Abstract:

Drawing from national statistical data and data from expressway routes, the authors analyze the data from spatial and temporal perspectives using multiple linear regression for data fitting to introduce new depreciation factors considering the growth of new energy vehicles, thereby aiming to further reduce energy consumption during tunnel operation. The following conclusions are presented: (1) The proportion of new energy vehicle ownership in China has been rapidly growing in recent years, while that in economically developed areas is generally high. The mixing rate of new energy vehicles in areas with a high proportion of new energy vehicle ownership is generally high and gradually decreases in areas with a low proportion. (2) A linear relationship exists between the mixing rate of new energy vehicles and the distance from the central city center, demonstrating positive and negative correlations with time and distance, respectively. (3) Considering the degree of new energy vehicle integration, a calculation formula for the reduction factor in highway tunnel operation ventilation design under the influence of new energy vehicle integration is provided, thereby offering a reduced basis for the required air volume calculation during tunnel design stages.

Key words: highway tunnel, operational ventilation, new energy vehicle, reduction factor, multiple linear regression