Smart Search 



Title of the article METHODOLOGICAL ASPECTS OF LITHIUM-ION NMC CELLS CYCLE LIFE TESTING
Authors

DOBREGO Kirill V., D. Sc. in Phys. and Math., Project Manager for the Development of Energy Storage Systems, Aktiv OMZ LLC, 1AK-GROUP, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.

BELEVICH Alexander V., Deputy Director General for Highly Automated Electric Transport, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.

IGNATCHIK Igor V., Head of the Battery Design Sector of the R&D Center “Electromechanical and Hybrid Power Units of Mobile Machines”, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.

ANANCHIKOV Anton A., Ph. D. in Eng., Assoc. Prof., Head of the Laboratory of Electrohydraulic Control Systems of the R&D Center “Electromechanical and Hybrid Power Units of Mobile Machines”, Joint Institute of Mechanical Engineering of the NAS of Belarus, Minsk, Republic of Belarus, This email address is being protected from spambots. You need JavaScript enabled to view it.

In the section MECHANICAL ENGINEERING COMPONENTS
Year 2025
Issue 1(70)
Pages 43–52
Type of article RAR
Index UDK 621.355:004.94
DOI https://doi.org/10.46864/1995-0470-2025-1-70-43-52
Abstract The paper considers an “accelerated” approach to experimental research, which consists in obtaining one basic degradation track and subsequent extrapolation of the results to other temperature and current operating conditions of the cell. The results of long-term cycling of a lithium-ion NMC cell produced by Soundon New Energy Technology in a current mode of 0.5C at room temperature are presented. Various methods for determining internal resistance from current-voltage measurements are discussed. It is shown that the internal resistance does not demonstrate a pronounced monotonic trend of change during cycling and cannot be used as an indicator of the state of health of cells of this type. Experimental data on capacity degradation are approximated with high accuracy by a function containing linear and exponential terms. Using the manufacturer’s data on cycling at room and elevated (45 °C) temperatures, a correction factor (Arrhenius function with an activation energy of 55 kJ/mol) was obtained, which makes it possible to extrapolate the results of the experimental study to the region of higher temperatures. Based on experimental data, a model of continuous cell degradation is proposed that can take into account time-varying current conditions and variable load patterns. The corresponding model can be integrated into the battery management module to monitor the underlying trend of capacity loss.
Keywords lithium-ion battery, test methodology, service life, capacity loss, internal battery resistance, approximation, extrapolation
  You can access full text version of the article.
Bibliography
  1. 1H 2023 energy storage market outlook. Available at: https://about.bnef.com/blog/1h-2023-energy-storage-market-outlook (accessed April 7, 2023).
  2. Guo J., Li Y., Pedersen K., Stroe D.-I. Litium-ion battery operation, degradation, and aging mechanism in electric vehicles: an overview. Energies, 2021, vol. 14, iss. 17. DOI: https://doi.org/10.3390/en14175220.
  3. Kulova T.L. Neobratimye protsessy na elektrodakh litiy-ionnogo akkumulyatora. Diss. dokt. khim. nauk [Irreversible processes on lithium-ion battery electrodes. D. Sc. Thesis]. Moscow, 2011. 399 p. (in Russ.).
  4. Gutierrez M., et al. Towards a better understanding of the degradation mechanisms of Li-ion full cells using Si/C composites as anode. Journal of power sources, 2022, vol. 533. DOI: https://doi.org/10.1016/j.jpowsour.2022.231408.
  5. Krupp A., et al. Semi-empirical cyclic aging model for stationary storages based on graphite anode aging mechanisms. Journal of power sources, 2023, vol. 561. DOI: https://doi.org/10.1016/j.jpowsour.2023.232721.
  6. Severson K.A., et al. Data-driven prediction of battery cycle life before capacity degradation. Nature energy, 2019, vol. 4, iss. 5, pp. 383–391. DOI: https://doi.org/10.1038/s41560-019-0356-8.
  7. Oxford battery degradation dataset 1. Available at: https://ora.ox.ac.uk/objects/uuid:03ba4b01- cfed-46d3-9b1a-7d4a7bdf6fac (accessed March 15, 2024).
  8. Battery research group. Available at: https://calce.umd.edu/battery-research-group (accessed March 15, 2022).
  9. Saha B., Goebel K. Battery data set. Available at: https://www.nasa.gov/content/prognostics-center-of-excellence-data-set-repository (accessed June 10, 2024).
  10. Studies. Available at: https://www.batteryarchive.org/study_summaries.html (accessed May 11, 2024).
  11. Dos Reis G., Strange C., Yadav M., Li S. Lithium-ion battery data and where to find it. Energy and AI, 2021, vol. 5. DOI: https://doi.org/10.1016/j.egyai.2021.100081.
  12. Zhang Y., Wik T., Bergström J., Pecht M., Zou C. A machine learning-based framework for online prediction of battery ageing trajectory and lifetime using histogram data. Journal of power sources, 2022, vol. 526. DOI: https://doi.org/10.1016/j.jpowsour.2022.231110.
  13. Birkl C.R., Roberts M.R., McTurk E., Bruce P.G., Howey D.A. Diagnosis and prognosis of degradation in lithium-ion batteries. Journal of power sources, 2017, vol. 341, pp. 373–386. DOI:
    https://doi.org/10.1016/j.jpowsour.2016.12.011.
  14. Piłatowicz G., Marongiu A., Drillkens J., Sinhuber P., Sauer D.U. A critical overview of definitions and determination techniques of the internal resistance using lithium-ion, lead-acid, nickel metal-hydride batteries and electrochemical double-layer capacitors as examples. Journal of power sources, 2015, vol. 296, pp. 365–376. DOI: https://doi.org/10.1016/j.jpowsour.2015.07.073.
  15. Grinchik N.N., Dobrego K.V., Chumachenko M.A. Ob izmerenii elektricheskogo soprotivleniya zhidkikh elektrolitov akkumulyatornykh batarey [On the measurement of electric resistance of liquid electrolytes of accumulator battery]. Energetika. Proceedings of CIS higher education institutions and power engineering associations, 2018, vol. 61, no. 6, pp. 494–507.
    DOI: https://doi.org/10.21122/1029-7448-2018-61-6-494-507 (in Russ.).
  16. Diao W., Saxena S., Han B., Pecht M. Algorithm to determine the knee point on capacity fade curves of lithium-ion cells. Energies, 2019, vol. 12, iss. 15. DOI: https://doi.org/10.3390/en12152910.
  17. Feinauer M., Wohlfahrt-Mehrens M., Hölzle M., Waldmann T. Temperature-driven path dependence in Li-ion battery cyclic aging. Journal of power sources, 2023, vol. 594. DOI: https://doi.org/10.1016/j.jpowsour.2023.233948.
  18. Dobrego K.V., Koznacheev I.A. Universalnaya imitatsionnaya model degradatsii akkumulyatornykh batarey s optimizatsiey parametrov po geneticheskomu algoritmu [Universal simulation model of battery degradation with optimization of parameters by genetic algorithm]. Energetika. Proceedings of CIS higher education institutions and power engineering associations, 2022, pp. 65, no. 6, pp. 481–500. DOI: https://doi.org/10.21122/1029-7448-2022-65-6-481-498 (in Russ.).