Multiobjective Differential Evolution-Based Performance Optimization for Switched Reluctance Motor Drives

The simple structure, low manufacturing cost, rugged behavior, high torque per unit volume, and wide torque-speed range make a switched reluctance motor (SRM) very attractive for industrial applications. However, these advantages are overshadowed by its inherent high torque ripple, acoustic noise, and difficulty to control. The controlled parameters in SRM drives can be selected as the turn-on angle, the turn-off angle, and the current reference. This paper investigates the problem of optimal control parameters considering the maximum average torque, minimum copper losses, and minimum torque ripple as the main objectives in SRM drives. The use of evolutionary algorithms (EAs) to solve problems with multiple objectives has attracted much attention recently. Differential evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. A multiobjective DE (MODE) technique is introduced here to find the optimal firing angles under multiple operating conditions. The simulation results carried out on a 4-phase 8/6 pole SRM show that the proposed MODE can be a reliable alternative for generating optimal control in the multiobjective optimization of SRM drive systems.