Design optimization of Switched Reluctance Machine using Particle Swarm Optimization

This paper presents Particle Swarm Optimization (PSO) based design optimization of Switched Reluctance Machine (SRM). The SRM design is formulated as multiobjective constrained optimization problem. The objective functions for obtaining desired design are maximization of average torque and minimization of torque ripple with stator and rotor pole arc as design variables. The optimization procedure is tested on 8/6, four-phase, 5 HP, 1500 rpm SRM. The results are compared and investigated with those obtained from Genetic Algorithm (GA) technique and FEA simulation. The results demonstrate that the proposed method is effective and outperforms GA in terms of solution quality, accuracy, constraint handling and computational time.