Design Optimization of Axial Flux Surface Mounted Permanent Magnet Brushless DC Motor For Electrical Vehicle Based on Genetic Algorithm

Abstract

This paper presents the design optimization of axial flux surface mounted Permanent Magnet Brushless DC motor based on genetic algorithm for an electrical vehicle application. The rating of the motor calculated form vehicle dynamics is 250 W, 150 rpm. The axial flux surface mounted Permanent Magnet Brushless DC (PMBLDC) motor was designed to fit in the rim of the wheel. There are several design variables e.g. air gap flux density, slot loading, magnet spacer width, ratio of outer to inner diameter, air gap length, current density and space factor). The main contribution in the present work is to propose the best combination of design variables obtained using genetic algorithm (GA) optimization technique and design of motor based on optimized design variables. Final validation is carried out with the help of 3-D finite element analysis (FEA) for GA based constraint and unconstraint design. The entire procedure based on GA is explained with the help of block diagram. Efficiency of the axial flux surface mounted PMBLDC motor is enhanced from 88.15 to 91.5 % using GA based design optimization. Proposed optimization technique and methodology will be useful for performance improvement of any nonlinear engineering design involving various design variables for specific application.