Parametric study on thermal management system for the range of full (Tesla Model S)/ compact-size (Tesla Model 3) electric vehicles

Abstract

Electric vehicle is slowly taking over the market share of internal combustion engine vehicle around the globe and range extension study turns into a one key research area. Electric vehicle thermal management system plays a large role in driving range, whereas existing literature mainly focus on component level and lack the vehicle level range analysis. This study conducts a parametric study on the vehicle level thermal management and its impacts on the range of two vehicles (full size - Tesla Model S/ compact size – Tesla Model 3). Vehicle level thermal system model is built considering air conditioning refrigerant loop, indirect battery liquid cooling loop, and cabin cooling air loop. In addition, vehicle propulsion system model is built and utilized in the range simulation. Five feedback controllers are designed for the thermal management system to control the temperature of battery pack, cabin climate, condenser subcool, evaporator superheat, and chiller superheat. Various factors are considered in the parametric study including air conditioning system on/off switch, vehicle size, driving cycle, ambient temperature, cabin target temperature, and battery pack target temperature. In the results analysis, the performance of five feedback controllers is evaluated in step response and a driving cycle. Energy consumption of aerodynamic drag, rolling resistance, thermal management, regenerative braking, and auxiliary load are discussed in the parametric study. The results show that turning air conditioning system on could potentially reduce the EV range by 38–45 % at city driving condition. In addition, Ambient temperature shows significant nonlinear impact on EV range and the impact gets worse as temperature turns higher. For Tesla Model 3, when the ambient temperature rises from 30 °C to 35 °C and then to 40 °C, the range drops by 3.3 % and 13.4 %, respectively. Compared with ambient temperature, cabin temperature and battery pack temperature settings have less impact on the range. The code utilized in this study is made open source via Github (https://github.com/binxuAI/EV_TMS), which can be utilized as the guidance in the thermal management range impact analysis and concept design of electric vehicle.