An experimental-based Domino prediction model of thermal runaway propagation in 18, 650 lithium-ion battery modules. (December 2021)

• Record Type: Journal Article
• Authors: Zhai, Hongju; Li, Huang; Ping, Ping; Huang, Zonghou; Wang, Qingsong
• Is Part Of: International journal of heat and mass transfer. Volume 181(2021)
• Publication Date: 2021-12
• Subjects: Lithium-ion battery safety -- Thermal runaway propagation -- Probability -- Domino effect; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2021.122024
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: A Domino prediction model of thermal runaway propagation is proposed. This model proposes that whether the battery thermal runaway is a probability event. The thermal runaway propagation path and probability is analyzed. The thermal runaway propagation process is divided into four stages. Abstract: Currently, the thermal safety issue of lithium-ion battery (LIB) has become a major challenge to restrict its development. In this work, the thermal runaway propagation (TRP) process of the 18, 650-type LIB module is studied by experimental and modeling methods. A novel experimental-based Domino prediction model is proposed, which can predict the TRP path and its probability. The calculation part of the model is realized with the Matlab software. This model for the first time proposes that whether the battery thermal runaway (TR) is a probability event, and the probability is a function of its temperature. To verify the feasibility of the model, the TRP process in a 4 × 4 arrangement battery module with three different first TR battery locations is detailed analyzed. The results show that the dangerous level ranking of cell locations from low to high is the corner location, the edge location, and the location near the module center. Higher dangerous level means more maximum probability TRP paths and higher probability. Moreover, it was found that the whole TRP process can be divided into four stages: the TRP trigger stage, the heat accumulation stage, the Domino effect stage, and the TRP stop stage. The proposed model can effectively predict the TRP process in modules, and the results have important reference value for the design of the battery thermal management system and the research on the method of blocking TRP.