Multi-objective optimization of an air cooling battery thermal management system considering battery degradation and parasitic power loss

The battery thermal management system (BTMS) can effectively ensure that the batteries work in a safe temperature range and solve the problems caused by high temperature. This paper investigates an air cooling BTMS with 32 cylindrical lithium-ion batteries (LIBs). Previous BTMS studies pay little attention to cost, this work focuses on the economic cost to address the cost problem caused by the parasitic power consumption of BTMS. First, the battery degradation model is established, and the cycle life of the battery is determined through capacity loss. Second, the computational fluid dynamics (CFD) simulation is used to study the influence of design parameters on the maximum temperature (MT) of the battery module and the pressure drop. Then, this study proposes to use cyclical cost (including battery cycle life and parasitic power loss) to evaluate the economy. The MT and cyclical cost are simultaneously considered as the optimization objectives to form an optimization model via the surrogate model method. Finally, two multi-objective optimization algorithms are used to drive the optimization process. The results suggest that the MT drops from 314.58 K to 314.22 K, while the cyclical cost drops from 0.92 €/cycle to 0.85 €/cycle, a reduction of 7.6 %. The developed method could improve the economy while ensuring the heat dissipation performance of the battery, which provides guidance for the design of BTMS to meet the needs of consumers.