Visualization analysis of research trends on thermal runaway warning of lithium-ion batteries: a bibliometric study

Lithium-ion battery thermal runaway warning (LIBTRW) is critical for ensuring the safety of electric vehicles and energy storage systems. From the Web of Science Core Collection database, this study systematically retrieves 1190 relevant articles published from 2003 to 2025. Using VOSviewer and CiteSpace, this study presents the first bibliometric analysis of LIBTRW research, including the development trends, research patterns, collaboration networks, publication sources, and citation characteristics. Keyword clustering and evolution path analysis are further performed to identify research hotspots and summarize mainstream early warning methods. The results reveal that the field has experienced an explosive growth since 2019. China dominates publication volume, while European and North American countries exhibit higher average citations per article. Tsinghua University and Beijing Institute of Technology are core research institutions. Scholars such as Ouyang MG, Feng XN, and Wang QS constitute the core author group. The Journal of Energy Storage, Journal of Power Sources, and Applied Energy are the primary publication sources. Research hotspots have shifted from early studies on thermal runaway mechanisms and temperature and voltage monitoring toward systematic directions, including multi-parameter fusion warning, gas sensing, and expansion force monitoring. Ten major research clusters are systematically identified, revealing a technological evolution path from mechanism elucidation to fault diagnosis and then to intelligent early warning. Based on these findings, future research should prioritize sensor reliability validation in real-world scenarios, robust deep learning methods with improved generalization, and module-level early warning testing to bridge the gap between academic research and engineering practice.