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To integrate electromobility into modern urban mobility, it is necessary to assess the usability and potential of hybrid, plug-in and battery electric vehicles (BEVs) to meet urban mobility requirements, as well as their impact on electric distribution grid. Despite the progress that has been made in this field over the last decade, many technical issues still need to be addressed. This paper presents the results of a large-scale analysis of real-world driving data from activity databases, anonymously collected by Global Positioning System devices installed on conventional fuel vehicles. These data were processed to derive whether different types of BEVs and recharging strategies can meet urban mobility needs. The impact of the electric energy demand on the grid from a partially electrified urban fleet has also been addressed. The study involves approximately 28,000 vehicles, 4.5 million trips and 36 million kilometres in the Italian provinces of Modena and Firenze, monitored over a one-month period (i.e. May 2011). The results can contribute to assess the future integration of the electromobility in urban environment, their impact on the electric energy demand profile as well as possible scenarios for future European transport policies.

a b s t r a c tThe large scale deployment of electric vehicles in urban environment will play a key-role over the next decades to reduce air-pollutants in densely populated areas, but it will also require the development of an adequate recharge infrastructure. The purpose of this paper is to demonstrate how driving patterns databases and data mining can be used to appropriately design this infrastructure. This application focuses on the Italian province of Firenze, involving about 12,000 conventional fuel vehicles monitored over one month, estimating a fleet share shift from conventional fuel vehicles to battery electric vehicles ranging from 10% to 57%, and a mileage share shift from 1.6% to 36.5%. The increase of electric energy demand from electric vehicles ranges from 0.7% to 18% of the total demand in the province, with a number of charging spots three-to-six times higher than the number of circulating electric vehicles. Additionally the results show that a Vehicle-to-Grid interaction strategy can contribute to reduce from 5% to 50% the average daily electric energy demand in specific locations. This paper provides a description of the developed model and focuses on the valuable potential of the proposed methodology to support future policies for designing alternative fuel infrastructure in urban areas.

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