Parametric study and optimization on novel fork‐type mini‐channel network cooling plates for a Li‐ion battery module under high discharge current rates

Summary When a lithium‐ion battery works under high current, its working temperature is easy to exceed the allowable working temperature, resulting in the decrease of battery life. This may cause the non‐uniformity of the internal working temperature of the battery and affect the working parameters of the battery. Therefore, an effective thermal management system is needed to enhance the thermal performance of the battery, improve the work efficiency, and extend the service life of the battery. In this study, we propose a new type of fork type mini‐channel cooling plate based on genetic optimization algorithm to reduce the working temperature of battery and obtain better thermal uniformity. First, the thermal performance of co‐current type cooling plates is experimentally and numerically studied. The heat transfer ability of cross flow cooling plates used to cool the Li‐ion Battery is evaluated by parametric method. Second, a multi‐objective genetic algorithm optimization is finally performed, considering the balance of the maximum value for temperature and pressure drop. Compared with the previous study, the reduction of temperature difference of this cooling plate can be up to 2°C. In contrast, the pressure drop penalty and thermal resistance of the optimized cooling plates can be reduced by 20% and 40%, respectively. Thirdly the thermal performance of a battery module with eight battery cells is also examined numerically. The maximum ∆T of the battery pack among cells is 4.83°C for V = 48 mL/s, which implies that the battery pack can work normally. This study indicates that batteries with the proposed new cooling plates have much better temperature uniformity. To reduce the operating temperature of lithium battery and prolong the cycle life, we aim to propose a novel fork‐type mini‐channel network cooling plate, and the performance of cooling plate for the Li‐ion battery is experimentally and numerically studied. A multi‐objective genetic algorithm optimization is performed considering the balance of the maximum temperature and pressure drop. The results showed that the cooling plate kept the battery at a normal operating temperature.