Efficiency optimization of electric motors: A comparative study of stochastic algorithms

Abstract. This paper presents a comparative study of three popular, population based stochastic algorithms viz. Genetic Algorithms, Particle Swarm Optimization and Differential Evolution for maximizing the ef-ficiency of electric motors. The simulation results for a hypothetical textile mill load diagram show that although all the three algorithms gave more or less similar results in comparison to each other, their perfor-mance is better than the traditional techniques