In order to ensure the safe and smooth operation of new energy vehicles, accelerate their development and promotion, and alleviate the environmental crisis, we adopt a “normalized voltage difference curve” to analyze the safety features of power battery packs. Furthermore, we formulate the control strategies of online early warning about faults in the charging process of electric vehicles on the short-term and mid-long-term scales. Thus, the basic performance of single batteries is analyzed and the trend in battery voltage can be accurately and clearly characterized. In this study, we mainly investigate the early warning control strategies of mid-long-term charging affected by the temperature rise in battery charging. Then, an objective function is established and the genetic algorithm is used for optimal control. Finally, the data about the charging status provided by the charging-pile monitoring platform verify the proposed online early warning of the charging data based on the battery model.