| Abstract |
In this paper the extended Kalman filter theory is applied to the electrical parameter estimation of induction motors. This filter only uses machine quantities, which can be easily measured: the stator voltages and currents, and the rotor speed. The model of the induction motor is characterized by four parameters, which have to be simultaneously estimated. The filter settings are presented and discussed. These settings and the initial parameters set are deduced directly from the motor indicated characteristics. Experimental results show that the Kalman filter can perform a fast identification of the motor model. Then the model accuracy is evaluated by comparison of estimated and measured torque. Today the extended Kalman filter can be used as a parameter estimator for the tuning of the indirect field-oriented controller. Soon, it will also allow adaptive direct field-oriented control. |
