基于改进扩展卡尔曼滤波的PMSM在线参数辨识  

PMSM online parameter identification method based on improved extended Kalman filter

作　　者：李英春[1] 侯金明 王培瑞 LI Yingchun;HOU Jinming;WANG Peirui(College of Electrical and Control Engineering,Shaanxi University of Science&Technology,Xi’an 710021,China)

机构地区：[1]陕西科技大学电气与控制工程学院,陕西西安710021

出　　处：《中国测试》2022年第11期47-53,共7页China Measurement & Test

基　　金：国家自然科学基金资助项目(59493300);教育部博士点基金资助项目(9800462)。

摘　　要：为解决永磁同步电机多参数辨识过程中辨识精度较小、收敛速度慢的问题,设计一种基于扩展卡尔曼滤波的在线参数辨识方法。首先,结合永磁同步电机数学模型,采用Popov超稳定理论设置自适应律,经过模型参考自适应算法辨识出电机实时转动惯量;其次,将转动惯量送入扩展卡尔曼滤波模块,最终实现电机电感和磁链的在线辨识,引入的转动惯量能够实时更新修正电感与磁链的辨识结果。Matlab仿真表明:所提出的方法收敛速度快、误差较小且稳定性好,在负载变化时能够实时修正辨识结果。所设计系统辨识误差小于1%,验证其可行性。In order to solve the problems of low identification accuracy and slow convergence speed in the process of multi-parameter identification of permanent magnet synchronous motors,an online parameter identification method based on extended Kalman filter is designed.First,combined with the mathematical model of the permanent magnet synchronous motor,the Popov ultra-stable theory is used to set the adaptive law,and the real-time moment of inertia of the motor is identified through the model reference adaptive algorithm;secondly,the moment of inertia is sent to the extended Kalman filter module to finally realize the motor inductance and on-line identification of flux linkage,the introduced moment of inertia can update and correct the identification results of inductance and flux linkage in real time.Matlab simulation shows that the proposed method has fast convergence speed,small error and good stability,and it can correct the identification results in real time when the load changes.The experimental results show that the identification error of the designed system is less than 1%,which verifies its feasibility.

关 键 词：永磁同步电机 模型参考自适应 扩展卡尔曼滤波 参数辨识 

分 类 号：TM341[电气工程—电机]