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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The increased adoption of electric vehicles worldwide is largely caused by the uptake of private electric cars. In parallel other segments such as busses, city logistics and taxis, are increasingly becoming electrified. Amsterdam is an interesting case, as the municipality and the taxi sector have signed a voluntary agreement to realise a full electric taxi fleet by 2025. This paper investigates the results of a survey that was distributed amongst 3000 taxi drivers to examine perceptions and attitudes on the municipal charging incentives as well as taxi ride characteristics.
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The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery until a full battery of the EVs based on realworld data needs to be analyzed. Many researchers currently view this charging profile as a static load and ignore the actual charging behavior during the charging session. This study investigates how different factors influence the charging profile of individual EVs based on real-world data of charging sessionsin the Netherlands, enabling optimization analysis of EV smart charging schemes.
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A replacement of cars with conventional internal combustion engines (ICEs) by electric vehicles (EVs) is seen by many as a means to improve local air quality, reduce dependence on fossil fuels and CO2 emissions. The market for EV is slowly developing with a growing number of (subsidized) manufacturers offering EV models in different market segments to (subsidized) car owners. The number of EVs is still small in most countries, but policymakers and manufacturers see partial or even full replacement of ICEs by EVs as realistic in the coming decade. EV engines are powered by rechargeable lithium-ion batteries. Li-ion is produced from precursors, either liquid (brine metal salt) or solid (hard rocks). Lithium mining is still concentrated in a few countries. Lithium is used for batteries, ceramics, grease and medicine. This reliance comes at a cost, as conventional lithium mining creates several externalities. The following main question will be addressed: How to source a required volume of lithium in a way that reduces the environmental and social-economic impact of mining this resource? To address this question, we will use a combination of relevant literature and a local case study supported by a model-based estimation. The focus is on the Netherlands, an EV user country, but the approach is generic.
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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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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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The mass adoption of Electric Vehicles (EVs) might raise pressure on the power system, especially during peak hours. Therefore, there is a need for delayed charging. However, to optimize the charging system, the progression of charging from an empty battery to a full battery of the EVs, based on real-world data, needs to be analyzed. Currently, many researchers view this charging profile as a static load and ignore the actual charging behavior during the charging session. However, this study investigates how different factors influence the charging profile of individual EVs based on real-world data of charging sessions in The Netherlands, and thereby enable optimization analysis of EV smart charging schemes.
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Densely populated areas are major sources of air, soil and water pollution. Agriculture, manufacturing, consumer households and road traffic all have their share. This is particularly true for the country featured in this paper: the Netherlands. Continuous pollution of the air and soil manifests itself as acification, decalcification and eutrofication. Biodiversity becomes lower and lower in nature areas. Biological farms are also under threat. In case of mobility, local air pollution may have a huge health impact. Effective policy is called for, after high courts blocked construction projects, because of foreseen building- and transport-related NOx emissions. EU law makers are after Dutch governments, because these favoured economics and politics over environmental and liveability concerns. But, people in the Netherlands are strongly divided. The latest provincial elections were dominated by environmental concerns, next to many socio-economic issues. NOx and CO2 emissions by passenger cars are in focus. Technical means and increasing fuel economy norms strongly reduced NOx emissions to a still too high level. A larger number of cars neutralized a technological reduction of CO2 emissions. The question is: What would be the impact of a drastic mandatory reduction in CO2, NOx, and PM10 emissions on car ownership and use in the Netherlands? The authors used literature, scenario analysis and simulation modelling to answer this question. Electric mobility could remove these emissions. Its full impact will only be achieved if the grid-mix, which is still dominated by fossil fuels, becomes green(er), which is a gradual, long-term, process. EVs compete with other consumers of electricity, as many other activities, such as heating, are also electrifying. With the current grid-mix, it is inevitable that the number of km per vehicle per year is reduced to reach the scenario targets (−25% resp. −50% CO2 emissions by cars). This calls for an individual mobility budget per car user.
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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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Electrification of transportation, communication, working and living continues worldwide. Televisions, telephones, servers are an important part of everyday life. These loads and most sustainable sources as well, have one thing in common: Direct Current. The Dutch research and educational programme ‘DC – road to its full potential’ studies the impact of feeding these appliances from a DC grid. An improvement in energy efficiency is expected, other benefits are unknown and practical considerations are needed to come to a proper comparison with an AC grid. This paper starts with a brief introduction of the programme and its first stages. These stages encompass firstly the commissioning, selection and implementation of a safe and user friendly testing facility, to compare performance of domestic appliances when powered with AC and DC. Secondly, the relationship between the DC-testing facility and existing modeling and simulation assignments is explained. Thirdly, first results are discussed in a broad sense. An improved energy efficiency of 3% to 5% is already demonstrated for domestic appliances. That opens up questions for the performance of a domestic DC system as a whole. The paper then ends with proposed minor changes in the programme and guidelines for future projects. These changes encompass further studying of domestic appliances for product-development purposes, leaving less means for new and costly high-power testing facilities. Possible gains are 1) material and component savings 2) simpler and cheaper exteriors 3) stable and safe in-house infrastructure 4) whilst combined with local sustainable generation. That is the road ahead. 10.1109/DUE.2014.6827758
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