IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i17p5220-d620518.html
   My bibliography  Save this article

Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview

Author

Listed:
  • Jia Guo

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
    Department of Material Production, Aalborg University, 9220 Aalborg, Denmark)

  • Yaqi Li

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
    Department of Material Production, Aalborg University, 9220 Aalborg, Denmark)

  • Kjeld Pedersen

    (Department of Material Production, Aalborg University, 9220 Aalborg, Denmark)

  • Daniel-Ioan Stroe

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

Abstract

Understanding the aging mechanism for lithium-ion batteries (LiBs) is crucial for optimizing the battery operation in real-life applications. This article gives a systematic description of the LiBs aging in real-life electric vehicle (EV) applications. First, the characteristics of the common EVs and the lithium-ion chemistries used in these applications are described. The battery operation in EVs is then classified into three modes: charging, standby, and driving, which are subsequently described. Finally, the aging behavior of LiBs in the actual charging, standby, and driving modes are reviewed, and the influence of different working conditions are considered. The degradation mechanisms of cathode, electrolyte, and anode during those processes are also discussed. Thus, a systematic analysis of the aging mechanisms of LiBs in real-life EV applications is achieved, providing practical guidance, methods to prolong the battery life for users, battery designers, vehicle manufacturers, and material recovery companies.

Suggested Citation

  • Jia Guo & Yaqi Li & Kjeld Pedersen & Daniel-Ioan Stroe, 2021. "Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview," Energies, MDPI, vol. 14(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5220-:d:620518
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/17/5220/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/17/5220/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shichun Yang & Cheng Deng & Yulong Zhang & Yongling He, 2017. "State of Charge Estimation for Lithium-Ion Battery with a Temperature-Compensated Model," Energies, MDPI, vol. 10(10), pages 1-14, October.
    2. Xinrong Huang & Yuanyuan Li & Anirudh Budnar Acharya & Xin Sui & Jinhao Meng & Remus Teodorescu & Daniel-Ioan Stroe, 2020. "A Review of Pulsed Current Technique for Lithium-ion Batteries," Energies, MDPI, vol. 13(10), pages 1-18, May.
    3. de Hoog, Joris & Timmermans, Jean-Marc & Ioan-Stroe, Daniel & Swierczynski, Maciej & Jaguemont, Joris & Goutam, Shovon & Omar, Noshin & Van Mierlo, Joeri & Van Den Bossche, Peter, 2017. "Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation," Applied Energy, Elsevier, vol. 200(C), pages 47-61.
    4. Peter M. Attia & Aditya Grover & Norman Jin & Kristen A. Severson & Todor M. Markov & Yang-Hung Liao & Michael H. Chen & Bryan Cheong & Nicholas Perkins & Zi Yang & Patrick K. Herring & Muratahan Ayko, 2020. "Closed-loop optimization of fast-charging protocols for batteries with machine learning," Nature, Nature, vol. 578(7795), pages 397-402, February.
    5. Qiao Zhu & Neng Xiong & Ming-Liang Yang & Rui-Sen Huang & Guang-Di Hu, 2017. "State of Charge Estimation for Lithium-Ion Battery Based on Nonlinear Observer: An H ∞ Method," Energies, MDPI, vol. 10(5), pages 1-19, May.
    6. Liu, Kailong & Ashwin, T.R. & Hu, Xiaosong & Lucu, Mattin & Widanage, W. Dhammika, 2020. "An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    7. Mathieu, Romain & Briat, Olivier & Gyan, Philippe & Vinassa, Jean-Michel, 2021. "Comparison of the impact of fast charging on the cycle life of three lithium-ion cells under several parameters of charge protocol and temperatures," Applied Energy, Elsevier, vol. 283(C).
    8. Xin Sui & Maciej Świerczyński & Remus Teodorescu & Daniel-Ioan Stroe, 2021. "The Degradation Behavior of LiFePO 4 /C Batteries during Long-Term Calendar Aging," Energies, MDPI, vol. 14(6), pages 1-21, March.
    9. Bogdan Ovidiu Varga & Arsen Sagoian & Florin Mariasiu, 2019. "Prediction of Electric Vehicle Range: A Comprehensive Review of Current Issues and Challenges," Energies, MDPI, vol. 12(5), pages 1-19, March.
    10. Amela Ajanovic & Reinhard Haas, 2018. "Electric vehicles: solution or new problem?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 7-22, December.
    11. Balali, Yasaman & Stegen, Sascha, 2021. "Review of energy storage systems for vehicles based on technology, environmental impacts, and costs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. Xiong, Rui & Pan, Yue & Shen, Weixiang & Li, Hailong & Sun, Fengchun, 2020. "Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kateřina Nováková & Anna Pražanová & Daniel-Ioan Stroe & Vaclav Knap, 2023. "Second-Life of Lithium-Ion Batteries from Electric Vehicles: Concept, Aging, Testing, and Applications," Energies, MDPI, vol. 16(5), pages 1-19, February.
    2. Andre Leippi & Markus Fleschutz & Michael D. Murphy, 2022. "A Review of EV Battery Utilization in Demand Response Considering Battery Degradation in Non-Residential Vehicle-to-Grid Scenarios," Energies, MDPI, vol. 15(9), pages 1-22, April.

    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. Penelope K. Jones & Ulrich Stimming & Alpha A. Lee, 2022. "Impedance-based forecasting of lithium-ion battery performance amid uneven usage," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Muhammad Junaid Alvi & Hee-Je Kim, 2019. "Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(3), pages 1-33, January.
    3. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
    4. Jiang, Bo & Zhu, Jiangong & Wang, Xueyuan & Wei, Xuezhe & Shang, Wenlong & Dai, Haifeng, 2022. "A comparative study of different features extracted from electrochemical impedance spectroscopy in state of health estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 322(C).
    5. Rauf, Huzaifa & Khalid, Muhammad & Arshad, Naveed, 2022. "Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    6. Zhang, Chen & Wang, Hongmin & Wu, Lifeng, 2023. "Life prediction model for lithium-ion battery considering fast-charging protocol," Energy, Elsevier, vol. 263(PE).
    7. Chen, Zhang & Chen, Liqun & Ma, Zhengwei & Xu, Kangkang & Zhou, Yu & Shen, Wenjing, 2023. "Joint modeling for early predictions of Li-ion battery cycle life and degradation trajectory," Energy, Elsevier, vol. 277(C).
    8. Minella Bezha & Ryo Gondo & Naoto Nagaoka, 2019. "An Estimation Model with Generalization Characteristics for the Internal Impedance of the Rechargeable Batteries by Means of Dual ANN Model," Energies, MDPI, vol. 12(5), pages 1-21, March.
    9. Fan, Zhaohui & Fu, Yijie & Liang, Hong & Gao, Renjing & Liu, Shutian, 2023. "A module-level charging optimization method of lithium-ion battery considering temperature gradient effect of liquid cooling and charging time," Energy, Elsevier, vol. 265(C).
    10. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    11. Shunli Wang & Pu Ren & Paul Takyi-Aninakwa & Siyu Jin & Carlos Fernandez, 2022. "A Critical Review of Improved Deep Convolutional Neural Network for Multi-Timescale State Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 15(14), pages 1-27, July.
    12. Ingvild B. Espedal & Asanthi Jinasena & Odne S. Burheim & Jacob J. Lamb, 2021. "Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles," Energies, MDPI, vol. 14(11), pages 1-24, June.
    13. Yashraj Tripathy & Andrew McGordon & Anup Barai, 2020. "Improving Accessible Capacity Tracking at Low Ambient Temperatures for Range Estimation of Battery Electric Vehicles," Energies, MDPI, vol. 13(8), pages 1-18, April.
    14. Pietro Iurilli & Luigi Luppi & Claudio Brivio, 2022. "Non-Invasive Detection of Lithium-Metal Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-14, September.
    15. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    16. Yuqiang Zeng & Buyi Zhang & Yanbao Fu & Fengyu Shen & Qiye Zheng & Divya Chalise & Ruijiao Miao & Sumanjeet Kaur & Sean D. Lubner & Michael C. Tucker & Vincent Battaglia & Chris Dames & Ravi S. Prashe, 2023. "Extreme fast charging of commercial Li-ion batteries via combined thermal switching and self-heating approaches," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    17. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    18. Chen, Wanying & Gong, Yeming & Chen, Qi & Wang, Hongwei, 2024. "Does battery management matter? Performance evaluation and operating policies in a self-climbing robotic warehouse," European Journal of Operational Research, Elsevier, vol. 312(1), pages 164-181.
    19. Rakshith Subramanya & Matti Yli-Ojanperä & Seppo Sierla & Taneli Hölttä & Jori Valtakari & Valeriy Vyatkin, 2021. "A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves," Energies, MDPI, vol. 14(5), pages 1-23, February.
    20. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).

    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:gam:jeners:v:14:y:2021:i:17:p:5220-:d:620518. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.