Spatial and Temporal Analysis of Location and Usage of Public Electric Vehicle Charging Infrastructure in the United States

Q3 Social Sciences
L. Juhász, H. Hochmair
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引用次数: 0

Abstract

Switching to electric vehicles (EVs) has increased rapidly over recent years. This paradigm change provides an important pillar in the United States transport sector to reach sustainability goals. EVs rely on a network of charging locations to operate. This study analyses the spatial distribution, accessibility and usage patterns of the public EV infrastructure in the US. First, using a negative binomial regression model, the influence of socio-economic and other factors on the abundance of EV charging locations in a state is investigated. Second, analysis of the network’s use and of service areas generated around charging locations provides insight into the accessibility of these stations to populations living in urban and rural areas. Third, the study compares publicly available datasets on the EV charging infrastructure provided by different companies in the Miami urbanized area, and lastly, it analyses real-time data from the SemaConnect charging network. Results indicate increased access of residents to the EV charging infrastructure over the years. Economic activity, highway density and political preference were statistically associated with the number of charging stations. Charging behaviour was found to follow the patterns of a regular workday, indicating that EV owners rely primarily on the public infrastructure as opposed to charging their vehicles only at home.
美国公共电动汽车充电设施位置和使用的时空分析
近年来,转向电动汽车(ev)的人数迅速增加。这种模式的转变为美国运输部门实现可持续发展目标提供了重要的支柱。电动汽车依靠充电点网络运行。本研究分析了美国公共电动汽车基础设施的空间分布、可达性和使用模式。首先,采用负二项回归模型,研究了社会经济等因素对某一州电动汽车充电地点丰度的影响。其次,对充电站网络的使用情况和充电站周围服务区域的分析,可以深入了解这些充电站对城市和农村人口的可及性。第三,该研究比较了迈阿密城市化地区不同公司提供的电动汽车充电基础设施的公开数据集,最后,分析了SemaConnect充电网络的实时数据。结果表明,近年来,居民使用电动汽车充电基础设施的机会有所增加。经济活动、高速公路密度和政治偏好与充电站的数量在统计上相关。研究发现,充电行为与正常工作日的模式一致,这表明电动汽车车主主要依赖公共基础设施,而不是只在家里充电。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
GI_Forum
GI_Forum Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
23 weeks
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