Quantum sensor-based power battery runaway early warning system and method
By combining the electric and magnetic field characteristics of dual-channel quantum sensors and traditional sensors with deep learning models, the accuracy and reliability of early warning of thermal runaway of power batteries have been improved. This solves the problems of insufficient early warning signal perception and noise interference in existing technologies and provides early non-contact warning capabilities.
Patent Information
- Application Number
- CN202610837420.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-11
- Publication Date
- 2026-07-10
AI Technical Summary
Existing power battery thermal runaway early warning systems are insufficient in detecting early warning signals and lack reliability under complex vehicle operating conditions and noise interference, resulting in the inability to achieve reliable early warning.
A power battery runaway early warning system based on the joint judgment of electric field characteristics, magnetic field characteristics and traditional monitoring characteristics is adopted. It uses dual-channel quantum sensors and traditional sensors for joint monitoring, and combines deep learning models for signal processing and feature extraction to achieve multi-dimensional anomaly detection and early warning.
It significantly improves the accuracy of identifying internal anomalies in power batteries and the reliability of early warning of thermal runaway. It can issue warnings minutes to hours before thermal runaway occurs, thus improving the timeliness and reliability of the warnings.
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