Optimization of oil flow distribution inside the in-wheel motor assembly of electric vehicles for improved thermal performance

Abstract

The efficiency of an electric vehicle in-wheel motor depends largely on its thermal performance, which is contingent upon effective and active cooling. However, an experimental investigation of the in-wheel motor is challenging due to several factors, such as high-speed operational conditions and direct contact limitations. The present study aims to optimize the cooling oil flow distribution within the in-wheel motor assembly by varying the geometric parameters of the flow channel. A central composite design methodology was employed to develop the design of numerical analysis. A response surface analysis was conducted based on the computational results to formulate an empirical correlation. Finally, a multi-objective genetic algorithm was used to attain optimal design parameters of the in-wheel motor cooling channel. Moreover, the in-wheel motor assembly based on the optimal cooling channel design was numerically simulated to elucidate the influence of design parameters on the thermal performance of the motor at different operating conditions. The optimal design configuration leads to an overall improved heat dissipation at the maximum motor speed of 11000 rpm and reduced temperatures of critical in-wheel motor components such as bearings and resolvers by 8% and 6.4% respectively. Furthermore, average heat transfer enhancements of 0.1% and 8.1% over the direct spray cooling area and secondary spray cooling areas compared to the simple spray cooling configuration were observed at the maximum speed.