永磁直流电动机参数的粒子群算法优化设计

Optimization Design Parameters of Particle Swarm Algorithm on Permanent Magnet DC Motor

为提高永磁直流电动机实际运行性能,分析影响永磁直流电动机性能的主要可变设计参数,同时对电机优化设计中的优化目标、优化设计变量以及约束函数进行了研究。使用带有动态渐变惯性因子的粒子群法对电机的主要工作参数进行优化,同时与传统优化算法中正多面体法做出对比,使用VB软件完成了永磁直流电动机CAD系统优化设计模块的开发。优化结果显示,粒子群算法在电机参数的优化设计中有着较为良好的优化效果,永磁直流电动机运行效率得到了提高。

To improving the operate performance of permanent magnet DC motor, the main variable design parameters which affected the performance were analyzed, as well as, the motor optimization design in the optimization goal, optimiza- tion design variables and constraint functions were studied. PSO with dynamic gradient inertia factors was used to optimize the main working parameters and compared with the traditional regular polyhedron algorithm. VB software was used to complete the development of permanent magnet DC motor CAD system and optimization design module. The optimization results show that the PSO algorithm in the optimal design of the motor parameters has a relatively good optimization effect and its running efficiency is also improved.