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Optimization of Switched Reluctance Motor Drive Firing Angles Using Grey Wolf Optimizer for Torque Ripples Minimization

Switched reluctance motor (SRM) has various advantages which makes it an excellent candidate for many applications; nevertheless, its main drawback is torque ripples. This paper aims to enhance the SRM operation by reducing its torque ripples without the need for expensive and sophisticated physical changes in the motor materials or design. The SRM converter firing angles are optimized to produce the lowest possible torque ripples. The response surface method (RSM) is used to obtain the SRM optimization function that relates torque ripples with firing angles, and grey wolf optimizer (GWO) is used to minimize this function. The objective function convergence speed using the proposed GWO is compared with genetic algorithm (GA), and it is found to be faster than GA. Simulation and experimental results show the effectiveness of the proposed approach in enhancing SRM operation by providing the SRM converter firing angles that result the minimum feasible torque ripples.