Michael A Nicholas

Using Geographic Information Systems to Evaluate Siting and Networks of Hydrogen Stations

The lack of hydrogen fuel stations is a major barrier to the introduction of hydrogen vehicles. Given the high cost of constructing hydrogen stations, it is desirable to build as few stations as possible while still adequately serving consumers. Although several studies have addressed the general question of how many stations are needed, the literature has been largely silent on how to relate the location of stations to the sufficient number of hydrogen stations. A geographic information system (GIS) provides a tool for evaluating station siting decisions as part of a greater hydrogen network. A GIS model was developed for siting generic hydrogen stations in Sacramento County, California, with the economics of supplying those stations with hydrogen ignored for now. The analysis used average one-way driving time from home or work to a station as a metric to evaluate scenarios. When a network is posited with 30% as many retail fuel stations as now exist, average driving time from home to a station would be 16 s more than it is with the full existing network of stations. With 5% of existing stations supplying hydrogen (or any other alternative fuel), the average driving time to a station could be as little as 4 min in Sacramento County. These estimates assume free-flow traffic; actual times will vary. This modeling approach provides an analytical framework for siting early hydrogen fuel stations. Initial results suggest a few strategically sited stations could be sufficient to satisfy a large number of prospective consumers.

Detailed Analysis of Urban Station Siting for California Hydrogen Highway Network

Station availability is a major concern when the deployment of an alternative fuel such as hydrogen is considered. Too few stations will make the network inconvenient, while too many will make the refueling network cost prohibitive. As a follow-up analysis to two station siting analyses completed by the authors for the California Hydrogen Highway Network, this report takes a closer look at the regional differences between the four main metropolitan areas in California: Greater Los Angeles, the San Francisco Bay Area, the Sacramento metropolitan area, and the San Diego metropolitan area. The purpose of this analysis is twofold: to generate a general model to assess hydrogen needs in different regions, and to apply the model to compare its results with the California hydrogen highways report. In the analysis that follows, average driving time to the nearest station (convenience metric) is used to determine the number of stations necessary for each region. By using convenience to determine the share of stations, regions that are less dense will be served as well as those regions with high density. The results suggest that the percentage of stations needed to meet a convenience target differs among regions depending on density. For example, a 4-min average travel time in Sacramento requires 7.2% of stations, whereas it requires only 3.3% of stations in Los Angeles. The developed equation predicts station needs as a function of population density and a desired level of convenience; if the caveats explained in the paper are observed, the prediction equation can be applied to any region.

Consumer Perceptions and Use of Driving Distance of Electric Vehicles: Changes over Time Through Lifestyle Learning Process

Popular media and even researchers commonly assume that ownership of a battery electric vehicle (BEV) provides consumers less performance and mobility than consumers expect. A common claim is that consumers have constant worry about the range of their BEVs, often termed “range anxiety.” BMW converted 450 Mini Coopers to all-electric drive (named the Mini E) and leased them to fleets and 235 private households in the Los Angeles, California, and New York–New Jersey regions from spring 2009 to spring 2010. Through the course of the 1-year lease, University of California, Davis (UCD), researchers conducted multiple online surveys and in-person interviews and administered weeklong driving diaries. This paper explores the reactions of Mini E drivers to the driving distance of the Mini E through the framework of a lifestyle learning process. Over time, Mini E drivers learned how the 104-mi range of the Mini E fit into their lifestyles. Drivers adapted and explored with their Mini E through activities such as altering driving behavior (such as speed and trip routes), optimizing charging opportunities, planning trips, and educating themselves on distances to destinations with the help of online and mobile mapping tools. In the course of the UCD Mini E consumer study, researchers found evidence suggesting that the driving range was not a major concern for these early adopters. Even with no public charging available to their vehicle, 100% of survey respondents stated that BEVs were suitable for daily use. The results of this study will be of interest to policy makers and practitioners interested in expanding the BEV market.

Charging Behavior Impacts on Electric Vehicle Miles Traveled: Who Is Not Plugging In?

The growing market for plug-in electric vehicles (PEVs) features new models of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) with varying battery sizes and electric driving ranges. How are the various models being used in the real world? A common assumption in PEV impact analysis is that PEV owners will maximize their vehicles utility by appropriately sizing the battery to their driving needs and by charging their vehicle as much as possible to recover the cost of the vehicle purchase. On the basis of these assumptions, a high correlation between PHEV owner use of the vehicle and the number of plug-in events is expected, and drivers of PHEVs with a small battery are expected to plug in more than do owners of vehicles with a larger battery and similar driving patterns. The assumptions presented are examined through a survey of more than 3,500 PEV owners conducted in California in May and June 2013. The online survey included extensive data on driving and charging behavior using web map questions. Owners of all PEV models on the market, including more than 600 Volts and 800 Prius Plug-Ins, were surveyed. The results show that small-battery PHEV electric vehicle miles traveled are lower than longer-range PHEV or BEV electric vehicle miles traveled not only because of battery size but also because of public charging availability and charging behavior. Higher electric-range PHEV and BEV drivers charge more often and report more charging opportunities in areas where smaller-battery PHEVs could not find chargers.

Studying the PEV market in california: Comparing the PEV, PHEV and hybrid markets

Who is buying electric vehicles? Who is buying new cars in general? Is the first group a subset of the second? What are the similarities and differences of the two groups? Can we use hybrid buyers to predict the future plug-in electric vehicle (PEV) market? This study explores the characteristics of new car buyer households who purchased a new vehicle in California during 2011-2012 comparing three main populations: internal combustion engine (ICE) buyers, hybrid buyers and PEV buyers. We show that PEV households have different socio-demographic characteristics than ICE buyers with, for example, higher income, higher education, and more new cars while hybrid owners are a middle group with characteristics that fall between those of ICE and PEV owners. We also found differences among PEV buyers. Pure battery electric vehicle (BEV) and plug-in hybrid electric (PHEV) households have similar socio-demographic characteristics but they are differentiated by driving characteristics and home location. The PEV market today is based on small number of buyers and small number of potential new car buyers. Targeting the potential car buyers can more rapidly increase the market, create a used market and will open PEV options to larger segments of the population.

Exploring the Impact of the Federal Tax Credit on the Plug-In Vehicle Market

The effect of the federal Plug-In Electric Drive Vehicle Credit on plug-in electric vehicle (PEV) sales is assessed in the United States by using an ex post stated preference survey of more than 2,882 PEV owners in 11 states. This study attributes more than 30% of the PEV sales to the federal tax credit, with an impact of up to 49% for the Nissan LEAF. The incentive shifts buyers from internal combustion engine vehicles to plug-in vehicles and advances the purchase timing of new vehicles by 1 year or more. The impact of the incentive on buyers of varying sociodemographic and vehicle choice characteristics is explored through the use of three performance measures, including number of vehicles sold, kilowatt-hours of capacity sold, and electric vehicle miles traveled per year. The results of this paper add to the discussion of the impact of monetary incentives on the alternative-fuel vehicle market and present possibilities for improving the performance of monetary incentives in the PEV market.

Mobile App Support for Electric Vehicle Drivers: A Review of Today’s Marketplace and Future Directions

Mobile device applications (apps) are becoming an important source of information, control, and motivation for EV drivers. Here we review the current ecosystem of mobile applications that are available for EV drivers and consumers and find that apps are available in six basic categories: purchase decisions, vehicle dashboards, charging availability and payment, smart grid interaction, route planning, and driver competitions. The current range of the EV-specific mobile marketplace extends from pre-sale consumer information, charging information and control, and EV specific navigation features among other services. However, the market is highly fragmented, with applications providing niche information, and using various methodologies. In addition, we find that the barriers to more useful apps are a lack of vehicle and charger APIs (application programming interfaces), lack of data availability, reliability, format and types, and proprietary payment and billing methods. We conclude that mobile applications for EVs are a growing market that provide important direct benefits as well as ancillary services to EV owners, although the lack of uniformity and standards between both vehicle and charger systems is a serious barrier to the broader use of mobile applications for EVs.

Electric Vehicle Fast Charger Planning for Metropolitan Planning Organizations: Adapting to Changing Markets and Vehicle Technology

Presented is a tool to estimate fast charger demand and sample results on a current and future battery electric vehicle (BEV) scenario. The results highlight the data and methods needed to plan for fast charger demand. To plan for existing BEVs, origin and destination data are necessary for identifying which traffic is relevant to assess fast-charging demand. Also, as the battery size for BEVs increases, demand shifts from primarily inside metro areas to long-distance corridors outside metro areas. The sample results show the interactions of battery size, frequency of charging, and energy needed per charge. Although energy per charge increases with battery size, overall electricity demand per vehicle decreases with larger batteries.

Electric Vehicle Explorer

Most HCI research related to electric vehicle adoption has focused on mitigating barriers related to vehicle range and charging infrastructure, while relatively less attention has been given to helping consumers recognize the benefits of electric vehicles. A significant benefit is reduced energy costs; however, the complexity of comparing gasoline and electricity prices makes it difficult for consumers to quantify. This paper describes and evaluates an online tool called EV Explorer that enables users to compare personalized estimates of annual energy costs for multiple vehicles. We assessed the tool through an online experiment, gauging users’ perceptions—before and after using the tool—of their current energy costs, potential savings with electric vehicles, attitude toward electric vehicle charging, and intention to buy or lease an electric vehicle in the future. Statistically significant changes in each of these variables validate the tool as an educational and persuasive strategy to promote electric vehicle adoption.