Particle Swarm Optimization Approach for Optimal Design of Switched Reluctance Machine | Science Publications

American Journal of Applied Sciences

Mahadevan Balaji¹  Vijayarajan Kamaraj¹ 

关键词: Average torque;    genetic algorithm;    particle swarm optimization;    switched reluctance machine;    torque ripple;    finite element analysis;   

DOI  :  10.3844/ajassp.2011.374.381

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

Problem statement: Switched Reluctance Motors (SRMs) are widely used in variousapplications due to their inherent simplicity and rugged construction In SRM, torque output and torqueripple are sensitive to stator and rotor pole arcs and their selection is a vital part of SRM design process. Inthis study Particle Swarm Optimization technique is proposed for determining optimum pole arc of SRM.Approach: The problem of determining optimum pole arc is formulated as a multiobjective optimizationproblem with the objective of maximizing average torque and minimizing torque ripple. A comprehensiveprogram based on analytical model is developed in Matlab to compute the value of inductance and averagetorque. Results: The optimization procedure is tested on 8/6, four-phase, 5 HP, 1500 rpm SRM. The resultsare compared and investigated with those obtained from Genetic Algorithm (GA) technique and FiniteElement Analysis(FEA) simulation. Conclusion: The results demonstrate that the proposed method iseffective and outperforms GA in terms of solution quality, accuracy, constraint handling.

【 授权许可】

Unknown