Battery Voltage Deviation Diagnosis for Micro Short Detection
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Solution Overview
Problem
Current battery systems lack an effective method to diagnose internal micro short circuits, which can lead to permanent damage and safety issues such as overheating and circuit damage if not detected in time.
Innovation Solution
A diagnostic system comprising a voltage measuring unit and a control unit that calculates voltage deviations and variations over time, comparing these patterns to preset diagnosis patterns to determine if a micro short circuit has occurred, allowing for timely disconnection or replacement of affected batteries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voltage monitoring is performed on batteries, then battery state can be tracked, but internal micro short circuits cannot be detected
Solution Approach 1:
The system performs preliminary diagnosis by calculating voltage deviation variations at multiple time periods before a micro short circuit develops into a hard short. By analyzing the pattern of voltage deviations over time (comparing Vdeviation at T1, T2, T3 periods), the system detects early signs of micro short circuits and triggers warnings before permanent damage occurs.
2Productivity
If micro short circuits are not detected, then battery continues operating, but permanent damage and safety issues occur
Solution Approach 1:
The system performs preliminary diagnosis by calculating voltage deviation variations at multiple time periods before a micro short circuit develops into a hard short. By analyzing the pattern of voltage deviations over time (comparing Vdeviation at T1, T2, T3 periods), the system detects early signs of micro short circuits and triggers warnings before permanent damage occurs.
Solution Approach 2:
The system continuously monitors voltage deviations and compares them against threshold values (Vth1, Vth2, Vth3). When the voltage deviation variation pattern exceeds the threshold, the system provides feedback through a warning signal, enabling timely intervention to prevent hard shorts and ensure battery safety.
3Reliability
If voltage deviation patterns are analyzed at multiple time periods, then micro short circuits can be detected early, but system complexity increases
Solution Approach 1:
The diagnosis period is segmented into multiple time periods (T1, T2, T3), with voltage deviation calculated and compared at each segment. This segmentation allows the system to detect the progressive pattern of voltage deviations that characterizes micro short circuits, improving detection accuracy while keeping each individual measurement simple.
Solution Approach 2:
The system calculates voltage deviation at multiple time periods (excessive action) to ensure reliable detection of micro short circuits. By performing more measurements than a single-point check, the system captures the evolving pattern of voltage deviations, enabling accurate diagnosis despite the increased computational effort.
Data Source
AI summary
Aspects of the disclosed technology include techniques, a mechanism, and an apparatus for diagnosing a battery. One or more processors may measure voltages of a plurality of batteries and, based on the measured voltages, determine a voltage deviation of the plurality of batteries. The one or more processors may determine a voltage deviation variation of each battery of the plurality of batteries at predetermined times periods and may compare a pattern of the voltage deviation variations of each battery of the plurality of batteries with a preset diagnosis pattern to diagnose a state of each of the plurality of batteries.