Early multi-parameter detection study of lithium-ion batteries based on the ratio of blue to infrared light and gas concentration

Author：Liu, S. N., Lu, S., Zhou, Q. Y., Ruan, C. R.

Journal：Journal of Energy Storage

DOI:  10.1016/j.est.2024.112485

Keywords: Lithium-ion batteries, Early detection, H-2, CO, Ratio of blue to infrared light, thermal-runaway, electric vehicles, energy-storage, cells, model, temperature, challenges

Abstract: 

As the use of lithium-ion batteries in energy storage and transportation grows, the number of fires and explosions caused by battery thermal runaway increases, emphasizing the vital need for enhanced early detection technology. Existing research does not clarify the effect of airflow environment and detection location on battery smoke flow and detection effectiveness. The purpose of this study is to illuminate the environmental effects on battery smoke diffusion, allowing for the selection of more appropriate detection parameters while also improving detection sensitivity and robustness. Here, the investigation focuses on the smoke characteristics of 18650 LiFePO4 (LFP) batteries, using the ratio of blue to infrared light and concentrations of CO and H2. Additionally, a detrending algorithm was developed to interpret smoke signals, and the smoke characteristics of batteries in different states of diffusion after thermal runaway occurred at different states of charge (SOC) were further investigated. It is shown that the smoke signal values processed by the detrending algorithm are more suitable for smoke detection in thermal runaway batteries. Using smoke and fugitive gas growth rate parameters, the results show that airflow interference is important in promoting smoke diffusion. Notably, the ambient state and the SOC of the battery have a greater influence on the maximum concentration of CO compared to H2. The linear equations and the addition of the environmental influence parameter DR imply that H2 is a better choice as the primary gas parameter for identifying battery runaway. The airflow disruption reduced the smoke response time by around 40 % while having minimal influence on gas diffusion. This study establishes a theoretical foundation for optimizing battery operating environments and gives practical guidelines for the use of multiparameter monitoring and early detection of lithium-ion batteries. Furthermore, this study improves the safe management and protection of lithium batteries in their application.