Skip to main content

Preliminary Implementation of Model-Based Algorithms for Truck Tire Characterizations from Outdoor Sessions

  • Conference paper
  • First Online:
Proceedings of XXIV AIMETA Conference 2019 (AIMETA 2019)

Abstract

The tire behavior optimization is crucial for the definition of the best setup of the whole vehicle; in fact, its interface with the ground is constituted by the sum of small surfaces in which tire-road interaction forces are exchanged. The fundamental role that in the last years tires have played in automotive industry and the growing need to reproduce with a high level of detail the phenomena concerning with vehicle dynamics have given a strong impulse to the research in the field of vehicle systems and modelling.

This paper focuses on the possibility to modify and extend the use of a pre-existing tool for tires’ forces estimation to the heavy vehicles field, such as Truck, Bus, Agro and OTR. The tool developed by the UniNa Vehicle Dynamics research group, represents a customization of TRICK Tool software, able to predict truck tires behavior, based on standard sensors and signals acquired from the vehicle CAN bus. This enables to study vehicle dynamics and tires characteristics using the truck as a moving lab.

The final processing tool, named TRICK4TRUCK, returns a sort of “virtual telemetry” that includes forces and slips, evaluated on the basis of equilibrium and kinematics equations, useful to provide tire-road interaction characteristics and to predict and simulate the real tire behavior. This tool can be an important instrument for the interaction curves identification based on models such as the Pacejka’s MF one.

After some brief notes about the basics of heavy vehicle dynamics and tire-road interaction, the developed tool and procedures are presented, highlighting their features and their critical issues, describing the path followed for the realization and discussing results and possible application field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Guiggiani, M.: The Science of Vehicle Dynamics, 2nd edn. Springer, Heidelberg (2018)

    Google Scholar 

  2. Gent, A.N., Walter, J.D.: The Pneumatic Tire. Mechanical Engineering Faculty Research (2006)

    Google Scholar 

  3. Bosch, H.R.B., Hamersma, H.A., Els, P.S.: Parameterisation, validation and implementation of an all-terrain SUV FTire tyre model. J. Terramechanics 67, 11–23 (2016)

    Google Scholar 

  4. Vallim, M.B., Dos Santos, J.M.C., Costa, A.L.A.: Motorcycle analytical modeling including tire-wheel nonuniformities for ride comfort analysis. Tire Sci. Technol. 45, 101–120 (2017)

    Google Scholar 

  5. Xiong, Y., Tuononen, A.: Rolling deformation of truck tires: measurement and analysis using a tire sensing approach. J. Terrramech. 61, 33–42 (2015)

    Google Scholar 

  6. Farroni, F.: T.R.I.C.K.-tire/road interaction characterization & knowledge - a tool for the evaluation of tire and vehicle performances in outdoor test sessions. Mech. Syst. Signal Process. 72–73, 808–831 (2016)

    Google Scholar 

  7. Cabrera, J.A., Ortíz, A., Simón, A., García, F., Pérez La Blanca, A.: A versatile flat track tire testing machine. Veh. Syst. Dyn. 40(4), 271–284 (2003)

    Google Scholar 

  8. Farroni, F., Russo, M., Sakhnevych, A., Timpone, F.: TRT EVO: advances in real-time thermodynamic tire modeling for vehicle dynamics simulations. J. Automob. Eng. 233(1), 121–135 (2019)

    Google Scholar 

  9. Capone, G., Giordano, D., Russo, M., Terzo, M., Timpone, F.: Ph.An.Ty. MHA: a physical analytical tyre model for handling analysis - the normal interaction. Veh. Syst. Dyn.: Int. J. Veh. Mech. Mobil. 47(1), 15–27 (2009)

    Google Scholar 

  10. Gipser, M.: FTire - the tire simulation model for all applications related to vehicle dynamics. Veh. Syst. Dyn.: Int. J. Veh. Mech. Mobil. 45(1), 139–151 (2007)

    Google Scholar 

  11. Pacejka, H.B.: Tyre and Vehicle Dynamics, 2nd edn. Butterworth-Heinemann (2006)

    Google Scholar 

  12. Alagappan, A.V., Rao, K.V.N., Kumar, R.: A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations. Veh. Syst. Dyn.: Int. J. Veh. Mech. Mobil. 53(2), 154–178 (2014)

    Google Scholar 

  13. Farroni, F., Sakhnevych, A., Timpone, F.: Physical modelling of tire wear for the analysis of the influence of thermal and frictional effects on vehicle performance. J. Mater.: Des. Appl. 231(1–2), 151–161 (2017)

    Google Scholar 

  14. Rubinstein, D., Shmulevich, I., Frenckel, N.: Use of explicit finite-element formulation to predict the rolling radius and slip of an agricultural tire during travel over loose soil. J. Terramechanics 80, 1–9 (2018)

    Google Scholar 

  15. Markovitz, M., Wool, A.: Field classification, modeling and anomaly detection in unknown CAN bus networks. Veh. Communictions 1, 1–10 (2017)

    Google Scholar 

  16. Holdmann, P., Köhn, P., Möller, B., Willems, R.: Suspension kinematics and compliance - measuring and simulation. SAE Technical Paper Series, 724 (2018)

    Google Scholar 

  17. Joa, E., Yi, K., Hyun, Y.: Estimation of the tire slip angle under various road conditions without tire–road information for vehicle stability control. Control Eng. Pract. 86, 129–143 (2019)

    Google Scholar 

  18. Ružinskas, A., Sivilevicius, H.: Magic formula tyre model application for a tyre-ice interaction. Procedia Eng. 187, 335–341 (2017)

    Google Scholar 

  19. Farroni, F., Sakhnevych, A., Timpone, F.: A three-dimensional multibody tire model for research comfort and handling analysis as a structural framework for a multi-physical integrated system. J. Automob. Eng. 233(1), 136–146 (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrea Sammartino .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Farroni, F. et al. (2020). Preliminary Implementation of Model-Based Algorithms for Truck Tire Characterizations from Outdoor Sessions. In: Carcaterra, A., Paolone, A., Graziani, G. (eds) Proceedings of XXIV AIMETA Conference 2019. AIMETA 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-41057-5_84

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-41057-5_84

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41056-8

  • Online ISBN: 978-3-030-41057-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics