Charge process management of lithium-ion batteries based on digital twins: A new way to extend life

Effective management of the charging process is not only crucial for reducing costs and improving the efficiency of electric vehicles and renewable energy systems but also essential for enhancing the stability and safety of energy systems. Consequently, it has become a key focus in battery management system research. However, there is a contradiction between improving battery charging efficiency and extending service life, and the diversified battery use needs make this contradiction more prominent. This paper proposes a lithium-ion battery charging process management framework based on digital twin technology and Bayesian principle. A hybrid model is used to establish the digital twin of the lithium-ion battery charging state and health state. At the same time, the model evaluation reward and maturity evaluation reward are comprehensively considered in the decision-making process to improve the effectiveness of decision-making. Furthermore, the charging strategy is optimized according to the distinct characteristics of different battery life stages. The case analysis demonstrates that, compared to existing charging strategies, the proposed method effectively extends battery lifespan while meeting various battery performance requirements.