Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (4): 28-33,54.doi: 10.3969/j.issn.1000-565X.2016.04.005

• Power & Electrical Engineering • Previous Articles     Next Articles

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)

PDF

259

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