IDEAS home Printed from https://ideas.repec.org/a/taf/tjrtxx/v2y2014i3p187-204.html
   My bibliography  Save this article

Adhesion estimation and its implementation for traction control of locomotives

Author

Listed:
  • Maksym Spiryagin
  • Colin Cole
  • Yan Quan Sun

Abstract

During locomotive movement in traction or braking modes, body weight distribution varies between bogies in different proportions depending on many factors. Each bogie and wheelset thus experiences a different traction coefficient. Locomotive manufacturers introduce traction control system strategies for achieving optimal adhesion allowing for axle weight transfers. Determination of adhesion coefficients to input into traction control systems is a complex and difficult issue. Optimising this task requires solving the problem of how to estimate rail friction condition. This paper describes the algorithm which allows estimation of friction parameters for hauling locomotives, and uses a low computational cost solution based on existing approaches and input signals from sensors. The verification of the algorithm is performed using a co-simulation process between the multibody software and Matlab/Simulink package. Simulation results obtained confirm that the proposed approach is an efficient and practical tool that can be recommended for implementation for locomotive traction control systems.

Suggested Citation

  • Maksym Spiryagin & Colin Cole & Yan Quan Sun, 2014. "Adhesion estimation and its implementation for traction control of locomotives," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 2(3), pages 187-204, August.
  • Handle: RePEc:taf:tjrtxx:v:2:y:2014:i:3:p:187-204
    DOI: 10.1080/23248378.2014.924842
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23248378.2014.924842
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23248378.2014.924842?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ye Tian & W.J.T. (Bill) Daniel & Sheng Liu & Paul A. Meehan, 2015. "Comparison of PI and fuzzy logic based sliding mode locomotive creep controls with change of rail-wheel contact conditions," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 3(1), pages 40-59, February.
    2. Maksym Spiryagin & Qing Wu & Kai Duan & Colin Cole & Yan Quan Sun & Ingemar Persson, 2017. "Implementation of a wheel–rail temperature model for locomotive traction studies," International Journal of Rail Transportation, Taylor & Francis Journals, vol. 5(1), pages 1-15, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tjrtxx:v:2:y:2014:i:3:p:187-204. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjrt20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.