Research on the prediction of thermal runaway risk of new energy vehicle lithium battery based on improved LSTM-HMM

With the widespread adoption of new energy vehicles, the safety of lithium batteries, especially the issue of thermal runaway, is regarded as a critical challenge. To address this issue, an improved LSTM-HMM model is proposed in this study, aiming to enhance the accuracy and real-time performance of thermal runaway prediction. The model captures the time-series dynamics of key parameters such as battery temperature, voltage, and current, improving the shortcomings of the standard LSTM-HMM model. Experimental results show that the improved model outperforms traditional methods in terms of prediction accuracy and response speed, effectively enhancing the safety and reliability of the battery management system.