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.

CN122362152APending Publication Date: 2026-07-10CHANGCHUN UNIV OF SCI & TECH
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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

Technical Problem

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.

Method used

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.

Benefits of technology

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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Abstract

This invention relates to the field of battery runaway early warning technology, specifically to a power battery runaway early warning system and method based on quantum sensors. The power battery runaway early warning system based on quantum sensors includes: a multi-modal acquisition module that uses traditional sensors and a dual-channel quantum sensor to monitor the power battery pack and acquire monitoring data; a signal processing and feature extraction module that preprocesses and extracts features from the monitoring data; a BMS deep fusion module for anomaly detection, anomaly classification, and anomaly prediction; a hierarchical collaborative execution module that executes corresponding early warning actions based on the output results of the BMS deep fusion module; and storage of all data and early warning records on a cloud platform host computer for retrieval by the aforementioned modules when needed. This invention utilizes a dual-channel quantum sensor to collaboratively capture full-band electromagnetic fingerprints, integrates traditional sensor multi-dimensional verification, suppresses vehicle interference, and achieves reliable early warning of battery thermal runaway.
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