Modeling and design of shape optimized SRM with reduced ripple

Abstract

This paper describes the shape optimization and torque ripple minimization of switched reluctance machine (SRM) using genetic algorithm. In this paper, a novel method on the basis of genetic algorithm (GA) is proposed to reduce the torque dip, thereby reducing the associated torque ripple, with simultaneous reduction in size with increase in torque output using GA, by maximizing the flux linkage, torque per unit rotor volume and inductance ratio. The results are compared with that produced by a standard 8/6 pole, 4 phase SRM, The obtained results are encouraging and verified using finite element analysis (FEA).