Design optimization of axial flux permanent magnet brushless DC micromotor using response surface methodology and bat algorithm

Abstract

This paper presents design optimization technique of Axial Flux Permanent Magnet (AFPM) Brushless DC (BLDC) micromotor. The objective of the optimization process is to minimize the motor volume and improve joules efficiency with the constraints of minimum required torque and maximum back EMF using response surface modeling and Bat Algorithm (BA). Finite element computations have been used for numerical experiments on geometrical design variables in order to evaluate the coefficients of a second-order empirical model for the response surface representation. BA is used as an optimization technique to minimize volume and improve joules efficiency in separate optimization problem in terms of design variables. The optimization results were compared with other metaheuristic algorithms, including Genetic Algorithms (GA), and Particle Swarm Optimization (PSO). The bat algorithm shows a potential competitive against GA and PSO.