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According to the European Commission, electric vehicles (EVs) remain parked for 95% of their life, which makes them inefficient. In addition, EV sales are forecasted to rise over the following years, which will create additional electricity demand, especially during peak hours. This challenge coincides with the growing trend of homeowners installing renewable energy sources (RES) in their homes. Therefore, a potential solution to managing the increase in electricity costs and peak demand is the use of EVs as a flexible storage system by utilizing vehicle-to-grid (V2G) technology. The successful market penetration of V2G technology hinges significantly on the willingness of current and future EV drivers to participate. Hence, in the broader context of the promotion and transition to electromobility and related technologies (V2G), the main purpose of this paper was to shed light on the hitherto unknown attitudes of Greek drivers towards V2G technology. The adopted methodology involved a survey questionnaire with statements serving as indicators on a 5-point Likert scale. The results show that Greek drivers highly appreciate the positive environmental impact of EVs but are primarily driven by the potential economic incentives they might receive from engaging with V2G technology. In addition, they appear to be skeptical about both V2G technology and electromobility, mainly due to the increased upfront cost of EVs but also due to the immature V2G market. [ABSTRACT FROM AUTHOR]

This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the article elucidates the evolving ecosystem of smart charging solutions, considering aspects including advancements in charging protocols. Additionally, the review highlights challenges and prospects in the SECI domain, providing insightful information for scholars, practitioners, and policymakers involved in the dynamic field of electromobility. Technical potentials, including functionalities and integration with the smart grid, have been thoroughly reviewed. An analysis is conducted on the effects of intelligent charging on power distribution systems and strategies to lessen these effects. This study also examines the development of intelligent charging algorithms, optimisation methods, and security analysis. This paper, therefore, contributes to fostering a more thorough comprehension of the current state and future trajectories of Smart Electromobility Charging Infrastructure. [ABSTRACT FROM AUTHOR]

With more electric vehicles introduced in society, there is a need for the further implementation of charging infrastructure. Innovation in electromobility may result in new charging and discharging strategies, including concepts such as smart charging and vehicle-to-grid. This article provides an overview of vehicle charging and discharging innovations with a cable connection. A MATLAB/Simulink model is developed to show the difference between an electric vehicle with and without the vehicle-to-grid capabilities for electricity grid prices estimated for Sweden for three different electric vehicle user profiles and four different electric vehicle models. The result includes the state-of-charge values and price estimations for the different vehicles charged with or without a bidirectional power flow to and from the electric grid. The results show that there is a greater difference in state-of-charge values over the day investigated for the electric vehicles with vehicle-to-grid capabilities than for vehicles without vehicle-to-grid capabilities. The results indicate potential economic revenues from using vehicle-to-grid if there is a significant variation in electricity prices during different hours. Therefore, the vehicle owner can potentially receive money from selling electricity to the grid while also supporting the electric grid. The study provides insights into utilizing vehicle-to-grid in society and taking steps towards its implementation. [ABSTRACT FROM AUTHOR]

According to the European Commission, electric vehicles (EVs) remain parked for 95% of their life, which makes them inefficient. In addition, EV sales are forecasted to rise over the following years, which will create additional electricity demand, especially during peak hours. This challenge coincides with the growing trend of homeowners installing renewable energy sources (RES) in their homes. Therefore, a potential solution to managing the increase in electricity costs and peak demand is the use of EVs as a flexible storage system by utilizing vehicle-to-grid (V2G) technology. The successful market penetration of V2G technology hinges significantly on the willingness of current and future EV drivers to participate. Hence, in the broader context of the promotion and transition to electromobility and related technologies (V2G), the main purpose of this paper was to shed light on the hitherto unknown attitudes of Greek drivers towards V2G technology. The adopted methodology involved a survey questionnaire with statements serving as indicators on a 5-point Likert scale. The results show that Greek drivers highly appreciate the positive environmental impact of EVs but are primarily driven by the potential economic incentives they might receive from engaging with V2G technology. In addition, they appear to be skeptical about both V2G technology and electromobility, mainly due to the increased upfront cost of EVs but also due to the immature V2G market.

This study thoroughly analyses Smart Electromobility Charging Infrastructure (SECI), exploring its multifaceted dimensions and advancements. Delving into the intricate landscape of SECI, the study critically evaluates existing technologies, integration methodologies, and emerging trends. Through a systematic examination of literature and empirical studies, the article elucidates the evolving ecosystem of smart charging solutions, considering aspects including advancements in charging protocols. Additionally, the review highlights challenges and prospects in the SECI domain, providing insightful information for scholars, practitioners, and policymakers involved in the dynamic field of electromobility. Technical potentials, including functionalities and integration with the smart grid, have been thoroughly reviewed. An analysis is conducted on the effects of intelligent charging on power distribution systems and strategies to lessen these effects. This study also examines the development of intelligent charging algorithms, optimisation methods, and security analysis. This paper, therefore, contributes to fostering a more thorough comprehension of the current state and future trajectories of Smart Electromobility Charging Infrastructure.

Mobility as a Service (MaaS) and, more recently, electric Mobility as a Service (eMaaS) have increasingly been put forward to meet the economic, social, and environmental challenges linked to mobility. First, however, monitoring and evaluating such a scheme's performance is crucial, mainly through the definition of appropriate indicators. In this study, a standardised methodological approach is presented for the assessment of an eMaaS scheme. In addition, this methodological approach contains a range of innovative Key Performance Indicators (KPIs). The proposed KPIs refer to the evaluation of the scheme based on four pillars: (a) society, (b) users, (c) operators, and (d) internal operation. The methodology for evaluating the proposed KPIs includes identifying the available sources for data collection. For example, data can be collected through questionnaire surveys, focus group discussions, and the system's central dashboard. An appropriate set of indicators to evaluate a system from various perspectives is necessary to assess an eMaaS scheme in real-life conditions. Furthermore, the evaluation of the overall operation of the scheme will contribute to drawing valid conclusions (e.g., user acceptance, economic viability) for the implementation of eMaaS in urban areas. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) offers the possibility to produce components in a resource-efficient and environmentally friendly way. AM can also be used to optimise the design of components in mechanical and physical terms. In this way, functionally integrated, lightweight, highly efficient, and innovative components can be manufactured with the help of additive manufacturing in terms of Industry 4.0. Furthermore, requirements in the automotive industry for drivetrain components are increasingly being trimmed in the direction of efficiency and environmental protection. Especially in electromobility, the topic of green efficiency is an essential component. Exhaust emission legislation and driving profiles for evaluating vehicles are becoming increasingly detailed. This offers the potential to apply the advantages of AM to vehicle types such as conventional, utility vehicles, and nonroad mobile machinery (NRMM), independent of the electrical drivetrain technology (hybrid or fully electrical). AM also allows for us to produce optimally adapted components to the respective requirements and use cases. In this review, the intersections of AM and electromobility are illuminated, showing which solutions and visions are already available for the different vehicle types on the market and which solutions are being scientifically researched. Furthermore, the potential and existing deficit of AM in the field of electromobility are shown. Lastly, new and innovative solutions are presented and classified according to their advantages and disadvantages. [ABSTRACT FROM AUTHOR]

Mobility as a Service (MaaS) and, more recently, electric Mobility as a Service (eMaaS) have increasingly been put forward to meet the economic, social, and environmental challenges linked to mobility. First, however, monitoring and evaluating such a scheme’s performance is crucial, mainly through the definition of appropriate indicators. In this study, a standardised methodological approach is presented for the assessment of an eMaaS scheme. In addition, this methodological approach contains a range of innovative Key Performance Indicators (KPIs). The proposed KPIs refer to the evaluation of the scheme based on four pillars: (a) society, (b) users, (c) operators, and (d) internal operation. The methodology for evaluating the proposed KPIs includes identifying the available sources for data collection. For example, data can be collected through questionnaire surveys, focus group discussions, and the system’s central dashboard. An appropriate set of indicators to evaluate a system from various perspectives is necessary to assess an eMaaS scheme in real-life conditions. Furthermore, the evaluation of the overall operation of the scheme will contribute to drawing valid conclusions (e.g., user acceptance, economic viability) for the implementation of eMaaS in urban areas.

As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) offers the possibility to produce components in a resource-efficient and environmentally friendly way. AM can also be used to optimise the design of components in mechanical and physical terms. In this way, functionally integrated, lightweight, highly efficient, and innovative components can be manufactured with the help of additive manufacturing in terms of Industry 4.0. Furthermore, requirements in the automotive industry for drivetrain components are increasingly being trimmed in the direction of efficiency and environmental protection. Especially in electromobility, the topic of green efficiency is an essential component. Exhaust emission legislation and driving profiles for evaluating vehicles are becoming increasingly detailed. This offers the potential to apply the advantages of AM to vehicle types such as conventional, utility vehicles, and nonroad mobile machinery (NRMM), independent of the electrical drivetrain technology (hybrid or fully electrical). AM also allows for us to produce optimally adapted components to the respective requirements and use cases. In this review, the intersections of AM and electromobility are illuminated, showing which solutions and visions are already available for the different vehicle types on the market and which solutions are being scientifically researched. Furthermore, the potential and existing deficit of AM in the field of electromobility are shown. Lastly, new and innovative solutions are presented and classified according to their advantages and disadvantages.

As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%.

This paper seeks to identify bottlenecks in the energy grid supply regarding different market penetration of battery electric vehicles in Stuttgart, Germany. First, medium-term forecasts of electric and hybrid vehicles and the corresponding charging infrastructure are issued from 2017 to 2030, resulting in a share of 27% electric vehicles by 2030 in the Stuttgart region. Next, interactions between electric vehicles and the local energy system in Stuttgart were examined, comparing different development scenarios in the mobility sector. Further, a travel demand model was used to generate charging profiles of electric vehicles under consideration of mobility patterns. The charging demand was combined with standard household load profiles and a load flow analysis of the peak hour was carried out for a quarter comprising 349 households. The simulation shows that a higher charging capacity can lead to a lower transformer utilization, as charging and household peak load may fall temporally apart. Finally, it was examined whether the existing infrastructure is suitable to meet future demand focusing on the transformer reserve capacity. Overall, the need for action is limited; only 10% of the approximately 560 sub-grids were identified as potential weak points.

In order to electrify the transport sector, scores of charging stations are needed to incentivize people to buy electric vehicles. In urban areas with a high charging demand and little space, decision-makers are in need of planning tools that enable them to efficiently allocate financial and organizational resources to the promotion of electromobility. As with many other city planning tasks, simulations foster successful decision-making. This article presents a novel agent-based simulation framework for urban electromobility aimed at the analysis of charging station utilization and user behavior. The approach presented here employs a novel co-evolutionary learning model for adaptive charging behavior. The simulation framework is tested and verified by means of a case study conducted in the city of Munich. The case study shows that the presented approach realistically reproduces charging behavior and spatio-temporal charger utilization.

As electric vehicle market penetration grows steadily and charging demand along with it, the analysis of daily usage gains in significance. We propose in this paper a simple yet powerful tool based on a Markov chain that can model the stochastic nature of day to day usage of a charging station if adequate datasets on travel patterns are available. The model is generic and therefore can be tailored to different locations with different features. Within this work, we conducted a case study with the aim to verify the algorithm. By an additional sensitivity analysis, impacts of the made assumptions are considered. With a final analysis of two charging tariff designs the model provides valuable stochastic information about electricity consumption and annual revenues at a location of interest.