压缩空气储能用永磁同步电机分析与优化设计OA

A permanent magnet synchronous motor(PMSM),as a core component of a compressed air energy storage system,operates for extended periods under conditions characterized by enclosed environments,wide speed ranges,and frequent start-stop cycles,resulting in high temperature rise and significant noise.Furthermore,its excessive torque ripple causes instability during the motor mode switching process,thereby leading to a decline in overall performance.To address these issues,an innovative coordinated optimization strategy integrating the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)and response surface methodology(RSM)was proposed.This approach took the cogging torque,losses,and torque ripple of the PMSM as the optimization objectives for multi-objective design.A high-precision two-dimensional transient electromagnetic field model of the motor was constructed based on the electromagnetic simulation platform.The magnetic-thermal coupling calculation method was introduced to simulate the motor's temperature field,using electromagnetic losses calculated by the finite element method as the heat source.The temperature rise under different operating conditions was investigated,and the temperature rise characteristics of the motor were verified.To address the interactions among various parameter variables,the NSGA-Ⅱ algorithm was used to seek Pareto front solutions to resolve conflicts in multi-objective optimization.The optimization algorithm was designed to identify the optimal combination rather than individual optimal values.The results showed that the cogging torque,torque ripple,and losses of the optimized motor were significantly reduced,and the temperature rise of the motor's key structural components was also decreased.