Abstract

Electric vehicles require sufficient public charging infrastructure. This in turn necessitates detailed information on charging demand. In this paper we present a four-step approach to estimating public charging demand of electric vehicles. Previous methods are limited in their ability to provide differentiated results and adapt to future developments. Therefore, we account for user groups (private, carsharing, commercial), technical developments (vehicles, infrastructure), infrastructure availability, and carsharing development (operational area, business models, autonomous vehicles). Our approach also considers the interactions between these factors and allows for scenario analysis yielding the quantity and spatial distribution of public charging demand. We demonstrate our approach for Berlin, Germany. We find that the majority of public charging demand results from carsharing. This demand is concentrated in the city center, even when carsharing is available citywide. Public charging demand for commercial users is relatively low and located outside the city center. For private users, public charging demand shifts to the city center with an increasing market penetration of electric vehicles and technological advancements (increased range, charging speed). Public demand from private users increases dramatically when private infrastructure is absent. Finally, public charging demand shifts to the city center when private users do not have private infrastructure. Document type: Article

Abstract

Electric vehicles (EVs) have been discussed as a promising alternative to conventional cars and as a potential solution for mitigating environmental problems caused by road transport. This study analyzes the potential of the commercial use of EVs and the factors influencing user acceptance in commercial fleets. Empirical data on the daily use of EVs was collected by conducting online surveys, interviews, and workshops with the users. This paper summarizes the insights on potential advances and challenges related to the use of the vehicles in commercial fleets from a user perspective. The results suggest that EVs meet the mobility needs of different commercial users, bringing reputational and environmental related benefits for the companies. Main challenges for the deployment of EVs are related rather to the periphery of the EVs (e.g., infrastructure, market characteristics, and lack of experts in related service sectors as well as psychological barriers). Finally, policy and management recommendations in different fields drawn from a synthesis of the data collected within the study are introduced in this paper.

Abstract

The Amitran project provides a methodology for evaluating the effects of ICT measures in traffic and transport on energy efficiency and CO2 emissions. Last step of the methodology is the possibility to carry out a CBA or CEA of the ITS measures which are investigated. This paper presents the Amitran quick-scan CBA: the results will give the user an overview of the relevant effects in monetary terms that will give him or her a first indication to determine whether or not the ITS implementation is profitable for society.

Abstract

Information and communication technologies (ICT) applied to the transport sector are expected to play a significant role in reducing the carbon dioxide (CO2) emissions emitted by the transport sector. To foster the development and deployment of these technologies, known as “intelligent transport systems” (ITS), and direct the development into promising tracks their potential impact on CO2 emissions needs to be known in advance. Therefore a methodology for a reliable environmental evaluation is crucial, which is outline in this technical paper.

Abstract

Greenhouse gas emissions, in particular CO2 emissions, are a major environmental problem caused mainly by the transportation and the energy sectors. Electric vehicles have been proposed as a solution for mitigating greenhouse gas emissions in road transport. At the same time their potential emission reduction depends on the emissions from the generation of electricity used to charge the vehicles. This study analyzes indirect emissions of electric vehicles to examine optimization potential using real-world data. The results of the study suggest that charging during the daytime is associated with the usage of more electricity from renewable energy sources than charging in typical non-work hours. However, due to the highly violate character of renewable energy sources the differences are rather small. Also, CO2 emissions per kilometer driven depend on driving patterns influencing the energy demand of the vehicles. Accordingly, optimization potential using renewable energy-oriented time course of charging is found to be rather small with an average greenhouse gas emission reduction of 4%. Thus to achieve the potential of electric vehicles to solve environmental issues requires the optimization of driving and charging patterns as well as measures for reducing the carbon intensity in the electricity grid.

Abstract

Intelligent transport systems are accepted as an integral part of the transport system. They have high potential in reducing the carbon footprint of traffic while improving efficient and safe transport. The calculation of CO"inf"2"/inf" emissions arising from the transport sector incorporating the impact of ITS is a challenging task. A systematic assessment methodology will support developers, public authorities and investors in ITS solutions to make sound decisions based on comparable and transparent impact estimates. As the basis for such an assessment, the fragmentation of traffic in underlying processes is suggested. These processes can be divided into transport demand related processes and driver behaviour and vehicle related processes. Together these processes lead to traffic flow. Transport processes are influenced by various factors. Both the processes itself and the factors influencing them can be affected by ITS. A systematic analysis of the potential effects of ITS on all these levels is the prerequisite for choosing a suitable modelling approach to quantify the effects. It also ensures the transparency of the modelling process by elucidating the required model sensitivities. The details of such an approach and its context from user need to a standardised assessment methodology for ITS is described. © The Institution of Engineering and Technology 2015.