Underutilised charging stations can be a bottleneck in the swift transition to electric mobility. This study is the first to research cooperative behaviour at public charging stations as a way to address improved usage of public charging stations. It does so by viewing public charging stations as a common-pool resource and explains cooperative behaviour from an evolutionary perspective. Current behaviour is analysed using a survey (313 useful responses) and an analysis of large dataset (2.1 million charging sessions) on the use of public charging infrastructure in Amsterdam, The Netherlands. In such a way it identifies the potential, drivers and possible obstacles that electric vehicle drivers experience when cooperating with other drivers to optimally make use of existing infrastructure. Results show that the intention to show direct reciprocal charging behaviour is high among the respondents, although this could be limited if the battery did not reach full or sufficient state-of-charge at the moment of the request. Intention to show direct reciprocal behaviour is mediated by kin and network effects.
MULTIFILE
In this study we developed models in order to predict the need for public charging points. These models give municipalities an insight into various environmental and consumer related factors that determine the need for public charging points for electric vehicles in the neighbourhood. These factors include, amongst others, the average gross monthly income of households in a certain neighbourhood and the overall number of cars in a certain neighbourhood. On the basis of the models it turns out, among other factors, that neighbourhoods with households with a relatively high average gross monthly income, and a relatively high number of cars, need a relatively large number of public charging points for electric vehicles.
Deployment and management of environmental infrastructures, such as charging infrastructure for Electric Vehicles (EV), is a challenging task. For policy makers, it is particularly difficult to estimate the capacity of current deployed public charging infrastructure for a given EV user population. While data analysis of charging data has shown added value for monitoring EV systems, it is not valid to linearly extrapolate charging infrastructure performance when increasing population size.We developed a data-driven agent-based model that can explore future scenarios to identify non-trivial dynamics that may be caused by EV user interaction, such as competition or collaboration, and that may affect performance metrics. We validated the model by comparing EV user activity patterns in time and space.We performed stress tests on the 4 largest cities the Netherlands to explore the capacity of the existing charging network. Our results demonstrate that (i) a non-linear relation exists between system utilization and inconvenience even at the base case; (ii) from 2.5x current population, the occupancy of non-habitual charging increases at the expense of habitual users, leading to an expected decline of occupancy for habitual users; and (iii) from a ratio of 0.6 non-habitual users to habitual users competition effects intensify. For the infrastructure to which the stress test is applied, a ratio of approximately 0.6 may indicate a maximum allowed ratio that balances performance with inconvenience. For policy makers, this implies that when they see diminishing marginal performance of KPIs in their monitoring reports, they should be aware of potential exponential increase of inconvenience for EV users.
298 woorden: In the upcoming years the whole concept of mobility will radically change. Decentralization of energy generation, urbanization, digitalization of processes, electrification of vehicles and shared mobility are only some trends which have a strong influence on future mobility. Furthermore, due to the shift towards renewable energy production, the public and the private sector are required to develop new infrastructures, new policies as well as new business models. There are countless opportunities for innovative business models emerging. Companies in this field – such as charging solution provider, project management or consulting companies that are part of this project, Heliox and Over Morgen respectively – are challenged with countless possibilities and increasing complexity. How to overcome this problem? Academic research proposes a promising approach, namely the use of business model patterns for business model innovation. In short, these business model patterns are descriptions of proven practical solutions to common business model challenges. An example for a general pattern would be the business model pattern “Consumables”. It describes how to lock in a customer into an ecosystem by using a subsidized basic product and complement it with overpriced consumables. This pattern works really well and has been used by many companies (e.g. Senseo, HP, or Gillette). To support the business model innovation process of Heliox and Over Morgen as well as companies in the electric mobility space in general, we propose to systematically consolidate and develop business model patterns for the electric mobility sector and to create a database. Electric mobility patterns could not only foster creativity in the business model innovation process but also enhance collaboration in teams. By having a classified list of business model pattern for electric mobility, practitioners are equipped which a heuristic tool to create, extend and revise business models for the future.
Economic and environmental sustainability are the two main drivers behind today’s logistics innovation. On the one hand, Industry 4.0 technologies are leading towards self-organizing logistics by enabling autonomous vehicles, which can significantly make logistics transport efficient. Detailed impact analysis of autonomous vehicles in repetitive, short-distance inter-hub transport in logistics hubs like XL Business park is presently being investigated in KIEM project STEERS. On the other hand, the zero-emission technology (such as battery electric) can complement the autonomous logistics transport in making such a logistics hub climate-neutral. In such a scenario, an automatic vehicle charging environment (i.e., charging infrastructure and energy supply) for autonomous electric vehicles will play a crucial role in maximizing the overall operational efficiency and sustainability by reducing the average idle time of both vehicles and charging infrastructure. The project INGENIOUS explores an innovative idea for presenting a sustainable and environment-friendly solution for meeting the energy demand and supply for autonomous electric vehicles in a logistics hub. It will develop and propose an intelligent charging environment for operating autonomous electric vehicles in XL Business park by considering its real-life settings and operational demand. The project combines the knowledge of education and research institutes (Hogeschool van Arnhem en Nijmegen and The University of Twente), industry partners (HyET Solar Netherlands BV, Distribute, Bolk Container Transport and Combi Terminal Twente), and public institutes (XL Business Park, Port of Twente, Regio Twente and Industriepark Kleefse Waard). The project results will form a sound basis for developing a real-life demonstrator in the XL Business park in the subsequent RAAK Pro SAVED project. A detailed case study for Industriepark Kleefse Waard will also be carried out to showcase the broader applicability of the INGENIOUS concept.
