Multi-objective Optimization of a Dual Stator Brushless Hybrid Excitation Motor based on Response Surface Model and NSGA2

In this paper, a dual stator brushless hybrid excitation machine (DSBHEM) is designed and analyzed, with high flux regulation, high torque output and low torque ripple. There are many design parameters of the DSBHEM, which lead to the contradiction of speed range, torque output and torque ripple. Therefore, a framework of multi-objective optimization method (MOOM) is proposed to improve the overall performance of the DSBHEM. Firstly, the sensitivity of the design variables is analyzed, and the critical variables are extracted, and the response surface model (RSM) is constructed. The Pareto solution set is obtained by non-dominated sorting genetic algorithms 2 (NSGA2), and the optimal design is selected. The performance comparison between the initial and the optimal design is carried out. Finally, a prototype machine is manufactured to verify its performance.