Abstract

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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