电子科技2025，Vol.38Issue(9)：9-19,11.DOI:10.16180/j.cnki.issn1007-7820.2025.09.002
基于变遗忘因子递推最小二乘法的永磁同步电机电参数辨识
Electrical Parameter Identification of Permanent Magnet Synchronous Motor Based on Recursive Least Squares Method with Variable Forgetting Factor
摘要
Abstract
In view of the traditional RLS(Recursive Least Square)identification algorithm to online identify the electrical parameters of PMSM(Permanent Magnet Synchronous Motor),it is susceptible to the influence of"data saturation"and noise,and has the problems of low identification accuracy and poor anti-interference.A recursive least squares identification algorithm based on variable forgetting factor is adopted in this study,and the mechanism and method of resistor,flux and inductance identification based on recursive least squares algorithm are derived and established according to the voltage equations of the d and q axes.Based on the traditional algorithm,the"variable forgetting factor"which changes with the system working condition is introduced to eliminate the influence of data sat-uration and noise,and improve the identification accuracy of electrical parameters and the ability to resist load dis-turbance.In order to verify the correctness and effectiveness of the proposed method,simulation and experimental tests are carried out.The results show that the precision of resistance identification is 1.67％,flux identification is 1.13％and inductance identification is 0.61％.Compared with the traditional recursive least squares identification algorithm,the identification accuracy of each electrical parameter is higher,and the anti-interference is stronger.关键词
永磁同步电机/在线辨识/递推最小二乘/变遗忘因子/电参数辨识/抗干扰性/电气量/辨识精度Key words
permanent magnet synchronous motor/online recognition/recursive least square/variable forgetting factor/electrical parameter identification/anti-interference performance/electric capacity/identification accuracy分类
信息技术与安全科学引用本文复制引用
贝承荣,鲁文其,鲁玉军,董小艳,方狄永,岳伯伦,尤磊..基于变遗忘因子递推最小二乘法的永磁同步电机电参数辨识[J].电子科技,2025,38(9):9-19,11.基金项目
国家自然科学基金(52277068) （52277068）
浙江省科技厅重点研发计划(2024C01230,2023C01159,2022C01242)National Natural Science Foundation of China(52277068) （2024C01230,2023C01159,2022C01242）
The Key Research and Development Program of Zhejiang Science and Technology Department(2024C01230,2023C01159,2022C01242) （2024C01230,2023C01159,2022C01242）
