文献类型：期刊文献

中文题名：基于柯西变异粒子群算法的永磁同步电机参数辨识

英文题名：Permanent Magnet Synchronous Motors Parameters Identification Based on Cauchy Mutation Particle Swarm Optimization

作者：傅小利[1,2];顾红兵[2,3];陈国呈[2,3];邹俊忠[1];张见[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237;[2]江苏斯达工业科技有限公司,常州213022;[3]上海大学机电工程与自动化学院,上海200072

年份：2014

卷号：29

期号：5

起止页码：127

中文期刊名：电工技术学报

外文期刊名：Transactions of China Electrotechnical Society

收录：CSTPCD;;EI(收录号：20142317791794);Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

语种：中文

中文关键词：永磁同步电机;参数辨识;粒子群优化;柯西变异

外文关键词：PMSM,parameter identification,particle swarm optimization,Cauchy mutation

摘要：永磁同步电机(PMSM)参数影响矢量控制伺服系统的性能,因而需要对电机参数进行实时辨识。将电机的定子等效成一阶惯性系统,并在d-q同步旋转坐标系下建立定子的数学模型。提出平均最好位置和柯西变异相结合的改进粒子群算法,对永磁同步电机定子绕组的电阻、电感和磁链进行辨识。仿真和实验结果表明该辨识方法寻优能力强,搜索精度高,稳定性好,具有良好的动态性能。
The variation of permanent magnet synchronous motor(PMSM) parameters has an effect on the performance of vector control servo system, so they must to be identified at real time. The stator is equaled to 1st order inertia system and the mathematical model is built under d-q coordinates. A particle swarm optimization(PSO) based on mean best position and Cauchy mutation combined search is proposed and used to identify the resister, inductor and flux linkage of the stator. Both the simulation and the experiment examples demonstrate that the proposed algorithm has powerful optimizing ability, good stability and higher optimizing precision and good performance.