Braking process identification of high-speed trains for automatic train stop control.

Area of Science:

• Engineering
• Control Systems
• Transportation Systems

Background:

• Automatic Train Stop Control (ATSC) is crucial for Automatic Train Operation (ATO) systems.
• Accurate braking models are essential for enhancing ATSC strategies.
• Existing models may not fully capture the complexities of high-speed train braking.

Purpose of the Study:

• To develop an accurate braking process model for high-speed trains.
• To propose a novel identification method for the train braking system.
• To validate the model and identification technique using experimental data.

Main Methods:

• Formulating the high-speed train braking process as a single-point time delay model.
• Applying a Picard iteration-based identification method to the time delay system.
• Utilizing principles of ordinary differential equations for parameter identification.

Main Results:

• A straightforward and effective method for identifying train braking process parameters was developed.
• The proposed single-point time delay model accurately represents the braking dynamics.
• Experimental data confirmed the effectiveness of the developed model and identification method.

Conclusions:

• The developed braking model and Picard iteration-based identification method enhance the precision of ATSC.
• This approach offers a practical solution for improving high-speed train control strategies.
• The findings have significant implications for railway safety and efficiency.