Year: 2025
Type: article
Abstract: This paper addresses the issue of wheelset slip in trains caused by low-adhesion track surfaces and proposes an active anti-slip tracking control strategy. Considering the wide operational range of trains and the complex adhesion conditions between wheels and rails, a comprehensive model of the train, incorporating adhesion effects, is developed and then transformed into a mathematical model with perturbations. To tackle the slip phenomenon on low-adhesion track surfaces, a robust adhesion observer with high dynamic accuracy is designed. Building on this, an active anti-slip strategy is proposed to ensure that the control command does not exceed the maximum traction force available from the track surface. To further enhance controller performance, higher-order sliding mode control is integrated with a saturation compensation law. Finally, a Hardware-in-the-Loop (HIL) platform is constructed using a Digital Signal Processor (DSP) controller and a Modular Test (MT) PXI real-time simulator. The simulator loads the adhesion model, while the DSP controller executes the designed anti-slip control algorithm. Experimental results demonstrate that the proposed controller effectively prevents wheelset slip under low-adhesion conditions and significantly reduces tracking errors along the target speed-displacement curve.
Source: Applied Sciences
DOI: 10.3390/app15073909
Authors: Song Wang, Buzou Zhang, Yixuan Wang, Shuai Cao
Institution: Southwest Jiaotong University
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G3616454161, G645962859
OpenAlex ID: W4409103450