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Experimental validation of a physically based mathematical model of wheel rolling motion on a solid supporting surface during rectilinear driving

https://doi.org/10.26518/2071-7296-2026-23-4-554-566

EDN: IZIUXI

Abstract

Introduction. High-fidelity simulation of off-road and amphibious vehicle motion relies on accurate wheel-surface interaction models. Although empirical and semi-empirical wheel rolling models (Pacejka, Guo and Lu) are dominant on solid surfaces, their input parameters are often ambiguous and do not have a direct physical interpretation, it is significantly limiting their predictive capabilities under complex, multi-mode driving conditions. Expensive and time-consuming specific sample testing is often required to obtain accurate characteristics.

Materials and Methods. This study presents an experimental validation of a physically based wheel dynamics model for non-deformable supporting surfaces. The mathematical description of the tire model with the use of brush analogy has been previously presented. A laboratory test bench was used as a validation environment to measure wheel kinematics and dynamics under a wide range of vertical loads in both driving and driven modes. Key parameters, including rolling radius, longitudinal slip, and torque have been measured directly on the rig. 

Results. Experimental data were used to validate the developed mathematical model, implemented in MATLAB/ Simulink. The model demonstrated match with experiment results in free-rolling mode, with a normalized root-meansquare error (RMS) below 1.2% for the covered distance. In driving mode, the error increased to approximately 10%, which, according to the analysis, is explained by the risen complexity of torque application and slip dynamics. 

Discussion and Conclusion. Unlike purely empirical models, all parameters of the developed model have a clear physical meaning and can be determined from a limited set of experiments. It makes this model a preferred choice for problems requiring the behavior prediction under various conditions.

About the Authors

M. M. Zhileykin
Scientific and Technical Center “Automated Technical Systems” Moscow Polytechnic University
Russian Federation

Zhileykin Mikhail Mikhailovich - Doctor of Technical Sciences, Professor, Senior Research Associate

38, B. Semyonovskaya St., Moscow, 107023

Scopus ID: 57201085829



O. A. Kozelkov
Scientific and Technical Center “Automated Technical Systems” Moscow Polytechnic University
Russian Federation

Kozelkov Oleg Aleksandrovich - Doctor of Technical Sciences, Professor, Head of Scientific and Technical Center “Automated Technical Systems”, Moscow Polytechnic University

38, B. Semyonovskaya St., Moscow, 107023



A. A. Kosenkov
Scientific and Technical Center “Automated Technical Systems” Moscow Polytechnic University
Russian Federation

Kosenkov Aleksey Aleksandrovich - postgraduate student, expert

38, B. Semyonovskaya St., Moscow, 107023



V. A. Neverov
Scientific and Technical Center “Automated Technical Systems” Moscow Polytechnic University
Russian Federation

Neverov Vsevolod Anatolyevich - Candidate of Technical Sciences, Research Associate

38, B. Semyonovskaya St., Moscow, 107023

Scopus ID: 57196422317



References

1. Yang S., Lu Y., Li S. An overview on vehicle dynamics //International Journal of Dynamics and Control. 2013. Т. 1. №. 4:385-395. https://doi.org/10.1007/s40435-013-0032-y EDN: ABOTXP

2. Zhang, T., Sun, Y., Wang, Y., Li, B., Tian, Y., & Wang, F. Y. A survey of vehicle dynamics modeling methods for autonomous racing: Theoretical models, physical/virtual platforms, and perspectives. IEEE Transactions on Intelligent Vehicles, 2024; 9(3), 4312-4334. https://doi.org/10.1109/tiv.2024.3351131 EDN: LBMDKQ

3. Rahnejat, H., Johns-Rahnejat, P. M., Dolatabadi, N., & Rahmani, R. Multi-body dynamics in vehicle engineering. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multibody Dynamics, 2024; 238(1), 3-25. https://doi.org/10.1177/1464419323118166

4. Pacejka, H. B. (Ed.). (2026). Tyre models for vehicle dynamics analysis. CRC Press.

5. Zhang, J., Liu, C., Zhao, J., Liu, H. Research on stability control of distributed drive vehicle with fourwheel steering. World Electric Vehicle Journal, 2024; 15(6), 228. https://doi.org/10.3390/wevj15060228 EDN: IUXMQK

6. Guo K.H., Lu D. The theoretical and experiment study on tire cornering properties under dynamic vertical load. Automot Eng,2005; 27(1), 89-92.

7. Guo, K. H. Vehicle handling dynamics theory. Jiangsu Science and Technology Press, 2011;Nanjing.

8. Xiong G.L., Guo, B., Chen, X. B. Co-simulation and virtual prototyping technology.2004; Beijing.

9. Blundell M., Harty D. The multibody systems approach to vehicle dynamics.2014; Butterworth-Heinemann.

10. Romano L., Aamo O.M., Aslund J., Frisk E. Stability analysis of linear single-track models with transient tyre dynamics. Vehicle System Dynamics, 2026; 64(3), 611-645. https://doi.org/10.1080/00423114.2024.2445163

11. Guo H., Yin Z., Cao D., Chen H., Lv C. A review of estimation for vehicle tire-road interactions toward automated driving. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018; 49(1), 14-30. https://doi.org/10.1109/TSMC.2018.2819500

12. Kobayashi T. Development of inverse magic formula for tire performance requirement analysis. Transactions of Society of Automotive Engineers of Japan, 2022; 53(5), 936-941.

13. Reshmin S.A. Qualitative Analysis of the Traction Force of a Rotating Drive Wheel with a Weightless Tire. Proc. Steklov Inst. Math. 315, 198–208 (2021). (in Russ.) https://doi.org/10.1134/S0081543821050151

14. Kireenkov A.A., Zhavoronok S.I., Nushtaev D.V. On tire models accounting for both deformed state and coupled dry friction in a contact spot // Computer Research and Modeling, 2021, vol. 13, no. 1, pp. 163-173. (in Russ.) https://doi.org/10.20537/2076-7633-2021-13-1-163-173. URL: http://crm.ics.org.ru/journal/article/3034/ (date accessed: 24.06.2026)

15. Fathi H., El-Sayegh Z., Ren J., El-Gindy M. Modeling and validation of a passenger car tire using finite element analysis. Vehicles,2024. 6(1), 384-402. https://doi.org/10.3390/vehicles6010016 EDN: RTTLIG

16. Behroozi M., Olatunbosun, O.A., Ding, W. Finite element analysis of aircraft tyre–Effect of model complexity on tyre performance characteristics. Materials & Design, 2012; 35, 810-819.

17. Fathi H., Khosravi M., El-Sayegh Z., El-Gindy, M. An advancement in truck-tire–road interaction using the finite element analysis. Mathematics, 2023; 11(11), 2462. https://doi.org/10.3390/math11112462 EDN: YFFSEU

18. Jagadeesh A., Premarathna W.A.A.S., Kumar A., Kasbergen C., Erkens S.M.J.G. Finite element modelling of jointed plain concrete pavements under rolling forklift tire. Engineering Structures, 2025; 328, 119705. https://doi.org/10.1016/j.eng-struct.2025.119705 EDN: XWLRMI

19. Ge Y., Yan Y., Yan X., Meng Z. Extending the tire dynamic model range of operating conditions based on finite element method. Advances in Mechanical Engineering, 2022; 14(3), 16878132221085454.

20. Yamashita H., Arnold A., Carrica P.M., Noack R.W., Martin J.E., Sugiyama H., Harwood C. Coupled multibody dynamics and computational fluid dynamics approach for amphibious vehicles in the surf zone. Ocean engineering, 2022; 257, 111607. https://doi.org/10.1016/j.oceaneng.2022.111607 EDN: OUBLAN

21. Zhileikin M.M., Padalki B.V. “A Mathematical Model of Rolling of an Elastic Wheel on Irregularities of a Non-Deformable Support Foundation.” News of Higher Educational Institutions. Mechanical Engineering 3 (672) (2016): 24–29. (in Russ.) EDN: VOJFZZ

22. Zhileikin M.M., Kozelkov O.A., Neverov V.A. Mathematical model of rolling on uneven support base of an elastic wheel based on a discrete set of contact elements. Gruzovik. 2025. No. 6. P. 8-16. (in Russ.) https://doi.org/10.36652/1684-1298-2025-6-8-16. EDN: BAVNVA.

23. Neil D. Bennett, Barry F.W. Croke, Giorgio Guariso, Joseph H.A. Guillaume, Serena H. Hamilton, Anthony J. Jakeman, Stefano Marsili-Libelli, Lachlan T.H. Newham, John P. Norton, Charles Perrin, Suzanne A. Pierce, Barbara Robson, Ralf Seppelt, Alexey A. Voinov, Brian D. Fath, Vazken Andreassian. Characterising performance of environmental models. Environmental modelling & software, 2013; 40, 1-20. https://doi.org/10.1016/j.envsoft.2012.09.011

24. Liu Z., Liu Y., Gao Q. In-plane flexible ring modeling and a nonlinear stiffness solution for heavyload radial tires. Mechanical Systems and Signal Processing, 2022; 171, 108956. https://doi.org/10.1016/j.ymssp.2022.108956 EDN: MBMMDO

25. Xia D., Liu Q., Lu D. Friction prediction and application to lateral or longitudinal slip force prediction. Machines, 2022; 10(9), 791. https://doi.org/10.3390/machines10090791 EDN: PENJSI

26. Junior A.D.S., Birkner C., Jazar R.N., Marzbani H. Coupled lateral and longitudinal controller for over-actuated vehicle in evasive maneuvering with sliding mode control strategy. IEEE Access, 2023; 11, 33792-33811. https://doi.org/10.1109/access.2023.3264277 EDN: GNPOKM


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For citations:


Zhileykin M.M., Kozelkov O.A., Kosenkov A.A., Neverov V.A. Experimental validation of a physically based mathematical model of wheel rolling motion on a solid supporting surface during rectilinear driving. The Russian Automobile and Highway Industry Journal. 2026;23(4):554-566. (In Russ.) https://doi.org/10.26518/2071-7296-2026-23-4-554-566. EDN: IZIUXI

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ISSN 2071-7296 (Print)
ISSN 2658-5626 (Online)