An indoor electric vehicle liquid nitrogen fire extinguishing control method and system based on AI intelligent analysis
By deploying multiple sensors in the electric vehicle charging area to generate fire perception data streams, and using deep convolutional neural networks and thermal imaging models to identify the thermal runaway center point, a liquid nitrogen injection strategy is generated. This solves the problem of insufficient accuracy in existing liquid nitrogen fire extinguishing systems and improves fire extinguishing efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGDONG JIUJIAN CONSTR GRP CO LTD
- Filing Date
- 2026-04-15
- Publication Date
- 2026-07-17
AI Technical Summary
Existing liquid nitrogen fire extinguishing systems lack the ability to accurately identify fire intensity and thermal runaway evolution trends, and cannot dynamically track changes in the thermal runaway center point, resulting in delayed fire extinguishing or waste of liquid nitrogen, making it difficult to effectively deal with electric vehicle lithium battery fires.
By deploying temperature sensors, smoke sensors, gas sensors, and flame spectrum sensors, data is collected in real time and multi-dimensional fire perception data streams are generated. Deep convolutional neural networks are used to extract spatiotemporal features and analyze the fire evolution trend. Combined with a thermal imaging 3D reconstruction model, the thermal runaway center point is identified, and a liquid nitrogen injection strategy is generated.
It enables early identification and accurate analysis of the evolution trend of thermal runaway in electric vehicle batteries, improving fire extinguishing response speed and liquid nitrogen utilization efficiency.
Smart Images
Figure CN122399286A_ABST