Parallel Battery Cell Fault Detection Using Voltage and DCIR
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Solution Overview
Problem
In parallel connected battery systems, the disconnection of a specific cell due to an open parallel connection line or a CID operation leads to overcurrent flow in remaining cells, causing cell deterioration and performance degradation, necessitating a method to detect such disconnections effectively.
Innovation Solution
A method and system that acquire and analyze discharge voltage data using machine learning techniques to identify changes indicative of CID operations or open parallel connection lines, followed by DCIR measurement to confirm connection failures, generating abnormality signals for real-time detection and prevention of cell deterioration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If parallel connection of battery cells is used to increase power and capacity, then the battery can meet high power requirements of medium and large devices, but disconnection of specific cells due to open parallel connection lines or CID operation causes overcurrent flow in remaining cells leading to cell deterioration and performance degradation
Solution Approach 1:
The system performs preliminary detection of cell disconnection by monitoring discharge voltage changes during normal operation before overcurrent damage occurs. The machine learning model predicts potential connection failures by analyzing voltage deviation patterns, enabling preventive action to be taken before the disconnection causes harmful overcurrent flow in remaining cells.
Solution Approach 2:
The system establishes a feedback loop where discharge voltage data is continuously collected, analyzed by the machine learning model, and used to generate detection results that trigger DCIR measurement for confirmation. This closed-loop feedback mechanism enables real-time monitoring and response to connection status changes, allowing the system to adapt to evolving battery conditions and maintain reliability.
2Reliability
If CID operation is performed to prevent overcharging and ensure safety, then battery protection is improved, but disconnection of the specific cell causes overcurrent flow in parallel connected normal cells leading to overloading and deterioration
Solution Approach 1:
The system monitors discharge voltage changes as feedback from CID operations and other connection events. The machine learning model analyzes these voltage deviations to detect when a cell disconnects following CID activation, enabling the system to identify and respond to the resulting overcurrent conditions in remaining cells before damage occurs.
Solution Approach 2:
The patent replaces physical inspection or manual testing of cell connections with an electronic detection system based on voltage monitoring and machine learning analysis. This substitution enables continuous, non-intrusive monitoring of cell connection status without requiring physical access to individual cells or interruption of normal battery operation.
3Difficulty of detecting and measuring
If discharge voltage monitoring is performed to detect cell disconnection, then connection failure detection capability is improved, but complex machine learning analysis and DCIR measurement increase system complexity and measurement time
Solution Approach 1:
The system performs preliminary filtering and analysis of discharge voltage data using the machine learning model to identify patterns indicative of connection failures. This preliminary action pre-processes the raw voltage data to extract meaningful features, reducing the complexity of subsequent DCIR measurement and analysis by focusing only on suspicious cases rather than requiring comprehensive measurement of all cells at all times.
Solution Approach 2:
The system changes the parameter being monitored from direct resistance measurement to discharge voltage deviation analysis. By detecting connection failures through voltage changes during normal discharge operations rather than requiring separate resistance measurements, the system reduces measurement time and system complexity while maintaining detection capability.
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 accurate real-time detection of cell connection failures due to CID operations or open parallel connection lines, preventing battery deterioration and performance degradation by confirming detection results through DCIR measurement.
Implementation Method 1
a monitoring unit configured to monitor a discharge voltage value of the battery
Implementation Method 2
a DCIR measurement unit configured to measure a direct current internal resistance value of the battery in a state in which a charging current flows through the battery
Data Source
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AI summary
The present invention relates to a method and system for detecting connection failure of a parallel connection cell, and more specifically, to a method and system for detecting connection failure of a parallel connected cell that provides improved accuracy by first detecting the cell connection failure due to the CID operation of the battery or opening the parallel connection line for a battery that is being discharged by the operation of an external device, and finally confirming the first detection result through DCIR measurement for the battery.