Secondary Battery Authentication Using Pause-Period Voltage Curves
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Solution Overview
Problem
There is a need for a precise technique to diagnose whether a secondary battery is a genuine product, as counterfeit or modified batteries may use inferior components or have defective control circuits.
Innovation Solution
A battery diagnosis system that includes a sensor to measure the voltage of a secondary battery and a processor to analyze the voltage curve over a diagnosis target period, which includes both charging and discharging periods and pause periods, to determine if the battery is genuine by comparing it to a normal curve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voltage monitoring is performed only during charging or discharging periods, then the diagnosis system is simpler, but the diagnosis precision is insufficient
Solution Approach 1:
The system performs preliminary voltage measurement during pause periods when no charging or discharging occurs. This preliminary action captures the open-circuit voltage characteristics before the actual charging/discharging begins, enabling more accurate authentication without requiring complex additional hardware.
Solution Approach 2:
The system continuously monitors voltage across all three periods (pause, charging, discharging) without interruption. This continuous monitoring ensures that no critical voltage characteristic is missed, improving diagnosis precision while using the existing sensor infrastructure without adding complex intermittent sampling mechanisms.
2Measurement precision
If voltage curve analysis includes pause period in addition to charging and discharging periods, then the diagnosis precision improves, but the diagnosis time increases
Solution Approach 1:
The system performs voltage measurement for a predetermined time during the pause period, which may be shorter than the complete pause duration. This partial measurement approach captures sufficient voltage characteristics for authentication while minimizing the time spent in diagnosis mode.
Solution Approach 2:
The diagnosis system operates periodically by selecting specific time points within the pause, charging, and discharging periods for voltage sampling. This periodic sampling approach reduces the total diagnosis time while still capturing the essential voltage curve characteristics needed for genuine product identification.
3Measurement precision
If multiple voltage parameters (voltage value and rate of change) are checked against multiple ranges, then the diagnosis precision improves, but the computational complexity increases
Solution Approach 1:
The authentication process is segmented into distinct evaluation stages: first checking voltage values against predetermined ranges, then checking rates of change against reference ranges. This segmentation allows the processor to handle complex multi-parameter analysis in manageable steps, improving accuracy without overwhelming computational resources.
Solution Approach 2:
The system evaluates multiple parameters (voltage value, rate of change) against different types of reference data (predetermined ranges, reference ranges derived from normal curves). By changing and comparing multiple parameters rather than relying on a single threshold, the system achieves high authentication accuracy using standard processing operations.
Data Source
AI summary
A battery diagnosis system includes a sensor that measures a voltage of a secondary battery, and a processor configured to diagnose whether the secondary battery is a genuine product based on a voltage curve indicating a time change of a voltage measured by the sensor during a diagnosis target period. The diagnosis target period includes both a charging and discharging period and a charging and discharging pause period.