Thermal Modeling with Surrogate Model-Based Optimization of Direct Oil Cooling Heat Transfer Coefficient for HEV Motor

Abstract

The oil cooling system using automatic transmission fluid applied to the traction motor for driving the P2 hybrid electric vehicle prevents deterioration of the motor performance due to temperature rise. Predicting the nonlinear behavior of automatic transmission fluid scattered through the motor shaft is complicated to approach mathematically. Therefore, in this study, the correlation process of oil cooling heat transfer coefficient by automatic transmission fluid under specific load conditions is proposed, and kriging surrogate model-based optimizations are performed to predict the motor temperature through a direct oil-cooled lumped parameter thermal network. The configured oil-cooled thermal model has high accuracy for temperature prediction but requires expansion.