Raman Spectrum Analysis Method of Thermal Runaway Gas from Lithium-ion Batteries

Da Chen; Chaolong Hao; Tiantian Liu; Zhou Han; Wei Zhang

doi:10.3788/CJL202249.2311001

Chinese Journal of Lasers, Volume. 49, Issue 23, 2311001(2022)

Raman Spectrum Analysis Method of Thermal Runaway Gas from Lithium-ion Batteries

Da Chen, Chaolong Hao, Tiantian Liu, Zhou Han, and Wei Zhang^*

Tianjin Engineering Research Center of Civil Aviation Energy Environment and Green Development, Civil Aviation University of China, Tianjin 300300, China

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Figures & Tables(11)

Fig. 1. Thermal runaway process of lithium-ion battery and generated gas

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Fig. 2. Experimental setup. (a) Schematic of gas detection system by laser Raman spectroscopy; (b) heat abuse device for lithium-ion battery

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Fig. 3. Raman spectra of gases. (a) Standard non-hydrocarbon reference gases; (b) standard hydrocarbon reference gases; (c) gases released from battery thermal abuse

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Fig. 4. Grid search results for battery pyrolysis gas after DWT parameter optimization. (a) Carbon monoxide; (b) hydrogen; (c) oxygen; (d) carbon dioxide; (e) methane; (f) ethylene ; (g) nitrogen; (h) propylene

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$Raman characteristic peaks of CO2 gases with different volume fractions after pretreatment$

Fig. 5. Raman characteristic peaks of CO₂ gases with different volume fractions after pretreatment

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Fig. 6. Experimental results for battery thermal abuse with different SOCs. (a)(b) 25%; (c)(d) 100%

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Table 1. Experimental battery parameters
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Table 1. Experimental battery parameters
Parameter Height /mm Diameter /mm Nominal capacity /(mA·h) Nominal voltage /V Discharge cut-off voltage /V Charging voltage /V
Value 65 18 3500 3.63 2.65 4.2

Table 2. Hydrocarbon gas content (volume fraction，%)

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Table 2. Hydrocarbon gas content (volume fraction，%)

No.	CH₄	C₂H₄	C₃H₆	No.	CH₄	C₂H₄	C₃H₆
1	1.86	1.70	0.11	16	0.88	0.19	1.58
2	0.89	0.41	0.18	17	2.79	1.90	1.67
3	2.80	2.11	0.26	18	0.88	0.62	1.82
4	1.84	0.83	0.41	19	0.35	2.30	1.89
5	0.88	2.53	0.50	20	2.23	1.00	2.02
6	2.80	1.15	0.58	21	0.71	1.78	2.42
7	1.84	2.86	0.73	22	2.97	1.42	2.19
8	0.35	1.62	0.80	23	1.50	0.07	2.31
9	1.85	0.30	0.89	24	0.71	1.78	2.42
10	0.90	2.03	0.98	25	2.26	0.50	2.49
11	2.78	0.72	1.12	26	1.47	2.20	2.59
12	1.83	2.42	1.19	27	0.47	0.90	2.70
13	0.88	1.14	1.27	28	2.24	2.63	2.79
14	2.82	2.78	1.37	29	1.47	1.26	2.91
15	1.83	1.47	1.51	30	3.02	2.99	2.99

Table 3. Raman characteristic peaks and DWT optimization parameters of target gases

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Table 3. Raman characteristic peaks and DWT optimization parameters of target gases

Gas	Characteristic wavenumber /cm^－1	Optimal wavelet parameter
Gas	Characteristic wavenumber /cm^－1	Scale	Symmlet
CO₂	1282，1390	9	Sym 4
O₂	1556	10	Sym 2
CO	2140	5	Sym 10
H₂	593	7	Sym 8
N₂	2328	6	Sym 6
CH₄	2920，3019，3073	4	Sym 2
C₂H₄	1344，1625，3019	8	Sym 9
C₃H₆	921.7，1298，2932，3015	8	Sym 6

Table 4. PLS modeling results for battery pyrolysis gas

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Table 4. PLS modeling results for battery pyrolysis gas

Gas	Training set		Validation set
Gas	R²	RMSEC /%	R²	RMSEP /%
CO₂	0.999	0.340	0.999	0.452
O₂	1.000	0.125	0.999	0.220
CO	0.994	0.221	0.988	0.327
H₂	0.998	0.115	0.988	0.337
N₂	0.999	0.276	0.998	0.430
CH₄	0.960	0.162	0.937	0.184
C₂H₄	0.999	0.040	0.991	0.091
C₃H₆	0.994	0.083	0.993	0.097

Table 5. Gas volume fractions in container after thermal runaway of lithium ion batteries ends
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Table 5. Gas volume fractions in container after thermal runaway of lithium ion batteries ends
SOC /% Volume fraction /%
O₂ N₂ CO H₂ CO₂ C₂H₄ C₃H₆ CH₄
25 0 56.05±0.14 18.47±0.29 9.42±0.14 13.03±0.1 0.68±0.03 0.48±0.05 0.43±0
100 0 39.74±0.14 32.06±0.21 13.86±0.12 15.19±0.08 0.36±0.08 0.47±0.07 0.63±0.01

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Da Chen, Chaolong Hao, Tiantian Liu, Zhou Han, Wei Zhang. Raman Spectrum Analysis Method of Thermal Runaway Gas from Lithium-ion Batteries[J]. Chinese Journal of Lasers, 2022, 49(23): 2311001

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