Battery SOH Detection Using Charging Curve Segment Correlation
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Solution Overview
Problem
Current methods lack reliability and accuracy in assessing battery state of health, leading to potential safety risks due to continued use of malfunctioning batteries.
Innovation Solution
A method and system for detecting battery state of health by extracting a target curve segment from a charging characteristic curve, establishing a corresponding relation between characteristic parameters and battery state of health, and using correlation coefficients to determine the battery's health, with optional assessment for abusive operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional battery state of health assessment methods are used, then the detection process is simple, but the reliability and accuracy of detection are poor
Solution Approach 1:
The charging characteristic curve is divided into multiple curve segments, and the target curve segment with the highest correlation to battery state of health is extracted for analysis. This segmentation approach focuses detection on the most informative portion of the charging curve, improving accuracy while managing complexity
Solution Approach 2:
The method extracts specific characteristic parameters (such as charging duration, voltage, current) from the target curve segment of the charging characteristic curve. By extracting only the relevant features rather than analyzing the entire curve, the method achieves high detection accuracy with controlled complexity
2Reliability
If no reliable battery state of health assessment method is used, then the system is simple, but safety incidents cannot be avoided
Solution Approach 1:
The method establishes a corresponding relation between characteristic parameters of the target curve segment and battery state of health through multiple charging cycles. This feedback mechanism continuously refines the assessment model, improving reliability by learning from accumulated charging data and adjusting the correlation relationships
Solution Approach 2:
The system performs preliminary charging cycles to collect charging data and establish the corresponding relation between characteristic parameters and battery state of health before actual assessment. This preliminary action creates a reference model that enables reliable future assessments without requiring complex real-time analysis
Data Source
AI summary
The invention discloses a method, a system, a device, and a medium for detecting a battery state of health. The method includes extracting a target curve segment from a first charging characteristic curve of a battery under test; and determining, according to a corresponding relation between characteristic parameters of the target curve segment and the battery state of health, the battery state of health matching the characteristic parameters of the target curve segment, and determining the battery state of health as the battery state of health of the battery under test. By utilizing said corresponding relation as the calculation basis, the invention improves the reliability and accuracy of the detection of battery state of health detection. The invention also tracks instances of abusive conditions that accelerate battery aging, assessing whether such conditions accelerate battery degradation and issuing warnings accordingly.