Probabilistic models of the capacity of the electrode material in a wide range of current loads

Cover Page

Cite item

Full Text

Abstract

An approach for constructing mathematical models of the current dependence of the capacity of electrode materials is proposed. The approach involves analyzing the probabilities of favorable and unfavorable events occurring on the elements of electrical equivalent circuits that can be used to model the electrode. Several probabilistic models that correspond to different combinations of a capacitor, a Warburg element and a constant phase element in an electrical circuit are proposed. As an example, the validation of specific models to describe the experimental current dependences of the capacity of Li3V2(PO4)3 or Li4Ti5O12 based composite electrodes with carbon nanomaterial is shown. The approach allows approximating such dependencies for a wide range of current loads – from 0.1 to 50 C.

About the authors

Arseni Vladimirovich Ushakov

Saratov State University

ORCID iD: 0000-0003-0495-7750
SPIN-code: 6225-0061
83, Astrakhanskaya St., Saratov, 410012

Kirill Sergeevich Rybakov

Saratov State University

ORCID iD: 0000-0003-4821-2910
SPIN-code: 5334-5760
83, Astrakhanskaya St., Saratov, 410012

Anna V. Khrykina

Saratov State University

ORCID iD: 0000-0003-1198-0107
SPIN-code: 5258-7703
83, Astrakhanskaya St., Saratov, 410012

Irina Mikhailovna Gamayunova

Saratov State University

83, Astrakhanskaya St., Saratov, 410012

References

  1. Potential Benefits of High-Power, HighCapacity Batteries (January 2020). United States Department of Energy. Washington, DC 20585. Available at: https://www.energy.gov/oe/downloads/potentialbenefits-high-power-high-capacity-batteries-january2020 (accessed Febrary 01, 2024).
  2. Bagotsky V. S. Fundamentals of Electrochemistry. 2nd ed. John Wiley & Sons, Inc., 2006. 722 p.
  3. Biesheuvel P. M., Dykstra J. E. Introduction to Physics of Electrochemical Processes. 2020. Available at: http://www.physicsofelectrochemicalprocesses.com (accessed Febrary 01, 2024).
  4. Biesheuvel P. M., Porada S., Dykstra J. E. The difference between Faradaic and non-Faradaic electrode processes. arXiv:1809.02930v4 [physics.chem-ph]. Available at: https://arxiv.org/pdf/1809.02930v4.pdf (accessed Febrary 01, 2024).
  5. Atkins P., De Paula J., Keeler J. Atkins’ physical chemistry. 11th ed. Oxford University Press, 2017, 928 p.
  6. Korovin N. V., Skundin A. M., eds. Khimicheskiye istochniki toka: spravochnik [Electrochemical Power Sources: handbook]. Moscow, MEI Publ., 2003. 740 p. (in Russian).
  7. Alviev Kh. Kh. The effect of discharge current upon battery capacity. Electrochemical Energetics, 2013, vol. 13, no. 4, pp. 225-227 (in Russian).
  8. Yazvinskaya N. N., Galushkin D. N., Galushkin N. E. Generalization of Peukert’s equation to build practical models of batteries. Izvestiya vuzov. Severo-kavkazskiy region. Technical Science, 2019, no. 2, pp. 60-68 (in Russian). https://doi.org/10.17213/0321-2653-2019-2-60-68
  9. Doyle M., Newman J. Analysis of capacity- rate data for lithium batteries using simplified models of the discharge process. Journal of Applied Electrochemistry, 1997, vol. 27, pp. 846-856. https://doi.org/10.1023/A:1018481030499
  10. Lain M. J., Kendrick E. Understanding the limitations of lithium ion batteries at high rates. Journal of Power Sources, 2021, vol. 493, article no. 229690. https://doi.org/10.1016/j.jpowsour.2021.229690
  11. Heubner C., Schneider M., Michaelis A. Diffusion-Limited C-Rate: A Fundamental Principle Quantifying the Intrinsic Limits of Li-Ion Batteries. Adv. Energy Mater., 2020, vol. 10, article no. 1902523. https://doi.org/10.1002/aenm.201902523
  12. Heubner C., Reuber S., Seeba J., Marcinkowski P., Nikolowski K., Schneider M., Wolter M., Michaelis A. Application-oriented modeling and optimization of tailored Li-ion batteries using the concept of Diffusion Limited C-rate. Journal of Power Sources, 2020, vol. 479, article no. 228704. https://doi.org/10.1016/j.jpowsour.2020.228704
  13. Heubner C., Nikolowski K., Reuber S., Schneider M., Wolter M., Michaelis A. Recent Insights into Rate Performance Limitations of Li-ion Batteries. Batteries & Supercaps, 2020, vol. 4, iss. 2, pp. 268-285. https://doi.org/10.1002/batt.202000227
  14. Parikh D., Christensen T., Li J. Correlating the influence of porosity, tortuosity, and mass loading on the energy density of LiNi0.6Mn0.2Co0.2O2 cathodes under extreme fast charging (XFC) conditions. Journal of Power Sources, 2020, vol. 474, article no. 228601. https://doi.org/10.1016/j.jpowsour.2020.228601
  15. Parikh D. Understanding the Limitations in Battery Components for Improving Energy Density under Extreme Fast Charging (XFC) Conditions, PhD diss., University of Tennessee, 2021. https://trace.tennessee.edu/utk_graddiss/6504 (accessed December 16, 2021).
  16. Wang F., Tang M. A Quantitative Analytical Model for Predicting and Optimizing the Rate Performance of Battery Cells. Cell Reports Physical Science, 2021, vol. 1, no. 9, article no. 100192. https://doi.org/10.1016/j.xcrp.2020.100192
  17. Mayilvahanan K. S., Hui Z., Hu K., Kuang J., McCarthy A. H., Bernard J., Wang L., Takeuchi K. J., Marschilok A. C., Takeuchi E. S., West A. C. Quantifying Uncertainty in Tortuosity Estimates for Porous Electrodes. Journal of The Electrochemical Society, 2021, vol. 168, no. 7, article no. 070537. https://dx.doi.org/10.1149/1945-7111/ac1316
  18. Weiss M., Ruess R., Kasnatscheew J., Levartovsky Y., Levy N. R., Minnmann P., Stolz L., Waldmann T., Wohlfahrt-Mehrens M., Aurbach D., Winter M., Ein-Eli Y., Janek J. Fast Charging of Lithium-Ion Batteries: A Review of Materials Aspects. Adv. Energy Mater., 2021, vol. 11, article no. 2101126. https://doi.org/10.1002/aenm.202101126
  19. Ivanishchev A. V., Ushakov A. V., Ivanishcheva I. A., Churikov A. V., Mironov A. V., Fedotov S. S., Khasanova N. R., Antipov E. V. Structural and electrochemical study of fast Li diffusion in Li3V2(PO4)3-based electrode material. Electrochimica Acta, 2017, vol. 230, pp. 479-491. https://doi.org/10.1016/j.electacta.2017.02.009
  20. Ushakov A. V., Makhov S. V., Gridina N. A., Ivanishchev A. V., Gamayunova I. M. Rechargeable lithium-ion system based on lithium-vanadium(III) phosphate and lithium titanate and the peculiarity of it functioning. Monatshefte für Chemie - Chemical Monthly, 2019, vol. 150, pp. 499-509. https://doi.org/10.1007/s00706-019-2374-4
  21. Kornyshev A. A. Double-Layer in Ionic Liquids: Paradigm Change? J. Phys. Chem. B, 2007, vol. 111, pp. 5545-5557. https://doi.org/10.1021/jp067857o
  22. O’Hanlon S., McNultyD., Tian R., Coleman J., O’Dwyer C. High Charge and Discharge Rate Limitations in Ordered Macroporous Li-ion Battery Materials. Journal of The Electrochemical Society, 2020, vol. 167, article no. 140532. https://doi.org/10.1149/1945-7111/abc6cb
  23. Tian R., Park S.-H., King P. J., Cunningham G., Coelho J., Nicolosi V., Coleman J. N. Quantifying the factors limiting rate performance in battery electrodes. Nature Communications, 2019, vol. 10, article no. 1933.
  24. Triola M. F., ed. Elementary statistics technology update. 12th ed. Pearson, 2016. 840 p.
  25. Lvovich V. F. Distributed Impedance Models. In: Impedance Spectroscopy: Applications to Electrochemical and Dielectric Phenomena. John Wiley & Sons, Inc., 2012. 368 p. https://doi.org/10.1002/9781118164075
  26. Bobyl A., Nam S.-C., Song J.-H., Ivanishchev A., Ushakov A. Rate Capability of LiFePO4 Cathodes and the Shape Engineering of Their Anisotropic Crystallites. J. Electrochem. Sci. Technol., 2022, vol. 13, pp. 438-452. https://doi.org/10.33961/jecst.2022.00248
  27. Agafonov D., Bobyl A., Kamzin A., Nashchekin A., Ershenko E., Ushakov A., Kasatkin I., Levitskii V., Trenikhin M., Terukov E. Phase-Homogeneous LiFePO4 Powders with Crystallites Protected by Ferric-Graphite-Graphene Composite. Energies, 2023, vol. 16, no. 3, article no. 1551. https://doi.org/10.3390/en16031551

Supplementary files

Supplementary Files
Action
1. JATS XML

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).