In-Wheel Switched Reluctance Motor Design for Electric Vehicles by Using a Pareto-Based Multiobjective Differential Evolution Algorithm

Abstract

In this paper, an in-wheel switched reluctance motor (IW-SRM) is designed by using a Pareto-based multiobjective differential evolution algorithm (PMODEA) for electric vehicles (EVs). The performance of the IW-SRM varies by the dimension parameters of the motor. Estimation of optimum motor dimensions is a multiobjective optimization problem. In dimension optimization of the IW-SRM for direct-driven EVs, torque, torque per motor lamination volume, and efficiency are specified as objective functions. The PMODEA is proposed for the solution of the multiobjective optimization problem as designing IW-SRM, and nondominant optimum solution set consisting of motor dimensions is obtained. This study provides flexibility to the decision maker, in selection of desired one from the existing solution set. The analysis of the selected motor is realized by considering optimum dimensions via the finite-element method (FEM). Then, the IW-SRM is manufactured, and then, the experimental results are obtained for static and dynamic analysis. FEM analysis results are compared with the experimental results. Eventually, it is observed that the results are satisfactory.