Model of interior pressure fluctuation in high-speed trains considering the dynamic characteristics of variable air volume systems

Abstract

High-speed trains experience significant interior pressure fluctuations when passing through tunnels, which can adversely affect passenger comfort and, in extreme cases, cause health issues. These fluctuations arise from rapid aerodynamic load changes and are challenging to predict accurately due to the limitations of existing models. To address this, this paper presents a stochastic modeling approach for interior pressure fluctuations, specifically tailored for the tunnel-passing scenario. The model is based on the continuity equation and the ideal gas law, integrated within a dynamic variable air volume system. It accounts for spatial airflow velocity variations, as well as the influence of airflow rate and the interior-exterior pressure difference on critical system components, including valve pressure reducing ratios, fan performance, and duct characteristics. By incorporating the effects of complex duct structures and fluctuating flow fields on gas mass transfer, the model achieves a 41.14% reduction in root mean square error and eliminates system time delays. This enhanced modeling framework provides a reliable tool for accurately predicting interior pressure dynamics during tunnel crossings, contributing to improved passenger comfort in train carriage.