Analysis and Multi-Objective Optimization Design of Permanent Magnet Vernier Motors

Permanent Magnet Vernier Motors (PMVMs) have become a research hotspot in the electric vehicle industry due to their unique magnetic gear effect and high torque density. However, under low-speed and high-torque operating conditions, PMVMs face issues such as torque ripple and cogging torque-induced vibration and noise, which severely impact the motor's performance and service life. To address these issues, a detailed mathematical model of the PMVM was first established and its working principle was analyzed. Sensitivity analysis of the structural parameters identified key parameters affecting electromagnetic torque performance. Subsequently, the Central Composite Design (CCD) response surface method and Multi-Objective Genetic Algorithm (MOGA) were applied to optimize these parameters, aiming to reduce torque ripple and cogging torque while enhancing the motor's efficiency and power density. The electromagnetic performance of the motor before and after optimization was verified using the finite element method. The results indicate that the optimized motor exhibits a smoother back electromotive force (EMF) waveform at the rated speed, with the total harmonic distortion reduced from 11.2% to 5.2%, significantly improving the motor's energy efficiency and operational stability.