Research on Diagnosis of Abnormal Connection in Battery Systems Based on Cloud Data
It is crucial to effectively identify abnormal connections in the battery system of new energy vehicles in order to address their operational safety issues.By utilizing an emergency warning cloud monitoring platform and big data analysis methods,combined with the similarities and differences in data patterns between normal vehicles and vehicles with abnormal or faulty connections,this paper aim.to explore the factors contributing to abnormal defects in power battery connections.A data-driven algorithm for identifying abnormal risk factors in the connection of new energy vehicle battery systems is developed.According to the risk factors,the degree of abnormal connection in the battery system is classified into different levels,and the results show that the proposed algorithm can accurately and effectively identify high-risk vehicles with abnormal connections.
Connection anomalyCloud platformFault diagnosisBig data
万方数据
维普
