Article(id=1244280830500123373, tenantId=1146029695717560320, journalId=1243978990336127019, issueId=1244280827157263057, articleNumber=null, orderNo=null, doi=10.7520/1001-4888-25-014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1737129600000, receivedDateStr=2025-01-18, revisedDate=1743091200000, revisedDateStr=2025-03-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1774589267610, onlineDateStr=2026-03-27, pubDate=1753977600000, pubDateStr=2025-08-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774589267610, onlineIssueDateStr=2026-03-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774589267610, creator=13701087609, updateTime=1774589267610, updator=13701087609, issue=Issue{id=1244280827157263057, tenantId=1146029695717560320, journalId=1243978990336127019, year='2025', volume='40', issue='4', pageStart='387', pageEnd='538', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1774589266813, creator=13701087609, updateTime=1774589721933, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1244282736148595306, tenantId=1146029695717560320, journalId=1243978990336127019, issueId=1244280827157263057, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1244282736148595307, tenantId=1146029695717560320, journalId=1243978990336127019, issueId=1244280827157263057, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=433, endPage=443, ext={EN=ArticleExt(id=1244280831833912053, articleId=1244280830500123373, tenantId=1146029695717560320, journalId=1243978990336127019, language=EN, title=Experimental study on life prediction parameters of lithium-ion batteries, columnId=null, journalTitle=Journal of Experimental Mechanics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Accurate prediction of the lifespan of lithium-ion batteries is crucial for ensuring the electrical safety of equipment. In the process of battery lifespan prediction, the selection of indirect parameters is a key link. However, at present, there are relatively few studies on the relationship between indirect parameters and the internal reaction mechanism of batteries. This paper conducts an experimental study on the relationship between indirect parameters in battery life prediction and the battery reaction mechanism, designs an integrated experimental scheme for battery charge and discharge cycles, electrochemical impedance and acoustic emission, and obtains the nonlinear evolution laws of capacity, impedance and mechanical damage with the number of cycles through experiments. By analyzing the evolution laws of charge transfer impedance (RCT) and solid-state electrolyte interface film impedance (RSEI), the mechanism by which RCT and RSEI affect the degradation of battery life by influencing the transmission and transfer of internal charges in the battery was discovered. Further, the intrinsic qualitative connection among battery capacity, impedance and damage was expounded. Subsequently, based on the qualitative connection between impedance and mechanical damage, the Pearson correlation coefficient was used to quantify the relationship between RCT, RSEI and the cumulative impact times of acoustic emission. The results show that the correlation coefficients of RCT and RSEI with the cumulative impact times of acoustic emission are both higher than 0.9, indicating that impedance is closely related to electrode mechanical damage. Impedance RCT and RSEI contain both electrochemical factors and electrode mechanical damage information. Moreover, the relationship between impedance and mechanical damage has been further verified through experiments with different charge and discharge rates and different electrode materials.

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精确预测锂离子电池寿命对保障设备用电安全至关重要,在电池寿命预测过程中,间接参数的选取是关键环节,然而目前对间接参数与电池内部反应机理的研究较少。本文针对电池寿命预测中的间接参数与电池反应机理的关系开展实验研究,设计了电池充放电循环、电化学阻抗和声发射一体化实验方案,通过实验获得了容量、阻抗和力学损伤随循环圈数的非线性演化规律;分析电荷转移阻抗RCT和固态电解质界面膜阻抗RSEI的演化规律,发现了RCTRSEI通过影响电池内部电荷的传输和转移来影响电池寿命衰退的机理,从而阐述了电池容量-阻抗-损伤的内在定性联系;根据阻抗和力学损伤的定性联系,采用皮尔逊相关系数量化了RCTRSEI与声发射累积撞击次数的关系,结果显示,RCTRSEI与声发射累积撞击次数的相关性系数均高于0.9。上述实验结果与分析表明,阻抗与电极力学损伤关系紧密,阻抗RCTRSEI既包含电化学因素又包含电极力学损伤信息,而且阻抗与力学损伤的关系也通过不同充放电倍率和不同电极材料的实验得到了验证。

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谢海妹(1988-),女,博士,副研究员。主要研究领域:储能材料力-电化学耦合和深海腐蚀力学。Email:;
宋海滨(1991-),男,博士,工程师。主要研究领域:纳米电极材料力-电化学耦合行为原位表征与机理分析、汽车底盘轻量化设计与仿真。Email:
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diagram of the electrochemical dynamic reaction process of the electrode and its mechanical damage;(b) schematic diagrams of the equivalent circuit and impedance spectrum corresponding to the electrochemical reaction process;(c) a schematic diagram of an acoustic emission signal impact, figureFileSmall=jOhxHJXYnSnvQ/3Gv50qAw==, figureFileBig=HHI3fnlJ8eHk/qkWKdj5ww==, tableContent=null), ArticleFig(id=1244340241012732489, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=图1, caption=(a)电极电化学动态反应过程及其力学损伤示意图;(b)电化学反应过程对应的等效电路和阻抗谱示意图;(c)1个声发射信号撞击示意图, figureFileSmall=jOhxHJXYnSnvQ/3Gv50qAw==, figureFileBig=HHI3fnlJ8eHk/qkWKdj5ww==, tableContent=null), ArticleFig(id=1244340241121784403, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=EN, label=Fig.2, caption=Assembly diagram of CR2032 button battery, figureFileSmall=4xYEMOO+8CxkkcruCltyVA==, figureFileBig=bGQX1csZbw8EjsWWdwnECw==, tableContent=null), ArticleFig(id=1244340241256002141, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=图2, caption=CR2032型纽扣电池装配示意图, figureFileSmall=4xYEMOO+8CxkkcruCltyVA==, figureFileBig=bGQX1csZbw8EjsWWdwnECw==, tableContent=null), ArticleFig(id=1244340241377636961, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=EN, label=Fig.3, caption=Battery cycling-impedance-acoustic emission integration experiment device diagram, figureFileSmall=H90tMNlAOF6PIUBxEZyknA==, figureFileBig=koDzm+MjInA37UNsm88+Og==, tableContent=null), ArticleFig(id=1244340241478300264, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=图3, caption=电池循环-阻抗-声发射一体化实验装置图, figureFileSmall=H90tMNlAOF6PIUBxEZyknA==, figureFileBig=koDzm+MjInA37UNsm88+Og==, tableContent=null), ArticleFig(id=1244340241587352174, 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figureFileSmall=6WIxiuV6/L6cn2QRFVtA6g==, figureFileBig=TuferrH+hQnMcwOPfHF5Ww==, tableContent=null), ArticleFig(id=1244340243776778903, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=图6, caption=不同倍率和电极材料的健康状态、阻抗和声发射累积撞击次数的演化曲线, figureFileSmall=6WIxiuV6/L6cn2QRFVtA6g==, figureFileBig=TuferrH+hQnMcwOPfHF5Ww==, tableContent=null), ArticleFig(id=1244340243940356767, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=EN, label=Fig.7, caption=The normalized evolution curves of the cumulative impact times of impedance and acoustic emission under different magnifications and different materials:(a) silicon-carbon electrode at C rate;(b) graphite electrode at C/2 rate;(c) graphite electrode at C rate;(d) the Pearson correlation coefficient r of the cumulative impact times of impedance and acoustic emissions, figureFileSmall=9v+ZFg4D0BbPUShRiwAPVw==, figureFileBig=ij6tGUdPGfM2MwhbQCIz2A==, tableContent=null), ArticleFig(id=1244340244070380192, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=图7, caption=不同倍率、不同材料下的阻抗和声发射累积撞击次数的归一化演化曲线:(a)C倍率下硅碳电极;(b)C/2倍率下石墨电极;(c)C倍率下石墨电极;(d)阻抗和声发射累积撞击次数的皮尔逊相关系数r, figureFileSmall=9v+ZFg4D0BbPUShRiwAPVw==, figureFileBig=ij6tGUdPGfM2MwhbQCIz2A==, tableContent=null), ArticleFig(id=1244340244187820713, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=EN, label=Tab.1, caption=

The whole experiment plan

, figureFileSmall=null, figureFileBig=null, tableContent=
实验实验目的重要参数测试条件倍率电极材料
充放电循环获得电池性能与寿命循环圈数、容量截止电压0.01 V~2 VC石墨
C硅碳
C/2石墨
C/2硅碳
电化学阻抗获得电极动态电化学过程 RSEIRCT测试频率0.01 Hz~500 kHz,振幅5 mVC石墨
C硅碳
C/2石墨
C/2硅碳
声发射获得电极力学损伤程度声发射信号撞击、幅度采集频率0~150 kHz,幅度阈值27 dBC石墨
C硅碳
C/2石墨
C/2硅碳
), ArticleFig(id=1244340244347204275, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=表1, caption=

整体实验方案设计

, figureFileSmall=null, figureFileBig=null, tableContent=
实验实验目的重要参数测试条件倍率电极材料
充放电循环获得电池性能与寿命循环圈数、容量截止电压0.01 V~2 VC石墨
C硅碳
C/2石墨
C/2硅碳
电化学阻抗获得电极动态电化学过程 RSEIRCT测试频率0.01 Hz~500 kHz,振幅5 mVC石墨
C硅碳
C/2石墨
C/2硅碳
声发射获得电极力学损伤程度声发射信号撞击、幅度采集频率0~150 kHz,幅度阈值27 dBC石墨
C硅碳
C/2石墨
C/2硅碳
), ArticleFig(id=1244340244502393531, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=EN, label=Tab.2, caption=

Charging and discharging cycle loading test process

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测试步骤测试工步加载条件结束条件
1静置静置时间2 min
2恒流放电C/2倍率电压≤0.01 V
3静置静置时间2 min
4恒流充电C/2倍率电压≥2 V
5恒压充电电压2 V电流≤0.02 mA
), ArticleFig(id=1244340244624028356, tenantId=1146029695717560320, journalId=1243978990336127019, articleId=1244280830500123373, language=CN, label=表2, caption=

充放电循环加载测试流程

, figureFileSmall=null, figureFileBig=null, tableContent=
测试步骤测试工步加载条件结束条件
1静置静置时间2 min
2恒流放电C/2倍率电压≤0.01 V
3静置静置时间2 min
4恒流充电C/2倍率电压≥2 V
5恒压充电电压2 V电流≤0.02 mA
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锂离子电池寿命预测参数的实验研究
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张子龙 1 , 谢海妹 1, 2, 3 , 宋海滨 4 , 张茜 1, 2, 3 , 仇巍 1, 2, 3 , 王毅泽 1, 2, 3 , 亢一澜 1, 2
实验力学 | 2025,40(4): 433-443
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实验力学 | 2025, 40(4): 433-443
锂离子电池寿命预测参数的实验研究
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张子龙1, 谢海妹1, 2, 3 , 宋海滨4 , 张茜1, 2, 3, 仇巍1, 2, 3, 王毅泽1, 2, 3, 亢一澜1, 2
作者信息
  • 1.天津大学机械工程学院力学系,天津 300350
  • 2.天津市现代工程力学重点实验室,天津 300350
  • 3.车用动力系统全国重点实验室,天津 300350
  • 4.北京经纬恒润科技股份有限公司,北京 100191

通讯作者:

谢海妹(1988-),女,博士,副研究员。主要研究领域:储能材料力-电化学耦合和深海腐蚀力学。Email:;
宋海滨(1991-),男,博士,工程师。主要研究领域:纳米电极材料力-电化学耦合行为原位表征与机理分析、汽车底盘轻量化设计与仿真。Email:
Experimental study on life prediction parameters of lithium-ion batteries
Zilong ZHANG1, Haimei XIE1, 2, 3 , Haibin SONG4 , Qian ZHANG1, 2, 3, Wei QIU1, 2, 3, Yize WANG1, 2, 3, Yilan KANG1, 2
Affiliations
  • 1.Department of Mechanics, School of Mechanical Engineering, Tianjin University, Tianjin 300350, China
  • 2.Tianjin Key Laboratory of Modern Engineering Mechanics, Tianjin 300350, China
  • 3.National Key Laboratory of Vehicle Power System, Tianjin 300350, China
  • 4.Beijing Jingwei Hirain Technologies Co., Inc., Beijing 100191, China
出版时间: 2025-08-01 doi: 10.7520/1001-4888-25-014
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精确预测锂离子电池寿命对保障设备用电安全至关重要,在电池寿命预测过程中,间接参数的选取是关键环节,然而目前对间接参数与电池内部反应机理的研究较少。本文针对电池寿命预测中的间接参数与电池反应机理的关系开展实验研究,设计了电池充放电循环、电化学阻抗和声发射一体化实验方案,通过实验获得了容量、阻抗和力学损伤随循环圈数的非线性演化规律;分析电荷转移阻抗RCT和固态电解质界面膜阻抗RSEI的演化规律,发现了RCTRSEI通过影响电池内部电荷的传输和转移来影响电池寿命衰退的机理,从而阐述了电池容量-阻抗-损伤的内在定性联系;根据阻抗和力学损伤的定性联系,采用皮尔逊相关系数量化了RCTRSEI与声发射累积撞击次数的关系,结果显示,RCTRSEI与声发射累积撞击次数的相关性系数均高于0.9。上述实验结果与分析表明,阻抗与电极力学损伤关系紧密,阻抗RCTRSEI既包含电化学因素又包含电极力学损伤信息,而且阻抗与力学损伤的关系也通过不同充放电倍率和不同电极材料的实验得到了验证。

阻抗演化  /  声发射  /  力学损伤  /  寿命预测参数  /  锂离子电池

Accurate prediction of the lifespan of lithium-ion batteries is crucial for ensuring the electrical safety of equipment. In the process of battery lifespan prediction, the selection of indirect parameters is a key link. However, at present, there are relatively few studies on the relationship between indirect parameters and the internal reaction mechanism of batteries. This paper conducts an experimental study on the relationship between indirect parameters in battery life prediction and the battery reaction mechanism, designs an integrated experimental scheme for battery charge and discharge cycles, electrochemical impedance and acoustic emission, and obtains the nonlinear evolution laws of capacity, impedance and mechanical damage with the number of cycles through experiments. By analyzing the evolution laws of charge transfer impedance (RCT) and solid-state electrolyte interface film impedance (RSEI), the mechanism by which RCT and RSEI affect the degradation of battery life by influencing the transmission and transfer of internal charges in the battery was discovered. Further, the intrinsic qualitative connection among battery capacity, impedance and damage was expounded. Subsequently, based on the qualitative connection between impedance and mechanical damage, the Pearson correlation coefficient was used to quantify the relationship between RCT, RSEI and the cumulative impact times of acoustic emission. The results show that the correlation coefficients of RCT and RSEI with the cumulative impact times of acoustic emission are both higher than 0.9, indicating that impedance is closely related to electrode mechanical damage. Impedance RCT and RSEI contain both electrochemical factors and electrode mechanical damage information. Moreover, the relationship between impedance and mechanical damage has been further verified through experiments with different charge and discharge rates and different electrode materials.

impedance evolution  /  acoustic emission  /  mechanical damage  /  life prediction parameters  /  lithium-ion battery
张子龙, 谢海妹, 宋海滨, 张茜, 仇巍, 王毅泽, 亢一澜. 锂离子电池寿命预测参数的实验研究. 实验力学, 2025 , 40 (4) : 433 -443 . DOI: 10.7520/1001-4888-25-014
Zilong ZHANG, Haimei XIE, Haibin SONG, Qian ZHANG, Wei QIU, Yize WANG, Yilan KANG. Experimental study on life prediction parameters of lithium-ion batteries[J]. Journal of Experimental Mechanics, 2025 , 40 (4) : 433 -443 . DOI: 10.7520/1001-4888-25-014
锂离子电池由于具有能量密度高、循环寿命长的优势,已被广泛应用于电动汽车和储能等领域[15]。锂离子电池的充放电循环过程中存在力-电化学耦合效应,这会导致电极材料力学损伤,进而影响电池的使用寿命乃至造成安全隐患[67]。因此,研究力-电化学耦合衰退机制对实现电池寿命的准确预测具有重要意义。
目前在锂离子电池寿命预测方面常用的预测方法主要有模型法、数据驱动法和融合法。模型法主要基于电池负载条件、材料特性和电化学机理来预测电池容量,常见的模型有等效电路模型、电化学模型和经验模型[810],然而这些模型的建立过程往往比较困难,且模型不适合非线性数据。数据驱动法则是通过建立参数之间的映射关系进行电池寿命预测的,常用的数据驱动法有高斯过程回归、人工神经网络和支持向量机等[1113],然而数据驱动法对数据性质要求较高,且预测精度受超参数选择影响较大。融合法中最常见的是将模型法和数据驱动法结合使用,也是当前寿命预测相关研究的热点。然而无论哪种方法,都需要用参数来表征寿命,因为电池容量是反映电池性能的核心参数,所以用容量来表征寿命更合理。但因为电池容量的检测成本高、时间长,在寿命预测中通常使用易于测量的间接参数来表征容量[14]。电池充放电循环过程中的参数较为容易测量,因此从充放电数据中提取间接参数是常见方式之一[1115]。JIA等[11]提取达到最低放电电压所需的时间作为表征电池容量衰减的间接参数。ZHANG等[12]从锂离子电池的增量容量曲线数据中提取电压微分容量曲线(dQ/dV)差值作为间接参数。尽管放电时间和dQ/dV差值可用于容量表征,但两者作为间接参数的依据仅是数据拟合,缺乏理论支撑。阻抗是反映电池内部动态电化学过程的1个重要参量,因此有部分研究选用阻抗作为间接参数来表征电池容量衰减。CHANG等[16]分析了LR2032锂离子电池的阻抗,发现固态电解质界面膜阻抗RSEI和电荷转移阻抗RCT随电池循环圈数的增加明显增大。SCHUSTER等[17]发现18650A型电池的R0RSEI与电池容量的衰退存在关联。MC CARTHY等[18]采用皮尔逊相关性分析方法证明了商用锂离子电池的RCT与容量相关。LI等[19]和ZHANG等[20]分别采用R0RCT作为预测的间接参数,给出了R0RCT与容量在不同荷电状态和温度下的对应关系。综上所述,尽管阻抗、充放电时间及dQ/dV差值等参数被广泛用于电池寿命预测,但阻抗与容量衰减的内在关联及其作为预测间接参数的理论基础仍不明确。
本文针对锂离子电池寿命预测中的间接参数与电池反应机理的关系开展实验研究,设计了电池循环、电化学阻抗和声发射一体化实验方案。首先分析了电池容量、阻抗和声发射参数随循环圈数的演化,并阐述了力学损伤、容量和阻抗的定性关系;然后结合循环过程中阻抗和声发射数据,通过相关性分析验证了阻抗与力学损伤的关联性;最后通过分析C和C/2充放电倍率及石墨和硅碳2种电极材料实验条件下的声发射和阻抗数据,证明了阻抗中蕴含着力-电化学耦合衰退的关键信息。
电池寿命与阻抗演化和电极力学损伤密切相关,阻抗反映电极电化学动态反应过程,力学损伤会引发电池寿命衰退[721]。为了探究阻抗作为间接参数用于寿命预测的机理,本文设计了电化学阻抗和声发射并行实验。
首先,本文选用电化学阻抗谱(Electrochemical Impedance Spectroscopy,EIS)法探究电极的电化学性能。电化学阻抗谱法是研究锂离子电池电极动态电化学反应的一种重要方法,电化学工作站对电池施加小振幅的正弦波电压信号,检测电池输出的电流响应,通过对比输入与输出信号得到电化学阻抗谱。锂离子电池在工作时主要涉及4个连续的反应过程,分别为锂离子的液相扩散、锂离子穿过SEI膜、锂离子与电子发生电荷转移及锂离子固相扩散,如图1(a)所示,这4个过程分别对应电化学阻抗谱的一部分。通过电路元件拟合电化学阻抗谱得到4个反应过程对应的阻抗,如图1(b)所示(其中CPE为常相位角元件,是电极的非理想电容,反映电极表面的非均匀性和非线性的程度)。
1)R0代表锂离子在电解液中的液相扩散及外电路的电阻,在EIS中对应曲线与横坐标的第1个交点。
2)RSEI代表锂离子通过固态电解质界面(Solid Electrolyte Interphase,SEI)膜的阻抗,对应EIS中的第1个半圆。
3)RCT代表锂离子在活性颗粒的表面与电子发生电荷转移(Charge Transfer,CT)的阻抗,对应EIS中的第2个半圆。
4)Warburg阻抗ZWS代表锂离子在活性颗粒内部的固相扩散阻抗,对应EIS尾部一条近45°的斜线。
然后,本文选用声发射方法探究电极的力学损伤情况。声发射方法是研究电极材料力学损伤严重程度的重要手段,锂离子电池在充放电循环时,电池内部锂离子的液相扩散、锂离子穿过SEI膜、锂离子与电子发生电荷转移及锂离子固相扩散这4个电化学反应过程持续进行,使电极材料产生裂纹并扩展,如图1(a)中阶段Ⅰ到阶段Ⅱ所示,电极裂纹的产生和扩展会发出声发射信号,而声发射信号可以通过声发射设备进行采集和分析。电池声发射信号分为连续型和脉冲型2类,连续型信号由副反应如气泡产生等过程发出,脉冲型信号由电极裂纹产生等过程发出,所以本文主要关注脉冲型声发射信号。脉冲型声发射信号的主要参数包括振幅、计数和阈值等,如图1(c)所示,这些参数值代表了电极力学损伤程度[2229]
为了研究电池容量的演化规律和衰退机理,本文开展了充放电循环实验下的电化学阻抗和声发射并行的一体化实验,整体方案见表1,其中C为电池放电倍率,表示放电快慢的量度,C和C/2表示完成放电需要1 h和2 h。首先是装配电池:本文采用的工作电极为商业石墨电极和商业硅碳电极,活性物质比例为95%,活性材料克容量分别为340 mA•h/g和420 mA•h/g;选择金属锂(厚度450μm)为对电极,商业极片为工作电极,微孔聚丙烯膜(厚度28μm)为隔膜,电解液溶质为0.1 mol/L的二氟草酸硼酸锂和1 mol/L的双氟磺酰亚胺锂,溶剂为碳酸甲乙酯和氟代碳酸乙烯酯的体积比为7∶3的混合溶剂;按照图2所示电池结构在充满氩气的真空手套箱(氧和水的体积分数≤1×10-5%)中组装成CR2032型纽扣式电池。
然后开展充放电循环实验:电池组装完成后在室温下使用LAND蓝电测试仪进行充放电循环实验,为保证充放电完全,依次经历静置、恒流放电、静置、恒流充电、恒压充电5步。具体流程见表2
最后进行充放电循环下的电化学阻抗和声发射并行实验,实验装置如图3所示。电池每充放电循环5圈进行1次电化学阻抗谱测量,同时在充放电循环过程中采集声发射信号。电化学阻抗谱采用电化学工作站进行测试,测试频率为0.01 Hz~500 kHz,振幅为5 mV,测试完成后进行等效电路拟合,得到RCT等阻抗。声发射信号使用传感器与采集系统采集和分析,为过滤掉连续型声发射信号,需要设置采集的信号频率和幅值范围:频率为0~150 kHz,幅值的阈值为27 dB,此频率和幅值范围主要是脉冲型声发射信号的范围。
阻抗R0RCTRSEI的大小常用来反映电池动态电化学过程的强弱,由于RSEIRCT与电极-电解液界面的离子接触和电荷转移过程相关,因此本文主要关注RSEIRCT2个阻抗。
锂离子在循环充放电过程中会持续嵌入和脱嵌电极,相当于对电极材料施加循环载荷,电极在循环载荷下会产生疲劳损伤,如电极裂纹的产生和扩展,这些损伤会反映到电极材料的阻抗信息上[3035]:电极力学损伤会破坏电极材料的连续性,使电极材料的有效接触面积减小,导致电荷传输路径的改变,引起电荷分布不均,进而削弱电荷传输效率、增大阻力,并使RCT增大[3639];SEI膜形成于石墨电极表面,电极裂纹导致原有SEI膜破裂,电极表面再次暴露于电解液中,从而形成新的SEI膜,膜厚度增大,离子穿透SEI膜阻力增大,从而使RSEI增大[4047]。此外,电极力学损伤和阻抗增加会引起容量衰减,电极力学损伤引起的孔隙度降低和晶格相变等会使电极活性物质减少,进而导致嵌入电极的锂离子减少;RCTRSEI的增加会使锂离子嵌入电极难度加大,同时SEI膜的增厚会消耗锂离子。因此电极的力学损伤和阻抗的增加会直接导致电池容量衰减,随着循环圈数的增加,电极力学损伤不断加重,阻抗和容量分别持续增加和衰减。
经过对损伤-阻抗-容量内在联系的分析,从电极材料的电化学反应过程出发,可知电极材料在循环过程中“疲劳损伤-阻抗增加-容量衰减”三者之间的内在因果关系:循环引起力学损伤,力学损伤引起阻抗增大,力学损伤与阻抗增大使容量衰减。
为了确认损伤-阻抗-容量的内在关系,需要获取循环过程中容量、阻抗和声发射参数的演化规律,硅碳负极材料因兼具硅的高容量与碳材料的结构稳定性,成为目前动力电池领域的研究热点,因此本文开展了针对硅碳负极电池的一体化实验,实验结果如图4所示。
图4(a)(b)展示了硅碳电极材料电池在C/2倍率下,充放电循环过程中的电流电压曲线及容量演化曲线。为便于后续的分析,采用电池健康状态(State of Health,SOH)代替容量,电池SOH为当前容量与最大容量的比值。从图4(b)中可以看出,电池SOH先稳定波动,随后呈先缓慢后迅速的非线性下降趋势。图4(c)(d)展示了锂离子电池在不同循环圈数下的电化学阻抗谱及拟合得到的R0RSEIRCT演化曲线。从图4(d)中可以看出,R0RCTRSEI均会随着循环圈数的增加而逐渐增大,其中RCTRSEI呈先缓慢后迅速的非线性增加,而R0增长趋势变化不大。图4(e)(f)为采集的声发射信号及声发射累积撞击次数演化曲线。从图4(e)中可见,声发射撞击信号的纵坐标表示该信号的幅值,从循环早期的阶段Ⅰ到循环后期的阶段Ⅱ,声发射累积撞击次数增加的同时,其幅值也在增加,说明幅值也可以代表电极力学损伤程度;从图4(f)中可见,声发射累积撞击次数随循环圈数的增加也呈现明显的非线性演化趋势,并且和RCTRSEI的演化规律相似。
基于2.1节中对损伤-阻抗-容量内在关联的分析,结合容量、阻抗和声发射参数的演化规律,发现RCTRSEI可作为电池寿命预测的间接表征参数,但其机理尚需进一步验证。本文采用皮尔逊相关系数(用r表示)分析阻抗和声发射参数之间的关联,以验证阻抗是否可以通过力-电化学耦合作用表征电池退化过程,从而支持阻抗作为寿命预测间接参数的合理性。皮尔逊相关系数越高,表明阻抗与声发射参数之间的关联越紧密,也就意味着阻抗受电极力学损伤程度影响越大。皮尔逊相关系数r计算公式如下:
式中:xy分别为阻抗和声发射参数。
为便于分析阻抗和声发射参数的变化规律,将数据进行归一化处理。归一化公式如下:
式中:XXg分别为归一化前后的阻抗和声发射参数;XmaxXmin分别为阻抗和声发射参数的最大值和最小值。
图5为C/2倍率下硅碳电极归一化阻抗和归一化声发射累积撞击次数的演化曲线,RCTRSEI与声发射累积撞击参数的皮尔逊相关系数分别高达0.9615和0.9388,表明两者都与声发射累积撞击高度相关,即电极力学损伤直接影响阻抗变化。因此,RCTRSEI作为电池寿命预测的多维度参数,不仅能表征电化学行为,还能反映电极力学损伤程度加重。
为验证所提间接参数分析方法是否具有普适性和可迁移性,本文设计了C/2和C充放电倍率及石墨和硅碳电极材料的实验,图6为不同电极材料在不同充放电倍率下电池容量、阻抗和声发射参数的演化曲线。
图6可以看出,无论是不同放电倍率还是不同电极材料,电池的归一化声发射累积撞击次数和阻抗的演化均有相似之处,都与容量的衰退呈相反的演化趋势。虽然高倍率下容量的衰退和阻抗的增加均比低倍率要快,且石墨和硅碳电极的参数演化规律有区别,但参数的演化趋势相似。根据图6展示的参数演化规律,本文对不同实验条件下的阻抗和声发射参数进行了相关性分析,结果如图7所示。
图7(a)~(c)为不同测试条件下归一化阻抗与归一化声发射累积撞击次数的演化关系,相关性分析结果显示两者的相关性系数r均大于0.96。此外,本文对每一种实验条件做了多组重复实验,1~4号电池为C/2倍率和石墨电极,5~7号电池为C/2倍率和硅碳电极,8~11号电池为C倍率和石墨电极,12~14号电池为C倍率和硅碳电极,相关性系数如图7(d)所示。从图7(d)中可见,RCTRSEI与声发射累积撞击次数的皮尔逊相关系数均超过了0.9,说明阻抗和声发射参数高度相关,而高倍率下的相关性系数比低倍率下略大,反映出高倍率下阻抗与力学损伤更密切,与高倍率下电极材料力学损伤更显著的特点一致。
锂离子电池损伤-阻抗-容量的定性关系表现为,电极力学损伤直接引起阻抗增加,而阻抗增加和电极力学损伤共同导致容量的衰减。声发射与阻抗的皮尔逊相关性定量分析证明了阻抗RCTRSEI均与电池容量的衰减机理紧密相关,两者既包含电化学信息又能反映电极力学损伤情况,因此都可以作为有效的间接参数来预测电池容量的衰减情况。
锂离子电池寿命预测的关键环节之一是间接参数的选取,阻抗是常用的间接参数,但目前缺乏阻抗与电池内部反应机理的研究。因此,本文针对阻抗与电极力学损伤的关系展开研究,设计了电池充放电循环、电化学阻抗和声发射一体化实验,并分析了损伤与阻抗存在的内在关联。实验结果显示,电池容量、RCTRSEI和声发射累积撞击次数均随着循环圈数的增加呈非线性演化趋势且规律相似,分析实验结果可发现,电极力学损伤引起阻抗增加,阻抗增加和电极力学损伤累积共同导致容量衰减,且皮尔逊相关性分析显示RCTRSEI与声发射累积撞击次数的相关性系数均超过了0.9,表明RCTRSEI均与电极力学损伤紧密相关,且阻抗与声发射参数的强相关性在不同倍率、不同材料体系中得到了论证。综合实验结果表明RCTRSEI反映了锂离子电池的力-电化学退化过程,可以将其作为锂离子电池寿命预测中兼具电化学动力学与力学损伤双重表征能力的间接参数。
  • 国家自然科学基金项目(12021002; 12472183; 12041201; 12425203)
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2025年第40卷第4期
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doi: 10.7520/1001-4888-25-014
  • 接收时间:2025-01-18
  • 首发时间:2026-03-27
  • 出版时间:2025-08-01
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  • 收稿日期:2025-01-18
  • 修回日期:2025-03-28
基金
国家自然科学基金项目(12021002; 12472183; 12041201; 12425203)
作者信息
    1.天津大学机械工程学院力学系,天津 300350
    2.天津市现代工程力学重点实验室,天津 300350
    3.车用动力系统全国重点实验室,天津 300350
    4.北京经纬恒润科技股份有限公司,北京 100191

通讯作者:

谢海妹(1988-),女,博士,副研究员。主要研究领域:储能材料力-电化学耦合和深海腐蚀力学。Email:;
宋海滨(1991-),男,博士,工程师。主要研究领域:纳米电极材料力-电化学耦合行为原位表征与机理分析、汽车底盘轻量化设计与仿真。Email:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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