Simultaneous Estimation of Speed and Rotor Resistance in Sensorless Induction Motor Vector Controlled Drive

Abstract

In this paper a new sensorless indirect vector controlled induction motor drive robust against rotor resistance variation is presented. The speed and rotor resistance are estimated simultaneously, which is reported in many papers as impossible. The estimation is achieved using a reduced order Kalman filter to reduce the computational burden. This algorithm uses a reduced order model of the motor. The model takes into account the coupling between the electrical and mechanical modes, which is true for small size machines. The method proposed in this paper is applicable to a large category of induction motor drives with a gradually varying load torque such as viscous friction, fan/blower and centrifugal pump. A fully real-time digital simulation, a new powerful tool for rapid control prototyping, is carried out to verify the effectiveness of the proposed method. Results show that accurate estimation is achieved under both transient and steady state conditions without injecting any external signal. This achievement is, to the best of authors' knowledge, reported for the first time and is believed to be of great importance for induction machine sensorless control.