cells and piezoelectric films convert energy in other forms to electricity. Typically, an input power conditioning unit is needed to bridge the energy harvester and the energy buffer. For example, a solar-powered wireless sensor node usually includes a maximum power point tracker (MPPT). Energy buffers such as rechargeable batteries and supercapacitors are devices

rithm while maintaining its timing performance. Section 5 concludes this chapter.

been extensively examined [8–14].

166 Supercapacitor Design and Applications

also considers the energy constraints.

**2.1. System model**

algorithm is developed for scheduling independent tasks.

**2. A power model for wireless sensor nodes**

The power model can be further abstracted to facilitate analyzing the power flow in wireless sensor nodes. As shown in **Figure 1**, the power model has three components: energy source, energy storage, and energy consumer. The energy source includes the energy harvester and the input power conditioning unit. For clarity, the energy buffer is referred to as the energy storage in this three-component model. The energy consumer combines the output power conditioning unit and the energy user. This abstracted model introduces two benefits. First, by separating energy buffers and power conditioning units, it is more convenient to study the impact of energy buffer characteristics on power management in wireless sensor nodes. Second, experiments with energy buffers can be readily designed and performed. The effects of input and output power conditioning units are taken into account in the process of designing the experiments.

#### **2.2. Energy source model**

The component models are shown in **Figure 2**. The energy source is modeled as a current pulse train. As shown in **Figure 2(a)**, each current pulse is characterized by three parameters: begin time *BS*, duration *DS*, and weight *WS*, which is the current magnitude. It should be noted that the energy source pulse is the conditioned pulse that is actually injected into the energy storage system. For example, in a solar-powered sensor node, the current pulse conditioned by the MPPT and fed into the energy storage system is the current pulse described in this energy source model. By tuning these three parameters, energy source profiles with different characteristics such as time span and power level can be generated.

#### **2.3. Energy storage model**

The energy storage system is a single supercapacitor. **Figure 2(b)** shows the variable leakage resistance (VLR) model [10, 11, 17, 18] for supercapacitors, which is a simplified equivalent circuit model. In this model, the first branch has three components: resistor *R*1, constant capacitor *C*0, and voltage-dependent capacitor *KV* \* *V*. The total capacitance of the first branch is *C*1 = *C*0 + *KV* \* *V*. This branch models the voltage dependency of supercapacitor capacitance. The second branch includes resistor *R*2 and capacitor *C*2. This branch models the charge redistribution behavior. The variable leakage resistor *R*3 characterizes the time varying selfdischarge.

In addition to the model parameters, the voltages across the capacitors in the VLR model are also critical to determine the supercapacitor state. The charge stored in a supercapacitor tends to redistribute among *RC* branches after a charging or discharging process because each branch

**Figure 2.** Wireless sensor node component models. (a) Energy source. (b) Energy storage. (c) Energy consumer.

has a different time constant. Charge redistribution is a transient response to the supercapacitor initial state, which is characterized by the initial voltages *V*1 and *V*2 across the capacitors *C*1 and *C*2. For example, if *V*1 > *V*2, the supercapacitor terminal voltage decreases with time because part of the charge stored in *C*1 is transferred to *C*2. Therefore, to characterize a supercapacitor, the initial voltages across the capacitors in the VLR model must be specified.

#### **2.4. Energy consumer model**

The second branch includes resistor *R*2 and capacitor *C*2. This branch models the charge redistribution behavior. The variable leakage resistor *R*3 characterizes the time varying self-

In addition to the model parameters, the voltages across the capacitors in the VLR model are also critical to determine the supercapacitor state. The charge stored in a supercapacitor tends to redistribute among *RC* branches after a charging or discharging process because each branch

**Figure 2.** Wireless sensor node component models. (a) Energy source. (b) Energy storage. (c) Energy consumer.

discharge.

168 Supercapacitor Design and Applications

When the energy consumer initiates an event, the energy storage system is assigned a task. The energy consumer is therefore modeled as a current pulse train. As shown in **Figure 2(c)**, each task is defined by four parameters: release time *R*, execution time *E*, absolute deadline *D*, and weight *W*. The release time is the instant of time at which the task becomes available for execution. The execution time is the amount of time required to complete the execution. The absolute deadline is the instant of time by which the task execution is required to be completed. Release time, execution time, and deadline are temporal parameters defining the timing constraint of a task. The weight of a task is its current magnitude. This parameter defines the energy constraint of a task.

#### **2.5. Task precedence constraint and effective release time**

In this chapter, the tasks are assumed to be dependent and nonpreemptable. In addition to the four parameters (release time, execution time, deadline, and weight) used to characterize the task model, a task may also have precedence constraints. If tasks are constrained to execute in some order, they are said to have precedence constraints. The precedence constraints among tasks are specified using precedence relations [20]. A task *Tp* is a predecessor of another task *Tq* (and *Tq* a successor of *Tp*) if *Tq* cannot begin the execution until the execution of *Tp* completes. This fact is usually denoted by *Tp* < *Tq*. Two tasks are independent when neither *Tp* < *Tq* nor *Tp* > *Tq*. A task with predecessors is ready for execution when the time is at or after its release time and executions of all the predecessors are completed. Without loss of generality, it is assumed that in this chapter a task may have no more than one predecessor or successor for simplicity.

The release times of tasks with precedence constraints are sometimes inconsistent with the precedence constraints, which means that the release time of a task may be later than that of its successor. **Figure 3** shows two tasks *Tp* and *Tq* using solid lines. If *Tp* < *Tq*, the release time of task *Tq* is earlier than the release time of *Tp*, which is not consistent with the precedence constraint. A parameter called the effective release time of a task is defined to deal with such inconsistency. The effective release time of a task without predecessor is equal to its release time. The effective release time of a task with predecessor is equal to the maximum value between its release time and the release time of its predecessor plus the execution time of its predecessor. For example, the effective release time *ERq* of *Tq* is defined by Eq. 1 depending on whether there is a precedence constraint. As shown in **Figure 3**, the task *Tq* denoted by dashed lines shows its effective release time if *Tp* < *Tq*.

$$ER\_q = \begin{cases} \max(R\_q, R\_p + E\_p), & T\_p < T\_q, \\ R\_q, & \text{otherwise.} \end{cases} \tag{1}$$

$$\begin{array}{c|c|c|c|c|c} \hline \text{Term} & \begin{array}{c|c|c} \top\_q & \top\_q & \\ \hline \\ R\_q & & \text{True} & \\ \hline \end{array} & \begin{array}{c|c|c} \hline \top\_q & & \\ \hline \\ R\_q & & \text{True} & \\ \hline \end{array} \end{array} \tag{2}$$

**Figure 3.** Definition of task effective release time.

#### **3. MFIFO algorithm development**

The MFIFO algorithm has three steps. First, create an initial schedule using the FIFO algorithm. This step takes care of the timing constraints and precedence constraints of tasks. Second, calculate the ready time adjustment margin based on the initial schedule. This margin determines how much delay is allowed if the ready time of the initial schedule is adjusted. Third, the ready time offset is determined based on supercapacitor state and energy harvesting. The start time of a task is the ready time plus the ready time offset.

#### **3.1. Create an initial schedule using FIFO algorithm**

The FIFO algorithm is used to create an initial schedule to ensure that the task precedence constraints are satisfied. The tasks are originally defined by the task set *T* = *Ti* (*Ri* , *Ei* , *Di* , *Wi* ) and the precedence constraints *Tp* < *Tq*. The precedence constraints are transformed into timing constraints by defining the effective release times. A task is then characterized by four parameters: effective release time *ER*, execution time *E*, deadline *D*, and weight *W*. The task set is now *TE* = *Ti* (*ERi* , *Ei* , *Di* , *Wi* ). The FIFO algorithm sorts the effective release times in the ascending order and determines the ready times of the tasks. The initial schedule is determined using Algorithm 1.

**Algorithm 1:** Create an initial schedule using FIFO algorithm.

**Require:** A set of *N* ready but not scheduled tasks: *T* = *Ti* (*Ri* , *Ei* , *Di* , *Wi* ) and task precedence constraints: *Tp* < *Tq*.

1: **for** *i* = 1 : *N* **do** 2: **if** *Tp* < *Tq* **then** 3: *ERq* = *max*(*Rq*, *Rp* + *Ep*) 4: **else** 5: *ERq* = *Rq* 6: **end if** 7: **end for** 8: Sort *N* tasks in the ascending order of their effective release times. 9: Current Time *TC* = 0. 10: **for** *i* = 1 : *N* **do** 11: Ready Time *Ai* = *max*(*TC*, *ERi* ) 12: Current Time *TC* = *Ai* + *Ei* 13: **end for**

14: Algorithm output is initial schedule *TFIFO* defined by task ready time *Ai* : *TFIFO* = *Ti* (*Ai* , *Ei* , *Di* , *Wi* ) and modified task set *TE* = *Ti* (*ERi* , *Ei* , *Di* , *Wi* ).

#### **3.2. MFIFO algorithm**

( , ), < ; <sup>=</sup> , . *qp p p q*

*R otherwise*

The MFIFO algorithm has three steps. First, create an initial schedule using the FIFO algorithm. This step takes care of the timing constraints and precedence constraints of tasks. Second, calculate the ready time adjustment margin based on the initial schedule. This margin determines how much delay is allowed if the ready time of the initial schedule is adjusted. Third, the ready time offset is determined based on supercapacitor state and energy harvesting.

The FIFO algorithm is used to create an initial schedule to ensure that the task precedence

the precedence constraints *Tp* < *Tq*. The precedence constraints are transformed into timing constraints by defining the effective release times. A task is then characterized by four parameters: effective release time *ER*, execution time *E*, deadline *D*, and weight *W*. The task

ascending order and determines the ready times of the tasks. The initial schedule is determined

(*Ri* , *Ei* , *Di* , *Wi* ) and

) and task precedence

). The FIFO algorithm sorts the effective release times in the

(*Ri* , *Ei* , *Di* , *Wi*

The start time of a task is the ready time plus the ready time offset.

**Algorithm 1:** Create an initial schedule using FIFO algorithm.

**Require:** A set of *N* ready but not scheduled tasks: *T* = *Ti*

constraints are satisfied. The tasks are originally defined by the task set *T* = *Ti*

**3.1. Create an initial schedule using FIFO algorithm**

set is now *TE* = *Ti*

using Algorithm 1.

constraints: *Tp* < *Tq*.

(*ERi* , *Ei* , *Di* , *Wi*

ïî (1)

*max R R E T T*

*q*

*ER*

170 Supercapacitor Design and Applications

**Figure 3.** Definition of task effective release time.

**3. MFIFO algorithm development**

*q*

í

ìï +

Once the initial schedule is determined, the ready time adjustment margin and ready time offset are calculated using the algorithms for the second and third steps in the MEDF algorithm [19], respectively. In particular, the release times used in the MEDF algorithm should be replaced by the effective release times. The complete MFIFO algorithm is summarized in Algorithm 2. The inputs of this algorithm include a set of *N* ready but not scheduled tasks, *T* = *Ti* (*Ri* , *Ei* , *Di* , *Wi* ); task precedence constraints, *Tp* < *Tq*; energy source model, *ES*(*BS*, *DS*, *WS*); and supercapacitor initial state, *V*1(*t* = 0) and *V*2(*t* = 0). The MFIFO algorithm is a three-step process:

1. **Step 1:** Create an initial schedule using Algorithm 1. The input of this algorithm is the task set *T* = *Ti* (*Ri* , *Ei* , *Di* , *Wi* ) and task precedence constraints *Tp* < *Tq*. The output is the initial schedule *TFIFO* defined by task ready time *Ai* : *TFIFO* = *Ti* (*Ai* , *Ei* , *Di* , *Wi* ) and modified task set *TE* = *Ti* (*ERi* , *Ei* , *Di* , *Wi* ).

2. **Step 2:** Calculate ready time adjustment margin of the initial schedule using the second algorithm in Ref. [19]. The inputs are the modified task set *TE* = *Ti* (*ERi* , *Ei* , *Di* , *Wi* ) and the initial schedule *TFIFO* = *Ti* (*Ai* , *Ei* , *Di* , *Wi* ). The output is the task ready time adjustment margin *Mi* .

3. **Step 3:** Determine ready time offset of the initial schedule using the third algorithm in Ref. [19]. The inputs are the modified task set *TE* = *Ti* (*ERi* , *Ei* , *Di* , *Wi* ), the initial schedule *TFIFO* = *Ti* (*Ai* , *Ei* , *Di* , *Wi* ), the ready time adjustment margin *Mi* , the energy source model *ES*(*BS*, *DS*, *WS*), and the supercapacitor initial state *V*1(*t* = 0) and *V*2(*t* = 0). The output is the modified schedule *TMFIFO* defined by task start time *Si* : *TMFIFO* = *Ti* (*Si* , *Ei* , *Di* , *Wi* ).

**Algorithm 2:** MFIFO algorithm

**Require:** A set of *N* ready but not scheduled tasks: *T* = *Ti* (*Ri* , *Ei* , *Di* , *Wi* ); task precedence constraints: *Tp* < *Tq*; energy source model: *ES*(*BS*, *DS*, *WS*); and supercapacitor initial state: *V*1(*t* = 0) and *V*2(*t* = 0).


## **4. MFIFO algorithm implementation and evaluation**

#### **4.1. Simulation setup**

The MFIFO algorithm is implemented and evaluated using a simulation setup similar to the one used for the MEDF algorithm [19]. The energy source and energy storage models are exactly the same. The energy consumer model is modified. Each task set has six periodic tasks and each periodic task has five jobs. Therefore, each task set is composed of 30 tasks. The timing and energy parameters of a task are defined in the same way as the one used for the MEDF algorithm, too. The precedence constraints are assigned with controlled randomness. The six periodic tasks are partitioned into three groups. Each group consists of two periodic tasks. For convenience, the six periodic tasks are numbered as {*P*1, *P*2, …, *P*6}. The three groups are then {*P*1, *P*2}, {*P*3, *P*4}, and {*P*5, *P*6}. For each group, a job of the first periodic task is randomly selected as the predecessor of a job randomly selected from the second periodic task. Therefore, three pairs of precedence constraints are assigned for each task set. For example, **Figure 4** shows that in the first group {*P*1, *P*2}, the third job *T*3 of the first periodic task *P*1 is selected as the predecessor of the second job *T*7 of the second periodic task *P*2: *T*3 < *T*7. The MFIFO algorithm is evaluated in terms of the two metrics used for the MEDF algorithm: deadline miss rate and energy violation rate.

**Figure 4.** Assignment of precedence constraint.

#### **4.2. An example**

*ES*(*BS*, *DS*, *WS*), and the supercapacitor initial state *V*1(*t* = 0) and *V*2(*t* = 0). The output is the

constraints: *Tp* < *Tq*; energy source model: *ES*(*BS*, *DS*, *WS*); and supercapacitor initial state: *V*1(*t* = 0)

4: Step 2: Calculate ready time adjustment margin of the initial schedule using the second

7: Step 3: Determine ready time offset of the initial schedule using the third algorithm in

8: Input: modified task set *TE*; initial schedule *TFIFO*; ready time adjustment margin *Mi*

energy source model: *ES*(*BS*, *DS*, *WS*); and supercapacitor initial state: *V*1(*t* = 0) and

10: MFIFO Algorithm Output: modified schedule *TMFIFO* defined by task start time *Si*

The MFIFO algorithm is implemented and evaluated using a simulation setup similar to the one used for the MEDF algorithm [19]. The energy source and energy storage models are exactly the same. The energy consumer model is modified. Each task set has six periodic tasks and each periodic task has five jobs. Therefore, each task set is composed of 30 tasks. The timing and energy parameters of a task are defined in the same way as the one used for the MEDF algorithm, too. The precedence constraints are assigned with controlled randomness. The six periodic tasks are partitioned into three groups. Each group consists of two periodic tasks. For convenience, the six periodic tasks are numbered as {*P*1, *P*2, …, *P*6}. The three groups are then {*P*1, *P*2}, {*P*3, *P*4}, and {*P*5, *P*6}. For each group, a job of the first periodic task is randomly selected as the predecessor of a job randomly selected from the second periodic task. Therefore, three pairs of precedence constraints are assigned for each task set. For example, **Figure 4** shows

.

: *TMFIFO* = *Ti*

(*Si* , *Ei* , *Di* , *Wi* ).

); task precedence

;

:

(*Ri* , *Ei* , *Di* , *Wi*

modified schedule *TMFIFO* defined by task start time *Si*

**Require:** A set of *N* ready but not scheduled tasks: *T* = *Ti*

1: Step 1: Create an initial schedule using Algorithm 1.

5: Input: modified task set *TE* and initial schedule *TFIFO*.

**4. MFIFO algorithm implementation and evaluation**

6: Output: task ready time adjustment margin *Mi*

9: Output: modified schedule *TMFIFO*.

(*Si* , *Ei* , *Di* , *Wi* ).

2: Input: task set *T* and task precedence constraints *Tp* < *Tq*. 3: Output: initial schedule *TFIFO* and modified task set *TE*.

**Algorithm 2:** MFIFO algorithm

172 Supercapacitor Design and Applications

algorithm in Ref. [19].

and *V*2(*t* = 0).

Ref. [19].

*V*2(*t* = 0).

*TMFIFO* = *Ti*

**4.1. Simulation setup**

An example is used to illustrate the implementation and evaluation of the MFIFO algorithm. The simulation setup is adopted from Ref. [19], which is used to illustrate the MEDF algorithm implementation and evaluation. The supercapacitor initial state is *V*1(*t* = 0) = *V*2(*t* = 0) = 1 V. Two periodic tasks are used to define the task timing and energy constraints. The job *T*2 from the first periodic task is selected as the predecessor of the job *T*4 from the second periodic task. The precedence constraint is therefore *T*2 < *T*4. The effective release time of task *T*4 is *ER*4 = *max*(*R*4, *R*2 + *E*2) = 88 s. The effective release times of the other five tasks are their release times. The task characteristics are listed in **Table 1** .


**Table 1.** Tasks with precedence constraints to be scheduled.

The FIFO schedule determined using Algorithm 1 is shown in **Figure 5** . All the tasks are scheduled for execution at their effective release times. The task *T*4 begins execution when its predecessor *T*2 completes execution. The precedence constraint is satisfied. All the tasks respect their deadlines. The deadline miss rate is therefore *αFIFO* = 0. The supercapacitor terminal voltage profile is shown in **Figure 6**. Two energy violations occur: *T*1 and *T*5. The minimum supercapacitor terminal voltages during the executions of the two tasks are 0.9670 and 0.9867 V, respectively. The energy violation rate is therefore *βFIFO* = 2/6 = 0.333.

**Figure 5.** Task schedule determined using FIFO algorithm.

**Figure 6.** Supercapacitor terminal voltage profile of FIFO schedule.

The task ready time adjustment margin and task ready time offset results are listed in **Tables 2** and **3**, respectively. The task start time is then determined, and the MFIFO schedule is finalized. The MFIFO schedule is shown in **Figure 7**. Tasks *T*1 and *T*5 are postponed for execution. All the deadlines are respected. Therefore, the deadline miss rate is still *αMFIFO* = 0. The MFIFO and FIFO algorithms have the same timing performance. The supercapacitor terminal voltage profile is shown in **Figure 8**. No energy violation occurs. The energy violation rate is *βMFIFO* = 0. This example demonstrates that the MFIFO algorithm is better than the FIFO algorithm in terms of energy performance while maintaining the same timing performance.


**Table 2.** FIFO schedule and ready time adjustment margin.

The FIFO schedule determined using Algorithm 1 is shown in **Figure 5** . All the tasks are scheduled for execution at their effective release times. The task *T*4 begins execution when its predecessor *T*2 completes execution. The precedence constraint is satisfied. All the tasks respect their deadlines. The deadline miss rate is therefore *αFIFO* = 0. The supercapacitor terminal voltage profile is shown in **Figure 6**. Two energy violations occur: *T*1 and *T*5. The minimum supercapacitor terminal voltages during the executions of the two tasks are 0.9670 and 0.9867

V, respectively. The energy violation rate is therefore *βFIFO* = 2/6 = 0.333.

**Figure 5.** Task schedule determined using FIFO algorithm.

174 Supercapacitor Design and Applications

**Figure 6.** Supercapacitor terminal voltage profile of FIFO schedule.

The task ready time adjustment margin and task ready time offset results are listed in **Tables 2** and **3**, respectively. The task start time is then determined, and the MFIFO schedule is finalized. The MFIFO schedule is shown in **Figure 7**. Tasks *T*1 and *T*5 are postponed for execution. All the deadlines are respected. Therefore, the deadline miss rate is still *αMFIFO* = 0. The MFIFO and FIFO algorithms have the same timing performance. The supercapacitor terminal voltage profile is shown in **Figure 8**. No energy violation occurs. The energy violation rate is *βMFIFO* = 0. This example demonstrates that the MFIFO algorithm is better than the FIFO algorithm in

terms of energy performance while maintaining the same timing performance.


**Table 3.** MFIFO schedule and ready time offset.

**Figure 7.** Task schedule determined using MFIFO algorithm.

**Figure 8.** Supercapacitor terminal voltage profile of MFIFO schedule.

#### **4.3. Evaluation results**

The simulations are run for 200 times using the setup specified in Ref. [19]. The deadline miss rates and energy violation rates are recorded for the FIFO and MFIFO schedules. The obtained evaluation metrics are sorted in the ascending order and plotted. As shown in **Figure 9** , 35 out of the 200 simulation runs have zero deadline miss rates. The FIFO and MFIFO algorithms always have the same deadline miss rates. The timing and precedence constraints of the FIFO schedules are preserved in the MFIFO schedules. The energy violation rates are shown in **Figure 10** . For the FIFO algorithm, 96 out of the 200 simulation runs have an energy violation rate *βFIFO* = 1. Among the 96 runs, the MFIFO schedules have an energy violation rate less than one for seven runs. Among the other 104 runs, the MFIFO algorithm results in an energy violation rate smaller than that of the FIFO algorithm for 81 runs. All together, the MFIFO schedules result in a smaller energy violation rate for 88 runs and a same energy violation rate for 112 runs. The simulation results verify that the MFIFO algorithm improves the energy performance of the FIFO algorithm and maintains the timing performance at the same time.

**Figure 9.** Deadline miss rates of FIFO and MFIFO algorithms.

The simulation setup is slightly modified to quantitatively compare the energy violation rates of the FIFO and MFIFO algorithms. The duty cycles of the six periodic tasks take the same value for each utilization. The utilization is *U* = 6 \* *DC*, where DC is the duty cycle. The duty cycle increases from 0.02 to 0.1 with a step of 0.02. The utilization is swept from 0.12 to 0.6 with a step of 0.12. The other parameters of the tasks including periods, phases, weights, and precedence constraints are still defined using the setup specified in Ref. [19]. The simulations are run for 30 times for each utilization. **Figure 11** shows the calculated mean absolute percentage error (MAPE) values for the different utilizations. The MAPE decreases as the utilization increases. The average MAPE for the five utilizations is 12.1%. The MFIFO algorithm reduces the average energy violation rate of the FIFO algorithm by 12.1%. The MAPE is 25% for utilization *U* = 0.12. Like the MEDF algorithm, the MFIFO algorithm improves the energy violation rate more significantly if the sensor node operates with a relatively low duty cycle.

**Figure 10.** Energy violation rates of FIFO and MFIFO algorithms.

**Figure 11.** MAPE versus utilization for MFIFO algorithm.

#### **5. Conclusion**

**Figure 8.** Supercapacitor terminal voltage profile of MFIFO schedule.

**Figure 9.** Deadline miss rates of FIFO and MFIFO algorithms.

The simulations are run for 200 times using the setup specified in Ref. [19]. The deadline miss rates and energy violation rates are recorded for the FIFO and MFIFO schedules. The obtained evaluation metrics are sorted in the ascending order and plotted. As shown in **Figure 9** , 35 out of the 200 simulation runs have zero deadline miss rates. The FIFO and MFIFO algorithms always have the same deadline miss rates. The timing and precedence constraints of the FIFO schedules are preserved in the MFIFO schedules. The energy violation rates are shown in **Figure 10** . For the FIFO algorithm, 96 out of the 200 simulation runs have an energy violation rate *βFIFO* = 1. Among the 96 runs, the MFIFO schedules have an energy violation rate less than one for seven runs. Among the other 104 runs, the MFIFO algorithm results in an energy violation rate smaller than that of the FIFO algorithm for 81 runs. All together, the MFIFO schedules result in a smaller energy violation rate for 88 runs and a same energy violation rate for 112 runs. The simulation results verify that the MFIFO algorithm improves the energy performance of the FIFO algorithm and maintains the timing performance at the same time.

The simulation setup is slightly modified to quantitatively compare the energy violation rates of the FIFO and MFIFO algorithms. The duty cycles of the six periodic tasks take the same value for each utilization. The utilization is *U* = 6 \* *DC*, where DC is the duty cycle. The duty

**4.3. Evaluation results**

176 Supercapacitor Design and Applications

This chapter proposes the MFIFO algorithm for nonpreemptable tasks with precedence constraints. The task precedence constraints are transformed into timing constraints by defining the effective release time of a task. The MFIFO algorithm takes into account the energy constraints of tasks in addition to the timing constraints. The MFIFO algorithm is implemented and evaluated. Simulation results show that the MFIFO algorithm improves the energy performance of the FIFO algorithm and maintains the timing performance at the same time.

## **Author details**

Hengzhao Yang1\* and Ying Zhang2

\*Address all correspondence to: hengzhao.yang@csulb.edu

1 Department of Electrical Engineering, California State University Long Beach, Long Beach, CA, USA

2 School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA

## **References**


[11] H. Yang, Y. Zhang, Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications, Journal of Power Sources 196 (20) (2011) 8866–8873.

**Author details**

178 Supercapacitor Design and Applications

CA, USA

GA, USA

**References**

Hengzhao Yang1\* and Ying Zhang2

Papers 55 (6) (2008) 1742–1750.

Papers 56 (11) (2009) 2519–2528.

in: ISLPED '06, 2006, pp. 197–202.

on Power Electronics 24 (2009) 510–517.

IPSN '05, 2005, pp. 463–468.

\*Address all correspondence to: hengzhao.yang@csulb.edu

1 Department of Electrical Engineering, California State University Long Beach, Long Beach,

2 School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta,

[1] S. Sudevalayam, P. Kulkarni, Energy harvesting sensor nodes: Survey and implications,

[2] C. Alippi, C. Galperti, An adaptive system for optimal solar energy harvesting in wireless sensor network nodes, IEEE Transactions on Circuits and Systems I, Regular

[3] T. Zhu, Z. Zhong, Y. Gu, T. He, Z.-L. Zhang, Leakage-aware energy synchronization for

[4] D. Brunelli, C. Moser, L. Thiele, L. Benini, Design of a solar-harvesting circuit for batteryless embedded systems, IEEE Transactions on Circuits and Systems I: Regular

[5] F. Simjee, P. H. Chou, Everlast: Long-life, supercapacitor-operated wireless sensor node,

[6] X. Jiang, J. Polastre, D. Culler, Perpetual environmentally powered sensor networks, in:

[7] H. Yang, Y. Zhang, Modeling and analysis of hybrid energy storage systems for wireless sensor networks, in: Proceedings of SPIE, Vol. 7647, 2010, pp. 76472U:1–76472U:10.

[8] B. E. Conway, W. Pell, T.-C. Liu, Diagnostic analyses for mechanisms of self-discharge of electrochemical capacitors and batteries, Journal of Power Sources 65 (1997) 53–59.

[9] Y. Diab, P. Venet, H. Gualous, G. Rojat, Self-discharge characterization and modeling of electrochemical capacitor used for power electronics applications, IEEE Transactions

[10] Y. Zhang, H. Yang, Modeling and characterization of supercapacitors for wireless sensor network applications, Journal of Power Sources 196 (8) (2011) 4128–4135.

IEEE Communications Surveys & Tutorials 13 (3) (2011) 443–461.

wireless sensor networks, in: MobiSys '09, 2009, pp. 319–332.


## *Edited by Zoran Stevic*

In this book, authors investigated asymmetric and symmetric supercapacitor configurations for different electrode materials. Besides the already standard activated carbon (AC), studies were done with other materials and technologies for their preparation and activation. Also, the research info was presented with different electrolytes in order to obtain a higher capacitance and potential window, with as small as possible serial resistance. Achieved high performance enables wide application, and some of the new applications (spacecraft power systems, powering heart pacemakers and wireless sensors) are also described in this book.

Supercapacitor Design and Applications

Supercapacitor Design

and Applications

*Edited by Zoran Stevic*

Photo by structuresxx / iStock