Cabin Heating Modelling and Simulation for ICE and EVs through 1D CAE

Abstract

<div class="section abstract"><div class="htmlview paragraph">India features diverse climatic zones, spanning from tropical in south to alpine in north. Since most of the regions are hot, vehicle cabin cooling analysis dominates over heating analysis, creating a notable technology gap that exists in cabin heating. Nonetheless, in colder regions of India and Europe, maintaining optimal cabin heating is crucial for human comfort. Furthermore, in climates prone to mist and frost formation, ensuring the accuracy and effectiveness of cabin heating mechanisms becomes crucial, as it directly correlates with safety considerations that comes prior to mere comfort requirements. To reduce the technology gap and physical testing in cold climatic conditions this work is proposed, which will enable us to predict cabin heating performance of vehicle on highway running as well as in stationary condition for Electric Vehicles (EV) and Internal Combustion Engine Vehicles (ICEV) in 1D Computer Aided Engineering (CAE) software. A detailed Transient Cabin Heating Model (T-CHM) has been developed with an accuracy of > 95%, to predict the temperatures of various components in a vehicle's heating system, including heater core, radiator, engine and Positive Temperature Coefficient (PTC) heater. This model can accurately predict the average temperatures in the vents and cabin during the critical phase when the vehicle is starting in cold climatic conditions. The robustness of model has been evaluated through comprehensive testing under various climatic conditions, with subsequent comparisons made against experimental data for vehicles and then temperatures are predicted for upcoming programs to optimize the components without extensive physical trials. This can be further enhanced for EVs by making an integrated circuit with battery heating and heat pump for efficient Heat Flux Management System (HFMS) which will enable us to predict and improve range of vehicles by minimizing separate power sources for thermal management and hence better energy utilization.</div></div>