Study of degradation of accumulators as part of the traction plant of quarry dump trucks

The paper presents the results of tests of lithium-iron-phosphate (LFP) cells, the purpose of which is to obtain an aging model of a traction battery (TAB) as part of the drive of an electric mining dump truck. The trend of modernization of vehicles used in mining is considered, taking into account the introduction of electrochemical energy storage devices into the traction unit. The analysis of current loads arising during work in a quarry is carried out. Based on the data obtained, an experimental matrix was formed, which includes degradation factors: currents in charge and discharge modes, as well as the frequency of mode changes characterized by the duration of time under traction. A series of tests was carried out on a specialized stand that forms the necessary current form, as well as supports simultaneous testing of up to 30 cells. For all experiments, the current currents, voltage and temperature of the cell were recorded. Based on the test results, cell degradation curves for various load modes are constructed. It is revealed that the cells loaded with high traction currents, braking and the duration of the traction mode are subject to the greatest wear, while the least is the long–term effect of a low traction current with a low braking current. The obtained results can be applied for a more accurate prediction of the degree of degradation of the TAB, as well as optimization of the algorithms of the battery management system.

Dedov S. I., Shtang A. A., Abramov E. Yu. Study of degradation of accumulators as part of the traction plant of quarry dump trucks. MIAB. Mining Inf. Anal. Bull. 2022;(122):102—114. [In Russ]. DOI: 10.25018/0236_1493_2022_122_0_102.

The study was carried out with the financial support of the RFBR and the State Research Institute of China within the framework of the scientific project No. 20-5853055 — «Study of the influence of forced and heavy cyclic charge and discharge modes on the physicochemical characteristics of functional materials and the life of lithium batteries».

DedovS. I.¹, assistant, e-mail: dedov@corp.nstu.ru, ORCID ID: 0000-0003-4750-3927;
Shtang A. A.¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: shtang@corp.nstu.ru, ORCID ID: 0000-0001-9772-1784;
Abramov E. Yu.¹, assistant, e-mail: e.abramov@corp.nstu.ru, ORCID ID: 0000-0002-5013-3288;
¹ Novosibirsk State Technical University,630073, Novosibirsk, Russia.

Dedov S. I., e-mail: dedov@corp.nstu.ru.

1. Stepanenko V. P. K Resource-saving promotion at isolated generating plants in the Republic of Sakha (Yakutia). MIAB. Mining Inf. Anal. Bull. 2018. No. 6, pp. 62–68. [In Russ]. DOI: 10.25018/0236-1493-2018-6-0−62−68.

2. Beklemishev A. M. Studies of the impact of power losses in threephase asynchronous motors on the cost of electricity in the construction of exploration wells. MIAB. Mining Inf. Anal. Bull. 2018, no. S53, pp. 20–30. [In Russ]. DOI: 10.25018/0236-1493-2018-1253-20-30.

3. Dubaniewicz T. H., Zlochower I., Barone T., Thomas R., Yuan L. Thermal Runaway Pressures of Iron Phosphate Lithium-Ion Cells as a Function of Free Space Within Sealed Enclosures. Mining, Metallurgy & Exploration. 2020, no. 38(1), pp. 539–547. DOI: 10.1007/ s42461-020-00349-9.

4. Shurov N. I., Dedov S. I., Shtang A. A. Determination of the combined power source parameters in a hybrid small class share taxi based on modelling energy consumption process. Journal of Physics: Conference Series. 2020, vol. 1661, p. 8. DOI: 10.1088/1742− 6596/1661/1/012193.

5. Feng Y., Dong Z., Yang J., Cheng, R. Performance modeling and cost-benefit analysis of hybrid electric mining trucks. 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA). 2016, pp. 1–6. DOI: 10.1109/ mesa.2016.7587102.

6. Zhou M., Gao Z., Zhang H. Research on regenerative braking control strategy of hybrid electric vehicle. Proceedings of 2011 6th International Forum on Strategic Technology. 2011. DOI: 10.1109/ifost.2011.6021027.

7. Zhang W., Yang J., Zhang W., & Ma F. Research on Regenerative Braking of Pure Electric Mining Dump Truck. World Electric Vehicle Journal. 2019, vol. 10, no. 2, p. 39. DOI: 10.3390/wevj10020039.

8. De Hoog, J., Timmermans, J.-M., Ioan-Stroe D., Swierczynski M., Jaguemont J., Goutam S., Van Den Bossche P. Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation. Applied Energy. 2017, vol. 200, pp. 47–61. DOI: 10.1016/j.apenergy.2017.05.018.

9. Petit M., Prada E., Sauvant-Moynot V. Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime. Applied Energy. 2016, vol. 172, pp. 398–407. DOI: https://doi.org/10.1016/j. apenergy.2016.03.119.

10. Schimpe M., von Kuepach M. E., Naumann M., Hesse H. C., Smith K., Jossen A. Comprehensive Modeling of Temperature-Dependent Degradation Mechanisms in Lithium Iron Phosphate Batteries. Journal of the Electrochemical Society. 2018, vol. 165, no. 2, pp. A181–A193. DOI: 10.1149/2.1181714jes.

11. Reniers J. M., Mulder G., Ober-Blöbaum S., Howey D. A. Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modeling. Journal of Power Sources. 2018, vol. 379, pp. 91–102. DOI: 10.1016/j. jpowsour.2018.01.004.

12. Smith K., Saxon A., Keyser M., Lundstrom B., Ziwei C., Roc, A. Life prediction model for grid-connected Li-ion battery energy storage system. 2017 American Control Conference (ACC). 2017. DOI: 10.23919/acc.2017.7963578.

13. Barré A., Deguilhem B., Grolleau S., Gérard M., Suard F., Riu D. A review on lithiumion battery ageing mechanisms and estimations for automotive applications. Journal of Power Sources. 2013, vol. 241, pp. 680–689. DOI: https://doi.org/10.1016/j.jpowsour.2013.05.040.

14. Su C., Chen H. J. A review on prognostics approaches for remaining useful life of lithium-ion battery. IOP Conference Series: Earth and Environmental Science. 2017, vol. 93,012040. DOI: https://doi.org/10.1088/1755−1315/93/1/012040.

15. Goebel K., Saha B., Saxena A., Celaya J., Christophersen J. Prognostics in Battery Health Management. IEEE Instrumentation & Measurement Magazine. 2008, vol. 11, no. 4, pp. 33–40. DOI: https://doi.org/10.1109/mim.2008.4579269.

16. Hussein A. A. Capacity Fade Estimation in Electric Vehicle Li-Ion Batteries Using Artificial Neural Networks. IEEE Transactions on Industry Applications. 2015, vol. 51, no. 3, pp. 2321–2330. DOI: https://doi.org/10.1109/tia.2014.2365152.

17. Nuhic A., Terzimehic T., Soczka-Guth T., Buchholz M., Dietmayer K., Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data driven methods. Journal of Power Sources. 2013, no. 239, pp. 680–688. DOI: 10.1016/j. jpowsour.2012.11.146.

18. Zhang J., & Lee J. A review on prognostics and health monitoring of Li-ion battery. Journal of Power Sources. 2011, no. 196(15), 6007−14. DOI: 10.1016/j. jpowsour.2011.03.101.

19. Spotnitz R. Simulation of capacity fade in lithium-ion batteries. Journal of Power Sources. 2003, vol. 113, no. 1, pp. 72–80. DOI: 10.1016/s0378−7753(02)00490−1.

20. Zhou W. Effects of external mechanical loading on stress generation during lithiation in Li-ion battery electrodes. Electrochimica Acta. 2015, vol. 185, pp. 28–33. DOI: 10.1016/j. electacta.2015.10.097.

21. Sсhurov N. I., Shtang A. A., Dedov S. I., Xiaogang W. Analiz vlijanija rezhimov dvizhenija jelektromobilej na process starenija tjagovyh akkumuljatorov na osnove cikla WLTC. Journal of Siberian Federal University. Engineering & Technologies. 2020, pp. 977–990. [In Russ]. DOI: https://doi.org/10.17516/1999−494x-0279.

22. Abramov E. Y., Dedov S. I. Laboratory facility development for studying the heavy charge and discharge modes effect on the degradation of lithium-ion batteries. Journal of Physics: Conference Series. 2021, vol. 2032, no. 1,012092. — DOI: 10.1088/1742−6596/2 032/1/012092.