A Hierarchical Fault Diagnosis Method for Lithium Battery Based on Polymorphic Jump

Enhancing the diagnosis accuracy of power battery fault is a crucial issue in electric vehicle (EV) security field, while the accomplishment of which requires the application of complicated algorithm in every cell. Whereas, existing battery management system (BMS) has a limited computing ability in executing complex algorithm. Therefore, to improve the performance of battery fault diagnosis, a more reasonable computing resource allocation is demanded. In this paper, a hierarchical compound fault diagnosis method for Lithium battery based on polymorphic jump is proposed to resolve the contradiction between diagnosis accuracy demand and lack of computing resource. Different fault risk levels are divided according to the strategy, and the diagnosis methods for each cell differ between different levels. Results of the validation experiment prove a significant improvement of diagnosis efficiency brought by the proposed diagnosis strategy.