湖南电力 ›› 2024, Vol. 44 ›› Issue (5): 17-23.doi: 10.3969/j.issn.1008-0198.2024.05.003

• 特约专栏:电力防灾减灾 • 上一篇    下一篇

基于声学检测技术的刀片储能锂电池热失控行为研究

徐松, 万涛, 李欣, 吴俊杰, 查方林, 魏加强, 蔡宇峰, 刘奕奕   

  1. 国网湖南省电力有限公司电力科学研究院,湖南 长沙 410208
  • 收稿日期:2024-08-01 修回日期:2024-08-30 出版日期:2024-10-25 发布日期:2024-11-06
  • 作者简介:徐松(1981),男,博士,正高级工程师,主要从事储能电池性能检测与评估、储能装置与电网交互技术等研究工作。
  • 基金资助:
    国网湖南省电力有限公司科技项目(5216A522001L)

Research on Thermal Runaway Behavior of Blade Energy Storage Lithium Batteries Based on Acoustic Detection Technology

XU Song, WAN Tao, LI Xin, WU Junjie, ZHA Fanglin, WEI Jiaqiang, CAI Yufeng, LIU Yiyi   

  1. State Grid Hunan Electric Power Company Limited Research Institute, Changsha 410208, China
  • Received:2024-08-01 Revised:2024-08-30 Online:2024-10-25 Published:2024-11-06

摘要: 随着电化学储能的规模化应用,开展储能锂电池热失控检测与及时预警研究对于保障储能电站的安全运行具有重要意义。搭建储能锂电池单体热失控性能检测试验平台,对刀片储能锂电池进行热失控条件下的声音信号检测,分析电池鼓包、泄压阀打开、泄气、爆炸起火等热失控不同发展阶段的声音特性与变化规律,表明声音特征对于热失控检测的有效性。针对热失控声音特征易受储能电池舱内通风散热风机、储能变流器等其他设备噪声干扰的问题,提出基于小波包分解与谱减法语音增强的热失控声音信号抗干扰分析方法。分析结果表明,所提出的方法能够有效剔除热失控声音信号中的风噪干扰,可准确还原出电池热失控声音特征,还原声信号与实际声信号相似系数达到0.96,为储能锂电池热失控声音检测与早期预警提供技术参考。

关键词: 储能电站, 刀片储能锂电池, 热失控, 声音特征, 抗干扰分析, 声学检测, 小波包, 谱减法

Abstract: With the large-scale application of electrochemical energy storage, thermal runaway detection and timely warning research of lithium battery is of great significance for ensuring the safe operation of energy storage power station. In this paper, a test platform for the thermal runaway performance of lithium battery is set up. The sound signal of blade energy storage lithium battery under thermal runaway condition is tested. The acoustic characteristics and change rules of different development stages of thermal runaway such as battery bulging, pressure relief valve opening, venting, explosion and fire are analyzed. It shows the effectiveness of sound feature for thermal runaway detection. Aiming at the problem that the sound characteristics of thermal runaway are easily disturbed by the noise of other equipment such as ventilation fans and PCS in the energy storage battery compartment, an anti-interference analysis method of thermal runaway sound signal based on wavelet packet decomposition and spectral subtraction speech enhancement is proposed. The analysis result shows that the proposed method can effectively eliminate the wind noise interference from the thermal runaway sound signal, and can accurately restore the battery thermal runaway sound characteristics. After denoising, the correlation coefficient between the original and the denoised sound signals reaches 0.96. The results can provide as technical reference for thermal runaway detection and early warning of the energy storage lithium battery.

Key words: energy storage power station, blade energy storage lithium batteries, thermal runaway, sound feature, anti-interference analysis, acoustic detection, wavelet packet, spectral subtraction

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