江汉大学学报（自然科学版）2026，Vol.54Issue(4)：26-36,11.DOI:10.16389/j.cnki.cn42-1737/n.2026.04.003
基于音频特征识别的锂电池热失控监测方法
A Monitoring Method for Lithium-Ion Battery Thermal Runaway Based on Audio Feature Recognition
摘要
Abstract
Lithium-ion batteries have been widely used in new energy vehicles and grid energy storage stations.However,the poor thermal stability of lithium battery systems remains a major challenge limiting their safe application.The acoustic signal generated when the safety valve of a lithium-ion battery bursts can provide an early warning of the thermal runaway process.In this study,a monitoring method for lithium-ion battery thermal runaway audio feature recognition is proposed.First,variational mode decomposition(VMD)combined with wavelet thresholding is employed for collaborative denoising.Then,traditional Mel-frequency cepstral coefficients(MFCCs)are fused with time-domain statistical features for feature extraction.Finally,a Bayesian-optimized support vector machine(SVM)model is adopted for pattern recognition.Experimental results demonstrate that the proposed method achieves effective recognition of safety valve acoustic signals from ternary lithium batteries and lithium iron phosphate batteries,with a recognition accuracy of up to 94.32％.The proposed method provides a promising approach for the early warning and monitoring of lithium-ion battery thermal runaway.关键词
锂电池/热失控/音频特征识别/声信号/模式识别Key words
lithium-ion battery/thermal runaway/audio feature recognition/acoustic signal/pattern recognition分类
信息技术与安全科学引用本文复制引用
闫浩杰,谢家乐,史庆武..基于音频特征识别的锂电池热失控监测方法[J].江汉大学学报（自然科学版）,2026,54(4):26-36,11.基金项目
国家自然科学基金项目(52207235) （52207235）
