A new state-of-health estimation method for Li-ion batteries based on interpretable belief rule base with expert knowledge credibility

State-of-health (SOH) estimation methods for Li-ion batteries are important for the safe operation of the entire system. However, it is often challenging due to the uncertainty within the batteries and the criteria for model interpretability. Belief rule base (BRB) is a rule-based expert system that has certain advantages for both aspects. However, several problems with BRB interpretability need to be solved urgently. First, expert knowledge credibility is often given subjectively, while objective information is neglected to be considered. Second, BRB interpretability is easily ignored or corrupted in the optimization process. Third, expert knowledge is assumed to be completely reliable information to be used as interpretability evaluation criterion. Therefore, a new SOH estimation method for Li-ion batteries based on interpretable BRB with expert knowledge credibility (IBRB-c) is proposed. In the IBRB-c, the calculation method of expert knowledge credibility is given. Then, an optimization algorithm with interpretability strategies is used. Finally, the concept of the fuzzy interpretable interval is proposed to design the interpretable evaluation criterion. The effectiveness of the proposed method is verified by using the experiment of NASA Li-ion battery as a case study. In the constructed IBRB-c model, the credibility of expert knowledge is calculated by combining subjective and objective information. Then, the fuzzy interpretability interval concept is proposed to design a new evaluation criterion that balances the accuracy and interpretability of the belief rule base model. In addition, two interpretability strategies are designed to improve interpretability.image