Application of an extended Kalman filter to parameter identification of an induction motor

Abstract

An extended Kalman filter is used to identify the parameters of an induction motor using measurements of the stator voltages, currents, and rotor speed. A model of the induction motor in the state space and the Kalman filter algorithm are shown. This filter is applied to the parameter identification of an inverter-fed induction motor. A simple and practical method of setting the covariance matrices of the noises, which are important in the Kalman filter algorithm, is proposed. The starting values of the state and parameter vectors as well as the covariance matrix of the estimation error are then shown, and, finally, the results of parameter identification are shown. The results demonstrate that the filter is capable of identifying the parameters.< >