Optimum Design on In-wheel Motor of New Energy Vehicles based on Improved Artificial Bee Colony Algorithm

Abstract

In order to improve the power density of the in-wheel motor and reduce its cost of materials. A multi-objective optimization method of in-wheel motor for electric vehicles (EV) is proposed based on an improved artificial colony algorithm. The new improved artificial colony algorithm is used to implement motor optimizing design with the geometry size and material parameters of motor as variables and the quality, cost and power consumption of the motor as the optimization goal. The results show that compared with conventional artificial colony algorithm, the convergence speed and global search ability of improved artificial colony algorithm is better and the quality, cost and power loss of optimized motor is relatively reduced, and the efficiency is improved.