Abstract

Background: Since the second half of 2021, the prices of natural gas, coal and oil have soared, but at the same time, the Russia-Ukraine conflict is likely to become a catalyst for Europe and the world to accelerate the green and low-carbon transformation of energy, prompting countries to accelerate investment in renewable energy, improve energy security and achieve energy independence and the energy crisis started in Europe and eventually spread around the world. Under the new circumstances, the global green and low-carbon energy transition is imperative. The International Energy Agency released the "2023 Global Electric Vehicle Outlook" report, which showed that global electric vehicle sales will grow by 35% in 2023 from the previous year to 14 million units, increasing the total share of the overall vehicle market to 18%. Replacing traditional fossil fuels with low energy consumption and low pollution has become a trend in the automotive industry.

Objective: Therefore, this paper studies the travel distribution pattern of electric vehicles in Dalian city, which paves the way for the future development of the electric vehicle industry.

Method: First of all, this paper predicted the number of electric vehicles in Dalian in the next five years. Next, the gravity model and double-constraint gravity model were used to predict and analyze the travel generation, attraction and distribution of each traffic district. The gravity model is based on the concept of gravity in physics, this model can simulate the travel attraction between transportation communities. The dual constraint gravity model is an extension of the gravity model, taking into account the impact of factors other than distance on traffic distribution. For example, land type, land intensity utilization coefficient, etc. Finally, taking Shahekou District of Dalian city as an example, this paper made an empirical analysis of the travel distribution of electric vehicles in Shahekou District.

Results: This article fully considers the impact of land use types on residents' travel. Residential land is an important factor affecting travel volume, while public facility land is an important factor affecting attraction volume. For areas with high travel attractions, it is necessary to consider building more charging facilities around them to solve the problem of difficult charging. The distribution results showed that the amounts of travel in each traffic community were not much different, but their attraction volumes were greatly different.

Conclusion: After understanding the distribution of electric vehicle traffic in various residential areas, it is possible to arrange the planning of public charging facilities more reasonably. The research provides practical guidance for the transportation planning of electric vehicles in such urban cities as Dalian city.