Optimization Design of Permanent Magnet Synchronous Motor Based on Multi-Objective Particle Swarm Optimization Algorithm

Permanent Magnet Synchronous Motors (PMSMs) are characterized by high power density, strong overload capability, high efficiency, and compact size. To enhance the torque performance of PMSMs, an optimization design method combining response surface model with Multi-Objective Particle Swarm Optimization (MOPSO) is proposed. First, the main dimensions of the motor are determined based on the requirements of the motor, followed by the selection of the structural type. The initial structural model of the motor is established using finite element software. Subsequently, sensitivity analysis is performed based on key dimensional parameters. Based on the sensitivity levels of these parameters, a response surface model is developed for highly sensitive parameters, and a multi-objective genetic optimization algorithm is applied for further optimization. Finally, a comparative analysis of the torque performance between the optimized and initial motor is conducted, demonstrating the effectiveness and feasibility of the proposed method.