An interpretable BRB model with interval optimization strategy for lithium battery capacity prediction

Accurately predicting the capacity of lithium battery is conducive to improving its safety. Affected by complex internal electrochemical reaction and external use conditions, prediction accuracy difficult guarantee; at same time, existing methods are unexplainable, resulting in inability trace process. Therefore, a model based on belief rule base with interpretability interval optimization strategy proposed this paper. First, reasoning process designed according modeling criteria. Second, achieve balance interpretability, whale algorithm, parameter method using proposed. Finally, through case study, model's effectiveness verified. Comparison other models shows that has certain advantages interpretability.