华南理工大学学报(自然科学版) ›› 2016, Vol. 44 ›› Issue (4): 28-33,54.doi: 10.3969/j.issn.1000-565X.2016.04.005

• 动力与电气工程 • 上一篇    下一篇

基于两段卡尔曼滤波的感应电机无位置传感器控制

张金良1,2 康龙云1,2 陈凌宇1 姚远1   

  1. 1. 华南理工大学 电力学院,广东 广州 510640; 2. 广东省绿色能源技术重点实验室,广东 广州 510640
  • 收稿日期:2015-06-08 修回日期:2015-12-08 出版日期:2016-04-25 发布日期:2016-04-12
  • 通信作者: 张金良(1985-) ,男,博士生,主要从事感应电机无传感器技术研究. E-mail:zjl.cyz@163.com
  • 作者简介:张金良(1985-) ,男,博士生,主要从事感应电机无传感器技术研究.
  • 基金资助:
    国家自然科学基金资助项目( 51377058, 61104181)

Position Sensorless Control of Induction Machines Based on Two-Stage Kalman Filtering

ZHANG Jin-liang1,2 KANG Long-yun1,2 CHEN Ling-yu1 YAO Yuan1   

  1. 1.School of Electric Power,South China University of Technology,Guangzhou 510640,Guangdong,China; 2.Key Laboratory of Clean Energy Technology of Guangdong Province,Guangzhou 510640,Guangdong,China
  • Received:2015-06-08 Revised:2015-12-08 Online:2016-04-25 Published:2016-04-12
  • Contact: 张金良(1985-) ,男,博士生,主要从事感应电机无传感器技术研究. E-mail:zjl.cyz@163.com
  • About author:张金良(1985-) ,男,博士生,主要从事感应电机无传感器技术研究.
  • Supported by:
    Supported by the National Natural Science Foundation of China( 51377058, 61104181)

摘要: 传统的扩展卡尔曼滤波算法已经被广泛地应用在感应电机无位置传感器控制系统中,但其存在运算量大的问题,尤其是应用于感应电机这种多阶、强耦合的系统时. 为了解决这一问题,文中引入一种与原算法数学模型上等效的两段式扩展卡尔曼滤波算法到感应电机无位置传感器控制中. 在两相静止坐标系下,取定子电流和转子磁链为全阶状态量,以转子电角度及角速度为状态增广量,以此设计两段式扩展卡尔曼滤波算法. 实验结果表明,相比传统卡尔曼滤波算法,该算法在保持与原算法相同参数辨识性能的情况下,能够有效地减少运算时间.

关键词: 感应电机, 无位置传感器控制, 两段式扩展卡尔曼滤波

Abstract: The conventional extended Kalman filtering ( EKF) algorithm has been widely applied to the position sensorless control of induction machines ( IM) .However,heavy computational burden may accompany with EKF,especiallyfor the IM with a high-order and strong-coupling mathematical model.In order to solve this problem,a novel control algorithm using the two-stage extended Kalman filtering ( TEKF) ,which is mathematically equivalent to the conventional EKF algorithm,is proposed.In this algorithm,the stator current and the rotor flux linkage in the stationary reference frame are taken as the full-order state variables,and the rotor electrical angle and angular speed are used as the augmented system state variables.Experimental results show that the proposed algorithm can effectively save the operation time without degrading the parameter identification performance of the conventional EKF algorithm.

Key words: induction machine, position sensorless control, two-stage extended Kalman filtering