Predictive Analysis of EV Battery Cooling Using PCM and Hardware Implementation

Abstract

Electric-vehicle (EV) batteries require proactive cooling strategies to maintain safe operating conditions and extend service life. This paper introduces a predictive analysis framework that integrates hardware implementation with computational monitoring to evaluate the effectiveness of Phase Change Material (PCM) in thermal regulation. Unlike hardware-only studies, the proposed system anticipates temperature variations under dynamic load conditions, enabling timely activation of safety mechanisms. Experimental validation confirmed stable operation between 27.0°C–28.2°C under normal conditions and an average of 32.0°C–32.8°C under load, while predictive monitoring demonstrated PCM’s capacity to absorb approximately 18 kJ of heat and sustain a liquid fraction of 0.6 at 41°C. The combined approach highlights the importance of prediction in real-time battery safety, offering a scalable and intelligent solution for advanced EV thermal management systems