Control-Oriented Model for Thermal Energy Management of Battery Electric Vehicles

This paper presents a control-oriented thermal model for a novel heating, ventilation, and air conditioning (HVAC) system with a heat pump designed specifically for battery electric vehicles (BEVs). The model is validated through high-fidelity simulations from GT-SUITE, achieving a root mean square error of$1.54 \,%$for cabin air temperature and$0.70 \,%$for battery temperature. The model is used for exploring energy reduction strategies. Optimal results demonstrate a$5.7 \,%$decrease in energy consumption during a cool-down scenario in high ambient temperatures. The usage of the model is showcased in a cabin thermal pre-conditioning problem where the vehicle is not occupied for an interval of600 \,sbetween two drives. Results show that the ability to predict occupancy and optimally manage cabin temperature could reduce energy usage by$12.9 \,%$, compared to maintaining cabin temperature at the same level. Another example examines the impact of predicted data uncertainty and the result shows that it is more energy-efficient to maintain cabin thermal comfort instead of turning off the HVAC system when the likelihood of passenger arrival is uncertain and exceeds approximately$60 \,%$of the predicted non-occupied interval.