Determination of current waveforms for torque ripple minimisation in switched reluctance motors using iterative learning: an investigation

The paper deals with the investigations on an iterative learning approach to determine the desired current waveforms for switched reluctance motors, which give rise to ripple-free torque. The current waveforms are generated by repeated corrections from iteration to iteration starting from the conventional rectangular pulse profile as the initial waveform. The scheme requires much less a priori knowledge of the magnetic characteristics of the motor. The algorithms have been formulated for both one-phase-on and two-phase-on schemes, for a four-phase switched reluctance motor, in the light of the principles behind iterative learning. Based on the observations from the simulation results of these schemes, a modified scheme has been proposed by incorporating a suitable commutation process, often called torque sharing functions, in order to generate reasonably smooth current waveforms for the ease of tracking by the stator circuit of the motor. The performances of all the proposed schemes have been verified by computer simulation.