MULTI-OBJECTIVE OPTIMIZATION OF BATTERY COOLING EFFICIENCY AND THERMAL SAFETY

Abstract

The increasing performance requirements of electric vehicles (EVs) and advanced energy storage systems have created significant challenges in maintaining efficient battery cooling and thermal safety. Lithium-ion batteries generate considerable heat during charging, discharging, and high-power operations, which can lead to temperature imbalance, accelerated degradation, reduced efficiency, and safety hazards such as thermal runaway. Conventional battery thermal management systems generally focus on individual optimization objectives, such as reducing temperature rise or improving cooling efficiency, without considering the trade-off between energy consumption, thermal uniformity, and safety performance. This paper proposes a Multi-Objective Optimization Framework for Battery Cooling Efficiency and Thermal Safety that integrates advanced thermal management techniques, intelligent optimization algorithms, real-time battery monitoring, and predictive thermal analysis. The proposed framework simultaneously evaluates cooling performance, temperature distribution, energy consumption, battery lifespan, and safety conditions to achieve optimal thermal regulation. Machine Learningbased optimization techniques analyze battery operating parameters and recommend adaptive cooling strategies under different driving and charging scenarios. Experimental analysis demonstrates that the proposed approach improves cooling efficiency, reduces thermal gradients, enhances temperature stability, and strengthens battery safety compared with conventional thermal management strategies. The proposed framework provides an intelligent, scalable, and energy-efficient solution for next-generation electric vehicle battery thermal management systems. Keywords: Multi-Objective Optimization, Battery Cooling, Thermal Safety, Lithium-Ion Battery, Electric Vehicle, Thermal Management System, Machine Learning, Heat Transfer Optimization, Battery Safety, Intelligent Control.