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使用基于荷电状态的参数检测锂离子电池退化中的拐点。

Detection of the knee point in lithium-ion battery degradation using a state-of-charge-dependent parameter.

作者信息

Kim Hyunjae, Kim Inwoo, Kim Minsoo, An Seongha, Ahn Hyo Chul, Park Dongmin, Lee Jun Hee, Kang Chun Yong, Choi Jang Wook

机构信息

School of Chemical and Biological Engineering and Institute of Chemical Process, Seoul National University, Gwanak-gu, Seoul 08826, Republic of Korea.

Hyundai Motor Group-Seoul National University Joint Battery Research Center, Seoul National University, Gwanak-gu, Seoul 08826, Republic of Korea.

出版信息

Proc Natl Acad Sci U S A. 2025 Jun 10;122(23):e2424838122. doi: 10.1073/pnas.2424838122. Epub 2025 Jun 3.

DOI:10.1073/pnas.2424838122
PMID:40460124
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12167950/
Abstract

The rapidly expanding lithium-ion battery (LIB) market has heightened the demand for efficient diagnostics for in-use cells and the reliable grading of used cells. Various purpose-built analysis tools and statistical algorithms have been developed, but often rely on redundant instrumentation and computationally intensive procedures. Here, we propose using the variance of the capacity difference between 0.2C and 1C, Var(Δ), based on the strong correlation between the interfacial state of the anode and mode of capacity degradation, as a measure of the health state of individual cells. A single-point "off-board" measurement of Var(Δ) indicates whether a particular cell is experiencing self-limiting or accelerating degradation and is thus near a knee point in its cycle life. This assessment additionally provides a quantitative criterion for differentiating used cells for reuse or recycling. Our findings suggest that utilizing state-of-charge-dependent key electrochemical properties enables the cell health to be accurately monitored, thereby promoting sustainability in the expanding battery market.

摘要

快速扩张的锂离子电池(LIB)市场增加了对在用电池进行高效诊断以及对废旧电池进行可靠分级的需求。已经开发了各种专用分析工具和统计算法,但这些往往依赖于冗余仪器和计算密集型程序。在此,我们基于阳极界面状态与容量退化模式之间的强相关性,提出使用0.2C和1C之间容量差的方差Var(Δ),作为衡量单个电池健康状态的指标。对Var(Δ)进行单点“离线”测量可表明特定电池是否正在经历自限性或加速退化,从而判断其是否接近循环寿命的拐点。该评估还提供了一个定量标准,用于区分可再利用或回收的废旧电池。我们的研究结果表明,利用与充电状态相关的关键电化学特性能够准确监测电池健康状态,从而在不断扩张的电池市场中促进可持续发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/265131e8fd52/pnas.2424838122fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/148ea8b387e4/pnas.2424838122fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/6080c7ae9e9d/pnas.2424838122fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/c3ed7dee939b/pnas.2424838122fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/937a75ffcfe5/pnas.2424838122fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/3c2e0ad50f8f/pnas.2424838122fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/265131e8fd52/pnas.2424838122fig06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/148ea8b387e4/pnas.2424838122fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/6080c7ae9e9d/pnas.2424838122fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/c3ed7dee939b/pnas.2424838122fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/937a75ffcfe5/pnas.2424838122fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/3c2e0ad50f8f/pnas.2424838122fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9624/12167950/265131e8fd52/pnas.2424838122fig06.jpg

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本文引用的文献

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Data-driven direct diagnosis of Li-ion batteries connected to photovoltaics.基于数据的光伏直连锂离子电池故障诊断。
Nat Commun. 2023 May 30;14(1):3138. doi: 10.1038/s41467-023-38895-7.
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Entropymetry for detecting microcracks in high-nickel layered oxide cathodes.用于检测高镍层状氧化物正极中微裂纹的嫡度量法。
Proc Natl Acad Sci U S A. 2022 Dec 20;119(51):e2211436119. doi: 10.1073/pnas.2211436119. Epub 2022 Dec 13.
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