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High penetration of electrical vehicles (EVs) and photovoltaics (PVs) can cause significant voltage issues in low voltage distribution grids. To certain extent, the transformer with on-load tap changers can regulate its output voltage, thus relieving the voltage issues and improve the hosting capacity of the grid. Smart transformer (ST) is a more powerful component providing faster and superior voltage regulation, as it can regulate the voltage, the frequency and the harmonic behavior of each feeder. This paper will discuss the benefit of this new feature offered by ST through simulation, analysis and comparison with traditional transformer, where load flow analysis, optimization and multiple line drop compensation (MLDC) methods are involved.

This paper deals with the design criteria, setting up and experimental tests concerning an architecture of DC micro-grid for fast recharging stations of road full electric and hybrid vehicles. The proposed DC fast charging architecture was conceived as the best solution coming from a comparative analysis among well known different architectures, mainly based on AC and DC bus. This analysis evaluated the impact on the main grid, efficiency and charging/discharging power when recharging different kinds of battery packs from real vehicles. Then, a laboratory recharging station was built by means of a 20 kW AC/DC bidirectional grid tie converter interconnected with two different high power DC/DC converters. Through this architecture, the first converter realizes a DC conversion stage at 800 V, whereas the other two converters allow the electric vehicles battery packs to be recharge and a storage buffer to save electric energy when required. Laboratory tests, described in this paper, were mainly devoted to characterize the recharging station in different operative conditions, such as island and vehicle-to-grid (V2G) operation mode, and connecting different types of storage systems to be recharged through the DC fast charging station. The experimental results allowed the identification of energy management and control strategies of each converter and whole recharging station, in order to optimize the energy losses of the power conversion and recharging times, taking into account its interaction with main grid, renewable energy sources, energy storage systems.

The strong interaction between electric vehicles and the charging infrastructure presents new challenges towards system-level optimization. Moreover choices between the power level, duration, and frequency of charging events can have direct impact both on energy efficiency, as well as the overall lifetime of vehicles. This paper presents a preliminary study into the optimization scheme for such systems, with the focus on an electric bus application. The results illustrate an energy saving when comparing the EMS and baseline strategy of ~ 1.6%improvement measured in kWh/km, alongside a potential cycle life prolongation factor improvement of the EMS compared to the baseline is 1.5 in average.

ABSTRACT Many studies consider substitution of aircraft services with high-speed train (HST) services on short-haul routes desirable for environmental reasons. This paper empirically examined this perception by evaluating local air pollution (LAP) and climate change impacts from a flight and an HST service between London and Paris. Comparing the emissions, the impact, and the cost of damage from the aircraft journey with the HST journey, it was found that substituting an aircraft seat with an HST seat is beneficial. These benefits are likely to occur on all routes on which aircraft and HST substitution is likely to take place. Despite the many limitations in the evaluation of environmental impact, the analysis suggests that such an evaluation is valuable and provides important information.

This paper is focused on the design criteria of the power conversion systems operating within ultra-fast charging stations for electric vehicles. The proposed architecture is based on a DC bus, which features the integration of renewable energy sources and buffered storage systems, performing the new concept of smart grid system. Simulations of the power converters and storage systems, working as power devices of recharging station architecture, are implemented in the Matlab-Simulink environment with models of each subcomponent provided by the Sim-Power-System tool. The reported simulations are mainly devoted to verify the design criteria of the architecture scheme and the control strategies of the power fluxes related to power converters. The advantages and convenience in terms of power quality and requirementsfrom the main grid are shown, also during the EV fastcharging operations. Finally, the resulted recharging times are evaluated as comparable to the fuelling times generally taken by traditional oil based vehicles.

Abstract In a context where electric mobility is gaining increasing importance as a more sustainable solution for urban environments, this work presents an analysis of electric mobility feasibility and adequacy based on private users' naturalistic driving data. Several scenarios were tested to evaluate different charging event opportunities and their impacts on electric mobility feasibility. In more detail, scenario 1 considered that vehicles would recharge whenever they are stopped for 2, 4 or 6 h, either on weekdays or weekend days; scenario 2 tested the hypothesis of recharging only during the night period; and scenario 3 assumed that vehicles would recharge during the day on weekdays. Furthermore, the potential energy impacts of electric mobility at a city level, by applying a driver and street level approach, were also estimated. Results revealed that electric mobility is highly feasible for weekday urban trips, while weekend trips due to their higher average distance are less suitable to be performed by EVs. Scenario 1, due to its higher recharging opportunities was found to be the best-case scenario. In this case, the percentage of eligible trips was found to be equal to or higher than 94% and 88% on weekdays and weekend days, respectively. Results showed also the lower electric mobility feasibility if considering only daytime charging, on weekdays (scenario 3). However, if considering night charging (scenario 2), the electric mobility eligibility was found to improve significantly. When considering a street level analysis, the potential reduction in energy consumption ranges in average from −60 to −70%, enabling the visualization of higher EV potential, with increasing potential for reducing energy consumption for increasing road grades. Concluding, since electric mobility is particularly suited for urban driving and most households detain 2 or more vehicles, there is a high potential to replace at least one ICEV by an EV. In this case, people may adapt their driving behavior, using the EV for their day-to-day urban driving while the ICEV would be used for longer trips. Nonetheless, the capacity to recharge during night plays a significant role on trips eligibility. Therefore, the availability of home-charge set-ups or a much higher deployment of public charging stations at residential locations are required in order to incentivize drivers to shift towards electric mobility.

This paper presents an overview of issues and technologies related to the proper design of charging infrastructures for road electric vehicles. The analysis is carried out taking into account that the recharging stations of electric vehicles might be integrated in smart grids, which interconnect the main grid with distributed power plants, different kinds of renewable energy sources, stationary electrical storage systems and electric loads. The study is introduced by an analysis of the main characteristics concerning different kinds of storage systems to be used for stationary and on-board applications. Then, different charging devices, modes and architectures are presented and described showing their characteristics and potentialities. DC and AC configurations of charging stations are compared in terms of the issues related to their impact on the main grid and the design of their main components. Specific attention was devoted also to the ultra-fast DC architecture, which appears a possible solution to positively affect a wide spread of plug-in hybrid and full electric road vehicles.

Carsharing is a mode of transportation that provides access to a set of vehicles in the form of organized short-term car rental, serving as a substitute for private car ownership with a number of transportation, environmental, and social benefits. Combining the mobility concept of carsharing with electric vehicles (EVs), referred to as e-carsharing, can contribute not only to more efficient use of the shared vehicles, but also to more sustainable urban mobility in smart cities. In this context, this paper advances the concept of university-based e-carsharing, to serve the mobility needs of an academic community in Bilbao, Spain, focusing on the technical design aspects to cover the energy requirements of the EV fleet of the proposed system through the installation of fast charging posts based on a battery-to-battery approach. In this regard, a MATLAB/Simulink model is implemented to simulate the fast charging infrastructure using the real-world data collected from the university parking lot in order to represent the potential utilization of the EVs. The simulation results confirm the effectiveness of the proposed system design, ensuring that the energy demand of the EVs is successfully covered and concurrently the charging station batteries operate out of the low charge zone.

The electric engine cooling system, where the coolant pump and the radiator fan are driven by electric motors, admits advanced control methods to decrease auxiliary energy consumption. Recent publications show the fuel saving potential of optimal control strategies for the electric cooling system through offline simulations. These strategies often assume full knowledge of the drive cycle and compute the optimal control sequence by expensive global optimization methods. In reality, the full drive cycle is unknown during driving and global optimization not directly applicable on resource-constrained truck electronic control units. This paper reports state-of-the-art engineering achievements of exploiting vehicular onboard prediction for a limited time horizon and minimizing the auxiliary energy consumption of the electric cooling system through real-time optimization. The prediction and optimization are integrated into a model predictive controller (MPC), which is implemented on a dSPACE MicroAutoBox and tested on a truck on a public road. Systematic simulations show that the new method reduces fuel consumption of a 40-tonne truck by 0.36% and a 60-tonne truck by 0.69% in a real drive cycle compared to a base-line controller. The reductions on auxiliary fuel consumption for the 40-tonne and 60-tonne trucks are about 26% and 38%, respectively. Truck experiments validate the consistency between simulations and experiments and confirm the real-time feasibility of the MPC controller.