**1. Introduction**

Transportation accounts for more than 25% of the world energy demand and consumes more than 60% of the oil used each year. Transportation is completely relied by almost 95% on the petroleum products. Lack of fossil fuel supplies and the negative greenhouse effect on the environment have motivated automotive engineers to fabricate new car generations to cope the fuel consumption and emissions issues. Hybrid vehicles are now a new product of the automobile industry. Such vehicles are becoming more impressive as they are very efficient and reduce pollution. Hybrid vehicles offer a great improvement on the air quality emissions for vehicles that are empowered by gasoline.

Hybrid electric vehicles (HEVs) are the type of hybrid vehicles and electric vehicles which combine the best features of internal combustion engines (ICEs) and electric motors (EMs).

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Hybrid vehicles can perform with much less emission and can save 50% less fuel than the other new conventional vehicles in the same class. Modern hybrid vehicles can now recharge the electrical power from the regenerative braking process and store the electrical energy from the electrical plug-in at outdoor parking locations using renewable energy resources. Hybrid electrical vehicles can completely remove the idle emissions by shutting down the combustion engines and restart them when running.

There are many advantage reasons for using the combination of ICEs and EMs over ICEs alone: EMs can stop completely during the ICEs idle period. EMs can use much less energy than ICEs in low speed (less than 50 km/h) where most of vehicles have to operate in cities. While ICE vehicles can operate better only on the highways with high speed (above 50 km/h) since the ICEs achieve higher level of power-to weight ratio. Therefore, the main advantage of ICEs is on the higher power that can provide to vehicles. Then, the combination of ICEs and EMs can maintain the optimal operation in both low speed on busy roads and high speed on highways. The ICEs can automatically turn on and recharge the batteries for EMs when they get low.

A distinction of HEVs can be divided into two main types: the serial type and parallel types. In the serial type, the ICEs are not mechanically connected to the vehicle powertrain, but they are used only to run the electrical generator to supply the electrical power to batteries for EMs. The EMs now can use the electrical energy from their batteries to propel the vehicle. In the parallel type, both ICE and EM power sources are independently operated; therefore, they can both individually or commonly propel the vehicles. The most general configuration is that the ICE and EM are connected by an automatically controlled clutch. For the EM driving in low speeds, the clutch between the ICE and the EM is open and only the EM runs the vehicle. In high speeds, this clutch is closed and the ICE is started and propelled the vehicle while the EM is stopped off. At very high speeds or at critical heavy loads, this EM can be automatically activated on to support the ICE to drive the vehicle. To conclude, serial hybrids are less efficient and are more suitable for short-distance travel before exhausting their batteries. However parallel hybrids fuel consumption is greater than serial hybrids; gas/diesel engine has domi‐ nating role in parallel hybrids and thus battery pack can have less capacity. More information about parallel hybrids in the literature can be referred in [1, 2], and [3] references.

Initial approaches to switch the transition between EM and ICE power sources were drawn on heuristic information on the characteristics of ICEs vs EMs. In reference [4], rule-based was used and in reference [5], fuzzy logic was used as typical controlled schemes. A set of rules was applied to separate the requirements between the two power sources. These control plans were introduced in the early hybrid implementations. However [4] and [5] did not fully investigate the fuel use optimization. The dynamic engagements of the clutch between the ICE and the EM must be controlled as smooth as possible at the right time of engagement. For the safety and comfort reasons, the clutch engagement and the torque transmission are not permitted to cause any unacceptable acceleration or exceeded jerk. Several other control strategies for smothering the clutches engagement have been attempted including the back stepping control in reference [6], the optimal control in the reference [7], and the model predictive control in reference [8] to achieve faster and smoother clutches engagement between ICE and EM. In our research, a new predictive model for controlling the speeds of ICEs and EMs is developed and applied to the engagement of the clutches, which can help to enhance the driving comfort and reduce the jerk on the parallel HEVs.

Hybrid vehicles can perform with much less emission and can save 50% less fuel than the other new conventional vehicles in the same class. Modern hybrid vehicles can now recharge the electrical power from the regenerative braking process and store the electrical energy from the electrical plug-in at outdoor parking locations using renewable energy resources. Hybrid electrical vehicles can completely remove the idle emissions by shutting down the combustion

There are many advantage reasons for using the combination of ICEs and EMs over ICEs alone: EMs can stop completely during the ICEs idle period. EMs can use much less energy than ICEs in low speed (less than 50 km/h) where most of vehicles have to operate in cities. While ICE vehicles can operate better only on the highways with high speed (above 50 km/h) since the ICEs achieve higher level of power-to weight ratio. Therefore, the main advantage of ICEs is on the higher power that can provide to vehicles. Then, the combination of ICEs and EMs can maintain the optimal operation in both low speed on busy roads and high speed on highways. The ICEs can automatically turn on and recharge the batteries for EMs when they get low.

A distinction of HEVs can be divided into two main types: the serial type and parallel types. In the serial type, the ICEs are not mechanically connected to the vehicle powertrain, but they are used only to run the electrical generator to supply the electrical power to batteries for EMs. The EMs now can use the electrical energy from their batteries to propel the vehicle. In the parallel type, both ICE and EM power sources are independently operated; therefore, they can both individually or commonly propel the vehicles. The most general configuration is that the ICE and EM are connected by an automatically controlled clutch. For the EM driving in low speeds, the clutch between the ICE and the EM is open and only the EM runs the vehicle. In high speeds, this clutch is closed and the ICE is started and propelled the vehicle while the EM is stopped off. At very high speeds or at critical heavy loads, this EM can be automatically activated on to support the ICE to drive the vehicle. To conclude, serial hybrids are less efficient and are more suitable for short-distance travel before exhausting their batteries. However parallel hybrids fuel consumption is greater than serial hybrids; gas/diesel engine has domi‐ nating role in parallel hybrids and thus battery pack can have less capacity. More information

about parallel hybrids in the literature can be referred in [1, 2], and [3] references.

Initial approaches to switch the transition between EM and ICE power sources were drawn on heuristic information on the characteristics of ICEs vs EMs. In reference [4], rule-based was used and in reference [5], fuzzy logic was used as typical controlled schemes. A set of rules was applied to separate the requirements between the two power sources. These control plans were introduced in the early hybrid implementations. However [4] and [5] did not fully investigate the fuel use optimization. The dynamic engagements of the clutch between the ICE and the EM must be controlled as smooth as possible at the right time of engagement. For the safety and comfort reasons, the clutch engagement and the torque transmission are not permitted to cause any unacceptable acceleration or exceeded jerk. Several other control strategies for smothering the clutches engagement have been attempted including the back stepping control in reference [6], the optimal control in the reference [7], and the model predictive control in reference [8] to achieve faster and smoother clutches engagement between ICE and EM. In our research, a new predictive model for controlling the speeds of ICEs and

engines and restart them when running.

28 New Applications of Electric Drives

The main motivation of using the model predictive control (MPC) scheme in this chapter is the ability of the MPC to determine the optimization actions online in both linear and nonlinear systems. Model predictive control involves new mathematic algorithms that calculate an infinite sequence of input and output variables in order to optimize the future behavior of the systems. To date, MPC strategy can be found in many application areas including aerospace, automotive and petrochemical industries as referred in reference [9]. One of the advantages of MPC is its ability to cope with constraints from the open-loop optimal control problems. Achieving solution from the general constrained nonlinear models within an infinite predic‐ tion sequence becomes impractical because the numerical means to solve these problems can be only applied for a finite horizon length in order to obtain a real-time numerical solution. Therefore, only a finite moving horizon regulator can be considered in which the optimal problem is performed over a finite prediction sequence, and the prediction cost after the end of the horizon is estimated from a terminal penalty as shown in reference [10]. For ensuring the stability within a finite prediction length, most of the nonlinear model predictive control (NMPC) strategies have used a terminal constraints region at the end of the prediction length as indicated in references [11, 12], and [13]. Another NMPC method using a terminal con‐ straints region named quasi-infinite horizon that guarantees the asymptotic closed-loop stability with the input constraints was developed in reference [14]. But then the nonlinear systems have both input constraints and output constraints, many difficulties will arise to satisfy the output constraints because of constraints imposed already in inputs. Therefore, another NMPC method without a terminal constraint region is developed in reference [15] using the softened output constraints. Further investigation on MPC such as robust model predictive control (RMPC) that guarantees stability in the existence of the model uncertainty using linear matrix inequalities (LMIs) subject to both input and output saturated constraints was developed in reference [16]. In this RMPC,the controller will soften the output constraints as penalty terms and add into its objective function. These terms will keep the output violation at low values until the constrained solution is returned.

If there are too many input and output constraints, the controller may not be able to provide the desired outputs because the MPC regulator is designed for always on-line implementation, any infeasible solution of the optimization problem cannot be allowed. In order to assure the system stability, the conventional MPC strategies usually want to delete or ignore some output constraints from its objective function. Deletion of some output constraints will make the system looser and then the probability that MPC can achieve an optimal solution will increase. Similarly, the robustness of MPC can also increase if some output setpoints can be relaxed and a new MPC scheme, which turns the constrained setpoints into constrained regions was developed in reference [17]. In our research, the robustness of MPC schemes is also examined with both deleting and changing the output constrained setpoints into constrained regions. In this case, the outputs violation can be regulated by changing the penalty values of the weighting items.

Coming next, we briefly present the characteristics of some typical HEV configurations. After that, one typical HEV configuration will be selected for developing its dynamic equations. Then, several MPC scheme are built to control the speeds of the ICEs and the EMs for each part of this HEV. Simulation and calculated examples are also provided after each section to illustrate our main ideas for each section. Finally, some conclusions are drawn and some suggestions for the future research are discussed.
