Intelligent Phase Change Material Selection for Enhanced Electric Vehicle Battery Thermal Regulation

Abstract

Efficient battery thermal regulation is essential for improving the safety, performance, and service life of lithium-ion batteries used in electric vehicles. Phase Change Materials (PCMs) have gained considerable attention as passive thermal management media because of their high latent heat storage capability and ability to maintain battery temperatures within an optimal operating range. However, selecting the most suitable PCM requires simultaneous consideration of multiple thermal, physical, and operational characteristics. This paper presents an Intelligent Phase Change Material Selection framework integrating machine learning, multicriteria decision analysis, predictive thermal modeling, and cloud-based battery monitoring to identify optimal PCM materials for electric vehicle battery systems. The proposed methodology evaluates thermal conductivity, latent heat capacity, melting temperature, density, thermal stability, and battery operating conditions to optimize PCM selection. Experimental evaluation demonstrates improvements in thermal regulation, temperature uniformity, battery safety, cooling efficiency, charging performance, and battery lifespan. The proposed intelligent framework provides a scalable and data-driven solution for advanced battery thermal management in sustainable electric mobility.