Advanced Lumped Parameter Thermal Network for Modeling of Cooling Solutions in Electric Vehicle Motor Applications

Electric motors used in electric vehicles (EVs) are robust, efficient machines capable of delivering a wide spectrum of torque across their drive cycle. Throughout their operation, inevitable losses are incurred within the power system, primarily in the form of heat energy, which is directly proportional to the square of the current. Managing this heat energy necessitates suitable cooling methods to effectively counteract the generated heat during operation. Thermal analysis serves as a predictive tool to anticipate and address these thermal challenges and is often executed through finite element analysis (FEA). However, the utilization of FEA comes with extended computation times, prompting the exploration of alternative thermal analysis methods like the lumped parameter thermal network (LPTN). Unlike FEA, LPTNs do not face significant reconstruction time issues during the design stage, presenting an advantage in the development of motors. Presented is an enhancement to the conventional LPTN design while broadening the scope of the motor design process by introducing an LPTN cooling model. The objective is to implement this model in the early stages of electromagnetic design, particularly focusing on cooled housing development. Additionally, a case study involving a 13 kW induction motor (IM) was conducted through experimental testing to validate the proposed LPTN model.