Battery Stack Voltage Diagnosis for Thermal Runaway Detection
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Solution Overview
Problem
Existing methods for diagnosing thermal runaway in lithium-ion electrochemical cells in electric batteries are prone to false positives and negatives, and lack cost-effectiveness and ease of implementation.
Innovation Solution
A method using electric voltage measurements from Battery Management Unit (BMU) instruments to diagnose thermal runaway by comparing cell and stack voltages with threshold values, confirming with additional checks to differentiate between instrument malfunctions and actual thermal events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing thermal runaway diagnosis methods are used, then thermal runaway can be detected, but false positives and false negatives occur reducing reliability
Solution Approach 1:
The diagnosis method is segmented into multiple independent diagnostic indicators (voltage drop rate, absolute voltage threshold, temperature threshold) that are evaluated separately and combined through logical operations. This segmentation allows each indicator to be optimized independently while reducing the impact of false signals from any single indicator, thereby improving both reliability and detection accuracy.
Solution Approach 2:
The system continuously monitors voltage and temperature parameters in real-time and uses feedback loops to adjust diagnostic thresholds based on historical data and system state. The multi-threshold approach with hysteresis creates a feedback mechanism that prevents false positives by requiring sustained deviation from normal parameters before triggering a thermal runaway diagnosis.
2Measurement precision
If complex diagnosis methods with multiple parameters are used, then detection accuracy improves, but implementation complexity and cost increase
Solution Approach 1:
The diagnostic method uses universal parameters (voltage and temperature) that are already measured by standard battery management system sensors. By making the existing sensors serve multiple functions (both normal operation monitoring and thermal runaway detection), the method achieves high detection accuracy without adding complex dedicated measurement equipment, thus avoiding increased implementation complexity and cost.
Solution Approach 2:
The system uses its own existing measurement infrastructure (voltage and temperature sensors) to perform thermal runaway diagnosis without requiring external or additional specialized equipment. The battery management system's existing data acquisition and processing capabilities are leveraged to execute the multi-threshold diagnostic algorithm, making the implementation cost-effective and simple.
3Ease of manufacture
If simple diagnosis methods are used, then ease of implementation improves, but false positives and negatives increase reducing efficiency
Solution Approach 1:
The system pre-calculates and stores voltage drop rate thresholds and temperature thresholds before actual thermal runaway events occur. These preliminary thresholds are derived from normal operating data and are ready for immediate comparison during real-time monitoring. This preliminary preparation enables the simple, fast comparison operations that maintain high diagnosis efficiency without sacrificing accuracy.
Solution Approach 2:
The diagnostic method uses inexpensive, easily obtainable voltage and temperature measurements that are already available from standard sensors. By relying on these cheap, readily available parameters rather than expensive specialized sensors or complex measurement systems, the method achieves ease of implementation while maintaining high diagnostic efficiency through the multi-threshold evaluation logic.
Data Source
AI summary
A method for the diagnosis of thermal runaway in an electric battery having at least one stack of electrochemical cells connected to one another in series. The diagnosis method provides for the steps of: measuring a first electric voltage at the ends of each electrochemical cell; measuring a second electric voltage at the ends of the entire stack of electrochemical cells; calculating a difference between the second electric voltage and the sum of all first electric voltages; and diagnosing a thermal runaway of an electrochemical cell, if the first electric voltage of the electrochemical cell is smaller than a first threshold value and if, simultaneously, the difference between the second electric voltage and the sum of all first electric voltages is smaller than a second threshold value.