An iterative learning approach to torque ripple minimization in switched reluctance motors

Switched reluctance motors are rapidly becoming popular because of their simple construction, ease of maintenance, low cost and high efficiency. However, because of its highly nonlinear nature of torque production mechanism, high torque ripple is generated with the conventional rectangular pulse excitation scheme. This paper deals with the preliminary investigations on the use of iterative learning to determine the current waveforms so as to minimize the torque ripple. The scheme requires much less a priori knowledge of the magnetic characteristics of the motor. The strategies have been formulated for both one-phase-on and two-phase-on schemes. The performance is verified with a four-phase switched reluctance motor by computer simulation. Copyright (C) 1998 IFAC.