IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i19p6236-d647503.html
   My bibliography  Save this article

Reliability-Based Robust Design Optimization of Lithium-Ion Battery Cells for Maximizing the Energy Density by Increasing Reliability and Robustness

Author

Listed:
  • Jinhwan Park

    (Graduate School of Mechanical Design & Production Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Donghyeon Yoo

    (Graduate School of Mechanical Design & Production Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Jaemin Moon

    (Graduate School of Mechanical Design & Production Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Janghyeok Yoon

    (Department of Industrial Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Jungtae Park

    (Department of Chemical Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Seungae Lee

    (Department of Chemical Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Doohee Lee

    (Department of Electrical and Electronics Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

  • Changwan Kim

    (School of Mechanical Engineering, Konkuk University, 120, Neung dong-ro, Gwangjin-gu, Seoul 05029, Korea)

Abstract

Lithium-ion batteries (LIBs) are increasingly employed in electric vehicles (EVs) owing to their advantages, such as low weight, and high energy and power densities. However, the uncertainty encountered in the manufacturing of LIB cells increases the failure rate and causes cell-to-cell variations, thereby degrading the battery capacity and lifetime. In this study, the reliability and robustness of LIB cells were improved using the design of experiments (DOE), and the reliability-based robust design optimization (RBRDO) approaches. First, design factors sensitive to the energy density and power density were selected as design variables through sensitivity analysis using the DOE. RBRDO was performed to maximize the energy density while reducing the failure rate and cell-to-cell variations. To verify the superiority of the reliability and robustness offered by RBRDO, the obtained results were compared with those from conventional deterministic design optimization (DDO), and reliability-based design optimization (RBDO). RBRDO increased the mean of the energy density by 33.5% compared to the initial value and reduced the failure rate by 98.9%, due to improved reliability, compared to DDO. Moreover, RBRDO reduced the standard deviation in the energy density (i.e., cell-to-cell variations) by 30.0% due to the improved robustness compared to RBDO.

Suggested Citation

  • Jinhwan Park & Donghyeon Yoo & Jaemin Moon & Janghyeok Yoon & Jungtae Park & Seungae Lee & Doohee Lee & Changwan Kim, 2021. "Reliability-Based Robust Design Optimization of Lithium-Ion Battery Cells for Maximizing the Energy Density by Increasing Reliability and Robustness," Energies, MDPI, vol. 14(19), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6236-:d:647503
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/19/6236/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/19/6236/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zubi, Ghassan & Dufo-López, Rodolfo & Carvalho, Monica & Pasaoglu, Guzay, 2018. "The lithium-ion battery: State of the art and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 292-308.
    2. Donghyeon Yoo & Jinhwan Park & Jaemin Moon & Changwan Kim, 2021. "Reliability-Based Design Optimization for Reducing the Performance Failure and Maximizing the Specific Energy of Lithium-Ion Batteries Considering Manufacturing Uncertainty of Porous Electrodes," Energies, MDPI, vol. 14(19), pages 1-15, September.
    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. Nikita V. Martyushev & Boris V. Malozyomov & Svetlana N. Sorokova & Egor A. Efremenkov & Denis V. Valuev & Mengxu Qi, 2023. "Review Models and Methods for Determining and Predicting the Reliability of Technical Systems and Transport," Mathematics, MDPI, vol. 11(15), pages 1-31, July.
    2. Yang, Jiong & Cheng, Fanyong & Liu, Zhi & Duodu, Maxwell Mensah & Zhang, Mingyan, 2023. "A novel semi-supervised fault detection and isolation method for battery system of electric vehicles," Applied Energy, Elsevier, vol. 349(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. Mohammed, Abubakar Gambo & Elfeky, Karem Elsayed & Wang, Qiuwang, 2022. "Recent advancement and enhanced battery performance using phase change materials based hybrid battery thermal management for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    2. Wang, Bin & Wang, Shifeng & Tang, Yuanyuan & Tsang, Chi-Wing & Dai, Jinchuan & Leung, Michael K.H. & Lu, Xiao-Ying, 2019. "Micro/nanostructured MnCo2O4.5 anodes with high reversible capacity and excellent rate capability for next generation lithium-ion batteries," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    3. Ma, Guijun & Zhang, Yong & Cheng, Cheng & Zhou, Beitong & Hu, Pengchao & Yuan, Ye, 2019. "Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    4. Fan, Ailong & Wang, Junteng & He, Yapeng & Perčić, Maja & Vladimir, Nikola & Yang, Liu, 2021. "Decarbonising inland ship power system: Alternative solution and assessment method," Energy, Elsevier, vol. 226(C).
    5. Gaffuri, Pierre & Stolyarova, Elena & Llerena, Daniel & Appert, Estelle & Consonni, Marianne & Robin, Stéphane & Consonni, Vincent, 2021. "Potential substitutes for critical materials in white LEDs: Technological challenges and market opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    6. 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).
    7. Calise, Francesco & Cappiello, Francesco Liberato & Cimmino, Luca & Dentice d’Accadia, Massimo & Vicidomini, Maria, 2023. "Renewable smart energy network: A thermoeconomic comparison between conventional lithium-ion batteries and reversible solid oxide fuel cells," Renewable Energy, Elsevier, vol. 214(C), pages 74-95.
    8. Omid Norouzi & Animesh Dutta, 2022. "The Current Status and Future Potential of Biogas Production from Canada’s Organic Fraction Municipal Solid Waste," Energies, MDPI, vol. 15(2), pages 1-17, January.
    9. Du, Peng & Cao, Liang & Zhang, Bao & Wang, Chunhui & Xiao, Zhiming & Zhang, Jiafeng & Wang, Dong & Ou, Xing, 2021. "Recent progress on heterostructure materials for next-generation sodium/potassium ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    10. Pedram Asef & Marzia Milan & Andrew Lapthorn & Sanjeevikumar Padmanaban, 2021. "Future Trends and Aging Analysis of Battery Energy Storage Systems for Electric Vehicles," Sustainability, MDPI, vol. 13(24), pages 1-28, December.
    11. 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.
    12. Maja Perčić & Nikola Vladimir & Marija Koričan, 2021. "Electrification of Inland Waterway Ships Considering Power System Lifetime Emissions and Costs," Energies, MDPI, vol. 14(21), pages 1-25, October.
    13. Nguyen-Tien, Viet & Dai, Qiang & Harper, Gavin D.J. & Anderson, Paul A. & Elliott, Robert J.R., 2022. "Optimising the geospatial configuration of a future lithium ion battery recycling industry in the transition to electric vehicles and a circular economy," Applied Energy, Elsevier, vol. 321(C).
    14. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Bianchi, Francesco & Domenghini, Piergiovanni & Cotana, Franco & Wang, Jinwen, 2022. "A techno-economic analysis of a solar PV and DC battery storage system for a community energy sharing," Energy, Elsevier, vol. 244(PB).
    15. Kriegler, Johannes & Hille, Lucas & Stock, Sandro & Kraft, Ludwig & Hagemeister, Jan & Habedank, Jan Bernd & Jossen, Andreas & Zaeh, Michael F., 2021. "Enhanced performance and lifetime of lithium-ion batteries by laser structuring of graphite anodes," Applied Energy, Elsevier, vol. 303(C).
    16. Sun, Li & Li, Guanru & You, Fengqi, 2020. "Combined internal resistance and state-of-charge estimation of lithium-ion battery based on extended state observer," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    17. Theodoros Kalogiannis & Md Sazzad Hosen & Mohsen Akbarzadeh Sokkeh & Shovon Goutam & Joris Jaguemont & Lu Jin & Geng Qiao & Maitane Berecibar & Joeri Van Mierlo, 2019. "Comparative Study on Parameter Identification Methods for Dual-Polarization Lithium-Ion Equivalent Circuit Model," Energies, MDPI, vol. 12(21), pages 1-35, October.
    18. Semyon D. Shraer & Nikita D. Luchinin & Ivan A. Trussov & Dmitry A. Aksyonov & Anatoly V. Morozov & Sergey V. Ryazantsev & Anna R. Iarchuk & Polina A. Morozova & Victoria A. Nikitina & Keith J. Steven, 2022. "Development of vanadium-based polyanion positive electrode active materials for high-voltage sodium-based batteries," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    19. Freitas Gomes, Icaro Silvestre & Perez, Yannick & Suomalainen, Emilia, 2020. "Coupling small batteries and PV generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 126(C).
    20. Mi Tian & Yanchunxiao Qi & Eun-Suok Oh, 2021. "Application of a Polyacrylate Latex to a Lithium Iron Phosphate Cathode as a Binder Material," Energies, MDPI, vol. 14(7), pages 1-10, March.

    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:19:p:6236-:d:647503. 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.