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In previous work, AC Compressor Cycling (ACC) was modeled by incorporating evaporator thermal inertia in Mobile Air Conditioning (MAC) performance simulation. Prediction accuracy of >95% in average cabin air temperature has been achieved at moderate ambient condition, however the number of ACC events in 1D CAE simulation were higher as compared to physical test [1]. This paper documents the systematic approach followed to address the challenges in simulation model in order to bridge the gap between physical and digital. In physical phenomenon, during cabin cooldown, after meeting the set/ target cooling of a cabin, the ACC takes place. During ACC, gradual heat transfer takes place between cold evaporator surface and air flowing over it because of evaporator thermal inertia.

High temperatures in the surface mounted permanent magnet (SMPM) synchronous motor adversely affect the power output at the motor shaft. Temperature rise may lead to winding insulation failure, permanent demagnetization of magnets and encoder electronics failure. Prediction and management of temperatures at different locations in the motor should be done right at the design stage to avoid such failures in the motor. The present work is focused on the creation of Lumped Parameter Thermal Network (LPTN) and CFD models of SMPM synchronous motor to predict the temperature distribution in the motor parts. LPTN models were created in Motor-CAD and Simulink which are suitable for parameter sensitivity analysis and getting quick results. Air is assumed to be a cooling medium to extract heat from the outer surface of motor. CFD models were useful in providing elaborate temperature distribution and also locating the hot-spots. Correlation models by both the methods, viz.