Wheel Slip Control Algorithms for Improving Adhesion Performance of Electric Locomotives
Low-friction surface conditions significantly contribute to the reduction of the wheel/rail adhesion capability and the occurrence of wheel/rail slipping behaviors, which may lead to the degradation of mechanical properties and frictional wear damage at the wheel/rail interface. To mitigate these undesirable consequences, modern railway locomotives are equipped with on-board anti-slip control systems. In this study, three different anti-slip controller models, comprising the traditional re-adhesion anti-slip controller and PID-based anti-slip controller with fixed threshold and with optimal threshold, are established. The wheel/rail rolling-slipping performances subjected to different anti-slip control algorithms under changing wheel/rail friction conditions are compared based on train-track interaction simulations. The results demonstrate that the PID-based anti-slip controller with an optimal threshold achieves the maximum utilization of wheel/rail adhesion in the presence of low-friction conditions, outperforming the other two types of anti-slip controllers. Additionally, the adoption of an anti-slip controller with a lower control threshold can effectively reduce the tread wear of locomotive wheels. This research can provide a deep going understanding of optimization design of anti-slip controller on railway vehicles.
Authors
- Wanming Zhai (ORCID: https://orcid.org/0000-0002-9490-8217)
- Xinru Guo (ORCID: https://orcid.org/0000-0003-0334-2199)
- Liang Ling (ORCID: https://orcid.org/0000-0002-9574-4875)
- Yunfan Yang (ORCID: https://orcid.org/0000-0002-4307-5569)
Institutions
- Hong Kong Polytechnic University (HK)
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1109/tits.2025.3540607
- Citations
- 4
- Primary Topic
- Railway Engineering and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 2.85
Funders
- National Natural Science Foundation of China