Optimization of Lithium-Ion Battery Charging Strategy Based on Aging State Scoring

Lithium-ion batteries experience accelerated aging during rapid charging, which has become a significant obstacle for fast charging. This paper proposes an optimized charging strategy that balances charging time and battery aging by integrating battery capacity loss and internal state scoring. Firstly, an equivalent circuit model is constructed, with parameter identification and model validation. Further, the relationship between the model parameters and cycle and capacity retention rate is discussed. Secondly, the parameters and capacity loss of batteries in different aging states are predicted based on the support vector regression model and verified by the variable current aging test. The results demonstrate high prediction accuracy and good generalization of the model. Subsequently, a scoring system for battery aging state is developed using the entropy weight method. Finally, NSGA-II is employed for multi-objective optimization, with the entropy weight method used to select the sequence with the highest value as the optimal strategy. The results show that compared to the 1C constant-current constant voltage charging strategy, the optimal charging strategy reduces the average charging time by 42.30% and decreases the battery score by 14.61%. Therefore, the proposed charging strategy effectively shortens the charging time without causing excessive damage to the battery.