Title :
Switched reluctance motor modeling with on-line parameter identification
Author :
Mir, S. ; Husain, I. ; Elbuluk, M.E.
Author_Institution :
Dept. of Electr. & Electron. Eng., Gen. Motors Res. Labs., Warren, MI, USA
Abstract :
A nonlinear model with on-line parameter estimation using recursive identification for switched reluctance motors (SRMs) is presented. The model is robust toward 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 simulations and experiments performed to test the model demonstrate the accuracy of estimation of the model.
Keywords :
machine theory; parameter estimation; position measurement; reluctance motors; rotors; nonlinear model; on-line parameter estimation; on-line parameter identification; parameter variations; position sensors; recursive identification; robust model; rotor position errors; self-tuning; switched reluctance motor modeling; system disturbances; AC machines; Industry Applications Society; Parameter estimation; Performance evaluation; Production; Reluctance machines; Reluctance motors; Robustness; Rotors; Torque control;
Journal_Title :
Industry Applications, IEEE Transactions on