The inconsistencies between the monomers of the power battery pack will occur due to the factors such as production process and service environment, which will affect the service life and driving safety of the battery. To meet the requirement of abnormal monomer diagnosis under inconsistent fault of power battery pack, based on data of vehicle network platform, a method of power battery monomer identification and early warning is proposed based on isolated forest method. The fault threshold T=0.75 is determined by counting the scores of normal and abnormal samples. At the same time, the data flowing into the diagnosis model is updated in real time by combining the sliding window to realize the recognition and warning of inconsistent monomers. The results show that the method can effectively identify inconsistent monomers, with the recall and accuracy of 0.91 and 0.95 respectively. When the size of sliding window is 15, the warning effect of real-time fault is the best. The research obtained in this paper is beneficial to reduce or avoid electric vehicle fire and explosion accidents caused by inconsistent power batteries, and is of great significance to promote the further popularization of electric vehicles.