Real time parameters estimation of an induction motor

This paper presents the implementation of a real time estimator for the mutual inductance and rotor resistance of an induction motor using an extended Kalman filter. Both digital computer simulation and laboratory experiments shown the good performance of the algorithm. The estimator for both rotor resistance and mutual inductance was implemented in an experimental test-bed integrated with a 1-HP squirrel-cage induction motor, an inertial and frictional load, a commercial PWM inverter, and a data acquisition system driven by the MATRIX-X package. The interesting features of the estimator are that: the method provides, using only one Kalman filter, estimations of the rotor current together with the identification of the parameters (mutual inductance and rotor resistance); the system does not require special test signals since the PWM inverter generates significant harmonics itself; the measurements required are stator current and rotor speed which could be either constant or time varying; the assumed standard induction motor model is expressed in d-q rotor coordinates; the covariance matrices of the filter play an important role in the design; since the model of the system is nonlinear the matrices have to be chosen in such a way that the convergency of the estimator is achieved; and the real time Kalman filter could be useful for the design of self-tuning drives, routine electrical tests and failure diagnostics in the electric part of the motor