Battery Cell Abnormality Detection Using Matrix-Decomposed Features
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Solution Overview
Problem
Detecting abnormality in individual battery cells within a battery pack is challenging due to their connection in series and/or parallel configurations, making it difficult to identify faulty cells among multiple cells.
Innovation Solution
An electronic device with a battery module, sensor circuit, and processor uses a matrix decomposition algorithm to analyze state values of battery cells, identifying abnormalities based on feature data derived from input data, specifically using a feature matrix with designated diagonal components substituted by 0, and providing user notifications for abnormal cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery charge/discharge characteristics are used for detection, then early abnormality detection is possible, but detection accuracy deteriorates due to external factors
Solution Approach 1:
The detection method is segmented into multiple independent measurement components: internal resistance measurement, open circuit voltage measurement, and temperature measurement. Each component measures a specific parameter independently, and their results are integrated to make a comprehensive determination about battery abnormality, thereby improving detection accuracy while maintaining early detection capability.
Solution Approach 2:
The patent introduces internal resistance as an intermediary parameter that indirectly reflects battery health status. Instead of directly measuring complex battery characteristics that are sensitive to external factors, the system measures internal resistance which serves as a stable intermediate indicator of battery degradation and abnormality.
2Measurement precision
If multiple measurement parameters are used, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The controller is designed with multi-functionality, serving both as the charging/discharging control unit and as the detection system. The same controller measures multiple parameters (voltage, current, temperature, internal resistance) and performs both charging management and abnormality detection functions, thereby improving detection accuracy without proportionally increasing device complexity.
Solution Approach 2:
The patent combines the charging control function and detection function into a single integrated system. The controller that manages charge/discharge operations also performs measurements of voltage, current, temperature, and internal resistance, and makes determination about battery abnormality. This merging reduces the need for separate dedicated detection hardware, maintaining simplicity while achieving multi-parameter measurement.
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
Effectively detects abnormal battery cells by analyzing state values through matrix decomposition, enabling timely identification and notification of faulty cells within a battery pack.
Implementation Method 1
measuring an internal resistance of the battery
Data Source
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AI summary
An electronic device according to an embodiment disclosed herein includes a battery module including a plurality of battery cells, a sensor circuit configured to obtain state values of each of the plurality of battery cells, and a processor configured to obtain values related to states of each of the plurality of cells as input data through the sensor circuit, obtain feature data based on a feature matrix derived from the input data by using a designated matrix decomposition algorithm, and identify whether each of the plurality of cells is abnormal, based on the feature data, in which the feature matrix is a matrix where values of a designated number of major diagonal components among a plurality of diagonal components of a diagonal matrix for the input data are substituted by 0. The feature matrix may be a matrix where values of a designated number of major diagonal components among a plurality of diagonal components of a diagonal matrix for the input data are substituted by 0.