Skip to main content

Challenges and Solutions for Integrating Simulation into a Transportation Device

  • Conference paper
  • First Online:
Intersections in Simulation and Gaming (ISAGA 2016, SimTecT 2016)

Abstract

The transportation area has seen an influx of condition monitoring devices in the last 5 years. A condition monitoring device typically has one or more sensors that it uses to measure the state of a component, analyze the measurement and provide a notification if the measurement is outside its normal operating tolerance. However, what happens if the component can’t be readily measured directly, like rolling contact, or when the device is operating in extreme environmental conditions? It can’t just be ignored. This is where simulation has a significant role to play. This paper explores the challenges in integrating a multi-body simulator into an on-board field device installed on a self-powered railway passenger vehicle. The device uses local sensors such as GPS to provide input to a simulator that calculates wheel-rail contact and L/V ratio. The L/V ratio is used as a derailment risk indictor in the rail sector. Wheel-rail contact is a good example of an area that can’t be directly measured, especially in the context of a tractive vehicle. The paper will also describe the use of simulation to verify and validate the device before installation in the field. The study findings show that, while on the cutting edge of available industrial computer technology, it is possible to integrate a multi-body simulator into a device suitable for installation in a powered vehicle. From the test perspective, it was found that simulation is useful as a tool for enabling realistic hardware integration testing before a device is installed into the field.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Knorr-Bremse: COMORAN: Condition Monitoring for Railway Applications (2010)

    Google Scholar 

  2. Ngigi, R.W., Pislaru, C., Ball, A., Gu, F.: Modern techniques for condition monitoring of railway vehicle dynamics. J. Phys: Conf. Ser. 364(1), 1–12 (2012)

    Google Scholar 

  3. Ward, C., Goodall, R.M., Dixon, R., Charles, G.: Condition monitoring of rail vehicle bogies. In: UKACC International Conference on Control, Coventry, UK (2010)

    Google Scholar 

  4. Fraser, C.S., Judd, A.M., Leahy, F.J.: The simplicity and complexity of straights and curves. In: The 5th International Symposium on Mobile Mapping Technology, Padua, Italy (2007)

    Google Scholar 

  5. Durazo-Cardenas, I., Starr, A., Tsourdos, A., Bevilacqua, M., Morineau, J.: Precise vehicle location as a fundamental parameter for intelligent self-aware rail-track maintenance systems. In: Proceedings of 3rd International Conference on Through-Life Engineering Services, pp. 220–223 (2014)

    Google Scholar 

  6. Xia, F., Cole, C., Wolfs, P.: Grey box-based inverse wagon model to predict wheel-rail contact forces from measured wagon body responses. Veh. Syst. Dyn. 46(Suppl), 469–479 (2008)

    Article  Google Scholar 

  7. Sun, Y., Cole, C., Spiryagin, M.: Monitoring vertical wheel-rail contact forces based on freight wagon inverse modelling. Adv. Mech. Eng. 7, 1–11 (2013)

    Google Scholar 

  8. Spiryagin, M., Sun, Y.Q., Cole, C., McSweeney, T., Simson, S., Persson, I.: Development of a real-time bogie test rig model based on railway specialised multibody software. Veh. Syst. Dyn. 51, 236–250 (2013)

    Article  Google Scholar 

  9. Spiryagin, M., Ahmad, S.S.N., Cole, C., Sun, Y.Q., McSweeney, T.: Wagon multibody model and its real-time application. In: Flores, P., Viadero, F. (eds.) New Trends in Mechanism and Machine Science. Mechanisms and Machine Science, vol. 24. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-09411-3_56

    Google Scholar 

  10. Gensys.1506 Reference Manual: User’s Manual for Program CALC. http://www.gensys.se

  11. Spiryagin, M., Cole, C., Sun, Y.Q., McClanachan, M., Spiryagin, V., McSweeney, T.: Design and Simulation of Rail Vehicles. Ground Vehicle Engineering Series. CRC Press, Boca Raton (2014)

    Book  Google Scholar 

  12. Global Positioning System Standard Positioning Service Performance Standard, Table 3.4-1 (2008)

    Google Scholar 

  13. Global Positioning System Precise Positioning Service Performance Standard, Table 3.4-1 (2007)

    Google Scholar 

  14. AS7509.3, Railway Rollingstock – Dynamic Behaviour – Part 3 – Passenger. 6.5.3 1 (b) (2009)

    Google Scholar 

  15. Ernest, P., Mazl, R., Preucil, L.: Train locator using inertial sensors and odometer. In: 2004 IEEE Intelligent Vehicles Symposium, Parma, Italy, pp. 860–865 (2004)

    Google Scholar 

  16. Hu, C., Chen, W., Chen, Y., Liu, D.: Adaptive Kalman filtering for vehicle navigation. J. Glob. Position. Syst. 2(1), 42–47 (2003)

    Article  Google Scholar 

  17. Xia, F., Cole, C., Wolfs, P.: An inverse railway wagon model and its applications. Veh. Syst. Dyn. 45, 583–605 (2007)

    Article  Google Scholar 

  18. Ward, C.P., Goodall, R.M., Dixon, R.: Creep force estimation at the wheel-rail interface. In: Proceedings of the 22nd Symposium on Dynamics of Vehicles on Roads and Tracks, Manchester, UK (2011)

    Google Scholar 

  19. Hussain I., Mei, T.X.: Identification of the wheel-rail contact condition for traction and braking control. In: Proceedings of the 22nd Symposium on Dynamics of Vehicles on Roads and Tracks, Manchester, UK (2011)

    Google Scholar 

  20. Petrov, V., Berg, M., Persson, I.: Estimation of wheel-rail friction for vehicle certification. Veh. Syst. Dyn. 52, 1099–1114 (2014)

    Article  Google Scholar 

  21. Spiryagin, M., Cole, C., Sun, Y.: Adhesion estimation and its implementation for traction control of locomotives. Int. J. Rail Transp. 1, 187–204 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the support of the Centre for Railway Engineering, Central Queensland University. The authors also acknowledge AB DEsolver for use of the GENSYS software in vehicle dynamics simulation for this study.

Icons made by Freepik from www.flaticon.com are licensed by Creative Commons BY 3.0 (http://creativecommons.org/licenses/by/3.0/).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chris Bosomworth .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bosomworth, C., Spiryagin, M., Cole, C., Alahakoon, S., Hayman, M. (2018). Challenges and Solutions for Integrating Simulation into a Transportation Device. In: Naweed, A., Wardaszko, M., Leigh, E., Meijer, S. (eds) Intersections in Simulation and Gaming. ISAGA SimTecT 2016 2016. Lecture Notes in Computer Science(), vol 10711. Springer, Cham. https://doi.org/10.1007/978-3-319-78795-4_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-78795-4_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78794-7

  • Online ISBN: 978-3-319-78795-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics