This study presents a method for analysing the traffic and electric performance of wireless Charge While Driving (CWD) systems for two types of electric vehicle: a light-van for freight distribution and a city car. After performing a preliminary design of the CWD system, a simplified traffic simulation, including an energy assessment for vehicles, is presented to test the design settings, such as the travelling speed on CWD and the percentage of equipped lanes. The speed range explored refers to quite low values because the design layout of the EVSE should be a compromise between the need to minimize the installation and maintenance costs and users' acceptance of the time required to obtain a proper recharge. The choice of the traffic modelling approach derives from the specific requirements of the CWD system defined in the eCo-FEV project, which may be assumed as having been installed along a low speed lane of a motorway. The simplified traffic model simulates the vehicles time series along the road, introducing their energy needs as an influencing factor of drivers' behaviour. The simulated scenarios involve electric light-vans travelling along a 5-km highway that have the opportunity to charge in motion if their State of Charge (SOC) is under an established threshold.

The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving (CWD) electric vehicles, from both traffic and energy points of view. To accurately quantify the electric power required from an energy supplier for the proper management of the charging system, a traffic simulation model is implemented. This model is based on a mesoscopic approach, and it is applied to a freight distribution scenario. Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems (ADAS). From the energy point of view, the analyses indicate that the traffic may have the following effects on the energy of the system: in a low traffic level scenario, the maximum power that should be supplied for the entire road is simulated at approximately 9 MW; and in a high level traffic scenario with lower average speeds, the maximum power required by the vehicles in the charging lane increases by more than 50 %.

This paper presents a research on traffic modelling developed for assessing traffic and energy performance of electric systems installed along roads for dynamic charging-while-driving (CWD) of fully electric vehicles (FEVs).The logic adopted by the developed traffic model is derived from a particular simulation scenario of electric charging: a freight distribution service operated using medium-sized vans. In this case, the CWD service is used to recover the state of charge of the FEV batteries to shortly start with further activities after arrival at the depot.The CWD system is assumed to be implemented in a multilane ring road with several intermediate on-ramp entrances, where the slowest lane is reserved for the dynamic charging of authorized electric vehicles. A specific traffic model is developed and implemented based on a mesoscopic approach, where energy requirements and charging opportunities affect driving and traffic behaviours. Overtaking manoeuvres as well as new entries in the CWD lane of vehicles that need to charge are modelled according to a cooperative driving system, which manages adequate time gaps between consecutive vehicles. Finally, a speed control strategy is simulated at a defined node to create an empty time-space slot in the CWD lane, by delaying the arriving vehicles. This simulated control, implemented to allow maintenance operations for CWD that may require clearing a charging zone for a short time slot, could also be applied to facilitate on-ramp merging manoeuvres.

The aim of this paper is to present a research study on a traffic model developed for analysing the performance of the wireless inductive systems for charging while driving (CWD) fully electric vehicles (FEVs) from both traffic and energy points of view. The design assumptions of the developed traffic model are aimed to simulate in particular a freight distribution service in a fully cooperative traffic environment. In this case, the CWD service could be used to guarantee the minimum state of charge (SOC) of the batteries at the arrival to the depot that allows the vehicles to shortly start with further activities. In this way, the fleet manager could avoid wasting time for the stationary recharge, thus increasing the level of service of the freight distribution. The CWD system is applied to a multilane ring road with several intermediate on-ramp entrances, where the slowest lane is reserved for the dynamic charging activities, when authorized vehicles are present. A specific traffic model has been developed and implemented adopting a mesoscopic approach, where vehicle energy needs and charging opportunities affect drivers' behavior. Overtaking maneuvers, as well as new entries in the CWD lane of vehicles that need to charge, have been modeled by taking into account a fully cooperative driving system among vehicles which manages adequate gaps between consecutive vehicles. Finally, a speed control strategy in which vehicles can be delayed to create an empty time-space slot in the CWD lane, is simulated at a defined node. This type of control, though is simulated to allow extraordinary maintenance operations, which may require a free charging zone for a given time slot, could also be applied to support merging maneuvers for on ramp vehicles.

This paper aims at providing a multisource data analysis, including direct data collection, focussed on daily average distances covered with motorized mobility. Its results can be used as a basis for policies involving a shift towards new propulsions, electric motors or hybrid electric vehicles (HEV) for road vehicles. A number of variables influence the propensity of drivers to use electric traction, even the option of plug-in hybrid electric vehicles (PHEV). This paper addresses one of these variables: the compliancy of electric traction—regarding both hybrid plug-in solutions and full-electric vehicles, in addition to the autonomy of batteries (range)—with the daily travels by road vehicles, mainly by automobiles. We want to understand whether the constraints leading towards a greater independence from crude oil rather than constraints concerning emissions, mainly in urban contexts, might be compliant with the habitual daily trips of drivers. We also want to understand if these daily trips have varied much during recent years and the consequences they may have on operational costs of plug-in automobiles. After introducing a general overview of road-motorized mobility in Italy, the paper compares data from other studies to provide an indication of average daily driving distances. This reveals how different recent analyses converge on a limited range of average road distances covered daily by Italians, which is compliant with ranges allowed by electric batteries, provided that their low energy density in comparison with that of oil-derived fuels do not arrive to imply a significant increase in vehicle mass. Subsequently, average distances in some EU countries are taken from the literature, and the results are also compared with U.S. data. The study extends the analysis of trends on the use of automobiles and road-vehicles to the international context by also addressing average daily distances covered for freight transport in some EU countries, thereby providing a further basis for comparison and for understanding whether the daily motorized mobility can be considered as a stable phenomenon. Finally, an analysis is provided of the economic operational advantages from using plug-in vehicles.