This study focuses on a charging strategy for battery packs, as battery pack charge control is crucial for battery management system. First, a single-battery model based on electrothermal aging coupling is proposed; subsequently, a battery pack cooling model and battery pack equilibrium management model are combined to form a complete battery pack model that describes the state parameters of the battery pack and the interaction between the individual batteries in the battery pack. Then, a multi-objective optimal charging strategy considering charging time, aging, and energy loss is proposed, and the equilibrium management, temperature, and battery parameters are restricted. A genetic algorithm method was used to optimize the adaptive multi-phase constant-current constant-voltage charging strategy. A fast charging strategy based on the shortest charging time is proposed. The results show that the fast charging strategy can significantly reduce charging time but leads to aging and increases energy loss. The contradictory relation between charging time and aging and the interaction between charging time and energy loss are revealed. The balance optimization charging strategy appears on the left side of the Pareto curve. Finally, a balanced charging strategy considering charging time, aging, and energy loss is obtained. In comparison with single batteries with the same average initial current charging, the constant current phase order decreases because of battery pack state parameters and equilibrium management, resulting in different charging strategies.
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