Battery Cell Voltage Variance Diagnosis for Abnormality Detection
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Solution Overview
Problem
Existing technologies lack effective methods to diagnose abnormal battery cells in a battery bank based on voltage variance, particularly for identifying different types of abnormalities such as capacity and insulation issues.
Innovation Solution
A battery diagnosis apparatus and method that calculates cumulative voltage variance and deviation for each battery unit, using a controller to identify abnormal vehicles and specific types of battery unit abnormalities by analyzing voltage information during charging cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voltage information is collected from multiple battery units to diagnose abnormalities, then diagnostic accuracy is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the battery bank into multiple individual battery units, each with its own voltage monitoring. By calculating cumulative voltage variance for each unit separately and comparing against threshold values, the system achieves high diagnostic accuracy without requiring a monolithic complex diagnostic system. Each battery unit is independently monitored and evaluated.
Solution Approach 2:
The patent introduces cumulative voltage variance as an intermediary parameter that mediates between raw voltage measurements and abnormality diagnosis. This intermediary metric simplifies the diagnostic process by transforming complex voltage fluctuation patterns into a single comparable value, reducing data processing complexity while maintaining diagnostic accuracy.
2Measurement precision
If cumulative voltage variance is calculated for each battery unit, then abnormality detection precision is improved, but computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary calculations of cumulative voltage variance continuously in the background during normal battery operation. This preliminary action ensures that when abnormality diagnosis is needed, the calculations are already complete or near-complete, reducing the processing time required for actual diagnosis while maintaining high detection precision.
Solution Approach 2:
The system implements feedback by continuously monitoring cumulative voltage variance and comparing it against predetermined threshold values. This feedback mechanism enables real-time abnormality detection without requiring complex batch processing, as the system automatically triggers diagnosis when variance exceeds thresholds, optimizing processing time based on actual need.
3Measurement precision
If deviation analysis is performed on voltage variance data, then ability to distinguish abnormality types is improved, but data processing complexity increases
Solution Approach 1:
The patent applies local quality analysis by examining the specific pattern of voltage variance deviation for each individual battery unit. By analyzing where and how each unit's voltage variance deviates from the expected range, the system can identify specific abnormality types (such as capacity degradation versus insulation problems) without requiring complex global analysis of all battery units simultaneously.
Solution Approach 2:
The patent utilizes parameter changes in the voltage variance data itself as diagnostic indicators. By monitoring how the cumulative voltage variance parameter changes over time and comparing it against expected ranges, the system can distinguish between different abnormality types based on the characteristic patterns of parameter deviation, avoiding the need for complex multi-parameter analysis.
Data Source
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AI summary
A battery diagnosis apparatus includes a voltage obtaining unit configured to obtain voltage information of each of a plurality of battery units included in each of a plurality of vehicles and a controller configured to calculate a cumulative voltage variance of each of the plurality of battery units, based on the voltage information, calculate at least one deviation that is deviation of cumulative voltage variances for each of the plurality of vehicles, and manage the plurality of battery units based on a distribution of the at least one deviation of the plurality of vehicles.