IDEAS home Printed from https://ideas.repec.org/a/nat/natene/v10y2025i2d10.1038_s41560-024-01675-8.html
   My bibliography  Save this article

Dynamic cycling enhances battery lifetime

Author

Listed:
  • Alexis Geslin

    (Stanford University
    Stanford University
    SLAC National Accelerator Laboratory)

  • Le Xu

    (Stanford University
    SLAC National Accelerator Laboratory)

  • Devi Ganapathi

    (Stanford University
    SLAC National Accelerator Laboratory)

  • Kevin Moy

    (Stanford University)

  • William C. Chueh

    (Stanford University
    Stanford University
    SLAC National Accelerator Laboratory)

  • Simona Onori

    (Stanford University
    SLAC National Accelerator Laboratory)

Abstract

Laboratory ageing campaigns elucidate the complex degradation behaviour of most technologies. In lithium-ion batteries, such studies aim to capture realistic ageing mechanisms to optimize cell chemistries and designs as well as to engineer reliable battery management systems. In this study, we systematically compared dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant current profiles. Surprisingly, we found that dynamic discharge enhances lifetime substantially compared with constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile led to an increase of up to 38% in equivalent full cycles at end of life. Explainable machine learning revealed the importance of both low-frequency current pulses and time-induced ageing under these realistic discharge conditions. This work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, highlighting the opportunities to revisit our understanding of ageing mechanisms at the chemistry, material and cell levels.

Suggested Citation

  • Alexis Geslin & Le Xu & Devi Ganapathi & Kevin Moy & William C. Chueh & Simona Onori, 2025. "Dynamic cycling enhances battery lifetime," Nature Energy, Nature, vol. 10(2), pages 172-180, February.
  • Handle: RePEc:nat:natene:v:10:y:2025:i:2:d:10.1038_s41560-024-01675-8
    DOI: 10.1038/s41560-024-01675-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41560-024-01675-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41560-024-01675-8?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. Sid-Ali Amamra & Yashraj Tripathy & Anup Barai & Andrew D. Moore & James Marco, 2020. "Electric Vehicle Battery Performance Investigation Based on Real World Current Harmonics," Energies, MDPI, vol. 13(2), pages 1-13, January.
    2. Ghassemi, Alireza & Hollenkamp, Anthony F. & Chakraborty Banerjee, Parama & Bahrani, Behrooz, 2022. "Impact of high-amplitude alternating current on LiFePO4 battery life performance: Investigation of AC-preheating and microcycling effects," Applied Energy, Elsevier, vol. 314(C).
    3. Sarasketa-Zabala, E. & Martinez-Laserna, E. & Berecibar, M. & Gandiaga, I. & Rodriguez-Martinez, L.M. & Villarreal, I., 2016. "Realistic lifetime prediction approach for Li-ion batteries," Applied Energy, Elsevier, vol. 162(C), pages 839-852.
    4. Jiangong Zhu & Yixiu Wang & Yuan Huang & R. Bhushan Gopaluni & Yankai Cao & Michael Heere & Martin J. Mühlbauer & Liuda Mereacre & Haifeng Dai & Xinhua Liu & Anatoliy Senyshyn & Xuezhe Wei & Michael K, 2022. "Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Qin, Yudi & Du, Jiuyu & Lu, Languang & Gao, Ming & Haase, Frank & Li, Jianqiu & Ouyang, Minggao, 2020. "A rapid lithium-ion battery heating method based on bidirectional pulsed current: Heating effect and impact on battery life," Applied Energy, Elsevier, vol. 280(C).
    6. Pablo Korth Pereira Ferraz & Julia Kowal, 2019. "A Comparative Study on the Influence of DC/DC-Converter Induced High Frequency Current Ripple on Lithium-Ion Batteries," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    7. Uddin, Kotub & Moore, Andrew D. & Barai, Anup & Marco, James, 2016. "The effects of high frequency current ripple on electric vehicle battery performance," Applied Energy, Elsevier, vol. 178(C), pages 142-154.
    8. William E. Gent & Grace M. Busse & Kurt Z. House, 2022. "The predicted persistence of cobalt in lithium-ion batteries," Nature Energy, Nature, vol. 7(12), pages 1132-1143, December.
    9. Arnaud Devie & George Baure & Matthieu Dubarry, 2018. "Intrinsic Variability in the Degradation of a Batch of Commercial 18650 Lithium-Ion Cells," Energies, MDPI, vol. 11(5), pages 1-14, April.
    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. Ghassemi, Alireza & Chakraborty Banerjee, Parama & Hollenkamp, Anthony F. & Zhang, Zhe & Bahrani, Behrooz, 2021. "Effects of alternating current on Li-ion battery performance: Monitoring degradative processes with in-situ characterization techniques," Applied Energy, Elsevier, vol. 284(C).
    2. Wang, Yixiu & Zhu, Jiangong & Cao, Liang & Gopaluni, Bhushan & Cao, Yankai, 2023. "Long Short-Term Memory Network with Transfer Learning for Lithium-ion Battery Capacity Fade and Cycle Life Prediction," Applied Energy, Elsevier, vol. 350(C).
    3. Evelina Wikner & Raik Orbay & Sara Fogelström & Torbjörn Thiringer, 2022. "Gender Aspects in Driving Style and Its Impact on Battery Ageing," Energies, MDPI, vol. 15(18), pages 1-15, September.
    4. Fan, Guodong & Zhang, Xi, 2023. "Battery capacity estimation using 10-second relaxation voltage and a convolutional neural network," Applied Energy, Elsevier, vol. 330(PA).
    5. Ghassemi, Alireza & Hollenkamp, Anthony F. & Chakraborty Banerjee, Parama & Bahrani, Behrooz, 2022. "Impact of high-amplitude alternating current on LiFePO4 battery life performance: Investigation of AC-preheating and microcycling effects," Applied Energy, Elsevier, vol. 314(C).
    6. Cai, Fengyang & Chang, Huawei & Yang, Zhengbo & Tu, Zhengkai, 2024. "Experimental study on self-heating strategy of lithium-ion battery at low temperatures based on bidirectional pulse current," Applied Energy, Elsevier, vol. 354(PB).
    7. Fan, Wenjun & Zhu, Jiangong & Qiao, Dongdong & Jiang, Bo & Wang, Xueyuan & Wei, Xuezhe & Dai, Haifeng, 2024. "Prediction of nonlinear degradation knee-point and remaining useful life for lithium-ion batteries using relaxation voltage," Energy, Elsevier, vol. 294(C).
    8. 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.
    9. Bảo-Huy Nguyễn & João Pedro F. Trovão & Ronan German & Alain Bouscayrol, 2020. "Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation," Energies, MDPI, vol. 13(21), pages 1-19, October.
    10. Gu, Xubo & Bai, Hanyu & Cui, Xiaofan & Zhu, Juner & Zhuang, Weichao & Li, Zhaojian & Hu, Xiaosong & Song, Ziyou, 2024. "Challenges and opportunities for second-life batteries: Key technologies and economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    11. Petit, Martin & Prada, Eric & Sauvant-Moynot, Valérie, 2016. "Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime," Applied Energy, Elsevier, vol. 172(C), pages 398-407.
    12. Ozkurt, Celil & Camci, Fatih & Atamuradov, Vepa & Odorry, Christopher, 2016. "Integration of sampling based battery state of health estimation method in electric vehicles," Applied Energy, Elsevier, vol. 175(C), pages 356-367.
    13. Qi Yao & Dylan-Dah-Chuan Lu & Gang Lei, 2021. "Accurate Online Battery Impedance Measurement Method with Low Output Voltage Ripples on Power Converters," Energies, MDPI, vol. 14(4), pages 1-16, February.
    14. Jorge Varela Barreras & Ricardo de Castro & Yihao Wan & Tomislav Dragicevic, 2021. "A Consensus Algorithm for Multi-Objective Battery Balancing," Energies, MDPI, vol. 14(14), pages 1-25, July.
    15. Wei, Gang & Huang, Ranjun & Zhang, Guangxu & Jiang, Bo & Zhu, Jiangong & Guo, Yangyang & Han, Guangshuai & Wei, Xuezhe & Dai, Haifeng, 2023. "A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards," Applied Energy, Elsevier, vol. 349(C).
    16. Zhao, Jingyuan & Wang, Zhenghong & Wu, Yuyan & Burke, Andrew F., 2025. "Predictive pretrained transformer (PPT) for real-time battery health diagnostics," Applied Energy, Elsevier, vol. 377(PD).
    17. Fu, Shiyi & Tao, Shengyu & Fan, Hongtao & He, Kun & Liu, Xutao & Tao, Yulin & Zuo, Junxiong & Zhang, Xuan & Wang, Yu & Sun, Yaojie, 2024. "Data-driven capacity estimation for lithium-ion batteries with feature matching based transfer learning method," Applied Energy, Elsevier, vol. 353(PA).
    18. Tian, Yong & Dong, Qianyuan & Tian, Jindong & Li, Xiaoyu & Li, Guang & Mehran, Kamyar, 2023. "Capacity estimation of lithium-ion batteries based on optimized charging voltage section and virtual sample generation," Applied Energy, Elsevier, vol. 332(C).
    19. Duy-Dinh Nguyen & The-Tiep Pham & Tat-Thang Le & Sewan Choi & Kazuto Yukita, 2023. "A Modulation Method for Three-Phase Dual-Active-Bridge Converters in Battery Charging Applications," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    20. da Silva, Samuel Filgueira & Eckert, Jony Javorski & Corrêa, Fernanda Cristina & Silva, Fabrício Leonardo & Silva, Ludmila C.A. & Dedini, Franco Giuseppe, 2022. "Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle," Applied Energy, Elsevier, vol. 324(C).

    More about this item

    Statistics

    Access and download statistics

    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:nat:natene:v:10:y:2025:i:2:d:10.1038_s41560-024-01675-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.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.