Evaluating the likely temporal variation in electric vehicle charging demand at popular amenities using smartphone locational data

Dixon, James and Elders, Ian and Bell, Keith (2020) Evaluating the likely temporal variation in electric vehicle charging demand at popular amenities using smartphone locational data. IET Intelligent Transport Systems. pp. 1-8. ISSN 1751-9578

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    Abstract

    'Destination charging' – the opportunity for drivers to charge their battery electric vehicles (EVs) while parked at amenities such as supermarkets, shopping centres, gyms and cinemas – has the potential to accelerate the rate of EV uptake. This paper presents a Monte Carlo (MC)-based method for the characterisation of EV destination charging at these locations based on smartphone users’ anonymised positional data captured in the Google Maps Popular Times feature. Unlike the use of household and travel surveys, from which most academic works on the subject are based, these data represent individuals’ actual movements rather than how they might recall or divulge them. Through a fleet EV charging approach proposed in this paper, likely electrical demand profiles for EV destination charging at different amenities are presented. Use of the method is presented firstly for a generic characterisation of EV charging in the car parks of gyms, based on a sample of over 2,000 gyms in around major UK cities, and secondly for a specific characterisation of hypothetical EV charging infrastructure installed at a large UK shopping centre to investigate the impact of varying the grid and converter capacity on the expected charging demand and level of service provision to the vehicles charging there.