Fin-Embedded PCM Tubes in BTMS: Heat Transfer Augmentation and Mass Minimization via Multi-Objective Surrogate Optimization

The rapid proliferation of electric vehicles (EVs) demands lightweight yet efficient battery thermal management systems (BTMS). The fin-embedded phase-change material energy storage tube (PCM-EST) offers significant potential due to its high thermal energy density and passive operation, but conventional designs face a critical trade-off: enhancing heat transfer typically increases mass, conflicting with EV lightweight requirements. To resolve this conflict, this study proposes a multi-objective surrogate optimization framework integrating computational fluid dynamics (CFD) and Kriging modeling. Fin geometric parameters—number, height, and tube length—were rigorously analyzed via ANSYS (2020 R1) Fluent simulations to quantify their coupled effects on PCM melting/solidification dynamics and structural mass. The results reveal that fin configurations dominate both thermal behavior and weight. An enhanced multi-objective particle swarm optimization (MOPSO) algorithm was then deployed to simultaneously maximize heat transfer and minimize mass, generating a Pareto-optimal solution. The optimized design achieves 8.7% enhancement in heat exchange capability and 0.732 kg mass reduction—outperforming conventional single-parameter designs by 37% in weight savings. This work establishes a systematic methodology for synergistic thermal-structural optimization, advancing high-performance BTMS for sustainable EVs.