Thermal management of Li-ion batteries: Experimentally validated model of active temperature control strategies with liquid cooling and multi-objective optimization

In the last decade, electric vehicles (EVs) have gained considerable attention in the transport sector as they represent a valid solution for reducing CO₂ emissions in the short term, contributing to the achievement of net zero emissions by 2050. Despite the technology of EVs has reached a good level of reliability, challenges related mainly to the Li-ion storage systems and to their thermal management, are still open. A properly designed battery thermal management system (BTMS) is intended to maintain the lithium battery within its optimal temperature range to preserve its cycle-life durability, performance, and safety. Research efforts are, therefore, addressed to improve and optimize thermal management solutions for vehicle battery packs.

In this work, an active indirect liquid BTMS for a Li-ion cell is designed and developed with the main goal of satisfying the thermal requirements of the storage cell, by also focusing on an optimal balance between BTMS performance and overall system efficiency. In particular, a laboratory test bench was designed and set-up to allow experimental tests focused on parameter identification/validation of an electro-thermal simulation model of the cell and on its temperature management.

Experimental tests and simulations were performed for different environmental temperatures and electric operating conditions. In particular, the proposed BTMS was analyzed during both cooling and heating operations showing a good behavior in managing the coolant flow rate to achieve the temperature set-point. Starting from the validated simulation model, an off-line multi-objective optimization procedure was carried out to properly set up the temperature control parameters on real driving conditions.

The obtained results show a good level of reliability of the proposed simulation models in fitting the electro-thermal behavior of the cell under tests in different operative conditions. In addition, the BTMS can properly manage the coolant flow rate to achieve the temperature set-points. Finally, the proposed optimization procedure allows a relevant reduction in the pump energy consumption in comparison with non-optimized solutions.