IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i12p2992-d1416806.html
   My bibliography  Save this article

Five-Stage Fast Charging of Lithium-Ion Batteries Based on Lamb Waves Depolarization

Author

Listed:
  • Tong Wang

    (School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)

  • Wei Liang

    (School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China)

Abstract

Lithium-ion batteries are essential for the development of consumer electronics and electric vehicles due to their high energy density, low self-discharge rate, and easy maintenance. To optimize the performance of lithium-ion batteries and meet the battery requirements of devices, it is necessary to charge the batteries at a faster rate. Therefore, this paper proposes a five-stage constant current charging method based on Lamb wave depolarization to enhance the charging efficiency. Specifically, the orthogonal experimental method is first used to determine the near-optimal value of the charging current in each stage of the five-stage constant current charging process. Subsequently, Lamb waves are introduced during the charging process of each constant current charging stage. Compared with the traditional five-stage constant current charging method, the five-stage constant current charging method based on Lamb wave depolarization improves the charging efficiency. The charging efficiency of the five-stage constant current charging method based on Lamb wave depolarization with an excitation voltage peak-to-peak amplitude Vpp of 120 and an excitation duration of 6 min is 20% higher than that of the traditional five-stage constant current charging method. The weakening of the polarization effect is positively correlated with the Lamb wave excitation voltage. In addition, the five-stage constant current charging method based on Lamb wave depolarization is superior to the five-stage constant current shelving depolarization charging method and the five-stage constant current negative pulse depolarization charging method in improving the charging efficiency.

Suggested Citation

  • Tong Wang & Wei Liang, 2024. "Five-Stage Fast Charging of Lithium-Ion Batteries Based on Lamb Waves Depolarization," Energies, MDPI, vol. 17(12), pages 1-15, June.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2992-:d:1416806
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/12/2992/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/12/2992/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2019. "Two-stage stochastic optimization for cost-minimal charging of electric vehicles at public charging stations with photovoltaics," Applied Energy, Elsevier, vol. 242(C), pages 769-781.
    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. Wang, Qi & Huang, Chunyi & Wang, Chengmin & Li, Kangping & Xie, Ning, 2024. "Joint optimization of bidding and pricing strategy for electric vehicle aggregator considering multi-agent interactions," Applied Energy, Elsevier, vol. 360(C).
    2. Zhou, Jianli & Wu, Yunna & Tao, Yao & Gao, Jianwei & Zhong, Zhiming & Xu, Chuanbo, 2021. "Geographic information big data-driven two-stage optimization model for location decision of hydrogen refueling stations: An empirical study in China," Energy, Elsevier, vol. 225(C).
    3. Arkadiusz Małek & Jacek Caban & Agnieszka Dudziak & Andrzej Marciniak & Piotr Ignaciuk, 2023. "A Method of Assessing the Selection of Carport Power for an Electric Vehicle Using the Metalog Probability Distribution Family," Energies, MDPI, vol. 16(13), pages 1-16, June.
    4. Jacek Caban & Arkadiusz Małek & Branislav Šarkan, 2024. "Strategic Model for Charging a Fleet of Electric Vehicles with Energy from Renewable Energy Sources," Energies, MDPI, vol. 17(5), pages 1-17, March.
    5. Jun Dong & Anyuan Fu & Yao Liu & Shilin Nie & Peiwen Yang & Linpeng Nie, 2019. "Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption," Sustainability, MDPI, vol. 11(24), pages 1-22, December.
    6. Emad Awada & Eyad Radwan & Suzan Abed & Akram Al-Mahrouk, 2024. "Economic Analysis and Design of Sustainable Solar Electric Vehicle Carport at Applied Science Private University in Jordan," Energies, MDPI, vol. 17(17), pages 1-20, August.
    7. Chiara Bordin & Asgeir Tomasgard, 2021. "Behavioural Change in Green Transportation: Micro-Economics Perspectives and Optimization Strategies," Energies, MDPI, vol. 14(13), pages 1-20, June.
    8. Yan, Rujing & Wang, Jiangjiang & Huo, Shuojie & Qin, Yanbo & Zhang, Jing & Tang, Saiqiu & Wang, Yuwei & Liu, Yan & Zhou, Lin, 2023. "Flexibility improvement and stochastic multi-scenario hybrid optimization for an integrated energy system with high-proportion renewable energy," Energy, Elsevier, vol. 263(PB).
    9. Zhang, Haifeng & Tian, Ming & Zhang, Cong & Wang, Bin & Wang, Dai, 2021. "A systematic solution to quantify economic values of vehicle grid integration," Energy, Elsevier, vol. 232(C).
    10. Wei, Shaoyuan & Murgovski, Nikolce & Jiang, Jiuchun & Hu, Xiaosong & Zhang, Weige & Zhang, Caiping, 2020. "Stochastic optimization of a stationary energy storage system for a catenary-free tramline," Applied Energy, Elsevier, vol. 280(C).
    11. Zhou, Yuekuan & Liu, Xiaohua & Zhao, Qianchuan, 2024. "A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid," Renewable Energy, Elsevier, vol. 221(C).
    12. Langenmayr, Uwe & Wang, Weimin & Jochem, Patrick, 2020. "Unit commitment of photovoltaic-battery systems: An advanced approach considering uncertainties from load, electric vehicles, and photovoltaic," Applied Energy, Elsevier, vol. 280(C).
    13. van der Meer, Dennis & Wang, Guang Chao & Munkhammar, Joakim, 2021. "An alternative optimal strategy for stochastic model predictive control of a residential battery energy management system with solar photovoltaic," Applied Energy, Elsevier, vol. 283(C).
    14. Alexandra Märtz & Uwe Langenmayr & Sabrina Ried & Katrin Seddig & Patrick Jochem, 2022. "Charging Behavior of Electric Vehicles: Temporal Clustering Based on Real-World Data," Energies, MDPI, vol. 15(18), pages 1-26, September.
    15. Edgar Sokolovskij & Arkadiusz Małek & Jacek Caban & Agnieszka Dudziak & Jonas Matijošius & Andrzej Marciniak, 2023. "Selection of a Photovoltaic Carport Power for an Electric Vehicle," Energies, MDPI, vol. 16(7), pages 1-16, March.
    16. Yin, WanJun & Wen, Tao & Zhang, Chao, 2023. "Cooperative optimal scheduling strategy of electric vehicles based on dynamic electricity price mechanism," Energy, Elsevier, vol. 263(PA).
    17. He, Fulin & Fathabadi, Hassan, 2020. "Novel standalone plug-in hybrid electric vehicle charging station fed by solar energy in presence of a fuel cell system used as supporting power source," Renewable Energy, Elsevier, vol. 156(C), pages 964-974.
    18. Mohammadzadeh, Narges & Zegordi, Seyed Hessameddin & Nikbakhsh, Ehsan, 2021. "Pricing and free periodic maintenance service decisions for an electric-and-fuel automotive supply chain using the total cost of ownership," Applied Energy, Elsevier, vol. 288(C).
    19. Yu, Zhenyu & Lu, Fei & Zou, Yu & Yang, Xudong, 2022. "Quantifying the real-time energy flexibility of commuter plug-in electric vehicles in an office building considering photovoltaic and load uncertainty," Applied Energy, Elsevier, vol. 321(C).
    20. Christos Karolemeas & Stefanos Tsigdinos & Panagiotis G. Tzouras & Alexandros Nikitas & Efthimios Bakogiannis, 2021. "Determining Electric Vehicle Charging Station Location Suitability: A Qualitative Study of Greek Stakeholders Employing Thematic Analysis and Analytical Hierarchy Process," Sustainability, MDPI, vol. 13(4), pages 1-21, February.

    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:17:y:2024:i:12:p:2992-:d:1416806. 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.