Modeling and simulation of phase change material-based passive and hybrid thermal management systems for lithium-ion batteries: A comprehensive review

Ensuring the efficient thermal management of lithium-ion batteries (LIBs) is crucial for enhancing their performance, safety, and longevity. Despite advancements in LIB technology, challenges persist in accurate heat generation modeling and effective temperature regulation, which are essential for preventing thermal runaway and ensuring battery reliability. This review comprehensively examines modeling and simulation approaches for phase change material-based passive and hybrid battery thermal management systems (BTMS). The study presents a detailed review of mathematical models and numerical techniques employed in LIB heat generation modeling, including simple thermal models and electrochemical-thermal models. Additionally, various thermal modeling methods of PCM such as the enthalpy-porosity model, apparent heat capacity model, and resistor-capacitor (RC) model are analyzed. The computational fluid dynamics (CFD) solvers, including ANSYS Fluent, COMSOL Multiphysics, and in-house numerical codes, are discussed to highlight their role in simulating heat transfer dynamics in BTMS. Key findings reveal that PCM-based BTMS can maintain battery temperatures within 20-50 degrees C while ensuring temperature uniformity (Delta T <= 5 degrees C), reducing peak temperature by up to 20 degrees C, and enhancing cycle life by 15-25 %. However, limitations such as low thermal conductivity (0.2-0.5 W/m & sdot;K), leakage issues, and long-term stability concerns require further advancements in PCM composites incorporating graphite, graphene, carbon nanotubes, and metal foams. The review also evaluates hybrid BTMS configurations, including PCM-air, PCMliquid, and PCM-heat pipe systems, comparing their thermal performance, structural complexity, and energy efficiency. Finally, this study highlights key research gaps and future directions, including the development of high-performance PCM composites, optimized hybrid BTMS for fast charging, AI-driven thermal management, and comprehensive experimental validation.