IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v259y2020ics0306261919318355.html
   My bibliography  Save this article

Optimization of multi-stage constant current charging pattern based on Taguchi method for Li-Ion battery

Author

Listed:
  • Jiang, Li
  • Li, Yong
  • Huang, Yuduo
  • Yu, Jiaqi
  • Qiao, Xuebo
  • Wang, Yixiao
  • Huang, Chun
  • Cao, Yijia

Abstract

Due to the complexity of characteristics, the charging performance of Li-ion batteries needs to be further improved. In this paper, Taguchi method is employed to search an optimal charging pattern for 5-stage constant-current charging strategy. The charging capacity, efficiency and time are analyzed as quality functions simultaneously, and the influences of charging currents at each stage on each quality function are revealed. This universal method provides a reasonable basis for the selection of the optimal currents. By reasonably updating the currents at each stage, a broader range is searched to make experimental results more representative. Compared with the constant current- constant voltage method, the obtained charging pattern improves the charging efficiency by 0.6–0.9%, and the temperature rise of the battery is reduced by about 2 °C. Compared with the charging pattern obtained by optimizing the charging time and capacity, the charging pattern obtained in this paper improved the charging efficiency by 2.8%, the temperature rise is reduced by 9.3 °C, and the charging capacity is basically the same.

Suggested Citation

  • Jiang, Li & Li, Yong & Huang, Yuduo & Yu, Jiaqi & Qiao, Xuebo & Wang, Yixiao & Huang, Chun & Cao, Yijia, 2020. "Optimization of multi-stage constant current charging pattern based on Taguchi method for Li-Ion battery," Applied Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318355
    DOI: 10.1016/j.apenergy.2019.114148
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919318355
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.114148?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. Li, Junqiu & Jin, Xin & Xiong, Rui, 2017. "Multi-objective optimization study of energy management strategy and economic analysis for a range-extended electric bus," Applied Energy, Elsevier, vol. 194(C), pages 798-807.
    2. Guo, Shanshan & Xiong, Rui & Wang, Kan & Sun, Fengchun, 2018. "A novel echelon internal heating strategy of cold batteries for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 219(C), pages 256-263.
    3. Ruan, Haijun & Jiang, Jiuchun & Sun, Bingxiang & Zhang, Weige & Gao, Wenzhong & Wang, Le Yi & Ma, Zeyu, 2016. "A rapid low-temperature internal heating strategy with optimal frequency based on constant polarization voltage for lithium-ion batteries," Applied Energy, Elsevier, vol. 177(C), pages 771-782.
    4. Yujie Cheng & Laifa Tao & Chao Yang, 2017. "Lithium-Ion Battery Capacity Estimation: A Method Based on Visual Cognition," Complexity, Hindawi, vol. 2017, pages 1-13, December.
    5. Chen, Xiaokai & Lei, Hao & Xiong, Rui & Shen, Weixiang & Yang, Ruixin, 2019. "A novel approach to reconstruct open circuit voltage for state of charge estimation of lithium ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 255(C).
    6. Sun, Fengchun & Xiong, Rui & He, Hongwen, 2016. "A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique," Applied Energy, Elsevier, vol. 162(C), pages 1399-1409.
    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. Pablo Carrasco Ortega & Pablo Durán Gómez & Julio César Mérida Sánchez & Fernando Echevarría Camarero & Ángel Á. Pardiñas, 2023. "Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review," Energies, MDPI, vol. 16(17), pages 1-51, August.
    2. 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).
    3. Syed Naeem Haider & Qianchuan Zhao & Xueliang Li, 2020. "Cluster-Based Prediction for Batteries in Data Centers," Energies, MDPI, vol. 13(5), pages 1-17, March.
    4. Liu, Yongjie & Huang, Zhiwu & He, Liang & Pan, Jianping & Li, Heng & Peng, Jun, 2023. "Temperature-aware charging strategy for lithium-ion batteries with adaptive current sequences in cold environments," Applied Energy, Elsevier, vol. 352(C).
    5. Román-Ramírez, L.A. & Marco, J., 2022. "Design of experiments applied to lithium-ion batteries: A literature review," Applied Energy, Elsevier, vol. 320(C).
    6. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(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. Jiang, Jiuchun & Ruan, Haijun & Sun, Bingxiang & Wang, Leyi & Gao, Wenzhong & Zhang, Weige, 2018. "A low-temperature internal heating strategy without lifetime reduction for large-size automotive lithium-ion battery pack," Applied Energy, Elsevier, vol. 230(C), pages 257-266.
    2. Borui Wang & Mingyin Yan, 2024. "Research on the Optimization of the Heating Effect of Lithium-Ion Batteries at a Low Temperature Based on an Electromagnetic Induction Heating System," Energies, MDPI, vol. 17(15), pages 1-24, July.
    3. Qin, Yudi & Xu, Zhoucheng & Xiao, Shengran & Gao, Ming & Bai, Jian & Liebig, Dorothea & Lu, Languang & Han, Xuebing & Li, Yalun & Du, Jiuyu & Ouyang, Minggao, 2023. "Temperature consistency–oriented rapid heating strategy combining pulsed operation and external thermal management for lithium-ion batteries," Applied Energy, Elsevier, vol. 335(C).
    4. Xiaogang Wu & Zhe Chen & Zhiyang Wang, 2017. "Analysis of Low Temperature Preheating Effect Based on Battery Temperature-Rise Model," Energies, MDPI, vol. 10(8), pages 1-15, August.
    5. Li, Junqiu & Xue, Qiao & Gao, Zhuo & Liu, Zengcheng & Xiao, Yansheng, 2024. "Frequency varying heating strategy for lithium-ion battery rapid preheating under subzero temperature considering the limitation of on-board current," Applied Energy, Elsevier, vol. 365(C).
    6. Ruan, Haijun & Jiang, Jiuchun & Sun, Bingxiang & Su, Xiaojia & He, Xitian & Zhao, Kejie, 2019. "An optimal internal-heating strategy for lithium-ion batteries at low temperature considering both heating time and lifetime reduction," Applied Energy, Elsevier, vol. 256(C).
    7. Borui Wang & Mingyin Yan, 2023. "Research on the Improvement of Lithium-Ion Battery Performance at Low Temperatures Based on Electromagnetic Induction Heating Technology," Energies, MDPI, vol. 16(23), pages 1-24, November.
    8. Wang, Yujie & Zhang, Xingchen & Chen, Zonghai, 2022. "Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges," Applied Energy, Elsevier, vol. 313(C).
    9. Li, Jun-qiu & Fang, Linlin & Shi, Wentong & Jin, Xin, 2018. "Layered thermal model with sinusoidal alternate current for cylindrical lithium-ion battery at low temperature," Energy, Elsevier, vol. 148(C), pages 247-257.
    10. Liu, Hanwu & Lei, Yulong & Fu, Yao & Li, Xingzhong, 2022. "A novel hybrid-point-line energy management strategy based on multi-objective optimization for range-extended electric vehicle," Energy, Elsevier, vol. 247(C).
    11. Li, Xiaoyu & Xu, Jianhua & Hong, Jianxun & Tian, Jindong & Tian, Yong, 2021. "State of energy estimation for a series-connected lithium-ion battery pack based on an adaptive weighted strategy," Energy, Elsevier, vol. 214(C).
    12. Ragab El-Sehiemy & Mohamed A. Hamida & Ehab Elattar & Abdullah Shaheen & Ahmed Ginidi, 2022. "Nonlinear Dynamic Model for Parameter Estimation of Li-Ion Batteries Using Supply–Demand Algorithm," Energies, MDPI, vol. 15(13), pages 1-20, June.
    13. Ma, Zeyu & Yang, Ruixin & Wang, Zhenpo, 2019. "A novel data-model fusion state-of-health estimation approach for lithium-ion batteries," Applied Energy, Elsevier, vol. 237(C), pages 836-847.
    14. Yang, Jibin & Xu, Xiaohui & Peng, Yiqiang & Zhang, Jiye & Song, Pengyun, 2019. "Modeling and optimal energy management strategy for a catenary-battery-ultracapacitor based hybrid tramway," Energy, Elsevier, vol. 183(C), pages 1123-1135.
    15. Li Zhai & Liwen Lin & Xinyu Zhang & Chao Song, 2016. "The Effect of Distributed Parameters on Conducted EMI from DC-Fed Motor Drive Systems in Electric Vehicles," Energies, MDPI, vol. 10(1), pages 1-17, December.
    16. He, Hongwen & Xiong, Rui & Peng, Jiankun, 2016. "Real-time estimation of battery state-of-charge with unscented Kalman filter and RTOS μCOS-II platform," Applied Energy, Elsevier, vol. 162(C), pages 1410-1418.
    17. 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).
    18. Huang, Deyang & Chen, Ziqiang & Zhou, Shiyao, 2021. "Model prediction-based battery-powered heating method for series-connected lithium-ion battery pack working at extremely cold temperatures," Energy, Elsevier, vol. 216(C).
    19. Bingxiang Sun & Xianjie Qi & Donglin Song & Haijun Ruan, 2023. "Review of Low-Temperature Performance, Modeling and Heating for Lithium-Ion Batteries," Energies, MDPI, vol. 16(20), pages 1-37, October.
    20. Wei, Zhongbao & Zhao, Jiyun & Ji, Dongxu & Tseng, King Jet, 2017. "A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model," Applied Energy, Elsevier, vol. 204(C), pages 1264-1274.

    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:259:y:2020:i:c:s0306261919318355. 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.