Multi-objective optimization of permanent magnet motor based on Improved Salp Swarm Algorithm and Spearman correlation

Abstract

In order to weaken the torque ripple caused by cogs torque and increase the output torque of permanent magnet synchronous motor, this paper proposes a multi-objective optimization method of permanent magnet synchronous motor based on Improved Multi-Objective Salp Swarm Optimization Algorithm (IMOSSA) and Spearman correlation analysis. Firstly, the improved strategy of Multi-Objective Salp Swarm Algorithm (MOSSA) was proposed, and the effectiveness of the improved algorithm was further verified by the performance test of the algorithm. Then, the motor simulation model was established, and the high correlation parameters were filtered out by Spearman correlation analysis. The response surface model was established by Response Surface Method (RSM), and the regression equation was given. The IMOSSA was used for iterative optimization. Through optimization, the experimental results show that under the premise of meeting the efficiency design requirements, the average output torque of the motor is increased by 21.35%, the torque ripple and cogging torque are reduced by 45.04% and 39.17% respectively, which verifies the effectiveness and feasibility of the proposed method.