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Wheel/rail adhesion research for mining locomotive and electric locomotive

The article describes the issue of determining the adhesion behavior in the “wheelrail” contact zone of the traction electric drive of mining and electric locomotives. The purpose of this article is researching the adhesion behavior in the wheel-rail contact zone. The article presents the requirements for the control system of the traction electric drive. Based on the requirements, the main task of the control system is determined. A typical structure of the control system is given and its decomposition by functions is presented: a traction drive control system and a traction force control system. A classification of traction force control systems according to control methods is presented. The control method for determining the behavior of adhesion in the wheel-rail contact zone is considered in detail. Equations are presented for calculating the adhesion torque and the adhesion coefficient, these equations are based on second-order differential equations describing the structure of the mechanical part of the traction drive. A definition is given for the observed adhesion torque and the observed adhesion coefficient. The mathematical modeling of the locomotive is presented. The results of mathematical modeling showed that the equations for calculating the observed adhesion torque and the observed adhesion coefficient give an error of less than 1%. A practical experiment was carried out directly on the object. The results of the practical experiment confirmed the theoretical methods for calculating the observed adhesion torque and the observed adhesion coefficient. Additionally, the presence of periodic noise in the signals of the observed adhesion torque and the observed adhesion coefficient was revealed, as a result of which the task for the next study was determined.

Keywords: mining locomotive, electric locomotive, traction power electric drive, adhesion, adhesion coefficient, wheel slip speed, adhesion torque, adhesion force.
For citation:

Kharisov I. R., Karyakin A. L. Wheel/rail adhesion research for mining locomotive and electric locomotive. MIAB. Mining Inf. Anal. Bull. 2024;(1-1):59—73. [In Russ]. DOI: 10.25 018/0236_1493_2024_011_0_59.

Acknowledgements:
Issue number: 1
Year: 2024
Page number: 59-73
ISBN: 0236-1493
UDK: 629.4.074:621.316.79:621.313.223.2:621.313.333
DOI: 10.25018/0236_1493_2024_011_0_59
Article receipt date: 15.05.2023
Date of review receipt: 04.09.2023
Date of the editorial board′s decision on the article′s publishing: 10.12.2023
About authors:

KharisovI. R.¹, Postgraduate Student, e-mail: nexuskharisa@gmail.com, https://orcid. org/0000-0001-5078-0533;
Karyakin A. L.¹, Dr. Sci. (Eng.), Professor, e-mail: karyakin.a@ursmu.ru, https://orcid. org/0000-0001-6196-3263.
¹ Ural State Mining University, Russia, 620144, Russia, Yekaterinburg, st. Kuibyshev, 30.

 

For contacts:

Kharisov I. R., e-mail: nexuskharisa@gmail.com.

Bibliography:

1. Samme G. V. Frictional interaction of wheel pairs of a locomotive with rails, Moscow, Marshrut Publ., 2005, 80 p. [In Russ].

2. Moaveni B., Fathabadi F. R., Molavi A. Supervisory predictive control for wheel slip prevention and tracking of desired speed profile in electric trains. ISA Transactions. 2020, vol. 101, pp. 102–115. DOI: 10.1016/j.isatra.2020.01.011.

3. Tavernini D., Metzler M., Gruber P., Sorniotti A. Explicit nonlinear model predictive control for electric vehicle traction control. IEEE Transactions on Control Systems Technology. 2019, vol. 27, no. 4, pp. 1438−1451. DOI: 10.1109/TCST.2018.2837097.

4. Makishima S., Kondo K., Shimoyama H., Sato D., Takahashi S., Koseki T. Wheel slip control technologies on Japanese railways. International Power Electronics Conference (IPEC-Himeji 2022ECCE Asia). 2022, pp. 692–697. DOI: 10.23919/IPEC-Himeji2022ECCE53331.2022.9807234.

5. Chernysheva T. A., Anikin V. V., Chernyshev I. A., Chernyshev A. Yu. Variable speed electric drive of centrifugal pump in oil lifting plants. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering. 2019, vol. 330, no. 12, pp. 168−178. [In Russ]. DOI: 10.18799/24131830/2019/12/2417.

6. Vasilyev B. Yu., Shpenst V. A., Kalashnikov O. V., Ulyanov G. N. Providing energy decoupling of electric drive and electric grids for industrial electrical installations. Journal of Mining Institute. 2018, vol. 329, pp. 41−49. [In Russ]. DOI: 10.25515/PMI.2018.1.41.

7. Chernishev A. Yu., Zhurikov S. A., Chernishev I. A. Electric drive of elevators for borehole geophysical survey complex. Bulletin of the Tomsk Polytechnic University. 2015, vol. 326, no. 3, pp. 63−69. [In Russ].

8. Tecle S. I., Zuizev A. M., Kostylev A. V. Improving sucker rod pump efficiency using frequency controlled induction motor. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering. 2022, vol. 333, no. 11, pp. 140–148. [In Russ]. DOI: 10.18799/24131830/2022/11/3955.

9. Sadr S., Kaburi D. A., Namazi M., Shiri A., Moghadam D. E. Modeling of wheel and rail slip and demonstration of the benefit of maximum adhesion control in train propulsion system. IEEE 23rd International Symposium on Industrial Electronics (ISIE). 2014, pp. 847–852. DOI: 10.1109/ISIE.2014.6864722.

10. Sung G.-M., Chen C.-R., Tien M.-H., Tseng C.-L., Lee C.-Y., Yu C.-P. Predictive direct torque control ASIC of three-phase induction motor using speed-sensorless control and neural network proportional-integral-derivative controller. IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2022, pp. 1659–1664. DOI: 10.1109/ SMC53654.2022.9945473.

11. Hadla H., Santos F. Performance comparison of field-oriented control, direct torque control, and model-predictive control for SynRMs. Chinese Journal of Electrical Engineering. 2022, vol. 8, no. 1, pp. 24–37. DOI: 10.23919/CJEE.2022.000003.

12. Konokhov D. V., Fedyaeva G. A., Tarasov A. N., Smorudova T. V. Simulation of system of energy efficient double-area velocity control in asynchronous drive with moment direct control. Bulleten of Bryansk State Technical University. 2016, no. 1(49), pp.127–133. [In Russ]. DOI: 10.12737/18303.

13. Hahn J.-O., Rajamani R., Alexander L. Gps-based real-time identification of tire-road friction coefficient. IEEE Transactions on Control Systems Technology. 2002, vol. 10, no. 3, pp. 331–343. DOI: 10.1109/87.998016.

14. Fedyaeva G. A., Kobishchanov V. V., Matyushkov S. Yu., Tarasov A. N. Modeling of control system of traction and braking mainline freight locomotives in soft-ware systems Matlab and «Universal mechanism». Bulleten of Bryansk State Technical University. 2013, no. 3(39), pp. 147–151. [In Russ].

15. Hwang D. H., Kim M. S., Jeon J. W., Lee J. H., Park D. Y., Kim Y. J., Ryoo H. J., Kim J. S. Аnti-slip control system of Korean high-speed train. Computers in Railways VII. 2000, pp. 613–622. DOI: 10.2495/CR000591.

16. Diao L., Zhao L., Jin Z., Wang L., Sharkh S. M. Taking traction control to task: highadhesion-point tracking based on a disturbance observer in railway vehicles. IEEE Industrial Electronics Magazine. 2017, vol. 11, no. 1, pp. 51–62. DOI: 10.1109/MIE.2016.2644699.

17. Huang Z., Xu Z., Chen B., Zhang R., Chen Y., Peng Q. Sliding mode control for urban railway anti-slip system based on optimal slip ratio estimation with forgetting factor recursive least-squares. Proceedings of the 36th Chinese Control Conference. 2017, pp. 9502–9507. DOI: 10.23919/ChiCC.2017.8028873.

18. Ohishi K., Kadowaki S., Smizu Y., Sano T., Yaskawa S., Koseki T. Anti-slip readhesion control of electric commuter train based on disturbance observer considering bogie dynamics. IECON 2006−32nd Annual Conference. 2006, pp. 5270–5275. DOI: 10.1109/IECON.2006.347734.

19. Ohishi K. Realization of fine motion control based on disturbance observer. 10th IEEE International Workshop on Advanced Motion Control. 2008, pp. 1–8. DOI: 10.1109/ AMC.2008.4516032.

20. Sadr S., Kaburi D. A., Namazi M., Shiri A., Moghadam D. E. Modeling of wheel and rail slip and demonstration of the benefit of maximum adhesion control in train propulsion system. IEEE 23rd International Symposium on Industrial Electronics (ISIE). 2014, pp. 847–852. DOI: 10.1109/ISIE.2014.6864722.

21. Borisov S. V., Koltunova Е. А., Kladiev S. N. Traction asynchronous electric drive of mine electric locomotive simulation model structure improvement. Journal of Mining Institute. 2021, vol. 247, p. 114–121. [In Russ]. DOI: 10.31897/PMI.2021.1.12.

22. Pichlik P. Locomotive Wheel slip controller based on power dissipation in wheel-rail contact. International Conference on Electrical Drives & Power Electronics (EDPE). 2019, pp. 211–216. DOI: 10.1109/EDPE.2019.8883900.

23. Can K., Jingchun H., Wenqi D., Xiaokang W. Adhesion control method based on optimal slip velocity searching and tracking. 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI). 2019, pp. 1200–1207. DOI: 10.1109/ ICEMI46757.2019.9101798.

24. Pichlík P., Bauer J. Analysis of the locomotive wheel slip controller operation during low velocity. IEEE Transactions on Intelligent Transportation Systems. 2021, vol. 22, no. 3, pp. 1543–1552. DOI: 10.1109/TITS.2020.2971832.

25. Kaplin A. Y., Stepanov M. G. Analysis of algorithm for complex processing of goniometric information in a moving object navigation system. Informatsionno upravliaiushchie sistemy (Information and control systems). 2016, no. 2, pp. 89–94. [In Russ]. DOI: 10.15217/issn1684−8853.2016.2.89.

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