Abstract
With the rapid and continuous development of new energy vehicles, safety issues during charging have become increasingly prominent. Thus, there is an urgent need to strengthen charging safety management. However, current charging detection methods have limitations, such as difficulty in monitoring local battery pack currents, and indirect monitoring through temperature and gas sensors lead to lag. To address these limitations, this article proposes a safety monitoring method based on an improved lithium-ion battery magnetic field sensing model that covers the entire charging process. Specifically, thermal field analysis was introduced to the existing electric magnetic coupling model, resulting in an electric thermal magnetic multi-physical field coupling model. By conducting experiments, the study verified that the accuracy of the improved model has increased by 15.5 %. Based on this model, the study proposed a method for predicting and warning of abnormal currents using BP neural network and mathematical statistical laws. The results showed that the current prediction accuracy of this method reached 96.4 %. Such high accuracy ensures real-time comprehensive monitoring of the current information of lithium-ion battery packs, thereby eliminating the hidden dangers of charging safety accidents caused by the lack of local current detection.
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