CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 13018 > Article
Paper
14 February 2024 High speed train optimal adhesion control method based on a Cubature Kalman filter
Jieping Tang, Bolaji Balogun Alanamu, Song Wang, Jingchun Huang, Zhongcai Qiu
Author Affiliations +
Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130180I (2024) https://doi.org/10.1117/12.3023955
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
The safe running of high-speed trains depends on the adhesion between the wheel and the rail. This paper suggests an optimal adhesion control for high-speed trains based on the use of the CKF (Cubature Kalman Filter) in order to completely exploit the adhesion between the wheel and rail and attain the ideal adhesion condition. The method allows for the approximative estimate of train speed using CKF and is based on the wheel-rail dynamics and high-speed train adhesion model. The extremum search algorithm without steady-state oscillation is used to build an optimization adhesion control, which eventually directs the train to run as closely as feasible to the peak adhesion point, overcoming the effects of external interference and estimating errors on the system. Finally, MATLAB/Simulink is used to create a simulation model of the adhesion control for the traction transmission of the CRH2 high-speed train. With an average adhesion utilization rate over 95%, the simulation results demonstrate the viability of the suggested approach, ensuring the effective and secure running of high-speed trains.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Jieping Tang, Bolaji Balogun Alanamu, Song Wang, Jingchun Huang, and Zhongcai Qiu "High speed train optimal adhesion control method based on a Cubature Kalman filter", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130180I (14 February 2024); https://doi.org/10.1117/12.3023955
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 7 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Adhesion
Error analysis
Linear filtering
Algorithm development
Mathematical modeling
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top