Battery monomer voltage sampling fault identification method based on cloud online data

The invention discloses a battery monomer voltage sampling fault identification method based on cloud online data. The method comprises the following steps: S1, uploading vehicle-mounted end BMS data to a cloud through T-BOX; s2, data processing; s3, outlier monomer data are searched according to the Z score of the voltage differential data; s4, judging whether two battery monomer numbers with the highest outlier degree are adjacent or not for the monomer data judged as the outlier, if so, turning to S5, and if not, indicating that the sampling fault is not generated; and S5, judging that the voltage differential data of the adjacent monomers are outlier, judging whether the voltage differential data are symmetrically or approximately symmetrically distributed, if so, indicating that the sampling fault occurs, and if not, indicating that the sampling fault does not occur. According to the invention, the problem of fault false alarm of the battery management system caused by symmetrical or approximately symmet