Charging an electric vehicle needs to be as simple as possible for the user. He needs to park his car, plug his vehicle and identify to start charging. There is no need to understand the technology and protocols needed to reach this simple task.For the students and researchers of the Amsterdam University of Applied Science (AUAS / HvA), there is a need to understand as deep as possible all the techniques involved in this technology.The purpose of this document is to give to the reader the information he needs to understand how an electric car can be charged and how he can use these knowledges to analyses and interpret data.
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Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
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Residential public charging points are shared by multiple electric vehicle drivers, often neighbours. Therefore, charging behaviour is embedded in a social context. Behaviours that affect, or are influenced by, other publiccharging point users have been sparsely studied and lack an overarching and comprehensive definition. Consequently, very few measures are applied in practice to influence charging behaviour. We aim to classify and define the social dimension of charging behaviour from a social-psychological perspective and, using a behaviour change framework, identify and analyse the measures to influence this behaviour. We interviewed 15 experts onresidential public charging infrastructure in the Netherlands. We identified 17 charging behaviours rooted in interpersonal interactions between individuals and interactions between individuals and technology. These behaviours can be categorised into prosocial and antisocial charging behaviours. Prosocial charging behaviour provides or enhances the opportunity for other users to charge their vehicle at the public charging point, for instance by charging only when necessary. Antisocial charging behaviour prevents or diminishes this opportunity, for instance by occupying the charging point after charging, intentionally or unintentionally. We thenidentified 23 measures to influence antisocial and prosocial charging behaviours. These measures can influence behaviour through human–technology interaction, such as providing charging etiquettes to new electric vehicle drivers or charging idle fees, and interpersonal interaction, such as social pressure from other charging point users or facilitating social interactions to exchange requests. Our approach advocates for more attention to the social dimension of charging behaviour.
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Electric vehicles have penetrated the Dutch market, which increases the potential for decreased local emissions, the use and storage of sustainable energy, and the roll-out and use of electric car-sharing business models. This development also raises new potential issues such as increased electricity demand, a lack of social acceptance, and infrastructural challenges in the built environment. Relevant stakeholders, such as policymakers and service providers, need to align their values and prioritize these aspects. Our study investigates the prioritization of 11 Dutch decision-makers in the field of public electric vehicle charging. These decision-makers prioritized different indicators related to measurements (e.g., EV adoption rates or charge point profitability), organization (such as fast- or smart-charging), and developments (e.g., the development of mobility-service markets) using the best-worst method. The indicators within these categories were prioritized for three different scenario's in time. The results reveal that priorities will shift from EV adoption and roll-out of infrastructure to managing peak demand, using more sustainable charging techniques (such as V2G), and using sustainable energy towards 2030. Technological advancements and autonomous charging techniques will become more relevant in a later time period, around 2040. Environmental indicators (e.g., local emissions) were consistently valued low, whereas mobility indicators were valued differently across participants, indicating a lack of consensus. Smart charging was consistently valued higher than other charging techniques, independent of time period. The results also revealed that there are some distinct differences between the priorities of policymakers and service providers. Having a systematic overview of what aspects matter supports the policy discussion around EVs in the built environment.
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Electrification of mobility exceeds personal transport to increasingly focus on particular segments such as city logistics and taxis. These commercial mobility segments have different motives to purchase a full electric vehicle and require a particular approach to incentivize and facilitate the transition towards electric mobility. A case where a municipality was successful in stimulating the transition to electric mobility is the taxi sector in the city of Amsterdam. Using results from a survey study (n = 300), this paper analyses the differences in characteristics between taxi drivers that either have or do not have interest in purchasing a full electric taxi vehicle. Results show a low intention across the sample to adopt a full electric vehicle and no statistically significant differences in demographics between the two groups. Differences were found between the level of acceptability of the covenant, the rated attractiveness of the incentives, the ratings of full electric vehicle attributes and the consultation of objective and social information sources. These results can be used by policy makers to develop new incentives that target specific topics currently influencing the interest in a full electric taxi vehicle.
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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.
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Recent studies show that charging stations are operated in an inefficient way. Due to the fact that electric vehicle (EV) drivers charge while they park, they tend to keep the charging station occupied while not charging. This prevents others from having access. This study is the first to investigate the effect of a pricing strategy to increase the efficient use of electric vehicle charging stations. We used a stated preference survey among EV drivers to investigate the effect of a time-based fee to reduce idle time at a charging station. We tested the effect of such a fee under different scenarios and we modelled the heterogeneity among respondents using a latent class discrete choice model. We find that a fee can be very effective in increasing the efficiency at a charging station but the response to the fee varies among EV drivers depending on their current behaviour and the level of parking pressure they experience near their home. From these findings we draw implications for policy makers and charging point operators who aim to optimize the use of electric vehicle charging stations.
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A number of studies have investigated the possibility of extending Electric Vehicle (EV) Lithium-ion battery life by deliberately choosing to store the battery at a low to moderate state of charge. Recently, there has been considerable interest shown in the scheme of a deliberate discharge and subsequent recharge of a battery to yield an overall reduction in battery degradation whilst carrying out Vehicle-to-Grid (V2G) services (so-called `beneficial V2G'). This paper presents an investigation of the conditions permitting successful operation of this method by examining incremental time variation of the relevant parameters for two types of cells from results of the same physical size and chemistry, and similar capacity. These two types of cells are found in this present analysis to offer differing degrees of suitability for beneficial V2G.
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Within the FREVUE project 80 fully electric freight vehicles have been deployed. It showed that city logistics operations can be performed by electric freight vehicles, but that at the moment the high vehicle purchasing costs are still a barrier for large scale utilisation of electric freight vehicles for logistics operations. Only for small EFVs (lighter than 3.5 tons) a short term feasible business case is possible. For the larger vans and rigid trucks, a feasible business case is not yet possible from an operator’s perspective, often not even with subsidies. Copyright © 2018 Society of Automotive Engineers of Japan, Inc. All rights reserved
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The Netherlands is a frontrunner in the field of public charging infrastructure, having a high number of public charging stations per electric vehicle (EV) in the world. During the early years of adoption (2012-2015) a large percentage of the EV fleet were Plugin Hybrid Electric Vehicles (PHEV)due to the subsidy scheme at that time. With an increasing number of Full Electric Vehicles (FEVs) on the market and a current subsidy scheme for FEV only, a transition of the EV fleet from PHEV to FEV is expected. This is hypothesized to have effect on charging behavior of the complete fleet, reason to understand better how PHEVs and FEVs differ in charging behavior and how this impacts charging infrastructure usage. In this paper, the effects of the transition of PHEV to FEV is simulated by extending an existing Agent Based Model. Results show important effects of this transitionon charging infrastructure performance.
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