Multi-Objective Optimization of Concentrated Flux Interior Permanent Magnet In-wheel Motor with Distributed Winding

In this article, the multi-objective optimization method is proposed to improve the torque density for the concentrated flux double-layer interior permanent magnet (IPM) motor, which enhances the efficiency of the optimization processes. Firstly, the sensitivity analysis of stator and rotor parameters is performed, and some key optimization parameters are obtained. Then, the average torque and torque ripple agent models are constructed by using the response surface method (RSM). Besides, the optimal parameters are acquired based on the non-dominated sorting genetic algorithm (NSGA-II). In addition, the electromagnetic performance of the initial and optimal motors are compared, including air-gap flux density, back electromotive force (back-EMF), average torque, and torque ripple. Finally, a 75kW prototype is manufactured and tested to verify the proposed optimization method.