主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

Fire Science and Technology ›› 2026, Vol. 45 ›› Issue (6): 43-48.doi: 10.20168/j.1009-0029.2026.06.0043.06

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Built-in sensing technologies for early warning systems in lithium-ion battery fires

Li Changhao1, Zhang Dongsheng2, Zhang Guangtai3, Cao Yuancheng4, Cheng Qi5,6   

  1. (1. State Grid Anhui Electric Power Research Institute, Anhui Provincial Key Laboratory of Fire Safety and Emergency Technology for New Power Systems (State Grid Fire Protection Technology Center for Transmission and Distribution Facilities), Hefei Anhui 230601, China; 2. Hefei Gotion High-tech Power Energy Co., Ltd., Hefei Anhui 230088, China; 3. NR Electric Power Electronics Co., Ltd., Changzhou Jiangsu 213025, China;4. Huazhong University of Science and Technology, Wuhan Hubei 430074, China; 5. Faculty of Physics and Electronic Science, Hubei University, Wuhan Hubei 430062, China; 6. Yichang Brunp Recycling Techno-logy Co., Ltd., Yichang Hubei 443215, China)
  • Received:2025-06-09 Revised:2025-09-02 Online:2026-06-15 Published:2026-06-15

Abstract: Thermal runaway early warning for lithium-ion batteries remains a critical challenge in the safety management of new energy vehicles. Conventional external sensors are limited in their ability to detect internal early fault indicators, whereas built-in sensing technology enables in-situ and real-time monitoring of multiple parameters, such as temperature, strain and gas, by embedding miniaturized sensors into critical internal regions of the battery, thereby significantly improving the timeliness and accuracy of early warnings. This paper provides a comprehensive review of recent advances in built-in sensing technologies, including fiber Bragg grating strain sensors, flexible thin-film temperature sensors, and their multi-functional integrated systems, with particular emphasis on their effectiveness in detecting early thermal runaway signals. Additionally, the paper critically analyzes key challenges encountered in practical applications, such as material compatibility, structural integration, multi-signal decoupling, signal transmission reliability, and long-term operational stability. It further emphasizes that the integration of intelligent algorithms with multi-physical sensing represents a promising approach for developing next-generation active battery safety systems.

Key words: lithium-ion battery, built-in sensor, thermal runaway warning, multi-parameter monitoring, fiber Bragg grating(FBG), flexible sensing