Battery Module Thermal Runaway Prediction Using Cell State Data
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Solution Overview
Problem
Current methods for detecting thermal runaway in battery modules are inadequate, as they either add significant weight and cost or fail to provide timely detection, leading to potential catastrophic events such as fires and explosions.
Innovation Solution
A method that continuously captures current, temperature, and state of charge values for each cell in a battery module, using these parameters to calculate temperature and runaway predictor values, allowing for early detection of thermal runaway events with minimal false alarms and precise location identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical improvements such as safety vents, steel containers, pressure switches, structural foam, heat resistant barriers, gaps, or fuses are implemented at cell and module level, then the harm caused by thermal runaway is reduced, but additional weight, cost, and size are added to the battery module
Solution Approach 1:
The patent replaces mechanical/physical safety measures (vents, containers, barriers, fuses) with an electrical detection system that uses current, temperature, and state of charge sensors combined with a prediction algorithm to detect thermal runaway events, thereby achieving safety without the associated weight and cost of physical protective structures
Solution Approach 2:
The detection system utilizes existing operational parameters (current, temperature, state of charge) that are already measured for battery management purposes, transforming this routine data into predictive safety information without requiring additional dedicated sensors or physical safety components
2Reliability
If physical improvements such as safety vents, steel containers, pressure switches, structural foam, heat resistant barriers, gaps, or fuses are implemented at cell and module level, then the harm caused by thermal runaway is reduced, but additional cost is added to the battery module
Solution Approach 1:
The patent replaces costly physical safety components with a software-based prediction system that processes existing sensor data through algorithms to identify thermal runaway risks, significantly reducing manufacturing costs while maintaining safety effectiveness
Solution Approach 2:
The system uses a predictive model that calculates runaway predictor values based on patterns in operational data, creating a virtual representation of thermal behavior that avoids the need for expensive physical safety prototypes and testing
3Reliability
If threshold comparison of temperatures or temperature prediction using look-up tables is used to predict thermal runaway, then thermal runaway events can be detected, but the detection time is not short enough for dedicated applications
Solution Approach 1:
The patent transforms the detection approach by changing from single-parameter threshold comparison to a multi-parameter prediction model that continuously calculates runaway predictor values using current, temperature, and state of charge data, enabling faster and more accurate detection of thermal runaway events
Solution Approach 2:
The system implements continuous monitoring and prediction with feedback loops that update runaway predictor values in real-time based on changing operational conditions, allowing the system to adapt and detect thermal runaway events more rapidly than static threshold methods
4Reliability
If threshold comparison of temperatures or temperature prediction using look-up tables is used to predict thermal runaway, then thermal runaway events can be detected, but false alarms and missed detections occur frequently
Solution Approach 1:
The patent improves detection accuracy by changing from simple temperature threshold comparison to a comprehensive prediction model that incorporates current, temperature, and state of charge parameters, calculating runaway predictor values that more precisely identify actual thermal runaway events while filtering out false alarms
Solution Approach 2:
The system performs preliminary calculation of runaway predictor values using pre-stored coefficients and patterns from look-up tables, preparing prediction data in advance to enable rapid and accurate discrimination between normal temperature variations and actual thermal runaway events
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables fast, accurate, and reliable prediction of thermal runaway, preventing domino effects and minimizing damage by using spatial and dynamic thermal, electric, and electrochemical parameters, thus providing timely interventions.
Implementation Method 1
The over current typically may occur due to an external short circuit in or outside the battery module. The common characteristic of thermal runaway events in Li-Ion battery cells, independent of the triggering event is that the separator starts to melt in a growing area, and the resulting current increase generates even more heat around the defect
Data Source
AI summary
A device for detecting a thermal runaway of a battery module with a number of cells includes a current acquisition module that is configured to capture a set of currents, and a temperature acquisition module that is configured to capture a set of temperatures. The device includes a state of charge capturing module that is configured to capture a set of states, and a resistance calculation module that is configured to derive a set of resistances. The device includes a temperature prediction module that is configured to calculate a set of temperature predictors, and a runaway prediction module that is configured to calculate a set of runaway predictors. A warning module that is configured to set a warning indicator when at least one runaway predictor value of the set of runaway predictors exceeds a predefined threshold value.