一种基于红外高光谱遥测的锂电池热失控气体监测方法
By using infrared hyperspectral telemetry technology and physical information neural networks, the problems of real-time monitoring and multi-component identification of thermal runaway gases in lithium batteries have been solved. This enables non-contact, long-distance, early warning and multi-component gas monitoring, and provides information on the gas plume distribution in lithium battery thermal runaway.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CIVIL AVIATION UNIV OF CHINA
- Filing Date
- 2026-06-18
- Publication Date
- 2026-07-17
AI Technical Summary
Existing lithium battery thermal runaway gas monitoring technologies have limitations such as slow response, susceptibility to poisoning, difficulty in covering the entire space, and inability to monitor in real time, making it impossible to achieve non-contact, real-time, multi-component gas monitoring.
Using infrared hyperspectral remote sensing technology, a physical information neural network is constructed through continuous hyperspectral data acquisition. The characteristic absorption peaks of the gas are used to identify the gas plume region, and differential spectral correction and graph attention spatial aggregation are performed to output the gas column concentration, thus realizing non-contact, real-time monitoring of multi-component gases.
It enables non-contact, long-distance, real-time monitoring of thermal runaway gases in lithium batteries, has strong early warning capabilities, can identify multiple gases at extremely low concentrations, provides spatial distribution information of gas plumes, and has strong resistance to environmental interference.
Smart Images
Figure CN122409557A_ABST