Switched reluctance motor modelling with on-line parameter identification

Abstract

A nonlinear model with on-line parameter estimation using recursive identification for switched reluctance motors is presented. The model is robust towards parameter variations in the motor or any system disturbances. The parameters of the model are adjusted to account for errors in rotor position, which allows the use of crude inexpensive position sensors. The proposed modeling approach allows self-tuning of SRMs in a production unit. The model has been tested through simulation and experimentation, which demonstrated the accuracy of estimation of the model.