Abstract
Maintaining the battery pack’s temperature in the desired range is crucial for fulfilling the thermal management requirements of a battery pack during fast charging. Furthermore, the temperature difference, temperature gradient, aging loss and energy consumption of the battery pack should be balanced to optimize its performance. This paper establishes the liquid cooling thermal management system model for an electric vehicle’s battery pack, which accurately characterizes the temperature distribution and electrical and aging characteristics of the battery pack. The discrepancies between the experimental and simulated results of battery’s fast charging-cooling suggest that maximum absolute temperature error is 2 °C, and the maximum relative voltage error is 1.5 %. Based on the non-dominated sorting genetic algorithm II algorithm, an optimization model with aging and temperature gradient of cells as objective functions is established. Three different thermal management strategies are created according to the optimization results. The comparison of these thermal management methods with the constant temperature cooling strategy demonstrates that the minimum temperature gradient strategy enhances the temperature consistency of the battery pack and reduces the maximum temperature gradient by 27 %. The minimum aging thermal management strategy depicts an aging loss of 0.091 %, reducing the charging time by 272 s and the maximum temperature gradient by 2.0 °C. The balanced thermal management strategy enables the battery pack to balance the temperature gradient and aging loss by optimizing the charging time, battery pack temperature difference, energy consumption and other indicators. The weight of each indicator is determined by its information entropy, which can be replaced according to the diverse needs to achieve different balanced thermal management strategies, providing a reference for the actual application of thermal management strategies.
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