Multi-objective optimization of an immersion hybrid preheating system for large-capacity lithium-ion batteries at low temperatures

Abstract

Low-temperature thermal management, which relies on high-efficiency preheating techniques to avoid performance attenuation and safety risks, is a critical bottleneck for the commercial application and stable operation of large-capacity lithium-ion battery energy storage systems. Herein, a novel immersion-based hybrid preheating system (IHPS) integrating dielectric immersion liquid convection and metallic thin-film conduction heating is proposed for low-temperature battery preheating. Comparative simulations show that the IHPS achieves higher heating rates than the two single-mode preheating strategies under the investigated conditions. Specifically, the battery temperature rise rate of the IHPS is 182.17%–229.94% higher than that of standalone immersion liquid preheating, and 62.27%–91.14% higher than that of independent metallic heating film preheating. Meanwhile, the IHPS reduces the heating-film electrical energy demand by 38.27%–47.62% compared with the single heating film scheme. To further balance preheating efficiency and battery module temperature uniformity, a complete multi-objective optimization design framework is established for the IHPS. The dominant structural and operational design variables are screened and quantitatively ranked via single-factor parametric analysis and global sensitivity analysis. Sequential global multi-objective optimization and local fine-tuning are conducted to obtain optimal system configurations. The optimized IHPS exhibits a 39.08%–135.62% enhancement in temperature rise rate and a 64.39%–77.38% reduction in maximum battery module temperature difference relative to the baseline prototype; the minimum battery module temperature difference reaches 2.94 °C after local parametric refinement. Finally, bench experiments are conducted for the three heating-film layouts under baseline operating conditions to evaluate the agreement between the numerical predictions and experimental measurements. For the tested baseline configurations, the maximum relative deviation in heating rate and maximum absolute deviation in average module temperature between experiments and simulations are 4.76% and 1.67 °C, respectively. This work provides a feasible design and optimization paradigm for rapid and thermally coordinated low-temperature preheating schemes with reduced heating-film electrical energy demand for large-capacity battery energy storage systems.