Performance optimisation of axial flux permanent magnet brushless DC motor for electric vehicle application with the genetic algorithm (GA) approach

Abstract

This paper presents the multi-objective performance optimisation of an axial flux permanent magnet brushless dc motor for electric vehicle application. An axial flux brushless motor is designed for direct drive application in electric two-wheelers. It is quite important to improve the efficiency and weight simultaneously, hence multi-objective optimisation is performed. The efficiency and weight of the motor are two opposite performance parameters hence it is a challenging task to improve both simultaneously. The main contribution of the present work is to propose the best combination of design variables obtained using the genetic algorithm optimisation technique. The proposed technique is validated with finite element analysis. The proposed optimisation technique is effective in performance improvement of axial flux brushless dc motors and practically implementable. The novelty of the proposed work is performance improvement without increasing manufacturing complexity – cost and adopting new materials. The proposed optimisation technique can be useful for multi-objective performance improvement of any nonlinear design involving various design variables.