A Comparative Study of Intelligents Algorithms for Optimizing Lithium-ion Battery Thermal Management Systems

Abstract

Controlling the temperature of lithium-ion batteries, also known as BTMS (Battery Thermal Management System), has become a crucial factor in guaranteeing their smooth operation, safety and lifespan, particularly in demanding fields such as electric vehicles and energy storage devices. To meet the thermal challenges posed by these batteries, several avenues have been explored. On the one hand, there are classic methods based on thermal modelling and analytical optimization, and on the other, more modern approaches involving intelligent algorithms. The smart algorithms, often supported by artificial intelligence and advanced optimization techniques, open up new prospects for improving the efficiency and precision of thermal control systems. It is interesting to note that in 2023, research work in this field saw a sharp increase, with growing interest in solutions incorporating AI. This study proposes a comparative analysis of these intelligent approaches applied to BTMS, based on data from the Web of Science database.