EKF-based rotor and stator resistance estimation in speed sensorless control of induction motors

Abstract

The system parameters of induction motor (IM) vary significantly with different operating conditions. The temperature-dependent variation of the stator and rotor resistances, which induces a large estimation error on speed and flux, has been a critical issue for speed-sensorless control. To estimate simultaneous variations of the stator and rotor resistances in speed sensorless control of IMs under different operating conditions, an estimator is developed based on extended Kalman filter (EKF) technique. In order to resolve the instability issue of simultaneous estimation of stator and rotor resistances, the stator resistance is estimated via consideration of its temperature dependence and the thermal dynamics of the stator windings, whereas the rotor resistance is estimated as a constant state. Simulation results show that the EKF estimator, along with a controller developed based on the direct field-oriented control (DFOC) technique, achieves simultaneous estimation of the continuously changing resistances and maximum speed estimation error and speed control error of about 0.67%. The broken-bar phenomenon of rotor is also detected based on the rotor resistance estimation. Simulation results also display promising robustness to variation of system parameters, such as rotor and stator thermal time constants, which are not estimated by the proposed EKF algorithm.

Compensation of Current Sensor Faults in Vector-Controlled Induction Motor Drive Using Extended Kalman Filters

“…Of course, in the event of failure of all CSs, the only way to restore the stator current comes down to its estimation using an open-loop observer [9], such as a Virtual Current Sensor (VCS), proposed in [12], or flux-based observer [13]. When it comes to speed-sensorless structures, extended Kalman filters (EKFs) are commonly presented [16][17][18][19][20][21][22][23][24][25][26]. Surprisingly, in the literature known to the authors, there is only one work [14] where an EKF was proposed for the current reconstruction.…”

“…Unfortunately, there is a lack of more such solutions when it comes to current-sensorless structures. In the field of speed-sensorless structures, EKFs are often used to simultaneously estimate state variables and both resistances [16,17,[21][22][23][24][25][26]. Unfortunately, the simultaneous estimation of both resistances in one consistent algorithm increases the order of the EKF.…”

“…The higher the order of the estimator, the greater the tendency to lose its stability. In the literature, some solutions have been proposed to solve this problem [16,17,[21][22][23]. However, at the same time, the computation burden increases significantly.…”