Lithium Battery Thermal Runaway Prediction via Capacitive Reactance
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Solution Overview
Problem
Current methods for predicting thermal runaway in lithium batteries are limited by their reliance on external signals that are susceptible to interference and require costly temperature sensors, providing late warnings and high dependency on detection equipment.
Innovation Solution
A method and system using capacitive reactance analysis, where environmental and state of charge data are acquired to establish a measurement frequency and threshold, measuring capacitive reactance curves via alternating current injection to determine thermal runaway levels and provide early warnings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temperature sensors are placed on the battery surface to measure temperature changes, then thermal runaway can be detected, but only surface temperature can be measured and it takes time for internal temperature to transfer to the surface, resulting in delayed detection
Solution Approach 1:
The patent replaces the mechanical/thermal measurement system (temperature sensors measuring heat transfer) with an electrical measurement system (capacitive reactance measurement). By injecting alternating current and measuring the capacitive reactance of the battery, the system directly detects internal temperature changes through electrical property changes, eliminating the time delay associated with thermal conduction to the surface.
2Measurement precision
If temperature sensors are configured for each battery to achieve accurate measurement, then detection accuracy improves, but costs increase significantly
Solution Approach 1:
The patent makes the BMS management system perform multiple functions: it not only manages battery operation but also serves as the measurement system for capacitive reactance detection. The existing MCU and communication interfaces in the BMS are utilized to inject test currents and measure responses, eliminating the need for separate dedicated temperature sensors on each battery cell.
Solution Approach 2:
The battery management system performs self-detection by using its own resources (power supply, measurement circuits, processing unit) to monitor the capacitive reactance of batteries. The BMS injects alternating current through the battery connections and measures the resulting voltage response, allowing the system to monitor itself without external specialized equipment.
3Reliability
If mechanical deformation, pressure increase, gas analysis, or smoke sensing methods are used to detect thermal runaway, then detection can be achieved, but signals are only detected when thermal runaway is about to occur with obvious signs, making prediction difficult and susceptible to external interference
Solution Approach 1:
The patent monitors changes in the capacitive reactance parameter of the battery, which changes with temperature. By tracking the variation of this electrical parameter over time and comparing it against threshold values, the system can detect early temperature rises that precede thermal runaway, providing advance warning before mechanical deformation, pressure buildup, or gas emission occurs.
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
This approach allows for timely and accurate prediction of thermal runaway, reducing the risk of safety accidents and energy storage losses by leveraging real-time capacitive reactance changes with temperature, minimizing equipment dependency.
Implementation Method 1
measuring a capacitive reactance curve of the battery module at the measurement frequency by using an alternating current injection method
Data Source
AI summary
A method and system for predicting thermal runaway in a lithium battery based on capacitive reactance analysis belong to the field of battery management technologies. The method includes: acquiring environmental temperature data, state of charge data, and battery material data of a battery module, and establishing a measurement frequency and a thermal runaway threshold according to a preset expert library; measuring a capacitive reactance curve of the battery module at the measurement frequency by using an alternating current injection method; and determining a thermal runaway level of the battery module according to the capacitive reactance curve, and performing thermal runaway early warning. The principle of detecting the capacitive reactance of the battery module is simple, real-time detection can be implemented by using a BMS system and an MCU controller, and the dependency on sensors and equipment is low.