4. Experimental results and discussions

OR-SRM has been manufactured by using motor sizes optimized via MOGA. The motor at manufacturing stage is given in Figure 12. OR-SRM is cooled via cooling channels shown in Figure 12 as the forced circulation air cooling. A nematic air dryer compressor is used to cool the OR-SRM. Thus, the temperature of the motor is prevented by these cooling channels to reach too high levels. Therefore, the changes in the winding resistance are minimized. Its negative effect on the efficiency is also reduced.

The manufactured OR-SRM is shown in Figure 13.

In this study, asymmetric half-bridge converter is designed and used to feed OR-SRM. A capacitor charged and discharged by switching IGBT is connected between the battery and

Figure 12. Stator windings of OR-SRM at manufacturing stage.

Figure 13. Manufactured OR-SRM.

converter. According to different speeds and reference currents, trigger angles of each phase winding are calculated. The trigger angles are correlated to the speed, battery voltage, reference current, and rotor position.

In this paper, we have proposed an optimum solution satisfying the torque and efficiency of OR-SRM via MOGA considering constrains of EV dynamics. The efficiency and torque values are the components of objective function. Torque density has not been involved in the objective function since the package length and outer diameter are specified to fit into 21-inch wheel rim. The solution of torque ripple problem might be considered by varying trigger angles in motor control stage rather involving it during OR-SRM design stage, which is well-known motor control method. As a future work, torque ripple will be involved in multi-objective

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In this study, a direct drive OR-SRM mounted in wheel is designed and manufactured for the subject EV. The dimensional and electrical parameters of 18/12 OR-SRM for EV have been calculated by multi-objective evolutionary algorithm. The mathematical equations derived by geometry of OR-SRM have been used to get results from objective functions resided in fitness

optimization function via analysis of dynamic solution.

Figure 15. Comparison of Maxwell 3D and experimental results.

5. Conclusion

Figure 14. OR-SRM test bed.

To compare the estimated torque obtained by Maxwell 3D and that of the manufactured motor, locked rotor experiment has been carried out. Herein, torque rate is measured by torque sensor mounted on tested while streaming the coil current, 75 A by locking OR-SRM rotor at designated positions.

Test bed of OR-SRM is shown in Figure 14. OR-SRM is loaded with an induction motor controlled by the direct torque control driver. Torque sensor is used for measuring torque of OR-SRM. The features of torque sensor have very short construction, broad input voltage range, current, and output voltage; the measurement accuracy is less than 0.5% of full scale; and measurement ranges change from 5 to 500 Nm. The control algorithm is run by dSPACE DS1103. Hall-effect current and voltage sensors are used for measuring motor phase and battery currents and battery voltage.

The comparison of Maxwell 3D and experimental results have been drawn in Figure 15.

Average rate of relative errors between Maxwell 3D and experimental results is estimated as 2.248%, for the angles at designated positions.

Outer Rotor SRM Design for Electric Vehicle without Reducer via Speed-Up Evolutionary Algorithm http://dx.doi.org/10.5772/intechopen.74451 147

Figure 14. OR-SRM test bed.

Figure 15. Comparison of Maxwell 3D and experimental results.

In this paper, we have proposed an optimum solution satisfying the torque and efficiency of OR-SRM via MOGA considering constrains of EV dynamics. The efficiency and torque values are the components of objective function. Torque density has not been involved in the objective function since the package length and outer diameter are specified to fit into 21-inch wheel rim. The solution of torque ripple problem might be considered by varying trigger angles in motor control stage rather involving it during OR-SRM design stage, which is well-known motor control method. As a future work, torque ripple will be involved in multi-objective optimization function via analysis of dynamic solution.

#### 5. Conclusion

converter. According to different speeds and reference currents, trigger angles of each phase winding are calculated. The trigger angles are correlated to the speed, battery voltage, refer-

To compare the estimated torque obtained by Maxwell 3D and that of the manufactured motor, locked rotor experiment has been carried out. Herein, torque rate is measured by torque sensor mounted on tested while streaming the coil current, 75 A by locking OR-SRM rotor at

Test bed of OR-SRM is shown in Figure 14. OR-SRM is loaded with an induction motor controlled by the direct torque control driver. Torque sensor is used for measuring torque of OR-SRM. The features of torque sensor have very short construction, broad input voltage range, current, and output voltage; the measurement accuracy is less than 0.5% of full scale; and measurement ranges change from 5 to 500 Nm. The control algorithm is run by dSPACE DS1103. Hall-effect current and voltage sensors are used for measuring motor phase and

The comparison of Maxwell 3D and experimental results have been drawn in Figure 15.

Average rate of relative errors between Maxwell 3D and experimental results is estimated as

ence current, and rotor position.

Figure 13. Manufactured OR-SRM.

146 New Trends in Electrical Vehicle Powertrains

Figure 12. Stator windings of OR-SRM at manufacturing stage.

battery currents and battery voltage.

2.248%, for the angles at designated positions.

designated positions.

In this study, a direct drive OR-SRM mounted in wheel is designed and manufactured for the subject EV. The dimensional and electrical parameters of 18/12 OR-SRM for EV have been calculated by multi-objective evolutionary algorithm. The mathematical equations derived by geometry of OR-SRM have been used to get results from objective functions resided in fitness

function. The vehicle dynamics, five independent variables of motor dimension, and the constraints including outer diameter and package length of the motor are employed by evolution algorithm. The multiparameters including stator and rotor pole arc angles, their yoke lengths, and inner diameter of rotor are optimized using objective functions such that the highest efficiency for deserved torque is obtained. Consequently, we can obviously suggest that this approach could be conducted to design a standard-type OR-SRM.

[4] Asgar M, Afjei E, Behbahani A, Siadatan A. A 12/8 double-stator switched reluctance motor for washing machine application. In: IEEE 6th Power Electronics, Drives Systems &

Outer Rotor SRM Design for Electric Vehicle without Reducer via Speed-Up Evolutionary Algorithm

http://dx.doi.org/10.5772/intechopen.74451

149

[5] Tursini M, Villani M, Fabri G, Di Leonardo L. A switched-reluctance motor for aerospace application: Design, analysis and results. Electric Power Systems Research. 2017;

[6] Öksüztepe E. In-wheel switched reluctance motor design for electric vehicles by using a pareto-based multiobjective differential evolution algorithm. IEEE Transactions on Vehic-

[7] Santiago JD, Bernhoff H, Ekergard B, Eriksson S, Ferhatovic S, Waters R, Leijon M. Electrical motor drivelines in commercial all-electric vehicles: A review. IEEE Transac-

[8] Xue XD, Cheng KWE, Cheung NC. Selection of electric motor drivers for electrical vehicles. In: IEEE Power Engineering Conference, AUPEC'08; Australasian Universities;

[9] Wenping C, Mecrow BC, Atkinson GJ, Bennett JW, Atkinson DJ. Overview of electric motor technologies used for more electric aircraft (MEA). IEEE Transactions on Industrial

[10] Rahman KM, Fahimi B, Suresh G, Rajarathnam AV, Ehsani M. Advantages of switched reluctance motor applications to EV and HEV: Design and control issues. IEEE Trans-

[11] Ramu K. Switched Reluctance Motor Drives: Modeling, Simulation, Analysis, Design,

[12] Miller TJE. Electronic Control of Switched Reluctance Machines. U.S.: Elsevier, Newnes;

[13] Yildirim M, Polat M, Oksuztepe E, Omac Z, Yakut O, Eren H, Kaya M, Kurum H. Designing in-wheel switched reluctance motor for electric vehicles. In: IEEE 16th International Power Electronics and Motion Control Conference and Exposition (PEMC); 2014.

[14] Sengor I, Polat A, Ergene LT. Design and analysis of switched reluctance motors. In: IEEE 8th International Conference on Electrical and Electronics Engineering (ELECO); Nov.

[15] Sakthivel P, Chandrasekar V, Arumugam R. Design of a 250w, low speed switched reluctance hub motor for two wheelers. In: IEEE 1st International Conference on Electrical

[16] Koibuchi K, Ohno T, Sawa K. A basic study for optimal design of switched reluctance motor by finite element method. IEEE Transactions on Magnetics. 1997;33(2):2077-2080

and Applications. U.S.: CRC Press, Taylor and Francis Group; Dec, 2017

Technologies Conference (PEDSTC); 2015. pp. 168-172

ular Technology. 2017;66(6):4706-4715

Electronics. 2012;59(9):3523-3531

tions on Vehicular Technology. 2012;61(2):475-484

actions on Industry Applications. 2000;36(1):111-121

Energy Systems (ICEES); Jan. 2011. pp. 176-181

142:74-83

2008. pp. 1-6

2001

pp. 793-798

2013. pp. 586-590
