Improving the Efficiency of Switched Reluctance Motors of Electric Cars Using Sigmoid Torque Sharing Function

Abstract

in this study, based on Genetic Algorithm (GA) a novel approach for torque ripple minimization for the switched reluctance motors was presented, the fitness function is assigned with three objectives, firstly to eliminate the backward torque generation, and to optimize the commutation angles in order to minimize the torque ripples and copper losses, the torque sharing functions (TSF) depends on the turn-on-, turn-off-, rise-, fall- angles, the lagging of the motor current rise and fall, due to its salient pole shaped structure requires different treatment, as they are not always at unity, angles are to be optimized to achieve the best outcome in the commutation region of operation.