Battery Aging Detection via Characteristic Curve Segmentation
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Solution Overview
Problem
Existing battery health monitoring methods fail to accurately detect inhomogeneous charge states and metal plating in lithium-ion batteries, leading to potential capacity loss and defects, as they only measure average charge status and do not account for electrode inhomogeneities.
Innovation Solution
A method that determines the aging state of a battery by analyzing significant sections or points in its characteristic curve, using a battery management system to record and adjust voltage and charge parameters over time, allowing for the detection of changes indicative of aging and inhomogeneities, such as shifts, broadening, or amplitude reduction in characteristic curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only average charge status is measured, then measurement simplicity is maintained, but measurement precision deteriorates because inhomogeneous charge states cannot be detected
Solution Approach 1:
The patent segments the battery monitoring approach by analyzing different sections of the characteristic curve separately. Instead of measuring only the average charge status, the method divides the characteristic curve into multiple sections and evaluates each section's position, shape, and amplitude independently. This segmentation enables detection of inhomogeneous charge states while using existing measurement infrastructure, thus improving measurement precision without proportionally increasing device complexity.
Solution Approach 2:
The patent transitions from one-dimensional average charge status measurement to multi-dimensional analysis by examining position, shape, and amplitude parameters of characteristic curve sections. This dimensional expansion allows detection of inhomogeneities that would be invisible in average measurements, significantly improving measurement precision while the analysis is performed computationally rather than requiring additional physical sensors.
2Measurement precision
If detailed characteristic curve analysis is performed, then aging detection accuracy is improved, but loss of time increases due to extensive data processing
Solution Approach 1:
The patent extracts only the most relevant features from the characteristic curve - specifically the position, shape, and amplitude of significant sections. Rather than processing the entire characteristic curve in detail, the method identifies and analyzes only those sections that contain aging information. This extraction approach maintains high aging detection accuracy while significantly reducing the computational burden and data processing time.
Solution Approach 2:
The patent applies partial action by focusing analysis on specific critical sections of the characteristic curve rather than the entire curve. By identifying sections that are most sensitive to aging effects and analyzing only those portions, the method achieves accurate aging detection with reduced processing requirements, balancing precision with time efficiency.
3Reliability
If battery operation continues without aging detection, then productivity is maintained, but reliability deteriorates due to undetected plating and capacity loss
Solution Approach 1:
The patent implements preliminary action by detecting aging signs and plating conditions before they lead to catastrophic failure. The method continuously monitors characteristic curve sections and identifies early indicators of degradation, allowing preventive measures to be taken. This early detection maintains reliability by preventing severe damage while minimizing interruptions to battery usage, as the system can alert users to upcoming issues without requiring immediate shutdown.
Solution Approach 2:
The patent establishes a feedback mechanism where characteristic curve analysis provides continuous information about battery aging state and plating risk. This feedback enables dynamic adjustment of battery operation parameters or user notification, allowing the system to maintain safe operation while optimizing productivity. The feedback loop ensures reliability improvements without excessive interruptions to normal battery usage.
Data Source
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AI summary
The present invention relates to methods for determining the aging state of a battery (10), in particular a lithium-ion battery, comprising the steps (A) acquiring at least one section (25) of a characteristic curve (20) of the battery (10) at a first time point (t1), (B) defining and/or determining at least one significant subsection (30) or point (33) in the section (25) of the characteristic curve (20) of the battery (10), (C) acquiring the corresponding significant subsection (30) or point (33) in the section (25) of the characteristic curve (20) of the battery (10) at a second time point (t2) after the first time point (t1), (D) determining a measure of change of the significant subsection (30) or point (33) in the section (25) of the characteristic curve (20) of the battery (10) at the first and second time points (t1, t2), and (E) generating a signal for determining the aging state. the battery (10) representative aging measure based on the change measure.