英格兰电池电动汽车拥有量系统研究

Justin Yiu, Jacek Pawlak, Ahmadreza Faghih Imani, Aruna Sivakumar
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摘要

电池电动汽车(BEV)是英国道路交通去碳化议程的重要组成部分。虽然英国出台了各种政策,如购买补贴和车辆税减免,但到 2023 年 9 月,英国的 BEV 普及率仅为 2.5%。分析英国电动汽车(EV)拥有率的大多数研究要么基于陈述偏好调查数据,要么将插电式混合动力汽车纳入分析范围,因为英国 BEV 拥有率数据稀少;而基于家庭显性偏好(RP)数据的研究则非常有限。本文利用英格兰的 RP 家庭数据建立了一个 BEV 拥有率模型,以发现影响因素或验证文献中的研究结果,或两者兼而有之。具体而言,本文利用英国全国出行调查(NTS)的特殊许可证数据子集,估算了一系列二元对数模型,将 BEV 拥有率作为若干社会人口、地区和时间因素的函数,并讨论了相关的政策影响。本研究发现,家庭收入、拥有多辆汽车(由于续航里程焦虑)和在街道上过夜停车(由于公共充电基础设施不足)等影响因素与之前的研究结果一致。另一方面,有抵押贷款的家庭、地理属性(如人口密度)和家庭组成(如成人和儿童数量)是本研究中发现的新因素。我们还提出了英格兰各地区未来电动汽车保有量预测模型,该模型清楚地表明,要实现电动汽车保有量的广泛增长,就必须改善公共充电基础设施,尤其是在北部地区。
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Systematic Study of Battery Electric Vehicle Ownership in England
Battery electric vehicles (BEVs) form a big part of the UK’s agenda for decarbonizing road transport. Although there have been various policies such as purchase grants and vehicle tax exemptions, the BEV penetration rate in the UK was only 2.5% in September 2023. Most research analyzing electric vehicle (EV) ownership in the UK is either based on stated preference survey data or includes plug-in hybrid vehicles in the analysis because of the sparsity of BEV ownership data; there is limited research based on household revealed preference (RP) data. This paper develops a BEV ownership model using RP household-level data from England to discover influential factors, to validate the findings in the literature, or both. Specifically, this paper uses the subset of the UK National Travel Survey (NTS) special license data to estimate a series of binary logit models of BEV ownership as a function of several sociodemographic, regional, and temporal factors, and discusses the related policy implications. Household income, multivehicle ownership (resulting from range anxiety), and overnight parking on street (resulting from insufficient public charging infrastructure) are influential factors found in this study that align with previous studies. On the other hand, households with a mortgage loan, geographical attributes (such as population density), and household composition (e.g., number of adults and children) are new factors identified in this study. We also present a future BEV ownership prediction model for regions of England which clearly suggests that improving public charging infrastructure, especially in the north, is required to achieve widespread growth in BEV ownership.
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