Rotor and Stator Resistance Estimation of Induction Motor Based on Augmented EKF

被引:0
|
作者
Talla, Jakub [1 ]
Peroutka, Zdenek [1 ]
Blahnik, Vojtech [1 ]
Streit, Lubos [1 ]
机构
[1] Univ W Bohemia, Fac Elect Engn, Reg Innovat Ctr Elect Engn, Plzen 30614, Czech Republic
关键词
ARTIFICIAL NEURAL-NETWORKS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper deals with rotor and stator resistance estimation of induction motor (IM) drive based on augmented Extended Kalman Filter (EKF). The proper knowledge of rotor flux magnitude and flux position is a necessary condition for high performance induction motor control (Rotor Flux Field Oriented Control - RFOC etc.). The rotor flux estimator for RFOC is typically based on mathematical model of induction motor in dq coordinates, which are sensitive to rotor resistance value. The rotor and stator resistances are temperature dependent and could increase up to twice the nominal values. This paper deals with rotor flux estimator for induction motor without any temperature sensors. Whereas the EKF based methods commonly used the rotating reference frame based IM models, presented method is based on the stationary reference frame model of the IM. The augmented state space vector of EKF model of IM is used for rotor flux and rotor and stator resistances estimation. The paper consist of simulation as well as experimental results.
引用
收藏
页码:253 / 258
页数:6
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