Multiobjective Design optimization of Axial Flux Permanent Magnet Brushless DC Micromotor Using Response Surface Methodology and Multi-Verse optimization Algorithm

This paper presents a multiobjective design optimization technique of Axial Flux Permanent Magnet (AFPM) Brushless DC (BLDC) micromotor. The two objectives of the optimization process are to minimize the micromotor volume and improve Joules efficiency with the constraints of minimum required torque and maximum required back EMF using response surface modeling and a novel Multi-Objective Multi-Verse optimization algorithm (MOMVO). Finite element computations are 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. The optimization results were compared with efficient multiobjective algorithm, the Non-Dominated Sorting Genetic Algorithm Version II (NSGA-II). The MOMVO algorithm shows a potential competitive against NSGA-II.