• Developed a mechanistic model for interior pressure fluctuations in high-speed trains using non-ideal gas state equation and polytropic process, improving accuracy over ideal gas assumptions.
• The model accurately predicts pressure variations in both overall trends and local details, validated by root mean square error, coefficient of determination, peak-to-peak error, and pressure change rate.
• Demonstrated practical applicability across various train types and tunnel scenarios, providing a foundation for evaluating passenger pressure comfort in high-altitude regions.
• Enables real-time pressure comfort control strategies by balancing computational accuracy and efficiency, crucial for high-speed train operations.