Simultaneous Optimization of Geometry and Firing Angles for In-Wheel Switched Reluctance Motor Drive



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Institute of Electrical and Electronics Engineers Inc.


Interests in using rare-earth free motors such as switched reluctance motors (SRMs) for electric and hybrid electric vehicles continue to gain popularity, owing to their low cost and robustness. Optimal design of an SRM, to meet specific characteristics for an application, should involve simultaneous optimization of the motor geometry and control in order to achieve the highest performance with the lowest cost. This paper presents a constrained multiobjective optimization framework for design and control of an SRM based on a nondominated sorting genetic algorithm II. The proposed methodology optimizes SRM operation for high volume traction applications by considering multiple criteria including efficiency, average torque, and torque ripple. Several constraints are defined by the considered application, such as the motor stack length, outer diameter, minimum operating power, minimum desired efficiency, rated speed, rated current, and supply voltage. The outcome of this optimization includes an optimal geometry, outlining variables such as air gap length, rotor inner diameter, stator pole arc angle, rotor pole arc angle, rotor back iron, stator pole height, and stator inner diameter as well as optimal turn-on and turn-off firing angles. Then the machine is manufactured according to the obtained optimal specifications. Comprehensive finite-element analysis and experimental results are provided to validate the theoretical findings. © 2017 IEEE.


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Electric vehicles, Automobiles, Finite element method, Genetic algorithms, Geometry, Hybrid electric vehicles, Magnetic devices, Rotors, Torque, Reluctance motors


©2017 IEEE