‘Destination charging’ – in which drivers charge their battery electric vehicles (EVs) while parked at amenities such as supermarkets, shopping centres, gyms and cinemas – has the potential to accelerate EV uptake. This study presents a Monte Carlo-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 study, likely electrical demand profiles for EV destination charging at different amenities are presented. Use of the method is presented first for a generic characterisation of EV charging in the car parks of gyms, based on a sample of over 2000 gyms in around major UK cities, and second 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.

中文翻译：

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使用智能手机位置数据评估热门设施的电动汽车充电需求可能的时间变化

“目的地充电”是指驾驶员将电动汽车停放在超级市场，购物中心，体育馆和电影院等设施时为电动汽车充电，这可能会加速电动汽车的普及。这项研究提出了一种基于蒙特卡洛的方法，用于基于在Google Maps Popular Times功能中捕获的智能手机用户的匿名位置数据来表征这些位置的EV目的地充电。与大多数关于该主题的学术作品所基于的家庭调查和旅行调查不同，这些数据代表的是个人的实际活动，而不是他们如何回忆或透露他们。通过本研究中提出的车队EV充电方法，介绍了不同便利设施下EV目的地充电的可能用电需求情况。