Design and Double-Stage Optimization of Synchronous Reluctance Motor for Electric Vehicles

Abstract

In this study, a high-power synchronous reluctance motor (SynRM) was designed for the traction motor of electric vehicle (EV) and its double-stage optimization was performed. Genetic algorithm and sensitivity analysis methods were used to obtain the best design parameters of the SynRM. Double-stage optimization was carried out to minimize the torque ripple and obtain the targeted torque, speed, and power values of the SynRM. In the first stage, the genetic algorithm method was used to improve the design parameters of the stator and rotor. With the improved stator and rotor design parameters obtained using this optimization technique, it was observed that the torque ripple decreased. In the second stage, the sensitivity analysis method was used. In this method, the effect of changing the skew angle of the stator on the torque ripple was investigated. The magnetic and performance analyses of the designed motor were examined in the optimization process. Analyses were made by ANSYS Maxwell using the finite element method (FEM). It has been observed that the targeted torque, power, speed, efficiency, and torque ripple minimization values are successfully achieved when the performance analysis of the motor is performed using the best stator and rotor parameters obtained through optimization. The results showed that SynRM produces high torque and high power with high efficiency and low torque ripple over a wide speed range. It has been revealed that it is quite proper to use the designed SynRM as a traction motor of new generation electric vehicles.