Battery Voltage Differential Smoothing for Short-Circuit Detection
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Solution Overview
Problem
Existing battery management systems struggle to accurately detect abnormal voltage drops caused by internal short-circuits in lithium-ion batteries during charging, necessitating improved methods for converting voltage data into differential signals using optimal smoothing parameters.
Innovation Solution
A battery management apparatus and method that determines an optimal smoothing parameter through a set algorithm to convert voltage data into a differential signal, utilizing a cost function to minimize curve fluctuations and detect abnormal voltage drops by classifying capacity values and applying hyper parameters for continuity, enabling accurate detection of battery deterioration and abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If smoothing processing is applied to convert voltage data into differential signals, then curve fluctuations are reduced, but measurement precision deteriorates due to loss of original data characteristics
Solution Approach 1:
The patent dynamically adjusts the smoothing parameter λ based on the charge state of the battery. During constant current charging, a larger λ is used for stronger smoothing, while during constant voltage charging or abnormal conditions, a smaller λ preserves data fidelity. This parameter adaptation resolves the contradiction by optimizing the balance between curve stability and measurement precision according to operational context.
Solution Approach 2:
The smoothing parameter is not fixed but dynamically changed based on charging conditions and detected abnormalities. The system transitions between different smoothing intensities depending on the charge period and detected voltage patterns, making the processing adaptive rather than static, thereby maintaining precision while achieving stability when needed.
2Ease of operation
If a fixed smoothing parameter is used, then processing simplicity is maintained, but detection accuracy deteriorates due to inability to adapt to different charge conditions
Solution Approach 1:
The system implements dynamic parameter adjustment where the smoothing parameter λ changes based on the charge period (CC/CV charging stages) and detected voltage characteristics. This allows the processing to adapt to different operational conditions, improving detection accuracy without significantly complicating the overall processing framework.
Solution Approach 2:
The system uses feedback from voltage differential analysis to detect abnormalities and adjust processing parameters accordingly. When abnormal voltage drops are detected, the system can modify smoothing intensity or trigger alerts, creating a closed-loop system that improves detection accuracy while maintaining operational simplicity through automated adjustments.
3Stability of the object's composition
If aggressive smoothing is applied to reduce curve shaking, then signal stability improves, but loss of information increases due to suppression of abnormal voltage drop signals
Solution Approach 1:
The patent employs conditional parameter adjustment where the smoothing parameter λ is reduced or set to a minimum value when abnormal voltage drops are detected or suspected. This prevents aggressive smoothing from suppressing critical abnormal signals while maintaining stability during normal operation, thus avoiding information loss about battery health issues.
Solution Approach 2:
The system performs preliminary detection of abnormal voltage patterns before applying strong smoothing, and takes counter-actions by reducing smoothing intensity when abnormalities are detected. This preliminary anti-action prevents the loss of critical information that would otherwise be suppressed by aggressive smoothing applied uniformly across all data.
Data Source
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AI summary
A battery management apparatus according to an embodiment includes a voltage measuring unit configured to measure a voltage of a battery cell and a controller configured to sample data regarding the voltage of the battery cell in a designated unit to convert the data into data in a monotonically increasing or monotonically decreasing form, smooth the data by using an optimal smoothing parameter determined according to a set algorithm, and convert the data regarding the voltage of the battery cell into a differential signal. Thus, in a pre-processing process for converting voltage data of a battery into a differential signal, an optimal smoothing parameter may be determined, which enables proper fitting with original data while reducing fluctuation of a curve of a smoothed differential signal.