IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v120y2017icp179-191.html
   My bibliography  Save this article

Influence analysis of static and dynamic fast-charging current profiles on ageing performance of commercial lithium-ion batteries

Author

Listed:
  • Abdel-Monem, Mohamed
  • Trad, Khiem
  • Omar, Noshin
  • Hegazy, Omar
  • Van den Bossche, Peter
  • Van Mierlo, Joeri

Abstract

The rate and shape of the charging current indubitably affect the charging time and the ageing rate of a battery. Depending on the application requirements, it is possible to use high-charging current in order to decrease the charging time. However, the influence of fast-charging current profiles should be investigated to identify their impact on battery functionality over time. In this article, static and dynamic fast-charging current profiles are applied to a high power 7 Ah LiFePO4-based cells (LFP), and the results of cycle-life and characterization tests are discussed. To select the proper fast-charging profile, the evaluation relies on some factors: discharge capacity retention, charging capacity, charging time, and cell temperature. After 1700 cycles, the results revealed that the dynamic fast-charging current profile has a prominent role in decreasing the degradation rate as well as the charging time of cells compared with the static fast-charging profile.

Suggested Citation

  • Abdel-Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Van den Bossche, Peter & Van Mierlo, Joeri, 2017. "Influence analysis of static and dynamic fast-charging current profiles on ageing performance of commercial lithium-ion batteries," Energy, Elsevier, vol. 120(C), pages 179-191.
  • Handle: RePEc:eee:energy:v:120:y:2017:i:c:p:179-191
    DOI: 10.1016/j.energy.2016.12.110
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216319156
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.12.110?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Galeotti, Matteo & Cinà, Lucio & Giammanco, Corrado & Cordiner, Stefano & Di Carlo, Aldo, 2015. "Performance analysis and SOH (state of health) evaluation of lithium polymer batteries through electrochemical impedance spectroscopy," Energy, Elsevier, vol. 89(C), pages 678-686.
    2. Omar, Noshin & Monem, Mohamed Abdel & Firouz, Yousef & Salminen, Justin & Smekens, Jelle & Hegazy, Omar & Gaulous, Hamid & Mulder, Grietus & Van den Bossche, Peter & Coosemans, Thierry & Van Mierlo, J, 2014. "Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model," Applied Energy, Elsevier, vol. 113(C), pages 1575-1585.
    3. Waag, Wladislaw & Käbitz, Stefan & Sauer, Dirk Uwe, 2013. "Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application," Applied Energy, Elsevier, vol. 102(C), pages 885-897.
    4. Luo, Xing & Wang, Jihong & Dooner, Mark & Clarke, Jonathan, 2015. "Overview of current development in electrical energy storage technologies and the application potential in power system operation," Applied Energy, Elsevier, vol. 137(C), pages 511-536.
    5. Abdel Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Mantels, Bart & Mulder, Grietus & Van den Bossche, Peter & Van Mierlo, Joeri, 2015. "Lithium-ion batteries: Evaluation study of different charging methodologies based on aging process," Applied Energy, Elsevier, vol. 152(C), pages 143-155.
    6. Fernández, I.J. & Calvillo, C.F. & Sánchez-Miralles, A. & Boal, J., 2013. "Capacity fade and aging models for electric batteries and optimal charging strategy for electric vehicles," Energy, Elsevier, vol. 60(C), pages 35-43.
    7. Krieger, Elena M. & Cannarella, John & Arnold, Craig B., 2013. "A comparison of lead-acid and lithium-based battery behavior and capacity fade in off-grid renewable charging applications," Energy, Elsevier, vol. 60(C), pages 492-500.
    8. Hegazy, Omar & Barrero, Ricardo & Van den Bossche, Peter & El Baghdadi, Mohamed & Smekens, Jelle & Van Mierlo, Joeri & Vriens, Wouter & Bogaerts, Bruno, 2016. "Modeling, analysis and feasibility study of new drivetrain architectures for off-highway vehicles," Energy, Elsevier, vol. 109(C), pages 1056-1074.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cai, Yishan & Yang, Lin & Deng, Zhongwei & Zhao, Xiaowei & Deng, Hao, 2018. "Online identification of lithium-ion battery state-of-health based on fast wavelet transform and cross D-Markov machine," Energy, Elsevier, vol. 147(C), pages 621-635.
    2. Liao, Xiaolin & Sun, Peiyi & Xu, Mengqing & Xing, Lidan & Liao, Youhao & Zhang, Liping & Yu, Le & Fan, Weizhen & Li, Weishan, 2016. "Application of tris(trimethylsilyl)borate to suppress self-discharge of layered nickel cobalt manganese oxide for high energy battery," Applied Energy, Elsevier, vol. 175(C), pages 505-511.
    3. Su, Laisuo & Zhang, Jianbo & Wang, Caijuan & Zhang, Yakun & Li, Zhe & Song, Yang & Jin, Ting & Ma, Zhao, 2016. "Identifying main factors of capacity fading in lithium ion cells using orthogonal design of experiments," Applied Energy, Elsevier, vol. 163(C), pages 201-210.
    4. Liu, Guangming & Ouyang, Minggao & Lu, Languang & Li, Jianqiu & Hua, Jianfeng, 2015. "A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications," Applied Energy, Elsevier, vol. 149(C), pages 297-314.
    5. Guan, Ting & Sun, Shun & Gao, Yunzhi & Du, Chunyu & Zuo, Pengjian & Cui, Yingzhi & Zhang, Lingling & Yin, Geping, 2016. "The effect of elevated temperature on the accelerated aging of LiCoO2/mesocarbon microbeads batteries," Applied Energy, Elsevier, vol. 177(C), pages 1-10.
    6. Mingant, R. & Bernard, J. & Sauvant-Moynot, V., 2016. "Novel state-of-health diagnostic method for Li-ion battery in service," Applied Energy, Elsevier, vol. 183(C), pages 390-398.
    7. Farmann, Alexander & Waag, Wladislaw & Sauer, Dirk Uwe, 2016. "Application-specific electrical characterization of high power batteries with lithium titanate anodes for electric vehicles," Energy, Elsevier, vol. 112(C), pages 294-306.
    8. Hao Sun & Bo Jiang & Heze You & Bojian Yang & Xueyuan Wang & Xuezhe Wei & Haifeng Dai, 2021. "Quantitative Analysis of Degradation Modes of Lithium-Ion Battery under Different Operating Conditions," Energies, MDPI, vol. 14(2), pages 1-19, January.
    9. Wang, Chengshan & Liu, Yixin & Li, Xialin & Guo, Li & Qiao, Lei & Lu, Hai, 2016. "Energy management system for stand-alone diesel-wind-biomass microgrid with energy storage system," Energy, Elsevier, vol. 97(C), pages 90-104.
    10. Tao, Laifa & Cheng, Yujie & Lu, Chen & Su, Yuzhuan & Chong, Jin & Jin, Haizu & Lin, Yongshou & Noktehdan, Azadeh, 2017. "Lithium-ion battery capacity fading dynamics modelling for formulation optimization: A stochastic approach to accelerate the design process," Applied Energy, Elsevier, vol. 202(C), pages 138-152.
    11. Lyons, P.F. & Wade, N.S. & Jiang, T. & Taylor, P.C. & Hashiesh, F. & Michel, M. & Miller, D., 2015. "Design and analysis of electrical energy storage demonstration projects on UK distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 677-691.
    12. Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Qin, Taichun, 2019. "State of health estimation of lithium-ion batteries based on the constant voltage charging curve," Energy, Elsevier, vol. 167(C), pages 661-669.
    13. Raijmakers, L.H.J. & Danilov, D.L. & Eichel, R.-A. & Notten, P.H.L., 2019. "A review on various temperature-indication methods for Li-ion batteries," Applied Energy, Elsevier, vol. 240(C), pages 918-945.
    14. Mathieu, Romain & Baghdadi, Issam & Briat, Olivier & Gyan, Philippe & Vinassa, Jean-Michel, 2017. "D-optimal design of experiments applied to lithium battery for ageing model calibration," Energy, Elsevier, vol. 141(C), pages 2108-2119.
    15. Zhang, Yuan Ci & Briat, Olivier & Boulon, Loïc & Deletage, Jean-Yves & Martin, Cyril & Coccetti, Fabio & Vinassa, Jean-Michel, 2019. "Non-isothermal Ragone plots of Li-ion cells from datasheet and galvanostatic discharge tests," Applied Energy, Elsevier, vol. 247(C), pages 703-715.
    16. Cui, Yingzhi & Zuo, Pengjian & Du, Chunyu & Gao, Yunzhi & Yang, Jie & Cheng, Xinqun & Ma, Yulin & Yin, Geping, 2018. "State of health diagnosis model for lithium ion batteries based on real-time impedance and open circuit voltage parameters identification method," Energy, Elsevier, vol. 144(C), pages 647-656.
    17. Goh, Taedong & Park, Minjun & Seo, Minhwan & Kim, Jun Gu & Kim, Sang Woo, 2018. "Successive-approximation algorithm for estimating capacity of Li-ion batteries," Energy, Elsevier, vol. 159(C), pages 61-73.
    18. Filip Maletić & Mario Hrgetić & Joško Deur, 2020. "Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack," Energies, MDPI, vol. 13(3), pages 1-16, January.
    19. Hu, Xiaosong & Li, Shengbo Eben & Jia, Zhenzhong & Egardt, Bo, 2014. "Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles," Energy, Elsevier, vol. 64(C), pages 953-960.
    20. Oh, Ki-Yong & Epureanu, Bogdan I., 2016. "Characterization and modeling of the thermal mechanics of lithium-ion battery cells," Applied Energy, Elsevier, vol. 178(C), pages 633-646.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:120:y:2017:i:c:p:179-191. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.