Optimization of Cogging Torque of Hybrid Excitation Motor Based on Genetic Algorithm and TOPSIS Method

Abstract

Aiming at the problem that the cogging torque of tangential magnetizing parallel structure hybrid excitation synchronous motor (TMPS-HESM) increases sharply with the increase of the excitation current. According to the generation principle of cogging torque, the feasibility of changing the rotor pole shoe width, magnetic pole eccentricity and air gap length to reduce cogging torque is discussed. With the help of Maxwell & Workbench & Optislong co-simulation software, the model of 8-pole 48-slot TMPS-HESM is established. The genetic algorithm is used for global multi-objective optimization. After the pareto optimal solution set is obtained, the optimal solution is selected objectively by using the superior and inferior solution distance method (TOPSIS). Finally, the other performances before and after optimization are researched. The results show that the use of genetic algorithm and TOPSIS method to optimize the motor parameters can improve the efficiency of multi-objective optimization. It not only solves the problem of the sharp increase in cogging torque caused by the increase of the excitation current of the TMPS-HESM, but also effectively weakens the torque ripple. The average torque is improved.