Modeling and Analysis of Wireless “Charge While Driving” Operations for Fully Electric Vehicles

Abstract 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

Perspectives on electrification for the automotive sector: A critical review of average daily distances by light-duty vehicles, required range, and economic outcomes

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

Discrete Choice Experiments to identify user preference for electric mobility

Electric vehicles are seen as a sustainable alternative in the current fight against increasing pollution worldwide. However, they are still seeing a limited spread among drivers and one of the challenges is to deepen the knowledge about the users' perceptions of this innovative means of transport. The current paper presents the work done in this framework by creating two Discrete Choice Experiments. The first one investigates aspects related to car ownership characteristics and performances, whereas the second one focuses on the features of the charging infrastructure. We describe the whole process that guided us to the current final version of these experiments. This includes the preliminary stage of a literature review and a productive discussion with stakeholders in the project framework arriving at the spread of questionnaires in two different Pilots. The current work stresses the need for all these passages to propose reliable experiments that could get new insights on the users' perception of electric vehicles

Transportation Energy Futures Series: Effects of Travel Reduction and Efficient Driving on Transportation: Energy Use and Greenhouse Gas Emissions

Since the 1970s, numerous transportation strategies have been formulated to change the behavior of drivers or travelers by reducing trips, shifting travel to more efficient modes, or improving the efficiency of existing modes. This report summarizes findings documented in existing literature to identify strategies with the greatest potential impact. The estimated effects of implementing the most significant and aggressive individual driver behavior modification strategies range from less than 1% to a few percent reduction in transportation energy use and GHG emissions. Combined strategies result in reductions of 7% to 15% by 2030. Pricing, ridesharing, eco-driving, and speed limit reduction/enforcement strategies are widely judged to have the greatest estimated potential effect, but lack the widespread public acceptance needed to accomplish maximum results. This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation

Associations Between Environmental Quality and Adult Asthma Prevalence in Medical Claims Data

As of 2014, approximately 7.4% of U.S. adults had current asthma. The etiology of asthma is complex, involving genetics, behavior, and environmental factors. To explore the association between cumulative environmental quality and asthma prevalence in U.S. adults, we linked the U.S. Environmental Protection Agency\u27s Environmental Quality Index (EQI) to the MarketScan® Commercial Claims and Encounters Database. The EQI is a summary measure of five environmental domains (air, water, land, built, sociodemographic). We defined asthma as having at least 2 claims during the study period, 2003–2013. We used a Bayesian approach with non-informative priors, implementing mixed-effects regression modeling with a Poisson link function. Fixed effects variables were EQI, sex, race, and age. Random effects were counties. We modeled quintiles of the EQI comparing higher quintiles (worse quality) to lowest quintile (best quality) to estimate prevalence ratios (PR) and credible intervals (CIs). We estimated associations using the cumulative EQI and domain-specific EQIs; we assessed U.S. overall (non-stratified) as well as stratified by rural-urban continuum codes (RUCC) to assess rural/urban heterogeneity. Among the 71,577,118 U.S. adults with medical claims who could be geocoded to county of residence, 1,147,564 (1.6%) met the asthma definition. Worse environmental quality was associated with increased asthma prevalence using the non-RUCC-stratified cumulative EQI, comparing the worst to best EQI quintile (PR:1.27; 95% CI: 1.21, 1.34). Patterns varied among different EQI domains, as well as by rural/urban status. Poor environmental quality may increase asthma prevalence, but domain-specific drivers may operate differently depending on rural/urban status