Sustainable Hybrid Battery Thermal Management Systems for EVs: Advances in Lithium-Ion Cooling Strategies and AI-Driven Control

Abstract Battery thermal management systems (BTMS) are essential for ensuring the safe, efficient, and reliable operation of lithium-ion batteries by regulating temperature and limiting electrochemical degradation. This article reviews recent sustainable advancements in BTMS, with a focus on hybrid cooling strategies and the integration of artificial intelligence (AI) and machine learning (ML). Conventional approaches -air cooling, liquid cooling, and phase change materials (PCMs) are evaluated in terms of performance and limitations.Hybrid configurations, particularly liquid cooling combined with PCMs, demonstrate superior thermal control, enhanced energy efficiency, and suitability for high-power applications. Studies indicate that such systems can reduce thermal stress by up to 35% and energy consumption by nearly 20%. In addition, the integration of battery management systems (BMS) with BTMS enables real-time monitoring, early fault detection, and maintenance of optimal operating temperatures, thereby improving battery health and lifespan.Furthermore, AI- and ML-based frameworks enhance BTMS through predictive thermal modeling, intelligent fault diagnosis, and adaptive control under varying conditions. These data-driven approaches can extend battery life by up to 30% and reduce the risk of thermal runaway by approximately 50%. Overall, the integration of hybrid cooling strategies with AI-driven control offers a scalable and sustainable pathway for improving the safety, efficiency, and durability of lithium-ion battery systems.