Weight optimization of axial flux dual air-gap permanent magnet brushless DC motor for electrical vehicle

Abstract

This paper presents weight optimization of axial flux dual air-gap permanent magnet brushless dc motor based on genetic algorithm optimization technique for an electric vehicle application. First, the initial motor design is carried out as per calculated motor rating based on vehicle dynamics and application requirements. Design of a permanent magnet motor is a complex and nonlinear process involving various design variables. Genetic algorithm based optimization technique is proposed for weight minimization of axial flux permanent magnet brushless dc motor. Optimization with an objective of minimum motor weight is performed. Three-dimensional finite element analysis is executed to authenticate the proposed genetic algorithm based weight optimization. The optimization technique is elucidated with necessary flowchart. Close agreement between results obtained from finite element analysis and analytical design establishes the correctness of the proposed optimization technique. It is analysed that the weight of dual air gap axial flux PMBLDC motor is reduced considerably using GA based design optimization.