微特电机 ›› 2021, Vol. 49 ›› Issue (11): 7-13.

• 理论研究 • 上一篇    下一篇

基于A-FFRLS算法的永磁同步电机转动惯量辨识研究

田威, 张幽彤, 李建航   

  1. 北京理工大学 清洁车辆实验室,北京 100081
  • 收稿日期:2021-06-07 出版日期:2021-11-28 发布日期:2021-11-16
  • 作者简介:田威(1997—),男,硕士,研究方向为永磁同步电机高精度测试。

Research on Moment of Inertia Identification of Permanent Magnet Synchronous Motor Based on A-FFRLS Algorithm

TIAN Wei, ZHANG You-tong, LI Jian-hang   

  1. Low Emission Vehicle Research Laboratory,Beijing Institute of Technology, Beijing 100081, China
  • Received:2021-06-07 Online:2021-11-28 Published:2021-11-16

摘要: 转动惯量是永磁同步电机(PMSM)速度控制模型的关键参数,不同工况下其辨识值的准确与否直接影响控制器参数设定,进而影响电机调速系统的动态性能。针对传统转动惯量辨识策略存在的时效性差、精度低等问题,提出了一种自适应遗忘因子递推最小二乘法(A-FFRLS)的辨识算法。该算法使用遗忘因子递推最小二乘法(FFRLS)与模糊控制理论相结合的方式,使惯量辨识系统可以评估算法辨识结果与实际值之间的差距,并依据差距大小自适应调整遗忘因子值,使惯量估计值能够快速且准确的逼近真实值。仿真结果以及实验结果均证明,该算法在保证收敛速度的同时,能够有效提高辨识结果的精确性。

关键词: 永磁同步电机, 转动惯量辨识, 自适应遗忘因子递推最小二乘法, 模糊控制

Abstract: Moment of inertia is the key parameter of PMSM speed control model.The accuracy of its identification value under different working conditions directly affects the controller parameter setting, and then affects the dynamic performance of motor speed control system. Aiming at the problem of high delay and low accuracy, an adaptive forgetting factor recursive least square(A-FFRLS) method was proposed. Combining the forgetting factor recursive least squares (FFRLS) method with fuzzy control theory,the method could adaptively adjust the forgetting factor value according to the gap between estimate value and actual value of the moment of inertia, so as to approximate the true value quickly and accurately. Both the simulation results and the test results prove that the proposed method can effectively improve the accuracy of the identification results while ensuring the convergence speed.

Key words: permanent magnet synchronous motor(PMSM), moment of inertia identification, adaptive forgetting factor recursive least square(A-FFRLS)method, fuzzy control

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