Battery SOC-OCV Curve Shift Detection for Abnormal State Estimation
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Solution Overview
Problem
The correlation between state of charge (SOC) and open circuit voltage (OCV) in lithium ion batteries with lithium iron phosphate and graphite electrodes has a small-variation region, making it difficult to estimate abnormal states such as deterioration or internal short-circuits, particularly in the range of 30 to 95% SOC.
Innovation Solution
A state estimation apparatus that estimates the state of an assembled battery by monitoring the varying position of the SOC-OCV correlation, specifically focusing on the intermediate region between two small-variation regions, to detect abnormalities and deterioration by comparing the position of the variation region relative to the actual capacity of the energy storage devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If OCV is used to estimate battery state in the small-variation region (30-95% SOC), then the measurement is simple and non-intrusive, but the estimation precision deteriorates due to small OCV variations
Solution Approach 1:
The patent divides the SOC range into multiple regions: small-variation regions (30-50% and 50-95% SOC) and an intermediate region (around 50% SOC). By segmenting the monitoring approach and focusing on the intermediate region where OCV variations are more pronounced, the system achieves better estimation precision while maintaining the simplicity of OCV measurement.
2Device complexity
If traditional OCV monitoring is used in the small-variation region, then the device complexity is low, but the ability to detect abnormalities and deterioration is insufficient
Solution Approach 1:
The patent establishes a reference SOC-OCV curve from new battery data before deterioration occurs. By comparing the actual SOC-OCV correlation against this pre-established reference, the system can detect deviations indicating abnormality or internal short-circuits. This preliminary action of creating a reference baseline enables reliable abnormality detection without complex additional hardware.
3Measurement precision
If monitoring frequency is increased to detect abnormalities early, then the detection precision improves, but the loss of time and energy for measurements increases
Solution Approach 1:
The patent applies different monitoring strategies to different SOC regions. Instead of uniformly monitoring across all SOC ranges, the system focuses monitoring efforts on the intermediate region (around 50% SOC) where OCV variations provide better detection sensitivity. This localized quality approach improves detection precision while minimizing the time and energy lost to measurements in less informative regions.
Data Source
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AI summary
A state estimation apparatus disclosed in the present specification is a battery management unit estimating the state of an assembled battery including a plurality of energy storage devices. The energy storage devices each have a small-variation region II and a small-variation region IV where an OCV variation amount relative to a residual capacity is smaller, and a variation region I, a variation region III, and a variation region V where the OCV variation amount relative to the residual capacity is greater than that in the small-variation region II and the small-variation region IV. The battery management unit estimates whether or not the assembled battery is usable based on a varying position (a variation in position from a first position to a second position) of the variation region III relative to the actual capacity of the plurality of energy storage devices.