Optimal cabin thermal management strategy for battery life extension in electric vehicles

In recent years, the transportation sector has witnessed a shift away from traditional combustion-based propulsion, driven by growing concerns over air pollution and climate change. Among the multitude of emerging technologies, battery electric vehicles (BEVs) have emerged as a prominent and highly supported solution. However, despite their increasing popularity, questions persist regarding their practical benefits in the current scenario. Challenging aspects are electric energy mix, battery longevity, and BEVs driving range. In this context, the following project aims to improve battery durability in BEVs. Then, to achieve this target, the main focus is on the Heating Ventilation and Air Conditioning (HVAC) unit, the most impacting auxiliary in terms of battery loads. Specifically, this system handles the cabin's thermal conditions in order to fulfill the passengers comfort request. In the literature efforts attempting to face similarly this problem can be evidenced, i.e. [3] , [4], [8]. Building upon these previous works, our aim was to develop a simplified solution that could potentially be implemented and executed in real-time. The proposed Integrated Energy and Thermal Management (IETM) strategy effectively minimizes the battery degradation rate at each instant. The IETM controller intelligently allocates battery power to the HVAC system, ensuring both thermal comfort and traction power needs as required by the driver. The key innovations in this model turn around the battery's State of Health (SOH) model, which relies on real data from A123 26650 battery cells tested to the end of their lifespan. This provides a realistic foundation for estimating the benefits of the IETM strategy. An important part for the project involved the implementation of a realistic model for the cabin thermodynamics, the HVAC system layout and its respective control logic. After the assessment of all the models and after checking the effectiveness of the IETM controller, the results about the advantages brought by the intelligent allocation of power to the HVAC were quantified over both WLTP cycle and EPA (UDDS and HWFET) drive schedules. Our findings demonstrated both reduced battery degradation and a positive impact on energy consumption. The improvements due to the IETM controller, depending on the cabin comfort settings, ranged from 3.1 % to 4.5 % in terms of battery capacity degradation reduction and from 0.5 % to 2.8 % in energy consumption improvement. At the end of this work, also the results found by using the IETM controller together with the eco-driving controller, namely Cooperative Adaptive Cruise Control (CACC), developed within the same comprehensive project are given. They evidence a slightly dependency for the IETM controller on the CACC, but the total benefits are almost the exact sum of the two. Future research could involve real-time assessment of the IETM strategy using onboard vehicle systems. Additionally, an analysis can be conducted to spot which are the most impacting inputs to be predicted for finding the best benefits by using the IETM controller, i.e. solar radiation, external temperature and so on.