锂电池热失控早期典型气体精准检测方法

doi:10.19799/j.cnki.2095-4239.2024.0101

摘要/Abstract

摘要：

锂电池储能是消纳新能源发电，达成国家“双碳”目标的重要途径，是地面储能及工商业储能的核心装备，锂电池热失控消防安全是储能大规模应用的前提保障。锂电池热失控早期典型气体检测是储能消防预警的主要手段，但是在混合气体场景下各气体传感器数据存在交叉干扰，导致检测失准而造成预警延迟或误报警，进而导致消防隐患。针对上述问题，围绕典型气体H₂和CO的浓度精准检测，提出一种混合气体场景下传感器数据的解耦方法。通过建立各传感器在不同单一气体环境下的响应模型，建立不同气体对传感器的交叉耦合关系；进而推导混合气体场景下各传感器信号与气体组分与浓度的构成关系，建立方程组得出各气体的精确浓度数据，实现各传感器数据解耦。最后，搭建H₂和CO混合气体场景，用于模拟不同化学体系、不同SOC的锂电池热失控早期气体环境，进行实验测试，结果显示在0~1000 mL/m³浓度范围内的检测误差小于50 mL/m³，检测精度最大提升了15%，验证了本文所提方法的有效性。

关键词: 锂电池储能, 热失控, 气体检测, 交叉干扰, 数据交叉解耦算法

Abstract:

Lithium battery energy storage plays a crucial role in harnessing new energy for power generation and achieving the national "dual-carbon" objectives. This technology is indispensable for ground-based, industrial, and commercial energy-storage applications. A critical aspect of its widespread adoption is ensuring the safety of lithium batteries against thermal runaway and fire hazards. To this end, early detection of gases typically released during the thermal runaway phase of a lithium battery is essential for fire warning in energy storage. However, accurately identifying these gases poses challenges in environments with mixed gases owing to cross-interference from data collected by various gas sensors. Such interferences often lead to inaccurate detections, delayed or false alarms, and potential fire hazards. To address these issues, we propose a decoupling method designed to enhance the precision of detecting typical gases, namely H₂ and CO concentrations, in mixed gas environments. This method involves establishing response models for each sensor in different single-gas environments and understanding the cross-coupling relationships between different gases and sensors. By deriving the relationship between the sensor signals and the gas components and concentrations in mixed-gas scenarios, we can establish an equation system. This system is crucial for obtaining precise concentration data for each gas, thus facilitating the decoupling of sensor data. In experimental testing with a mixed gas scenario of H₂ and CO, which was built to simulate the early gas environment of lithium battery thermal runaway across different chemical systems and different states of charge. The results demonstrated a detection error of less than 50 mL/m³ within the concentration range of 0—1000 mL/m³. The maximum improvement in detection accuracy reached 15%, validating the effectiveness of the proposed method outlined in this study.

Key words: lithium battery energy storage, thermal runaway, gas detection, cross interference, data cross decoupling algorithm

中图分类号:

TM 912

刘宝泉, 曹小雨. 锂电池热失控早期典型气体精准检测方法[J]. 储能科学与技术, 2024, 13(6): 1995-2009.

Baoquan LIU, Xiaoyu CAO. Accurate typical gas detection of lithium battery in early thermal runaway period[J]. Energy Storage Science and Technology, 2024, 13(6): 1995-2009.

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电池种类	荷电状态	注入气体浓度	加算法前误差最大值	加算法前误差最小值	加算法后误差最大值	加算法后误差最小值	提升精度平均值
LFP	100% SOC	100 mL/m³ H₂ 30 mL/m³ CO	120	25	29	5	5.37%
		100 mL/m³ H₂ 30 mL/m³ CO	46	13	37	4	2.7%
		150 mL/m³ H₂ 45 mL/m³ CO	162	31	46	9	9.46%
		150 mL/m³ H₂ 45 mL/m³ CO	52	18	27	10	4.38%
	50% SOC	120 mL/m³ H₂ 20 mL/m³ CO	156	17	34	4	8.4%
		120 mL/m³ H₂ 20 mL/m³ CO	58	23	42	14	6.56%
		180 mL/m³ H₂ 30 mL/m³ CO	145	44	29	8	8.92%
		180 mL/m³ H₂ 30 mL/m³ CO	41	8	23	1	6.75%

NMC	100% SOC	40 mL/m³ H₂ 70 mL/m³ CO	127	25	46	5	10.04%
		40 mL/m³ H₂ 70 mL/m³ CO	84	11	37	3	2.62%
		80 mL/m³ H₂ 140 mL/m³ CO	112	35	45	15	9.36%
		80 mL/m³ H₂ 140 mL/m³ CO	87	31	42	15	3.46%
	50% SOC	50 mL/m³ H₂ 100 mL/m³ CO	106	15	41	5	9%
		50 mL/m³ H₂ 100 mL/m³ CO	104	19	42	8	3.4%
		75 mL/m³ H₂ 150 mL/m³ CO	115	30	48	10	9.8%
		75 mL/m³ H₂ 150 mL/m³ CO	91	16	39	9	3.17%

气体种类	气体浓度	传感器信号	交叉干扰系数
硫化氢	100 mL/m³	0 mL/m³	0%
乙烯	100 mL/m³	80 mL/m³	80%
一氧化氮	35 mL/m³	6 mL/m³	17.14%
二氧化氮	5 mL/m³	0 mL/m³	0%
乙醇	100 mL/m³	0 mL/m³	0%
氯气	10 mL/m³	1 mL/m³	10%
二氧化硫	20 mL/m³	0.6 mL/m³	3%
氢气	500 mL/m³	43 mL/m³	8.6%
氨气	50 mL/m³	1 mL/m³	2%
一氯甲烷	5 mL/m³	0 mL/m³	0%
环氧乙烷	10 mL/m³	0 mL/m³	0%
苯	100 mL/m³	1.5 mL/m³	1.5%
丙酮	100 mL/m³	3.5 mL/m³	3.5%
甲醇	200 mL/m³	0 mL/m³	0%

气体种类	气体浓度	传感器信号	交叉干扰系数
硫化氢	15 mL/m³	4 mL/m³	26.67%
二氧化硫	5 mL/m³	0 mL/m³	0%
一氧化碳	200 mL/m³	30 mL/m³	15%
一氧化氮	35 mL/m³	10 mL/m³	28.57%
二氧化氮	5 mL/m³	0.5 mL/m³	10%
氯气	10 mL/m³	0 mL/m³	0%
氯化氢	5 mL/m³	0 mL/m³	0%
乙烯	100 mL/m³	85 mL/m³	85%

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