Fengwei Liang
Papers
1
Total Citations
3
H-Index
1
About
Fengwei Liang is a researcher at the forefront of lithium battery safety, specializing in the intersection of machine vision and thermal runaway detection. His work addresses a critical challenge in energy storage: identifying and predicting battery failures before they escalate into catastrophic events. Liang’s most-cited paper, “Thermal runaway boundary recognition and early detection of lithium battery based on machine vision algorithm” (2025), introduces a novel approach that leverages visual data to recognize the subtle precursors of thermal runaway, offering a non-invasive, real-time monitoring solution. This contribution has already garnered 3 citations, signaling its early impact in a rapidly evolving field. By integrating computer vision with battery diagnostics, Liang’s research not only enhances safety protocols for electric vehicles and portable electronics but also opens new pathways for intelligent battery management systems. His work exemplifies a growing trend toward data-driven, predictive maintenance in energy technology. As the demand for safer, more reliable batteries intensifies, Liang’s innovative methods position him as a key contributor to the next generation of battery safety solutions.
Research Focus
Key Achievements
Top Papers
- 1