Development and validation of lumped parameter thermal network model on rotational oil spray cooled motor for electric vehicles

The rotational oil-spray-cooling method with motor has recently attracted attention because of its compact design and cooling performance. Rotational oil-spray-cooled motors require high computational resources and manufacturing costs; therefore, a precise simulation model is required. In this study, an asymmetric lumped parameter thermal network (LPTN) model of a rotational oil-spray-cooling motor is developed. The heat loss is calculated using correlation equations and electro-magnetic analysis, and the internal temperature distribution of the motor is predicted using conjugate heat transfer and multiphase flow computational fluid dynamics (CFD) analysis. The temperature of the coil inside the motor is measured using experiments. The developed LPTN model determined that the temperature prediction errors of coil parts were 0.15% and 4.42% at the nominal and maximum speeds, respectively.