Factors Affecting Demand for Plug-in Charging Infrastructure: An Analysis of Plug-in Electric Vehicle Commuters

The public sector and the private sector, which includes automakers and charging network companies, are increasingly investing in building charging infrastructure to encourage the adoption and use of plug-in electric vehicles (PEVs) and to ensure that current facilities are not congested. However, building infrastructure is costly and, as with road congestion, when there is significant uptake of PEVs, we may not be able to “build out of congestion.” We modelled the choice of charging location that more than 3000 PEV drivers make when given the options of home, work, and public locations. Our study focused on understanding the importance of factors driving demand such as: the cost of charging, driver characteristics, access to charging infrastructure, and vehicle characteristics. We found that differences in the cost of charging play an important role in the demand for charging location. PEV drivers tend to substitute workplace charging for home charging when they pay a higher electricity rate at home, more so when the former is free. Additionally, socio-demographic factors like dwelling type and gender, as well as vehicle technology factors like electric range, influence the choice of charging location

Big Data for Urban Sustainability: Integrating Personal Mobility Dynamics in Environmental Assessments.

To alleviate fossil fuel use, reduce air emissions, and mitigate climate change, “new mobility” systems start to emerge with technologies such as electric vehicles, multi-modal transportation enabled by information and communications technology, and car/ride sharing. Current literature on the environmental implications of these emerging systems is often limited by using aggregated travel pattern data to characterize personal mobility dynamics, neglecting the individual heterogeneity. Individual travel patterns affect several key factors that determine potential environmental impacts, including charging behaviors, connection needs between different transportation modes, and car/ride sharing potentials. Therefore, to better understand these systems and inform decision making, travel patterns at the individual level need to be considered. Using vehicle trajectory data of over 10,000 taxis in Beijing, this research demonstrates the benefits of integrating individual travel patterns into environmental assessments through three case studies (vehicle electrification, charging station siting, and ride sharing) focusing on two emerging systems: electric vehicles and ride sharing. Results from the vehicle electrification study indicate that individual travel patterns can impact the environmental performance of fleet electrification. When battery cost exceeds $200/kWh, vehicles with greater battery range cannot continuously improve travel electrification and can reduce electrification rate. At the current battery cost of$400/kWh, targeting subsidies to vehicles with battery range around 90 miles can achieve higher electrification rate. The public charging station siting case demonstrates that individual travel patterns can better estimate charging demand and guide charging infrastructure development. Charging stations sited according to individual travel patterns can increase electrification rate by 59% to 88% compared to existing sites. Lastly, the ride sharing case shows that trip details extracted from vehicle trajectory data enable dynamic ride sharing modeling. Shared taxi rides in Beijing can reduce total travel distance and air emissions by 33% with 10-minute travel time deviation tolerance. Only minimal tolerance to travel time change (4 minutes) is needed from the riders to enable significant ride sharing (sharing 60% of the trips and saving 20% of travel distance). In summary, vehicle trajectory data can be integrated into environmental assessments to capture individual travel patterns and improve our understanding of the emerging transportation systems.PhDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113510/1/caih_1.pd

Charging ahead on the transition to electric vehicles with standard 120 v wall outlets

Electrification of transportation is needed soon and at significant scale to meet climate goals, but electric vehicle adoption has been slow and there has been little systematic analysis to show that today's electric vehicles meet the needs of drivers. We apply detailed physics-based models of electric vehicles with data on how drivers use their cars on a daily basis. We show that the energy storage limits of today's electric vehicles are outweighed by their high efficiency and the fact that driving in the United States seldom exceeds 100 km of daily travel. When accounting for these factors, we show that the normal daily travel of 85-89% of drivers in the United States can be satisfied with electric vehicles charging with standard 120 V wall outlets at home only. Further, we show that 77-79% of drivers on their normal daily driving will have over 60 km of buffer range for unexpected trips. We quantify the sensitivities to terrain, high ancillary power draw, and battery degradation and show that an extreme case with all trips on a 3% uphill grade still shows the daily travel of 70% of drivers being satisfied with electric vehicles. These findings show that today's electric vehicles can satisfy the daily driving needs of a significant majority of drivers using only 120 V wall outlets that are already the standard across the United States

Cross-border Mobility for Electric Vehicles: Selected results from one of the first cross-border field tests in Europe

This book provides selected results from the accompanying research of the project CROME. The vision of the project was to create and test a safe, seamless, user-friendly and reliable mobility with electric vehicles between France and Germany as a prefiguration of a pan-European electric mobility system. Major aims were contributions to the European standardisation process of charging infrastructure for electric mobility and corresponding services, and to provide an early customer feedback

How Assumptions About Consumers Influence Estimates of Electric Vehicle Miles Traveled of Plug-in Hybrid Electric Vehicles: A Review of PHEV Use Data and Possible Implications for the SAEJ2841 Utility Factor (UF) Standard

To characterize the environmental impact and petroleum displacement potential of Plug-in Hybrid Electric Vehicles (PHEVs) it is necessary to know what fraction of travel occurs in each of the two energy use modes. Currently, the Society of Automotive Engineers (SAE) estimates the fraction of US travel a PHEV with a given Charge Depleting (CD) range will electrify based on travel data from a national, single drivingday diary and the assumption that PHEVs are charged onceper day. This estimate is used by policy makers, transportation researchers and automotive engineers for purposes which range from State Policy (California Zero Emission Vehicle (ZEV) Mandate), battery lifetime estimates, vehicle to grid interactions and other analyses. However, the SAEJ2841 standard is most realistic for instances where its assumptions are valid ; i.e. consumers do not base their PHEV purchase decision on their driving needs, charge once per day at home, don’t have access to or use public charging infrastructure, and drive their PHEV similarly to the vehicle it replaced. This combination of assumptions is only a single use case for PHEVs and represents untested, universal assumptions about how consumers will choose to purchase, drive and recharge PHEVs. We investigate these four assumptions made in the SAE J2841 standard, and compare each one against the best publically available consumer demonstration and academic analyses to begin the process of assessing assumptions and understanding potential implications for analyses or policies which currently use the SAE J2841. Overall, this analysis is meant to bring depth to the discussion of PHEV impacts and policy which seeks to incentivize electric driving

Study and Implementation of Compact Modeling Techniques for the Energy Analysis and Optimization of Complex Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen