锂离子电池热失控气体协同降噪空芯光纤增强拉曼光谱检测技术

Hollow-core Fiber Enhanced Raman Spectroscopy Detection Technique with Synergistic Noise Reduction for Thermal Runaway Gases of Lithium-ion Battery

准确检测热失控气体是保障锂离子电池安全可靠运行的关键。针对热失控气体常用检测方法易老化、交叉干扰和拉曼光谱灵敏度偏低等问题,该文提出锂离子电池热失控气体协同降噪空芯光纤增强拉曼光谱检测方法。基于低噪声阵列式相机(charge coupled device,CCD)和小孔协同降噪,使信噪比提升2.2倍,H_(2)、CO_(2)、C_(2)H_(2)、CO、CH_(4)、C_(2)H_(6)、C_(2)H_(4)体积分数检测下限分别达到3.71×10^(-5)、1.98×10^(-5)、6.2×10^(-6)、9.2×10^(-6)、2.6×10^(-6)、9.1×10^(-6)、4.1×10^(-6)。实现了18650电池H_(2)、CO_(2)、C_(2)H_(2)、CO、CH_(4)、C_(2)H_(6)、C_(2)H_(4)共7种热失控气体原位拉曼光谱动态分析,并在最终热失控气体产物中检测到H_(2)、CO_(2)、C_(2)H_(2)、CO、CH_(4)、C_(2)H_(6)、C_(2)H_(4)、C3H_(6)、HF共9种热失控气体组分。结果表明,空芯光纤拉曼光谱检测技术可为锂离子电池热失控气体分析提供支撑。

Accurate detection of thermal runaway gas is the key to ensure the safe and reliable operation of lithium-ion batteries. Aiming at the problems of easy aging, cross-interference and low Raman spectroscopy sensitivity of common methods for thermal runaway gas detection, this paper proposes a thermal runaway gas detection method for lithium-ion batteries based on hollow-core fiber enhanced Raman spectroscopy with synergistic noise reduction. Based on charge coupled device and pinhole synergistic noise reduction, the signal-to-noise ratio is increased by 2.2 times. The detection limits of H_(2), CO_(2), C_(2)H_(2), CO, CH_(4), C_(2)H_(6) and C_(2)H_(4) are 3.71×10^(-5), 1.98×10^(-5), 6.2×10^(-6), 9.2×10^(-6), 2.6×10^(-6), 9.1×10^(-6) and 4.1×10^(-6), respectively. Based on the Raman spectroscopy, the dynamic analysis of 7 thermal runaway fault gases (namely, H_(2), CO_(2), C_(2)H_(2), CO, CH_(4), C_(2)H_(6) and C_(2)H_(4)) of 18650 battery is completed. Finally, 9 thermal runaway gas components in total are detected, namely H_(2), CO_(2), C_(2)H_(2), CO, CH_(4), C_(2)H_(6), C_(2)H_(4), C3H_(6) and HF. The results show that the hollow-core fiber enhanced Raman spectroscopy technology can provide important supports for thermal runaway gas analysis of lithium-ion batteries.