Akademik Veri Yönetim Sistemi
Energy, cilt.339, 2025 (SCI-Expanded, Scopus)
This study evaluates the immersion cooling performance of optimized modules consisting of forty-five 1.6 Ah 18650 cells and twelve 6 Ah 32700 LFP cells (total 230.4 Wh), using the corner-enhanced Latin Hypercube Sampling (LHS)-Multi-Objective Genetic Algorithm (MOGA) optimization under varying C-rates and flow rates based on thermal–flow criteria. A validated single-cell model provides the basis for module-level simulations. The results indicate that the optimized 18650 module achieves an 88.08 % reduction in pressure drop compared to its base design, accompanied by a slight increase in average temperature. The optimized 32700 module exhibits an 84.66 % decrease in pressure drop and provides a more uniform temperature distribution, despite a modest temperature rise. When compared directly, the 18650 module manages heat more effectively, while the 32700 module stands out with lower pressure losses and a smaller volume for the same power capacity. Under a 4C discharge rate and 0.1 kg/s flow rate, the average temperature in the optimized 18650 module reaches 303.18 K, whereas it stabilizes at 302.54 K under 1C and 0.001 kg/s. Corresponding pressure drops are 143.39 Pa and 1 Pa, respectively. For the optimized 32700 module, the average temperature under 4C and 0.1 kg/s is 307.03 K, decreasing to 304.11 K at 1C and 0.001 kg/s. Pressure drop values for this module are obtained as 64.73 Pa at 0.1 kg/s and 0.48 Pa at 0.001 kg/s. The findings confirm that cell and optimized design influence thermal behavior and flow resistance in immersion-cooled battery modules.