Adaptive Health-Aware Fast Charging Strategy Development for Preventing Lithium Plating Based on Digital Twin Model

Developing smart fast charging strategies can effectively balance the charging efficiency and battery performance. The current mainstream method is to optimize fast charging protocols based on electrochemical models that quantitatively detect lithium deposition. This paper utilizes a high-fidelity battery digital twin model to extract the triggering potential of lithium deposition and thus construct a lithium deposition curve. Based on this, a health-aware fast charging strategy (FCS) is developed to analyze the electro-thermal aging behavior of batteries under various health factors. Subsequently, the influence of the number of steps in the charging protocol on battery aging is examined, leading to the development of a real-time health-aware FCS. The results show that although capacity loss caused by side reactions gradually increases with the number of charging steps, the time required to complete the fast charging process is significantly reduced. Furthermore, compared to the 2 C constant current charging strategy, the proposed health-aware variable current profile (VCP) charging strategy with a health factor of 20% demonstrates excellent performance in reducing capacity loss caused by lithium deposition, achieving up to a 17.59% reduction in capacity loss and effectively reducing capacity loss due to side reactions by 15.4%.