Research on Thermal Runaway Multiphysics Coupling Simulation and Sensor Optimization Layout of Lithium Iron Phosphate Energy Storage Battery Packs

ABSTRACT To address the safety risks caused by thermal runaway in lithium iron phosphate (LiFePO₄) energy storage batteries, and to improve the timeliness and accuracy of fault monitoring while ensuring the safe operation of energy storage systems, this study focuses on a 314 Ah liquid‐cooled battery module. It conducts a coupled gas‐mechanics‐acoustics multi‐physics simulation and experimental validation of the thermal runaway process. Mechanical response, acoustic propagation, and gas diffusion models were built using ABAQUS, COMSOL, and Ansys Fluent, respectively. Combined with experimentally measured stress peaks (1308 kg), acoustic signal characteristics, and hydrogen diffusion data, model inputs and validation were completed. The NSGA‐III multi‐objective optimization algorithm was applied to determine the optimal sensor configuration. The results show that: the thermal runaway stress is transmitted to the seventh cell in the module within 0.001 s, so the stress sensor should be placed on the large surface of this cell; the transient acoustic signal peak pressure during safety valve activation exceeds 17 Pa (sound pressure level > 118.6 dB), achieving millisecond‐level full coverage, and a single broadband acoustic sensor placed at the top center of the module is sufficient for monitoring; thermal runaway gas response is optimal in the top center area (Position 5), with the edge fault scenario detected first at 1.1 s and reaching the warning threshold (0.01 kmol/m³) at 1.6 s, while in the center fault scenario, the warning threshold is reached at 0.1 s. Gas sensors should therefore be preferentially arranged at the top center of the module. The sensor optimization layout strategy proposed in this paper provides theoretical and technical support for the safe operation of energy storage batteries and helps improve the effectiveness of fault monitoring in energy storage systems.

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Publication Details

Journal
Energy Science & Engineering
Published
2026-01-14
DOI
https://doi.org/10.1002/ese3.70440
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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Research on Thermal Runaway Multiphysics Coupling Simulation and Sensor Optimization Layout of Lithium Iron Phosphate Energy Storage Battery Packs

Lei Sun, Xin Jiang, Dongliang Guo, Peng Xiao et al.
Energy Science & Engineering
Advanced Battery Technologies Research
article

Research on Thermal Runaway Multiphysics Coupling Simulation and Sensor Optimization Layout of Lithium Iron Phosphate Energy Storage Battery Packs

Lei Sun, Xin Jiang, Dongliang Guo, Peng Xiao, Hailong Ruan, Jun Jia, Rong Sun
article en

Abstract

ABSTRACT To address the safety risks caused by thermal runaway in lithium iron phosphate (LiFePO₄) energy storage batteries, and to improve the timeliness and accuracy of fault monitoring while ensuring the safe operation of energy storage systems, this study focuses on a 314 Ah liquid‐cooled battery module. It conducts a coupled gas‐mechanics‐acoustics multi‐physics simulation and experimental validation of the thermal runaway process. Mechanical response, acoustic propagation, and gas diffusion models were built using ABAQUS, COMSOL, and Ansys Fluent, respectively. Combined with experimentally measured stress peaks (1308 kg), acoustic signal characteristics, and hydrogen diffusion data, model inputs and validation were completed. The NSGA‐III multi‐objective optimization algorithm was applied to determine the optimal sensor configuration. The results show that: the thermal runaway stress is transmitted to the seventh cell in the module within 0.001 s, so the stress sensor should be placed on the large surface of this cell; the transient acoustic signal peak pressure during safety valve activation exceeds 17 Pa (sound pressure level > 118.6 dB), achieving millisecond‐level full coverage, and a single broadband acoustic sensor placed at the top center of the module is sufficient for monitoring; thermal runaway gas response is optimal in the top center area (Position 5), with the edge fault scenario detected first at 1.1 s and reaching the warning threshold (0.01 kmol/m³) at 1.6 s, while in the center fault scenario, the warning threshold is reached at 0.1 s. Gas sensors should therefore be preferentially arranged at the top center of the module. The sensor optimization layout strategy proposed in this paper provides theoretical and technical support for the safe operation of energy storage batteries and helps improve the effectiveness of fault monitoring in energy storage systems.

Energy Science & Engineering
PLA Information Engineering University (CN), Zhengzhou University (CN), Henan University of Engineering (CN), Shanghai Electric (China) (CN)
State Grid Jiangsu Electric Power
Affordable and clean energy
Openalex Percentile: Top 88%
Advanced Battery Technologies Research
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