电气工程学报 ›› 2024, Vol. 19 ›› Issue (1): 3-22.doi: 10.11985/2024.01.002
• 特邀专栏:储能关键装备数字化智能安全管理技术 • 上一篇 下一篇
朱建功(), 戴海峰(
), 王学远(
), 姜波(
), 魏学哲(
)
收稿日期:
2023-08-01
修回日期:
2023-09-18
出版日期:
2024-03-25
发布日期:
2024-04-25
作者简介:
朱建功,男,1990年生,博士,副教授。主要研究方向为新能源汽车动力电池技术、电池寿命衰减解析、测量评估及预测优化。E-mail:zhujiangong@tongji.edu.cn;基金资助:
ZHU Jiangong(), DAI Haifeng(
), WANG Xueyuan(
), JIANG Bo(
), WEI Xuezhe(
)
Received:
2023-08-01
Revised:
2023-09-18
Online:
2024-03-25
Published:
2024-04-25
摘要:
电源技术的发展对绿色交通、规模化储能、智慧电网等领域具有重要作用。以电化学器件为代表的电化学电源具有反应机理复杂、多物理场、多尺度特性,同时工作过程中表现出强非线性、时变性及空间分布等特点,为电源的管理带来了挑战。本文以动力电池为对象,分别从模型、测量和管理三个方面阐述当前电池管理技术的研究现状及发展趋势,认为局限于本地的管理技术将逐渐走向全局的数字化管控,提出电化学数字电源的概念并诠释其内涵,旨在助力新能源汽车、氢电储能、新型电网、充电基础设施等电化学电源应用场景的发展。
中图分类号:
朱建功, 戴海峰, 王学远, 姜波, 魏学哲. 从电池管理到电化学数字电源*[J]. 电气工程学报, 2024, 19(1): 3-22.
ZHU Jiangong, DAI Haifeng, WANG Xueyuan, JIANG Bo, WEI Xuezhe. Battery Management towards the Digitalized Electrochemical Power Source[J]. Journal of Electrical Engineering, 2024, 19(1): 3-22.
表1
常用电池管理采样芯片"
芯片型号 | AD位数 | 最大 通道数 | 通信方式 | AD采样精度 | 转换开始至结果可读 所有通道总时间/μs | 所有通道数据 传输时间/μs | 最大采样 频率/Hz |
---|---|---|---|---|---|---|---|
MAX14920 (Maxim) | 16 | 16 | 1 Mbps SPI | 1.6 mV, f≤285 Hz 1.6 V, f≥1 kHz | 8 000 (含校准时间) | 256 | 121 |
LTC6811 (ADI) | 16 | 12 | 1 Mbps SPI | 1.2 mV, f≤7 kHz 4.7 mV, f≥14 kHz | 1 564 (含校准时间) | 192 | 569 |
MC33771(NXP) | 16 | 14 | 4 Mbps SPI | 0.8 mV | 520 | 56 | 1 736 |
表2
监测电池气体成分方法对比"
名称 | 是否原位探测 | 是否监测商用电池 | 电压相关 | 精度/ (×10-6) | 分辨率/ (×10-6) | 响应时间/s | 监测气体类型 |
---|---|---|---|---|---|---|---|
气相色谱质谱法 | × | × | × | 10 | 0.1 | 5 | H2,O2,CO,CO2,CH4,C2H4,挥发性有机(VOCs);非挥发性气体除外 |
傅里叶变换红外光谱法 | × | × | × | — | — | <10-6 | CO,CO2,CH4,C2H4,VOCs; 单原子和同核分子除外,如He,H2 |
核磁共振光谱 | × | × | × | — | — | >10-4 | H2,O2,CO,CO2,CH4,C2H4等 |
在线/微分电化学质谱技术 | √ | × | √ | 10 | 0.1 | 5 | H2,O2,CO,CO2,CH4,C2H4,VOCs等;惰性气体除外 |
原位拉曼光谱 | √ | √ | × | — | — | <10-6 | CH4,CO2,CO; H2、惰性气体除外 |
非色散红外气体传感器 | √ | √ | √ | 50 | 1 | 20 | H2,CO,CO2,CH4,C2H4; O2、惰性气体除外 |
[1] |
马紫峰, 贺益君, 陈建峰. 新能源化工技术[J]. 化工进展, 2021, 40(9):4687-4695.
doi: 10.16085/j.issn.1000-6613.2021-1613 |
MA Zifeng, HE Yijun, CHEN Jianfeng. Renewable energy chemical engineering and technology[J]. Chemical Industry and Engineering Progress, 2021, 40(9):4687-4695.
doi: 10.16085/j.issn.1000-6613.2021-1613 |
|
[2] |
史冬梅, 邱俊, 王晶. 美国先进电池领域发展态势及启示[J]. 储能科学与技术, 2022, 11(9):2933.
doi: 10.19799/j.cnki.2095-4239.2022.0207 |
SHI Dongmei, QIU Jun, WANG Jing. Development of advanced battery technologies and industries in the United States[J]. Energy Storage Science and Technology, 2022, 11(9):2933.
doi: 10.19799/j.cnki.2095-4239.2022.0207 |
|
[3] | AMICI J, ASINARI P, AYERBE E, et al. A roadmap for transforming research to invent the batteries of the future designed within the european large scale research initiative BATTERY 2030+[J]. Advanced Energy Materials, 2022, 12(17):2102785. |
[4] |
杨世春, 卢宇, 周思达, 等. 车用动力电池标准体系研究与分析[J]. 机械工程学报, 2023, 59(22):3-19.
doi: 10.3901/JME.2023.22.003 |
YANG Shichun, LU Yu, ZHOU Sida, et al. Research progress of standards for lithium-ion batteries on electric vehicle[J]. Journal of Mechanical Engineering, 2023, 59(22):3-19.
doi: 10.3901/JME.2023.22.003 |
|
[5] |
万燕鸣, 熊亚林, 王雪颖. 全球主要国家氢能发展战略分析[J]. 储能科学与技术, 2022, 11(10):3401.
doi: 10.19799/j.cnki.2095-4239.2022.0132 |
WAN Yanming, XIONG Yalin, WANG Xueying. Strategic analysis of hydrogen energy development in major countries[J]. Energy Storage Science and Technology, 2022, 11(10):3401.
doi: 10.19799/j.cnki.2095-4239.2022.0132 |
|
[6] | 肖曦, 田培根, 于璐, 等. 动力电池梯次利用储能系统电热安全研究现状及展望[J]. 电气工程学报, 2022, 17(1):206-224. |
XIAO Xi, TIAN Peigen, YU Lu, et al. Status and prospect of safety studies of cascade power battery energy storage system[J]. Journal of Electrical Engineering, 2022, 17(1):206-224. | |
[7] | 来鑫, 陈权威, 顾黄辉, 等. 面向“双碳”战略目标的锂离子电池生命周期评价:框架,方法与进展[J]. 机械工程学报, 2023, 58(22):3-18. |
LAI Xin, CHEN Quanwei, GU Huanghui, et al. Life cycle assessment of lithium-ion batteries for carbon-peaking and carbon-neutrality:Framework,methods,and progress[J]. Journal of Mechanical Engineering, 2023, 58(22):3-18. | |
[8] |
MEYERS J P, DOYLE M, DARLING R M, et al. The impedance response of a porous electrode composed of intercalation particles[J]. Journal of the Electrochemical Society, 2000, 147(8):2930-2940.
doi: 10.1149/1.1393627 |
[9] | LI S E, WANG B, PENG H, et al. An electrochemistry-based impedance model for lithium-ion batteries[J]. Journal of Power Sources, 2014,258:9-18. |
[10] | ORAZEM M E, TRIBOLLET B. Electrochemical impedance spectroscopy[M]. New York: John Wiley & Sons, 2011. |
[11] | RAMADESIGAN V, BOOVARAGAVAN V, PIRKLE J C, et al. Efficient reformulation of solid-phase diffusion in physics-based lithium-ion battery models[J]. Journal of the Electrochemical Society, 2010, 157(7):A854. |
[12] |
ZHU J, SUN Z, WEI X, et al. A new electrochemical impedance spectroscopy model of a high-power lithium-ion battery[J]. RSC Advances, 2014, 4(57):29988-29998.
doi: 10.1039/C4RA03924F |
[13] | CHEN C-F, VERMA A, MUKHERJEE P P. Probing the role of electrode microstructure in the lithium-ion battery thermal behavior[J]. Journal of the Electrochemical Society, 2017, 164(11):E3146-E3158. |
[14] | WANG Y, NI R, JIANG X, et al. An electrochemical-mechanical coupled multi-scale modeling method and full-field stress distribution of lithium-ion battery[J]. Applied Energy, 2023,347:121444. |
[15] |
JOHNSON V. Battery performance models in ADVISOR[J]. Journal of Power Sources, 2002, 110(2):321-329.
doi: 10.1016/S0378-7753(02)00194-5 |
[16] | 魏学哲, 邹广楠, 孙泽昌. 燃料电池汽车中电池建模及其参数估计[J]. 电源技术, 2004, 28(10):605-618. |
WEI Xuezhe, ZOU Guangnan, SUN Zechang. Modelling and parameter estimation of Li-ion battery in a fuel cell vehicle[J]. Chinese Journal of Power Sources, 2004, 28(10):605-618. | |
[17] | 高铭琨, 徐海亮, 吴明铂. 基于等效电路模型的动力电池 SOC 估计方法综述[J]. 电气工程学报, 2021, 16(1):90-102. |
GAO Mingkun, XU Hailiang, WU Mingbo. Review of SOC estimation methods for power battery based on equivalent circuit model[J]. Journal of Electrical Engineering, 2021, 16(1):90-102. | |
[18] | CHARBONNEAU V, LASIA A, BRISARD G. Impedance studies of Li+ diffusion in nickel manganese cobalt oxide (NMC) during charge/discharge cycles[J]. Journal of Electroanalytical Chemistry, 2020,875:113944. |
[19] |
NASERI F, SCHALTZ E, STROE D I, et al. An enhanced equivalent circuit model with real-time parameter identification for battery state-of-charge estimation[J]. IEEE Transactions on Industrial Electronics, 2022, 69(4):3743-3751.
doi: 10.1109/TIE.2021.3071679 |
[20] | ZHANG C, AMIETSZAJEW T, LI S, et al. Real-time estimation of negative electrode potential and state of charge of lithium-ion battery based on a half-cell-level equivalent circuit model[J]. Journal of Energy Storage, 2022,51:104362. |
[21] |
DOYLE M, NEWMAN J, GOZDZ A S, et al. Comparison of modeling predictions with experimental data from plastic lithium ion cells[J]. Journal of the Electrochemical Society, 1996, 143(6):1890-1903.
doi: 10.1149/1.1836921 |
[22] | NEWMAN J, THOMAS-ALYEA K E. Electrochemical systems[M]. New York: John Wiley & Sons, 2012. |
[23] |
NEWMAN J S, TOBIAS C W. Theoretical analysis of current distribution in porous electrodes[J]. Journal of the Electrochemical Society, 1962, 109(12):1183-1191.
doi: 10.1149/1.2425269 |
[24] |
NEWMAN J, TIEDEMANN W. Porous‐electrode theory with battery applications[J]. Aiche Journal, 1975, 21(1):25-41.
doi: 10.1002/aic.v21:1 |
[25] |
KIM G H, PESARAN A, SPOTNITZ R. A three-dimensional thermal abuse model for lithium-ion cells[J]. Journal of Power Sources, 2007, 170(2):476-489.
doi: 10.1016/j.jpowsour.2007.04.018 |
[26] | KIM G H, SMITH K, LEE K J, et al. Multi-domain modeling of lithium-ion batteries encompassing multi-physics in varied length scales[J]. Journal of the Electrochemical Society, 2011, 158(8):A955. |
[27] | LEE K J, SMITH K, PESARAN A, et al. Three dimensional thermal-,electrical-,and electrochemical-coupled model for cylindrical wound large format lithium-ion batteries[J]. Journal of Power Sources, 2013,241:20-32. |
[28] |
SMITH K, KIM G H, DARCY E, et al. Thermal/electrical modeling for abuse-tolerant design of lithium ion modules[J]. International Journal of Energy Research, 2010, 34(2):204-215.
doi: 10.1002/er.v34:2 |
[29] | LI W, FAN Y, RINGBECK F, et al. Electrochemical model-based state estimation for lithium-ion batteries with adaptive unscented Kalman filter[J]. Journal of Power Sources, 2020,476:228534. |
[30] | WANG D, ZHANG Q, HUANG H, et al. An electrochemical-thermal model of lithium-ion battery and state of health estimation[J]. Journal of Energy Storage, 2022,47:103528. |
[31] | LEE J J, KIM J S, LEE D C, et al. Design optimization of tab attachment positions and cell aspect ratio to minimize temperature difference in 45-Ah LFP large-format lithium-ion pouch cells[J]. Applied Thermal Engineering, 2021,182:116143. |
[32] | SRINIVASAN V, NEWMAN J. Discharge model for the lithium iron-phosphate electrode[J]. Journal of the Electrochemical Society, 2004, 151(10):A1517. |
[33] | SRINIVASAN V, WANG C Y. Analysis of electrochemical and thermal behavior of Li-ion cells[J]. Journal of the Electrochemical Society, 2003, 150(1):A98. |
[34] | GUO M, SIKHA G, WHITE R E. Single-particle model for a lithium-ion cell:Thermal behavior[J]. Journal of the Electrochemical Society, 2011, 158(2):A122. |
[35] | GUO M, WHITE R E. Mathematical model for a spirally-wound lithium-ion cell[J]. Journal of Power Sources, 2014,250:220-235. |
[36] | GUO M, WHITE R E. A distributed thermal model for a Li-ion electrode plate pair[J]. Journal of Power Sources, 2013,221:334-344. |
[37] | GUO M, WHITE R E. Thermal model for lithium ion battery pack with mixed parallel and series configuration[J]. Journal of the Electrochemical Society, 2011, 158(10):A1166. |
[38] |
LU X, BERTEI A, FINEGAN D P, et al. 3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling[J]. Nature Communications, 2020, 11(1):2079.
doi: 10.1038/s41467-020-15811-x pmid: 32350275 |
[39] | KASHKOOLI A G, FARHAD S, LEE D U, et al. Multiscale modeling of lithium-ion battery electrodes based on nano-scale X-ray computed tomography[J]. Journal of Power Sources, 2016,307:496-509. |
[40] | 程昀, 李劼, 贾明, 等. 锂离子电池多尺度数值模型的应用现状及发展前景[J]. 物理学报, 2015, 64(21):137-152. |
CHENG Yun, LI Jie, JIA Ming, et al. Application status and future of multi-scale numerical models for lithium ion battery[J]. Acta Physica Sinica, 2015, 64(21):137-152. | |
[41] |
ZHANG Y, TANG Q, ZHANG Y, et al. Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning[J]. Nature Communications, 2020, 11(1):1706.
doi: 10.1038/s41467-020-15235-7 pmid: 32249782 |
[42] | WU Y, LI W, WANG Y, et al. Remaining useful life prediction of lithium-ion batteries using neural network and bat-based particle filter[J]. IEEE Access, 2019,7:54843-54854. |
[43] | TOGASAKI N, YOKOSHIMA T, OGUMA Y, et al. Prediction of overcharge-induced serious capacity fading in nickel cobalt aluminum oxide lithium-ion batteries using electrochemical impedance spectroscopy[J]. Journal of Power Sources, 2020,461:228168. |
[44] | HU C, YE H, JAIN G, et al. Remaining useful life assessment of lithium-ion batteries in implantable medical devices[J]. Journal of Power Sources, 2018,375:118-130. |
[45] | 张凝, 徐皑冬, 王锴, 等. 基于粒子滤波算法的锂离子电池剩余寿命预测方法研究[J]. 高技术通讯, 2017, 27(8):699-707. |
ZHANG Ning, XU Aidong, WANG Kai, et al. Research on prediction of the remaining useful life of lithium-ion batteries based on particle filtering[J]. Chinese High Technology Letters, 2017, 27(8):699-707. | |
[46] | ZHANG H, MIAO Q, ZHANG X, et al. An improved unscented particle filter approach for lithium-ion battery remaining useful life prediction[J]. Microelectronics Reliability, 2018,81:288-298. |
[47] |
HE W, WILLIARD N, OSTERMAN M, et al. Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method[J]. Journal of Power Sources, 2011, 196(23):10314-10321.
doi: 10.1016/j.jpowsour.2011.08.040 |
[48] |
SEVERSON K A, ATTIA P M, JIN N, et al. Data-driven prediction of battery cycle life before capacity degradation[J]. Nature Energy, 2019, 4(5):383-391.
doi: 10.1038/s41560-019-0356-8 |
[49] | HUANG Y. Data-driven capacity estimation and cycle life prediction of lithium-ion batteries[D]. Karlsruhe: Karlsruhe Institute of Technology, 2020. |
[50] |
庞晓青, 李佳承, 刘文学, 等. 模型与数据融合的大尺寸快充锂电池分布式温度估计[J]. 机械工程学报, 2023, 59(22):20-32.
doi: 10.3901/JME.2023.22.020 |
PANG Xiaoqing, LI Jiacheng, LIU Wenxue, et al. Estimation of distributed temperature of large-format fast-charging lithium-ion batteries based on a model-data fusion method[J]. Journal of Mechanical Engineering, 2023, 59(22):20-32.
doi: 10.3901/JME.2023.22.020 |
|
[51] | YANG J, FANG W, CHEN J, et al. A lithium-ion battery remaining useful life prediction method based on unscented particle filter and optimal combination strategy[J]. Journal of Energy Storage, 2022,55:105648. |
[52] | RAZAVI-FAR R, CHAKRABARTI S, SAIF M, et al. An integrated imputation-prediction scheme for prognostics of battery data with missing observations[J]. Expert Systems with Applications, 2019,115:709-723. |
[53] | PATIL M A, TAGADE P, HARIHARAN K S, et al. A novel multistage support vector machine based approach for Li ion battery remaining useful life estimation[J]. Applied Energy, 2015,159:285-297. |
[54] | CHEN D, ZHANG W, ZHANG C, et al. A novel deep learning-based life prediction method for lithium-ion batteries with strong generalization capability under multiple cycle profiles[J]. Applied Energy, 2022,327:120114. |
[55] | BASU S, HWANG G S. First-principles prediction of anomalously strong phase dependence of transport and mechanical properties of lithium fluoride[J]. Acta Materialia, 2022,235:118077. |
[56] | CHEN Z, YE K, LI M, et al. Lithiation mechanism of W18O49 anode material for lithium-ion batteries:Experiment and first-principles calculations[J]. Journal of Electroanalytical Chemistry, 2021,880:114885. |
[57] |
KANUNGO S, BHATTACHARJEE A, BAHADURSHA N, et al. Comparative analysis of LiMPO4 (M= Fe,Co,Cr,Mn,V) as cathode materials for lithium-ion battery applications-A first-principle-based theoretical approach[J]. Nanomaterials (Basel), 2022, 12(19):3266.
doi: 10.3390/nano12193266 |
[58] |
XIONG W, HU W, LI H. First-principles calculations of the atomic structure and electronic structure of F-doped Li(Ni0.8Co0.1Mn0.1)O2 cathode material for lithium-ion batteries[J]. Journal of Electronic Materials, 2022, 51(7):3944-3949.
doi: 10.1007/s11664-022-09653-0 |
[59] |
ALZATE-VARGAS L, VIKRANT K S N, ALLU S, et al. Atomistic modeling of LiF microstructure ionic conductivity and its influence on nucleation and plating[J]. Physical Review Materials, 2022, 6(9):095402.
doi: 10.1103/PhysRevMaterials.6.095402 |
[60] |
LU J, GUAN J, CHEN H, et al. Molecular dynamical investigation of lithium-ion adsorption on multilayer fullerene[J]. Coatings, 2022, 12(12):1824.
doi: 10.3390/coatings12121824 |
[61] | MABUCHI T, NAKAJIMA K, TOKUMASU T. Molecular dynamics study of ion transport in polymer electrolytes of all-solid-state Li-ion batteries[J]. Micromachines (Basel), 2021, 12(9):1012. |
[62] |
ZHU Y, HUANG Y, DU R, et al. Effect of Ni2+ on lithium-ion diffusion in layered LiNi1-x-yMnxCoyO2 materials[J]. Crystals, 2021, 11(5):465.
doi: 10.3390/cryst11050465 |
[63] | DIETRICH F, CISTERNAS E, MARCELO PASINETTI P, et al. Study on Li ion diffusion in LixV2O5 using first principle calculations and kinetic Monte Carlo simulations[J]. Journal of Physics D:Applied Physics, 2021, 55(11):13. |
[64] | GHALAMI CHOOBAR B, MODARRESS H, HALLADJ R, et al. Electrodeposition of lithium metal on lithium anode surface,a simulation study by:Kinetic Monte Carlo-embedded atom method[J]. Computational Materials Science, 2021,192:110343. |
[65] | LEE H, SITAPURE N, HWANG S, et al. Multiscale modeling of dendrite formation in lithium-ion batteries[J]. Computers & Chemical Engineering, 2021,153:107415. |
[66] | ZHANG L, LIU L, GAO X, et al. Modeling of lithium plating in lithium ion batteries based on Monte Carlo method[J]. Journal of Power Sources, 2022,541:231568. |
[67] | WEI Z, ZHAO J, HE H, et al. Future smart battery and management:Advanced sensing from external to embedded multi-dimensional measurement[J]. Journal of Power Sources, 2021,489:229462. |
[68] |
HUANG J, BOLES S T, TARASCON J M. Sensing as the key to battery lifetime and sustainability[J]. Nature Sustainability, 2022, 5(3):194-204.
doi: 10.1038/s41893-022-00859-y |
[69] | ZHU J, DEWI DARMA M S, KNAPP M, et al. Investigation of lithium-ion battery degradation mechanisms by combining differential voltage analysis and alternating current impedance[J]. Journal of Power Sources, 2020,448:227575. |
[70] |
HUANG J, ALBERO BLANQUER L, BONEFACINO J, et al. Operando decoding of chemical and thermal events in commercial Na(Li)-ion cells via optical sensors[J]. Nature Energy, 2020, 5(9):674-683.
doi: 10.1038/s41560-020-0665-y |
[71] |
ALBERO BLANQUER L, MARCHINI F, SEITZ J R, et al. Optical sensors for operando stress monitoring in lithium-based batteries containing solid-state or liquid electrolytes[J]. Nature Communications, 2022, 13(1):1153.
doi: 10.1038/s41467-022-28792-w pmid: 35241673 |
[72] | LYU S, LI N, SUN L, et al. Rapid operando gas monitor for commercial lithium ion batteries:Gas evolution and relation with electrode materials[J]. Journal of Energy Chemistry, 2022,72:14-25. |
[73] |
NARAYAN R, LABERTY‐ROBERT C, PELTA J, et al. Self-healing:An emerging technology for next-generation smart batteries[J]. Advanced Energy Materials, 2022, 12(17):2102652.
doi: 10.1002/aenm.v12.17 |
[74] |
XIAO Y, XU R, YAN C, et al. A toolbox of reference electrodes for lithium batteries[J]. Advanced Functional Materials, 2022, 32(13):2108449.
doi: 10.1002/adfm.v32.13 |
[75] | DOLLÉ M L, ORSINI F O, GOZDZ A S, et al. Development of reliable three-electrode impedance measurements in plastic Li-ion batteries[J]. Journal of the Electrochemical Society, 2001, 148(8):A851. |
[76] | SOLCHENBACH S, PRITZL D, KONG E J Y, et al. A gold micro-reference electrode for impedance and potential measurements in lithium ion batteries[J]. Journal of the Electrochemical Society, 2016, 163(10):A2265-A2272. |
[77] | LEVI M D, DARGEL V, SHILINA Y, et al. Impedance spectra of energy-storage electrodes obtained with commercial three-electrode cells:Some sources of measurement artefacts[J]. Electrochimica Acta, 2014,149:126-135. |
[78] | LA MANTIA F, WESSELLS C D, DESHAZER H D, et al. Reliable reference electrodes for lithium-ion batteries[J]. Electrochemistry Communications, 2013,31:141-154. |
[79] | JUAREZ-ROBLES D, CHEN C F, BARSUKOV Y, et al. Impedance evolution characteristics in lithium-ion batteries[J]. Journal of the Electrochemical Society, 2017, 164(4):A837-A847. |
[80] |
WAGNER N, FRIEDRICH K A. Application of electrochemical impedance spectroscopy for fuel cell characterization:PEFC and oxygen reduction reaction in alkaline solution[J]. Fuel Cells, 2009, 9(3):237-246.
doi: 10.1002/fuce.v9:3 |
[81] | 庄全超, 徐守东, 邱祥云, 等. 锂离子电池的电化学阻抗谱分析[J]. 化学进展, 2010, 22(6):1044. |
ZHUANG Quanchao, XU Shoudong, QIU Xiangyun, et al. Electrochemical impedance spectroscopy in lithium ion batteries diagnosis[J]. Progress in Chemistry, 2010, 22(6):1044. | |
[82] |
QAHOUQ J A A, XIA Z. Single-perturbation-cycle online battery impedance spectrum measurement method with closed-loop control of power converter[J]. IEEE Transactions on Industrial Electronics, 2017, 64(9):7019-7029.
doi: 10.1109/TIE.2017.2686324 |
[83] | KOCH R, KUHN R, ZILBERMAN I, et al. Electrochemical impedance spectroscopy for online battery monitoring-power electronics control[C]// Proceedings of the 2014 16th European Conference on Power Electronics and Applications,August 26-28, 2014,Lappeenranta,Finland. IEEE,2014:1-10. |
[84] |
LEE Y D, PARK S Y, HAN S B. Online embedded impedance measurement using high-power battery charger[J]. IEEE Transactions on Industry Applications, 2014, 51(1):498-508.
doi: 10.1109/TIA.2014.2336979 |
[85] |
WANG X, WEI X, CHEN Q, et al. A novel system for measuring alternating current impedance spectra of series-connected lithium-ion batteries with a high-power dual active bridge converter and distributed sampling units[J]. IEEE Transactions on Industrial Electronics, 2020, 68(8):7380-7390.
doi: 10.1109/TIE.2020.3001841 |
[86] |
DIN E, SCHAEF C, MOFFAT K, et al. A scalable active battery management system with embedded real-time electrochemical impedance spectroscopy[J]. IEEE Transactions on Power Electronics, 2016, 32(7):5688-5698.
doi: 10.1109/TPEL.2016.2607519 |
[87] | RAIJMAKERS L, SHIVAKUMAR K M, DONKERS M, et al. Crosstalk interferences on impedance measurements in battery packs[J]. IFAC-PapersOnLine, 2016, 49(11):42-47. |
[88] |
TOBISHIMA S I, TAKEI K, SAKURAI Y, et al. Lithium ion cell safety[J]. Journal of Power Sources, 2000, 90(2):188-195.
doi: 10.1016/S0378-7753(00)00409-2 |
[89] | YE Y, SHI Y, CAI N, et al. Electro-thermal modeling and experimental validation for lithium ion battery[J]. Journal of Power Sources, 2012,199:227-238. |
[90] |
KIM U S, SHIN C B, KIM C S. Effect of electrode configuration on the thermal behavior of a lithium-polymer battery[J]. Journal of Power Sources, 2008, 180(2):909-916.
doi: 10.1016/j.jpowsour.2007.09.054 |
[91] | WANG X, ZHU J, WEI X, et al. Non-damaged lithium-ion batteries integrated functional electrode for operando temperature sensing[J]. Energy Storage Materials, 2024,65:103160. |
[92] | PANCHAL S, DINCER I, AGELIN-CHAAB M, et al. Experimental temperature distributions in a prismatic lithium-ion battery at varying conditions[J]. International Communications in Heat and Mass Transfer, 2016,71:35-43. |
[93] | LI B, JONES C M, ADAMS T E, et al. Sensor based in-operando lithium-ion battery monitoring in dynamic service environment[J]. Journal of Power Sources, 2021,486:229349. |
[94] | NASCIMENTO M, FERREIRA M S, PINTO J L. Real time thermal monitoring of lithium batteries with fiber sensors and thermocouples:A comparative study[J]. Measurement, 2017,111:260-273. |
[95] | 刘光明, 欧阳明高, 卢兰光, 等. 锂离子电池内部温度场的传递函数在线估计[J]. 汽车安全与节能学报, 2013, 4(1):61-66. |
LIU Guangming, OUYANG Minggao, LU Languang, et al. Online estimation of internal temperature field of lithium-ion batteries using a transfer function[J]. Journal of Automotive Safety and Energy, 2013, 4(1):61-66. | |
[96] | RICHARDSON R R, IRELAND P T, HOWEY D A. Battery internal temperature estimation by combined impedance and surface temperature measurement[J]. Journal of Power Sources, 2014,265:254-261. |
[97] |
HANDE A. Internal battery temperature estimation using series battery resistance measurements during cold temperatures[J]. Journal of Power Sources, 2006, 158(2):1039-1046.
doi: 10.1016/j.jpowsour.2005.11.027 |
[98] |
张广续, 魏学哲, 陈思琦, 等. 高温循环老化对锂离子电池安全性影响研究[J]. 机械工程学报, 2023, 59(22):33-45.
doi: 10.3901/JME.2023.22.033 |
ZHANG Guangxu, WEI Xuezhe, CHEN Siqi, et al. Research on the impact of high-temperature cyclic aging on the safety of lithium-ion batteries[J]. Journal of Mechanical Engineering, 2023, 59(22):33-45.
doi: 10.3901/JME.2023.22.033 |
|
[99] |
来鑫, 马云杰, 郑岳久, 等. 一种基于几何特征变换与迁移的锂离子电池电化学阻抗谱曲线重构方法[J]. 机械工程学报, 2023, 59(22):140-149.
doi: 10.3901/JME.2023.22.140 |
LAI Xin, MA Yunjie, ZHENG Yuejiu, et al. A reconstruction method of electrochemical impedance spectrum curve of lithium-ion batteries based on geometric feature transformation and migration[J]. Journal of Mechanical Engineering, 2023, 59(22):140-149.
doi: 10.3901/JME.2023.22.140 |
|
[100] | SCHMIDT J P, ARNOLD S, LOGES A, et al. Measurement of the internal cell temperature via impedance:Evaluation and application of a new method[J]. Journal of Power Sources, 2013,243:110-117. |
[101] |
SRINIVASAN R, CARKHUFF B G, BUTLER M H, et al. Instantaneous measurement of the internal temperature in lithium-ion rechargeable cells[J]. Electrochim Acta, 2011, 56(17):6198-6204.
doi: 10.1016/j.electacta.2011.03.136 |
[102] |
DO D V, FORGEZ C, BENKARA K E K, et al. Impedance observer for a Li-ion battery using Kalman filter[J]. IEEE Transactions on Vehicular Technology, 2009, 58(8):3930-3937.
doi: 10.1109/TVT.2009.2028572 |
[103] |
AL NAZER R, CATTIN V, GRANJON P, et al. Broadband identification of battery electrical impedance for HEVs[J]. IEEE Transactions on Vehicular Technology, 2013, 62(7):2896-2905.
doi: 10.1109/TVT.2013.2254140 |
[104] |
HOWEY D A, MITCHESON P D, YUFIT V, et al. Online measurement of battery impedance using motor controller excitation[J]. IEEE Transactions on Vehicular Technology, 2014, 63(6):2557-2566.
doi: 10.1109/TVT.25 |
[105] |
HUANG W, QAHOUQ J A. An online battery impedance measurement method using DC-DC power converter control[J]. IEEE Transactions on Industrial Electronics, 2014, 61(61):5987-5995.
doi: 10.1109/TIE.2014.2311389 |
[106] |
RICHARDSON R R, HOWEY D A. Sensorless battery internal temperature estimation using a kalman filter with impedance measurement[J]. IEEE Transactions on Sustainable Energy, 2015, 6(4):1190-1199.
doi: 10.1109/TSTE.2015.2420375 |
[107] |
BHIDE S, SHIM T. Novel predictive electric Li-ion battery model incorporating thermal and rate factor effects[J]. IEEE Transactions on Vehicular Technology, 2011, 60(3):819-829.
doi: 10.1109/TVT.2010.2103333 |
[108] | ZHU Shengxin, HAN Jindong, AN Hongyan, et al. A novel embedded method for in-situ measuring internal multi-point temperatures of lithium ion batteries[J]. Journal of Power Sources, 2020,456:227981. |
[109] |
LOULI A J, ELLIS L D, DAHN J R. Operando pressure measurements reveal solid electrolyte interphase growth to rank Li-ion cell performance[J]. Joule, 2019, 3(3):745-761.
doi: 10.1016/j.joule.2018.12.009 |
[110] | RYALL N, GARCIA-ARAEZ N. Highly sensitive operando pressure measurements of Li-ion battery materials with a simply modified swagelok cell[J]. Journal of the Electrochemical Society, 2020,167:110511. |
[111] | RAGHAVAN A, KIESEL P, SOMMER L W, et al. Embedded fiber-optic sensing for accurate internal monitoring of cell state in advanced battery management systems part 1:Cell embedding method and performance[J]. Journal of Power Sources, 2017,341:466-573. |
[112] | GANGULI A, SAHA B, RAGHAVAN A, et al. Embedded fiber-optic sensing for accurate internal monitoring of cell state in advanced battery management systems part 2:Internal cell signals and utility for state estimation[J]. Journal of Power Sources, 2017,341:474-482. |
[113] | HU Xiaoran, JIANG Zhaolian, YAN Liqin, et al. Real-time visualized battery health monitoring sensor with piezoelectric/pyroelectric poly (vinylidene fluoride-trifluoroethylene) and thin film transistor array by in-situ poling[J]. Journal of Power Sources, 2020,467:228367. |
[114] |
牛少军, 吴凯, 朱国斌, 等. 锂离子电池硅基负极循环过程中的膨胀应力[J]. 储能科学与技术, 2022, 11(9):2989.
doi: 10.19799/j.cnki.2095-4239.2022.0194 |
NIU Shaojun, WU Kai, ZHU Guobin, et al. Studies on the swelling force during cycling of Si-based anodes in lithium ion batteries[J]. Energy Storage Science and Technology, 2022, 11(9):2989.
doi: 10.19799/j.cnki.2095-4239.2022.0194 |
|
[115] | MIAO Ziyun, LI Yanpeng, XIAO Xiangpeng, et al. Direct optical fiber monitor on stress evolution of the sulfur-based cathodes for lithium-sulfur batteries[J]. Energy & Environmental Science, 2022,15:2029-2038. |
[116] | MATASSO A, WETZ D, LIU F. The effects of internal pressure evolution on the aging of commercial Li-ion cells[J]. Journal of the Electrochemical Society, 2014, 162(1):A92-A97. |
[117] |
MATASSO A, WONG D, WETZ D, et al. Correlation of bulk internal pressure rise and capacity degradation of commercial LiCoO2 cells[J]. Journal of the Electrochemical Society, 2014, 161(14):A2031-A2035.
doi: 10.1149/2.0221414jes |
[118] | MATASSO A, WONG D, WETZ D, et al. Effects of high-rate cycling on the bulk internal pressure rise and capacity degradation of commercial LiCoO2 cells[J]. Journal of the Electrochemical Society, 2015, 162(6):A885-A891. |
[119] |
LIU X, REN D, HSU H, et al. Thermal runaway of lithium-ion batteries without internal short circuit[J]. Joule, 2018, 2(10):2047-2064.
doi: 10.1016/j.joule.2018.06.015 |
[120] | ROWDEN B, GARCIA-ARAEZ N. A review of gas evolution in lithium ion batteries[J]. Energy Reports, 2020,6:10-18. |
[121] |
KONG W, LI H, HUANG X, et al. Gas evolution behaviors for several cathode materials in lithium-ion batteries[J]. Journal of Power Sources, 2005, 142(1-2):285-291.
doi: 10.1016/j.jpowsour.2004.10.008 |
[122] | GALUSHKIN N Е, YAZVINSKAYA N N, GALUSHKIN D N. Mechanism of gases generation during lithium-ion batteries cycling[J]. Journal of the Electrochemical Society, 2019, 166(6):A897-A908. |
[123] | GERELT-OD B, KIM J, SHIN E, et al. In situ Raman investigation of resting thermal effects on gas emission in charged commercial 18650 lithium ion batteries[J]. Journal of Industrial and Engineering Chemistry, 2021,96:339-344. |
[124] | WANG S, LIU J, RAFIZ K, et al. An on-line transient study on gassing mechanism of lithium titanate batteries[J]. Journal of the Electrochemical Society, 2019, 166(16):A4150-A4157. |
[125] |
SCHMIEGEL J P, LEIßING M, WEDDELING F, et al. Novel in situ gas formation analysis technique using a multilayer pouch bag lithium ion cell equipped with gas sampling port[J]. Journal of the Electrochemical Society, 2020, 167(6):060516.
doi: 10.1149/1945-7111/ab8409 |
[126] |
CHOE C Y, JUNG W S, BYEON J W. Damage evaluation in lithium cobalt oxide/carbon electrodes of secondary battery by acoustic emission monitoring[J]. Materials Transactions, 2015, 56(2):269-273.
doi: 10.2320/matertrans.M2014396 |
[127] | DAVIES G, KNEHR K W, VAN TASSELL B, et al. State of charge and state of health estimation using electrochemical acoustic time of flight analysis[J]. Journal of the Electrochemical Society, 2017, 164(12):A2746-A2755. |
[128] |
DENG Z, HUANG Z, SHEN Y, et al. Ultrasonic scanning to observe wetting and “Unwetting” in Li-ion pouch cells[J]. Joule, 2020, 4(9):2017-2029.
doi: 10.1016/j.joule.2020.07.014 |
[129] | 张忠义, 羌嘉曦, 杨林, 等. 混合动力汽车电池管理系统[J]. 机电工程技术, 2006, 35(1):61-74. |
ZHANG Zhongyi, QIANG Jiaxi, YANG Lin, et al. Battery management system for HEVs[J]. Mechanical & Electrical Engineering Technology, 2006, 35(1):61-74. | |
[130] | 杨朔, 何莉萍, 钟志华. 基于 CAN 总线的电动汽车电池管理系统[J]. 贵州工业大学学报, 2004, 33(2):90-94. |
YANG Shuo, HE Liping, ZHONG Zhihua. A battery monitoring system based on CAN bus for electric vehicles[J]. Journal of Guizhou University of Technology, 2004, 33(2):90-94. | |
[131] | 魏学哲, 孙泽昌, 邹广楠. 模块化的 HEV 锂离子电池管理系统[J]. 汽车工程, 2004, 26(6):629-631. |
WEI Xuezhe, SUN Zechang, ZOU Guangnan. A modularized Li-ion battery management system for HEVs[J]. Automotive Engineering, 2004, 26(6):629-631. | |
[132] | 佘承其, 张照生, 刘鹏, 等. 大数据分析技术在新能源汽车行业的应用综述——基于新能源汽车运行大数据[J]. 机械工程学报, 2020, 55(20):3-16. |
SHE Chengqi, ZHANG Zhaosheng, LIU Peng, et al. Overview of the application of big data analysis technology in new energy vehicle industry:Based on operating big data of new energy vehicle[J]. Journal of Mechanical Engineering, 2020, 55(20):3-16. | |
[133] | 洪吉超. 基于运行大数据的电动汽车动力电池安全控制管理研究[D]. 北京: 北京理工大学, 2020. |
HONG Jichao. Research on safety control management of electric vehicle power battery based on operation big data[D]. Beijing: Beijing Institute of Technology, 2020. | |
[134] | HONG J, WANG Z, YAO Y. Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks[J]. Applied Energy, 2019,251:113381. |
[135] |
YANG S, HE R, ZHANG Z, et al. CHAIN:Cyber hierarchy and interactional network enabling digital solution for battery full-lifespan management[J]. Matter, 2020, 3(1):27-41.
doi: 10.1016/j.matt.2020.04.015 |
[136] | WANG Y, XU R, ZHOU C, et al. Digital twin and cloud-side-end collaboration for intelligent battery management system[J]. Journal of Manufacturing Systems, 2022,62:124-134. |
[137] |
ZHANG C, LIU S. Meta-energy:When integrated energy internet meets metaverse[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(3):580-583.
doi: 10.1109/JAS.2023.123492 |
[1] | 金建新, 虞儒新, 刘刚, 许林波, 马延强, 王浩彬, 胡晨. 锂离子电池健康状态估算方法研究进展*[J]. 电气工程学报, 2024, 19(1): 33-48. |
[2] | 于淼, 朱昱豪, 顾鑫, 商云龙. 基于膨胀应力的锂离子电池剩余使用寿命预测*[J]. 电气工程学报, 2024, 19(1): 49-56. |
[3] | 朱昱豪, 汪腾, 顾鑫, 侯林飞, 商云龙. 锂离子电池全寿命周期个性化退役与评价方法*[J]. 电气工程学报, 2024, 19(1): 79-86. |
[4] | 黄霁蓝, 张家华, 刘自程, 汪志远, 赵炫. 基于模型预测VSFPWM的串联绕组逆变器电磁干扰抑制研究*[J]. 电气工程学报, 2024, 19(1): 206-215. |
[5] | 王森, 杨奕, 郭强, 马雯, 黄勇军. 面向电流源型PWM整流器的双矢量模型预测直接功率控制*[J]. 电气工程学报, 2024, 19(1): 216-225. |
[6] | 于仲安, 张军令, 陈可怡. 基于GA-ELM的锂电池SOC估计及主动均衡*[J]. 电气工程学报, 2024, 19(1): 326-333. |
[7] | 任爽, 杨凯, 商继财, 祁继明, 魏翔宇, 蔡永根. 基于CNN-BiGRU-Attention的短期电力负荷预测[J]. 电气工程学报, 2024, 19(1): 344-350. |
[8] | 孔维相, 石颉, 杜国庆, 袁晨翔, 张鑫越. 基于统计检验的漏电断路器寿命预测方法研究[J]. 电气工程学报, 2024, 19(1): 382-390. |
[9] | 龚奕畅, 朱昱豪, 顾鑫, 汪腾, 商云龙. 基于多参量的动力电池剩余使用价值定义与评价方法*[J]. 电气工程学报, 2024, 19(1): 117-123. |
[10] | 李佳欣, 鲍晓华, 狄冲, 燕靖文, 朱庆龙. 充水式潜水电机温度场仿真分析*[J]. 电气工程学报, 2024, 19(1): 141-149. |
[11] | 李瑞英, 李国丽, 鞠鲁峰, 王群京. 基于D-H参数的磁阻式球形电机动力学建模*[J]. 电气工程学报, 2024, 19(1): 150-158. |
[12] | 林希, 张浩民, 刘振祥. 基于收缩因子改进PSO算法的J-A磁滞模型参数辨识*[J]. 电气工程学报, 2024, 19(1): 187-195. |
[13] | 金英爱, 余文宾, 马纯强. 新能源汽车储能系统快速充电策略研究综述*[J]. 电气工程学报, 2024, 19(1): 23-32. |
[14] | 崔宇朋, 余杨, 韦明秀, 李振眠, 余建星. 改进博弈论四重组合赋权法下的开口甲板多目标拓扑优化设计[J]. 机械工程学报, 2023, 59(9): 263-273. |
[15] | 黄胜, 李涤尘, 张晓宇, 崔滨, 李青宇, 张安峰. 多光束变光斑激光定向能量沉积工艺及分析模型[J]. 机械工程学报, 2023, 59(9): 285-297. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||