IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i12p3617-d576904.html
   My bibliography  Save this article

The Importance of Optical Fibres for Internal Temperature Sensing in Lithium-ion Batteries during Operation

Author

Listed:
  • Markus S. Wahl

    (Department of Energy and Process Engineering & ENERSENSE, NTNU, 7491 Trondheim, Norway)

  • Lena Spitthoff

    (Department of Energy and Process Engineering & ENERSENSE, NTNU, 7491 Trondheim, Norway)

  • Harald I. Muri

    (Department of Electronic Systems & ENERSENSE, NTNU, 7491 Trondheim, Norway)

  • Asanthi Jinasena

    (Department of Energy and Process Engineering & ENERSENSE, NTNU, 7491 Trondheim, Norway)

  • Odne S. Burheim

    (Department of Energy and Process Engineering & ENERSENSE, NTNU, 7491 Trondheim, Norway)

  • Jacob J. Lamb

    (Department of Energy and Process Engineering & ENERSENSE, NTNU, 7491 Trondheim, Norway
    Department of Electronic Systems & ENERSENSE, NTNU, 7491 Trondheim, Norway)

Abstract

Lithium-ion batteries (LiBs) are widely used as energy storage systems (ESSs). The biggest challenge they face is retaining intrinsic health under all conditions, and understanding internal thermal behaviour is crucial to this. The key concern is the potentially large temperature differences at high charge/discharge rates. Excess heat created during charge/discharge will accelerate irreversible aging, eventually leading to failure. As a consequence, it is important to keep battery states within their safe operating range, which is determined by voltage, temperature, and current windows. Due to the chemically aggressive and electrically noisy environment, internal temperature measurement is difficult. As a result, non-invasive sensors must be physically stable, electromagnetic interference-resistant, and chemically inert. These characteristics are provided by fibre Bragg grating (FBG) sensors, which are also multiplexable. This review article discusses the thermal problems that arise during LiB use, as well as their significance in terms of LiB durability and protection. FBG-based sensors are described as a technology, with emphasis on their importance for direct temperature measurement within the LiB cell.

Suggested Citation

  • Markus S. Wahl & Lena Spitthoff & Harald I. Muri & Asanthi Jinasena & Odne S. Burheim & Jacob J. Lamb, 2021. "The Importance of Optical Fibres for Internal Temperature Sensing in Lithium-ion Batteries during Operation," Energies, MDPI, vol. 14(12), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3617-:d:576904
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/12/3617/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/12/3617/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Raijmakers, L.H.J. & Danilov, D.L. & Eichel, R.-A. & Notten, P.H.L., 2019. "A review on various temperature-indication methods for Li-ion batteries," Applied Energy, Elsevier, vol. 240(C), pages 918-945.
    2. Shah, K. & McKee, C. & Chalise, D. & Jain, A., 2016. "Experimental and numerical investigation of core cooling of Li-ion cells using heat pipes," Energy, Elsevier, vol. 113(C), pages 852-860.
    3. Aleksandra Fortier & Max Tsao & Nick D. Williard & Yinjiao Xing & Michael G. Pecht, 2017. "Preliminary Study on Integration of Fiber Optic Bragg Grating Sensors in Li-Ion Batteries and In Situ Strain and Temperature Monitoring of Battery Cells," Energies, MDPI, vol. 10(7), pages 1-11, June.
    4. Jaiswal, Abhishek, 2017. "Lithium-ion battery based renewable energy solution for off-grid electricity: A techno-economic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 922-934.
    5. Opitz, A. & Badami, P. & Shen, L. & Vignarooban, K. & Kannan, A.M., 2017. "Can Li-Ion batteries be the panacea for automotive applications?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 685-692.
    6. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2015. "Performance comparison of four lithium–ion battery technologies under calendar aging," Energy, Elsevier, vol. 84(C), pages 542-550.
    7. Jiaqiang Huang & Laura Albero Blanquer & Julien Bonefacino & E. R. Logan & Daniel Alves Dalla Corte & Charles Delacourt & Betar M. Gallant & Steven T. Boles & J. R. Dahn & Hwa-Yaw Tam & Jean-Marie Tar, 2020. "Operando decoding of chemical and thermal events in commercial Na(Li)-ion cells via optical sensors," Nature Energy, Nature, vol. 5(9), pages 674-683, September.
    8. Diouf, Boucar & Pode, Ramchandra, 2015. "Potential of lithium-ion batteries in renewable energy," Renewable Energy, Elsevier, vol. 76(C), pages 375-380.
    9. De Vita, Armando & Maheshwari, Arpit & Destro, Matteo & Santarelli, Massimo & Carello, Massimiliana, 2017. "Transient thermal analysis of a lithium-ion battery pack comparing different cooling solutions for automotive applications," Applied Energy, Elsevier, vol. 206(C), pages 101-112.
    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. Amiri, Mahshid N. & Håkansson, Anne & Burheim, Odne S. & Lamb, Jacob J., 2024. "Lithium-ion battery digitalization: Combining physics-based models and machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 200(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. Raijmakers, L.H.J. & Danilov, D.L. & Eichel, R.-A. & Notten, P.H.L., 2019. "A review on various temperature-indication methods for Li-ion batteries," Applied Energy, Elsevier, vol. 240(C), pages 918-945.
    2. Han, Gaoce & Yan, Jize & Guo, Zhen & Greenwood, David & Marco, James & Yu, Yifei, 2021. "A review on various optical fibre sensing methods for batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    3. Kanbur, Baris Burak & Kumtepeli, Volkan & Duan, Fei, 2020. "Thermal performance prediction of the battery surface via dynamic mode decomposition," Energy, Elsevier, vol. 201(C).
    4. Ghorbanzadeh, Milad & Astaneh, Majid & Golzar, Farzin, 2019. "Long-term degradation based analysis for lithium-ion batteries in off-grid wind-battery renewable energy systems," Energy, Elsevier, vol. 166(C), pages 1194-1206.
    5. 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.
    6. Zubi, Ghassan & Fracastoro, Gian Vincenzo & Lujano-Rojas, Juan M. & El Bakari, Khalil & Andrews, David, 2019. "The unlocked potential of solar home systems; an effective way to overcome domestic energy poverty in developing regions," Renewable Energy, Elsevier, vol. 132(C), pages 1425-1435.
    7. Zubi, Ghassan & Dufo-López, Rodolfo & Pasaoglu, Guzay & Pardo, Nicolás, 2016. "Techno-economic assessment of an off-grid PV system for developing regions to provide electricity for basic domestic needs: A 2020–2040 scenario," Applied Energy, Elsevier, vol. 176(C), pages 309-319.
    8. Come Zebra, Emília Inês & van der Windt, Henny J. & Nhumaio, Geraldo & Faaij, André P.C., 2021. "A review of hybrid renewable energy systems in mini-grids for off-grid electrification in developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    9. Zhao, Rui & Gu, Junjie & Liu, Jie, 2017. "Optimization of a phase change material based internal cooling system for cylindrical Li-ion battery pack and a hybrid cooling design," Energy, Elsevier, vol. 135(C), pages 811-822.
    10. Yuqiang Zeng & Fengyu Shen & Buyi Zhang & Jaeheon Lee & Divya Chalise & Qiye Zheng & Yanbao Fu & Sumanjeet Kaur & Sean D. Lubner & Vincent S. Battaglia & Bryan D. McCloskey & Michael C. Tucker & Ravi , 2023. "Nonintrusive thermal-wave sensor for operando quantification of degradation in commercial batteries," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    11. 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.
    12. Goh, Taedong & Park, Minjun & Seo, Minhwan & Kim, Jun Gu & Kim, Sang Woo, 2017. "Capacity estimation algorithm with a second-order differential voltage curve for Li-ion batteries with NMC cathodes," Energy, Elsevier, vol. 135(C), pages 257-268.
    13. Holger C. Hesse & Michael Schimpe & Daniel Kucevic & Andreas Jossen, 2017. "Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids," Energies, MDPI, vol. 10(12), pages 1-42, December.
    14. Yue Ren & Chunhua Jin & Shu Fang & Li Yang & Zixuan Wu & Ziyang Wang & Rui Peng & Kaiye Gao, 2023. "A Comprehensive Review of Key Technologies for Enhancing the Reliability of Lithium-Ion Power Batteries," Energies, MDPI, vol. 16(17), pages 1-38, August.
    15. Shi, Haotian & Wang, Shunli & Huang, Qi & Fernandez, Carlos & Liang, Jianhong & Zhang, Mengyun & Qi, Chuangshi & Wang, Liping, 2024. "Improved electric-thermal-aging multi-physics domain coupling modeling and identification decoupling of complex kinetic processes based on timescale quantification in lithium-ion batteries," Applied Energy, Elsevier, vol. 353(PB).
    16. Sun, Li & Sun, Wen & You, Fengqi, 2020. "Core temperature modelling and monitoring of lithium-ion battery in the presence of sensor bias," Applied Energy, Elsevier, vol. 271(C).
    17. Ostanek, Jason K. & Li, Weisi & Mukherjee, Partha P. & Crompton, K.R. & Hacker, Christopher, 2020. "Simulating onset and evolution of thermal runaway in Li-ion cells using a coupled thermal and venting model," Applied Energy, Elsevier, vol. 268(C).
    18. Yang, Jie & Yu, Fan & Ma, Kai & Yang, Bo & Yue, Zhiyuan, 2024. "Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles," Renewable Energy, Elsevier, vol. 224(C).
    19. Parlikar, Anupam & Truong, Cong Nam & Jossen, Andreas & Hesse, Holger, 2021. "The carbon footprint of island grids with lithium-ion battery systems: An analysis based on levelized emissions of energy supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    20. Yang, Yang & Yuan, Wei & Zhang, Xiaoqing & Yuan, Yuhang & Wang, Chun & Ye, Yintong & Huang, Yao & Qiu, Zhiqiang & Tang, Yong, 2020. "Overview on the applications of three-dimensional printing for rechargeable lithium-ion batteries," Applied Energy, Elsevier, vol. 257(C).

    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:12:p:3617-:d:576904. 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.