Torque and ripple improving of a SR motor using robust particle swarm optimization of drive current and dimension

Abstract

In this paper, the robust optimization shape and drive of switched reluctance motors (SRMs) are discussed using robust particle swarm optimization (RPSO). The shape optimum goal of the algorithm was found for maximum torque value and minimum torque ripple, following changing the geometric parameters. The drive optimum aim of the algorithm was found minimum torque ripple, following changing the current profiles. The optimization process was carried out using a combination of RPSO and Finite Element Method (FEM). Fitness value was calculated by FEM analysis using COMSOL 4.2, and the RPSO was realized by MATLAB 2011. The proposed method has been applied to two case studies and also compared with seeker optimization algorithm. The results show that the optimized SRM using RPSO has higher torque value, lower torque ripple and higher robustness, indicating the validity of this methodology for SRM design and implementation.