IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v271y2020ics0306261920307443.html
   My bibliography  Save this article

Actively temperature controlled health-aware fast charging method for lithium-ion battery using nonlinear model predictive control

Author

Listed:
  • Yin, Yilin
  • Choe, Song-Yul

Abstract

Previous research has shown that a drastic reduction of charging time compared to constant current constant voltage (CC/CV) charging protocol is possible while suppressing degradation causes by combining constant charging and pulse discharging current. However, effects of temperature variation on side reaction and lithium plating and effects of the frequency of pulse current on lithium stripping have not been considered. In fact, charging currents and operating temperatures dominantly affect the cycle life of battery, where both side reaction and lithium plating are competing. In this paper, reduced order electrochemical life models are developed and validated against experimental data collected at different currents and temperatures and then used to find out optimal temperatures at given charging currents with respect to degradation rates. Thereafter, an optimal charging current at different SOCs has been found using nonlinear model predictive control and then the optimal temperature is determined from the relationship obtained by the models, which reduces side reaction rate and lithium plating rate. In addition, pulse discharging current is added to promote the lithium stripping that recovers ions out of the plated lithium, where the amplitude and frequency of the pulse current are optimized using the models. Finally, the proposed charging method and the 1 C CC/CV charging method were tested in Battery-In-the-Loop using a large format pouch type lithium ion battery to compare each other, where 61% and 39% of charging time is reduced up to 80% and 100% SOC, respectively, while the capacity fade is comparable.

Suggested Citation

  • Yin, Yilin & Choe, Song-Yul, 2020. "Actively temperature controlled health-aware fast charging method for lithium-ion battery using nonlinear model predictive control," Applied Energy, Elsevier, vol. 271(C).
    • Handle: RePEc:eee:appene:v:271:y:2020:i:c:s0306261920307443
    DOI: 10.1016/j.apenergy.2020.115232
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920307443
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.115232?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. Zhang, Caiping & Jiang, Jiuchun & Gao, Yang & Zhang, Weige & Liu, Qiujiang & Hu, Xiaosong, 2017. "Charging optimization in lithium-ion batteries based on temperature rise and charge time," Applied Energy, Elsevier, vol. 194(C), pages 569-577.
    2. 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.
    3. Zou, Changfu & Hu, Xiaosong & Wei, Zhongbao & Tang, Xiaolin, 2017. "Electrothermal dynamics-conscious lithium-ion battery cell-level charging management via state-monitored predictive control," Energy, Elsevier, vol. 141(C), pages 250-259.
    4. Bi, Yalan & Choe, Song-Yul, 2020. "An adaptive sigma-point Kalman filter with state equality constraints for online state-of-charge estimation of a Li(NiMnCo)O2/Carbon battery using a reduced-order electrochemical model," Applied Energy, Elsevier, vol. 258(C).
    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.
    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. Guan-Jhu Chen & Yi-Hua Liu & Yu-Shan Cheng & Hung-Yu Pai, 2021. "A Novel Optimal Charging Algorithm for Lithium-Ion Batteries Based on Model Predictive Control," Energies, MDPI, vol. 14(8), pages 1-18, April.
    2. Wang, Yujie & Zhou, Caijie & Chen, Zonghai, 2022. "Optimization of battery charging strategy based on nonlinear model predictive control," Energy, Elsevier, vol. 241(C).
    3. Song, Minseok & Choe, Song-Yul, 2022. "Parameter sensitivity analysis of a reduced-order electrochemical-thermal model for heat generation rate of lithium-ion batteries," Applied Energy, Elsevier, vol. 305(C).
    4. Jiang, Benben & Berliner, Marc D. & Lai, Kun & Asinger, Patrick A. & Zhao, Hongbo & Herring, Patrick K. & Bazant, Martin Z. & Braatz, Richard D., 2022. "Fast charging design for Lithium-ion batteries via Bayesian optimization," Applied Energy, Elsevier, vol. 307(C).
    5. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(C).
    6. 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).
    7. Gao, Yizhao & Liu, Chenghao & Chen, Shun & Zhang, Xi & Fan, Guodong & Zhu, Chong, 2022. "Development and parameterization of a control-oriented electrochemical model of lithium-ion batteries for battery-management-systems applications," Applied Energy, Elsevier, vol. 309(C).
    8. Ouyang, Quan & Fang, Ruyi & Xu, Guotuan & Liu, Yonggang, 2022. "User-involved charging control for lithium-ion batteries with economic cost optimization," Applied Energy, Elsevier, vol. 314(C).

    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. Saeed Mian Qaisar, 2020. "Event-Driven Coulomb Counting for Effective Online Approximation of Li-Ion Battery State of Charge," Energies, MDPI, vol. 13(21), pages 1-20, October.
    2. Jiang, Benben & Berliner, Marc D. & Lai, Kun & Asinger, Patrick A. & Zhao, Hongbo & Herring, Patrick K. & Bazant, Martin Z. & Braatz, Richard D., 2022. "Fast charging design for Lithium-ion batteries via Bayesian optimization," Applied Energy, Elsevier, vol. 307(C).
    3. Joris De Hoog & Joris Jaguemont & Mohamed Abdel-Monem & Peter Van Den Bossche & Joeri Van Mierlo & Noshin Omar, 2018. "Combining an Electrothermal and Impedance Aging Model to Investigate Thermal Degradation Caused by Fast Charging," Energies, MDPI, vol. 11(4), pages 1-15, March.
    4. Nguyen, Su & Peng, Wei & Sokolowski, Peter & Alahakoon, Damminda & Yu, Xinghuo, 2018. "Optimizing rooftop photovoltaic distributed generation with battery storage for peer-to-peer energy trading," Applied Energy, Elsevier, vol. 228(C), pages 2567-2580.
    5. 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).
    6. Boshi Wang & Haitao Min & Weiyi Sun & Yuanbin Yu, 2021. "Research on Optimal Charging of Power Lithium-Ion Batteries in Wide Temperature Range Based on Variable Weighting Factors," Energies, MDPI, vol. 14(6), pages 1-21, March.
    7. Li, Yunjian & Li, Kuining & Xie, Yi & Liu, Jiangyan & Fu, Chunyun & Liu, Bin, 2020. "Optimized charging of lithium-ion battery for electric vehicles: Adaptive multistage constant current–constant voltage charging strategy," Renewable Energy, Elsevier, vol. 146(C), pages 2688-2699.
    8. Pietro Iurilli & Luigi Luppi & Claudio Brivio, 2022. "Non-Invasive Detection of Lithium-Metal Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-14, September.
    9. Tian, Yong & Huang, Zhijia & Tian, Jindong & Li, Xiaoyu, 2022. "State of charge estimation of lithium-ion batteries based on cubature Kalman filters with different matrix decomposition strategies," Energy, Elsevier, vol. 238(PC).
    10. 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.
    11. 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).
    12. Xu, Yuan-wu & Wu, Xiao-long & Zhong, Xiao-bo & Zhao, Dong-qi & Sorrentino, Marco & Jiang, Jianhua & Jiang, Chang & Fu, Xiaowei & Li, Xi, 2021. "Mechanism model-based and data-driven approach for the diagnosis of solid oxide fuel cell stack leakage," Applied Energy, Elsevier, vol. 286(C).
    13. Li, Niansi & Liu, Xiaoyong & Yu, Bendong & Li, Liang & Xu, Jianqiang & Tan, Qiong, 2021. "Study on the environmental adaptability of lithium-ion battery powered UAV under extreme temperature conditions," Energy, Elsevier, vol. 219(C).
    14. Ramadan, Mohamad & Murr, Rabih & Khaled, Mahmoud & Olabi, Abdul Ghani, 2018. "Mixed numerical - Experimental approach to enhance the heat pump performance by drain water heat recovery," Energy, Elsevier, vol. 149(C), pages 1010-1021.
    15. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
    16. 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.
    17. 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.
    18. Lai, Qingzhi & Ahn, Hyoung Jun & Kim, YoungJin & Kim, You Na & Lin, Xinfan, 2021. "New data optimization framework for parameter estimation under uncertainties with application to lithium-ion battery," Applied Energy, Elsevier, vol. 295(C).
    19. Lyu, Guangzheng & Zhang, Heng & Miao, Qiang, 2023. "An interpretable state of health estimation method for lithium-ion batteries based on multi-category and multi-stage features," Energy, Elsevier, vol. 283(C).
    20. Xuekun Lu & Marco Lagnoni & Antonio Bertei & Supratim Das & Rhodri E. Owen & Qi Li & Kieran O’Regan & Aaron Wade & Donal P. Finegan & Emma Kendrick & Martin Z. Bazant & Dan J. L. Brett & Paul R. Shear, 2023. "Multiscale dynamics of charging and plating in graphite electrodes coupling operando microscopy and phase-field modelling," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    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:appene:v:271:y:2020:i:c:s0306261920307443. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.