Multi-objective optimization of external rotor permanent magnet motor based on enhanced whale algorithm

Abstract

Abstract In order to improve the output torque, suppress the torque ripple, and reduce the usage of permanent magnets when applying the external rotor permanent magnet synchronous motor (ERPMSM) as a belt conveyor drive motor, this paper proposed a multi-objective optimization method for ERPMSMs based on the enhanced multi-objective whale algorithm (E-MOWOA), parameter stratification and response surface methodology (RSM). Firstly, a finite element simulation model of the motor was established, and parameter stratification was carried out through Spearman correlation analysis to screen out the layer 1 and layer 2optimization parameters. Secondly, various improvement strategies were introduced for the traditional whale algorithm, and an E-MOWOA improvement strategy was proposed. The effectiveness of the algorithm improvement was verified through algorithm performance testing. Then the multi-objective optimization of parameters were carried out. For the layer 1 optimization parameters, the response surface method was adopted to establish a response surface model, provide regression equations, and use E-MOWOA for iterative optimization. For the layer 2 optimization parameters, parameterized scanning was used for optimization. Finally, a comparative analysis of the optimization effect was conducted through finite element simulation experiments and prototype experiments. The experimental results showed that after optimization, the average output torque of the motor was increased by 4.19%, the cogging torque was reduced by 22.92%, the torque ripple was reduced by 31.34%, the amplitude of the no-load back electromotive force fundamental wave was increased by 13.39%, and the cost of the permanent magnet was reduced by 7.83%, which verified the effectiveness and feasibility of the proposed method.