Sensorless-estimation of induction motors in wide speed range

Purpose - The purpose of this paper is to improve performance in the estimation of velocity and flux in the sensorless control of induction motors (IMs) over a wide speed range, including low and zero speed. Design/methodology/approach - Temperature and frequency dependent variations of stator (R_s) and rotor (R'_r) resistances are very effective on estimation performance in sensorless control over a wide speed range. To this aim, an extended Kalman filter (EKF) is designed, which estimates the stator resistance, R_s, load torque, t_L, velocity and flux. To provide robustness against R'_r variations, the extended model is also continuously updated with R'_r values from a look-up table, built via EKF estimation. Findings - As demonstrated by the experimental results, the estimated states and parameters undergo a very short transient and attain their steady-state values accurately, with no need for signal injection due to the inherent noise introduced by EKF. Originality/value - The value of this study is in the development of an EKF-based scheme, which solves the R _s-R'_r estimation problem in IM sensorless control. The successful experimental results obtained with the combined EKF and look-up table approach also offer a solution to all EKF-based estimation schemes which involve a high number of estimated parameters, hence, compromising estimation accuracy.