基于遗传算法的高速永磁电机联合仿真优化

Co-Simulation Optimization of High Speed Permanent Magnet Synchronous Motor Based on Genetic Algorithm and TOPSIS Method

为提升高速永磁同步电机(HSPMSM)优化效率与电磁性能,提出一种基于遗传算法和TOPSIS法的HSPMSM联合仿真优化方法。首先,借助ANSYS Maxwell有限元仿真软件对HSPMSM进行参数化建模,进一步建立4极30槽HSPMSM的Maxwell&Workbench&Optislong联合仿真模型;其次,运用遗传算法对电机进行全局多目标优化得到Pareto解集,使用优劣解距离法(TOPSIS)从解集中客观选取最优高速永磁同步电机设计方案;最后,对比优化设计前后高速电机的各项性能,仿真结果表明采用遗传算法和TOPSIS法不但提升了高速电机多目标优化效率,且有效削弱电机转矩脉动和齿槽转矩,电机转矩脉动从6.21%降低至2.96%,电机齿槽转矩从0.341 N·m降低至0.052 N·m,降低了85%。

To improve the optimization efficiency and electromagnetic performance of HSPMSM.This paper presents an optimization method of HSPMSM co-simulation based on genetic algorithm and TOPSIS method.Firstly,parametric modeling of HSPMSM was carried out with ANSYS Maxwell finite element simulation software.Furthermore,the Maxwell&Workbench&Optislong co-simulation model of HSPMSM with 4 poles and 30 slots was established.Secondly,the Pareto solution set is obtained by using genetic algorithm for global multi-objective optimization.The optimal design scheme of high speed permanent magnet synchronous motor was selected from solution set by using TOPSIS method.Finally,the performance of the high speed motor before and after the optimal design is compared.The simulation results show that the genetic algorithm and TOPSIS method can not only improve the multi-objective optimization efficiency of high speed motor.And effectively weaken the motor torque ripple and groove torque.Motor torque ripple decreased from 6.21%to 2.96%.The motor groove torque is reduced by 85%from 0.341 N·m to 0.052 N·m.