PHASE CHANGE MATERIAL-BASED INTELLIGENT THERMAL MANAGEMENT FOR HIGH-PERFORMANCE ELECTRIC VEHICLE BATTERIES

Abstract

The rapid expansion of high-performance electric vehicles has intensified the need for advanced battery thermal management systems capable of maintaining safe and uniform operating temperatures under fast charging, high discharge rates, aggressive driving conditions, and varying environmental conditions. Lithiumion batteries provide high energy density and favorable power characteristics, but their electrochemical performance, degradation rate, safety, and service life are strongly influenced by temperature. Conventional air- and liquidbased cooling methods can provide effective thermal control, yet they may increase auxiliary energy consumption, structural complexity, pumping requirements, and maintenance demands. Phase change materials offer a promising passive thermal management mechanism because they can absorb substantial quantities of transient heat through latent heat storage while maintaining the battery temperature within a comparatively narrow range. However, conventional phase change material systems suffer from limitations such as low thermal conductivity, delayed heat rejection, material leakage, insufficient adaptability to changing workloads, and reduced effectiveness during repeated thermal cycles. This paper proposes a phase change material-based intelligent thermal management framework for high-performance electric vehicle batteries by integrating composite phase change materials, distributed temperature sensing, battery operating data, intelligent thermal state assessment, adaptive cooling coordination, digital monitoring, and predictive control. The proposed methodology continuously acquires battery surface temperature, ambient temperature, current, voltage, charging rate, state of charge, and selected thermal indicators to determine emerging thermal risks. A composite phase change material layer absorbs transient heat around battery cells, while an intelligent supervisory mechanism evaluates spatial temperature distribution and coordinates auxiliary cooling only when passive heat absorption becomes insufficient. The framework supports real-time thermal monitoring, hotspot identification, predictive thermal risk assessment, and energy-aware cooling decisions. A representative performance analysis indicates that the proposed intelligent PCM-based configuration can reduce maximum battery temperature, improve cell-to-cell temperature uniformity, reduce auxiliary cooling demand, and enhance thermal stability compared with conventional passive and standalone cooling arrangements. The proposed approach provides a scalable foundation for safer, more energyefficient, and performance-oriented thermal management of next-generation electric vehicle battery packs.