Multi-objective optimization of efficient liquid cooling-based battery thermal management system using hybrid manifold channels

Abstract

Maintaining a battery cell at an optimal temperature improves both its performance and lifespan. This study proposes a cold plate equipped with hybrid manifold channels, positioned at the bottom of a high-capacity 280 Ah LiFeO4 battery pack. Based on the developed whole battery pack model, the response surface method elucidates the functional relationship between design parameters (i.e., the width of parallel channels, the width of manifold channels, the height of parallel channels, and the inlet velocity) and responses (i.e., the flow pressure drop, the temperature difference of the entire battery modules, and the temperature difference of the cold plate). Multi-objective optimization of design parameters is performed to search the Pareto front to maximize thermal performance and minimize flow pressure drop, employing the NSGA-II algorithm. Results reveal that the maximum battery temperature can be limited to 30.73–33.78 °C with a coolant pressure drop ranging from 7.66 kPa to 1.76 kPa, at a heating power of 10 kW/m3 for the battery cell. The optimal design configuration, identified through TOPSIS, limits the maximum battery temperature to an acceptable temperature of 45 °C at a discharging rate of 3C, with a pressure drop below 4.2 kPa. Compared to the 280 Ah LiFeO4 battery with natural air cooling and forced flow immersion cooling systems, the maximum battery temperature with a discharging rate of 1C is reduced by 17.6 °C and 11.7 °C, respectively.