Battery Cell Abnormality Detection from Ignition-Off Voltage Relaxation
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Solution Overview
Problem
Existing battery management systems in eco-friendly vehicles are insufficient in detecting abnormal signs of high-voltage batteries, posing a risk of accidents due to minor quality issues.
Innovation Solution
A method and apparatus that diagnose battery abnormalities by determining voltage changes during the ignition OFF mode, storing defective cell candidates, and increasing a counter value based on comparisons across ignition cycles, triggering a warning and vehicle control when a threshold is exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If monitoring logic for battery safety is applied in existing eco-friendly vehicles, then battery safety monitoring is provided, but it is still insufficient to detect abnormal signs of battery in advance and prevent accidents
Solution Approach 1:
The system performs preliminary diagnosis of battery cells during ignition OFF periods by measuring voltage changes. Defective cell candidates are identified and stored before actual failure occurs. The counter mechanism accumulates evidence of abnormalities across multiple ignition cycles, enabling early detection and warning before catastrophic failure, thus preventing accidents through advance detection.
2Measurement precision
If voltage changes of cells are monitored during ignition OFF mode period, then defective cell candidates can be determined, but additional monitoring complexity and data processing are required
Solution Approach 1:
The system extracts only the critical information needed for diagnosis: voltage changes during ignition OFF periods. By focusing solely on voltage differential measurements during this specific time window and comparing against a simple counter threshold, the system achieves high detection accuracy without requiring complex continuous monitoring of all battery parameters, thus reducing overall system complexity.
Solution Approach 2:
The battery cells themselves provide the diagnostic information through their natural voltage relaxation behavior during ignition OFF periods. The system leverages this self-characteristic of the battery cells without requiring external test equipment or complex excitation signals, simplifying the monitoring approach while maintaining diagnostic accuracy.
3Reliability
If a counter mechanism is used to track defective cell candidates across ignition cycles, then cell abnormality detection reliability is improved, but additional data storage and processing requirements are introduced
Solution Approach 1:
Instead of storing and analyzing all battery data continuously, the system applies local quality assessment by focusing only on specific ignition OFF period voltage changes. The counter mechanism stores only the essential diagnostic information (number of defective cell occurrences) rather than complete historical voltage data, minimizing data storage requirements while maintaining high detection reliability through targeted monitoring.
Data Source
AI summary
In a method and an apparatus for diagnosing abnormality in an eco-friendly vehicle battery, the method includes determining and storing a defective cell candidate based on a voltage change of each of cells forming a battery module during an ignition OFF mode period of the vehicle, increasing a counter value based on a comparison result of a defective cell candidate during a recent ignition OFF mode period and a defective cell candidate during an immediately previous ignition OFF mode period, and detecting a cell abnormality based on whether a current counter value is greater than or equal to a threshold counter value.