Estimating the demand for electric automobiles using fully disaggregated probabilistic choice analysis

This study uses probabilistic choice models to predict potential demand for electric cars. Survey data are employed to estimate separate utility functions for each of 51 subjects. This provides a sample distribution of consumer preferences for vehicle attributes including price, operating cost and range. The results indicate great diversity in individual trade-offs among attributes, with range and top speed generally being highly valued. The sample of utility functions is then used to predict potential market shares for various kinds of electric vehicles as second cars. Demand is quite limited, except when (a) electric cars are considerably more advanced than anything likely to be available in the near future, and (b) consumers fear massive gasoline shortages. The latter effect derives from an observed “bias” in favor of electric autos, which is plausibly interpreted as a hedge against disruptions in the gasoline market.     

Impact of electric vehicles on existing car usage: A mixed multiple discrete–continuous extreme value model approach

This study investigates how the introduction of electric vehicles may influence the usage of existing cars. A survey of 250 households in South Korea is used to analyze a future automobile market that includes electric vehicles taking into account the heterogeneity of consumer preferences and usage patterns. Based on consumer preferences, the future market share of various vehicles is estimated and the impact of promoting the usage of electric vehicles by government subsidization and tax incentives is analyzed.     

Technical efficiency of automobiles – A nonparametric approach incorporating carbon dioxide emissions

We conduct an empirical analysis of the technical efficiency of cars sold 2010 in Germany. The analysis is performed using traditional data envelopment analysis (DEA) as well as directional distance functions (DDF). The approach of DDF allows incorporating the reduction of carbon dioxide emissions as an environmental goal in the efficiency analysis. A frontier separation approach is used to gain deeper insight for diesel and gasoline cars. Natural gas driven cars and sport utility vehicles are also treated as different groups. The results show that the efficiency measurement is statistically yet not economically significantly influenced by the incorporation of carbon dioxide emissions. Moreover, we find that natural gas driven cars are highly inefficient even if the reduction of emissions is accounted for in the analysis.     

Forecasting automobile demand using disaggregate choice models

This paper presents a simulation model of the American automobile market. The simulation model combines a disaggregate model of household automobile number and type choice with an econometric model of used vehicle scrappage and simple models of new car supply. For fixed vehicle designs, consumer and producer interactions determine new car sales, used car scrappage and consumer vehicle holdings. The model allows automobiles to be highly differentiated and consumers to be heterogeneous. Short-run equilibrium is defined as supply equal to demand for every vehicle type during each market period. The automobile stock then evolves slowly as new vehicles are added and old vehicles are removed during each period. An empirical application of the simulation model with 12 consumer groups and 131 vehicle types is used to forecast automobile holdings. A base case scenario is run for 1978–1984 and compared with the observed market behavior during this period. Several other simulations are then run comparing different gasoline price scenarios with the base case for 1984–1990.     

What is the market potential of plug-in electric vehicles as commercial passenger cars? A case study from Germany

Commercial passenger cars are a possible early market segment for plug-in electric vehicles (PEVs). Compared to privately owned vehicles, the commercial vehicle segment is characterized by higher mileage and a higher share of vehicle sales in Germany. To this point, there are only few studies which analyze the commercial passenger car sector and arrive at contradictory results due to insufficient driving profile data with an observation period of only one day. Here, we calculate the market potential of PEVs for the German commercial passenger car sector by determining the technical and economical potential for PEVs in 2020 from multi-day driving profiles. We find that commercial vehicles are better suited for PEVs than private ones since they show higher average annual mileage and drive more regularly. About 87% of the analyzed three-week vehicle profiles can technically be fulfilled by battery electric vehicles (BEVs) with an electric driving range of about 110 km while plug-in hybrid electric vehicles (PHEVs) with an electric range of 40 km could obtain an electric driving share of 60% on average. In moderate energy price scenarios, PEVs can reach a market share of 2–4% in the German commercial passenger car sales by 2020 and especially the large commercial branches (Trade, Manufacturing, Administrative services and Other services) are important. However, our analysis shows a high sensitivity of results to energy and battery prices as well as electric consumptions.     

Real-world gaseous and particle emissions of a Bi-fuel gasoline/CNG Euro 6 passenger car

The objective of the present study is the assessment of the environmental impact of a bivalent (bi-fuel) vehicle, running either on gasoline or compressed natural gas (CNG). To that aim, a Euro 6 passenger car was tested under various real-world driving conditions. In order to cover the full range of conventional powertrains currently in the market, the tests were also repeated on a Euro 6 diesel passenger car. Both cars were driven in two routes, the first complying with the regulation limits and the second going beyond them. Carbon monoxide (CO), nitrogen oxides (NO_x) and particle number (PN) emissions were recorded using a Portable Emissions Measurement System (PEMS). Apart from the aggregated emission levels, in g/km, the exact emission location along the route was also assessed. Natural gas proved beneficial for CO and PN emissions, the level of which always remained below the respective legislation limits. On the other hand, under the dynamic driving conditions with gasoline, the relevant limits were exceeded. Cold start, occurring at the beginning of the urban part, and motorway driving were identified as major contributors to total emissions, especially in gasoline mode. However, the application of natural gas was associated with a penalty in NO_x emissions, which were significantly increased as compared to gasoline. Local peaks within the urban part were identified in CNG mode. In any case, the diesel vehicle was by far the highest NO_x emitter.     

Changes in fuel economy: An analysis of the Spanish car market

This paper estimates the role that technological change and car characteristics have played in the rate of fuel consumption of vehicles over time. Using data from the Spanish car market from 1988 to 2013, we estimate a reduced form equation that relates fuel consumption with a set of car characteristics. The results for the sales-weighted sample of vehicles show that energy efficiency would have improved by 30% and 42% for petrol and diesel cars respectively had car characteristics been held constant at 1988 values. However, the shift to bigger and more fuel-consuming cars reduced the gains from technological progress. Additionally, using the results of the fuel equation we show that, besides a natural growth rate of 1.1%, technological progress is affected by both the international price of oil and the adoption of mandatory emission standards. Moreover, according to our estimations, a 1% growth in GDP would modify car characteristics in such a way that fuel consumption would increase by around 0.23% for petrol cars and 0.35% for diesel cars.     

Hybrid- and battery-electric vehicles offer low-cost climate benefits in China

Car ownership in China is expected to grow dramatically in the coming decades. If growing personal vehicle demand is met with conventional cars, the increase in greenhouse gas emissions will be substantial. One way to mitigate carbon dioxide (CO₂) emissions from passenger travel is to meet growing demand for cars with alternative vehicles such as hybrid- and battery-electric vehicles (HEVs and BEVs). Our study examines the cost-effectiveness of transitioning from conventional cars to HEVs and BEVs, by calculating their marginal abatement cost (MAC) of carbon in the long-run. We find that transitioning from conventional to hybrid and battery electric light-duty, four-wheel vehicles can achieve carbon emissions reductions at a negative cost (i.e. at a net benefit) in China. In 2030, the average MAC is estimated to be about −$140/ton CO₂ for HEVs and −$515/ton CO₂-saved for BEVs, varying by key parameters. The total mitigation potential of each vehicle technology is estimated to be 1.38 million tons for HEVs and 0.75 million tons for BEVs.     

Impacts of highly automated vehicles on travel demand: macroscopic modeling methods and some results

Automated vehicles (AV) will change transport supply and influence travel demand. To evaluate those changes, existing travel demand models need to be extended. This paper presents ways of integrating characteristics of AV into traditional macroscopic travel demand models based on the four-step algorithm. It discusses two model extensions. The first extension allows incorporating impacts of AV on traffic flow performance by assigning specific passenger car unit factors that depend on roadway type and the capabilities of the vehicles. The second extension enables travel demand models to calculate demand changes caused by a different perception of travel time as the active driving time is reduced. The presented methods are applied to a use case of a regional macroscopic travel demand model. The basic assumption is that AV are considered highly but not fully automated and still require a driver for parts of the trip. Model results indicate that first-generation AV, probably being rather cautious, may decrease traffic performance. Further developed AV will improve performance on some parts of the network. Together with a reduction in active driving time, cars will become even more attractive, resulting in a modal shift towards car. Both circumstances lead to an increase in time spent and distance traveled.

     

A valuation of the environmental performance of vehicles: an analysis and comparison of two methodologies

The European Clean Vehicle Directive was introduced in 2009 to create an obligation on public authorities to take into account the impact of energy consumption, carbon dioxide (CO₂) emissions and pollutant emissions into their purchasing decisions for road transport vehicles. This should stimulate the market for clean and energy-efficient vehicles and improve transport's impact on environment, climate change and energy use. Therefore the so-called ‘Operational Lifetime Cost’ of a vehicle is calculated, divided into the cost for energy consumption, CO₂ and pollutant (nitrous oxide, particulate matter, non-methane hydrocarbons) emissions. In Belgium, a different methodology has been developed to calculate the environmental impact of a vehicle, called ‘Ecoscore’, based on a well-to-wheel approach. More pollutants are included compared to the Clean Vehicle methodology, but also indirect emissions are taken into account. In this paper, both methodologies are compared and used to analyze the environmental performance of passenger cars with different fuel types and from different vehicle segments. Similar rankings between both methodologies are obtained; however, the large impact of energy use (and CO₂ emissions) in the Clean Vehicle methodology disadvantages compressed natural gas cars, as well as diesel cars equipped with particulate filters, compared to the Ecoscore methodology.     

Electric vehicles and the urban environment

Abstract

Due to the increased traffic volume, especially in urban areas, cars have become the dominant source of atmospheric pollution. Actions taken to limit the pollution have not been able to counteract the polluting effect of this increase in cars. Limited petroleum resources have initiated the search for alternative fuels for vehicles. These alternatives, except for hydrogen and electricity, will however only give a limited decrease of pollution and for some components, such as aldehydes, the pollution will increase.

Electric vehicles are attractive from both energy and environmental points of view and substantial development programmes are devoted to high energy density batteries which are expected to increase the range and market for this alternative.

The scope of this paper is to compare the overall atmospheric pollution for electric vehicles with the corresponding figures for internal combustion engined (ICE) vehicles using either gasoline or such alternatives as methanol and liquid petroleum gas.

It is shown that the total atmospheric emission for electric vehicles, including what is produced from the power plant, would on a per mile basis be 20% of the comparative figure for an ICE vehicle meeting Californian legislation, which is among the most stringent in the world. For ground emission, which is the most important parameter regarding influence on man and environment the corresponding figure will be substantially lower. Also, the noise level for electric vehicles is radically lower than for cars with internal combustion engines.     

Who switches to hybrids? A study of a fuel conversion program in Colombia

Air pollution from mobile sources is an important environmental problem in larger cities. In 2001, a program was implemented to encourage the use of natural gas in vehicles in the Aburrá Valley in Colombia, with incentives to convert small cars from gasoline and diesel to hybrid engines with natural gas, most notably a cash subsidy. Using a survey administered to both commercial and private car owners we study the determinants of conversion under this fuel conversion program. We thus obtain information about the reasons for adoption of new technologies in vehicles. This allows us to discuss the possible outcomes of this type of policy. Results show that a large part of owners who switched would have done it anyway without the subsidy. Based on the findings, commercial vehicles are most likely to be converted to natural gas vehicles.     

Real-world gaseous emission characteristics of Euro 6b light-duty gasoline- and diesel-fueled vehicles

To accurately investigate vehicle emissions that have become major contributors to global air pollutants and greenhouse gases, test conditions have been transferred from laboratory type approval test cycles to real-world driving conditions. In this study, the real-world driving emissions of carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NO_x), and carbon dioxide (CO₂) from one gasoline and two diesel Euro 6b light-duty passenger vehicles were investigated by a portable emission measurement system (PEMS) in Lyon, France. NO_x and CO₂ emission controls remain critical to addressing the real-world driving emissions of Euro 6b vehicles. Notably, the tested gasoline vehicle emitted higher CO₂ emissions than diesel vehicles on all types of roads, especially on the urban road with an excess of 29.3–48.3%. The highest emission factors of gaseous pollutants generally occurred on the motorway for the gasoline vehicle, while on the urban road for diesel vehicles. In particular, for high-speed driving conditions, the gasoline vehicle gaseous emissions, especially NO_x emissions, were more affected by acceleration than diesel vehicle emissions. In addition, the CO emissions, especially THC emissions, for the gasoline vehicle, were more influenced by warm-start, especially cold-start, than those for diesel vehicles.     

Consumer attitudes about electric cars: Pricing analysis and policy implications

As electric vehicles (EVs) become more readily available, sales will depend on consumers’ interest and understanding. A survey of consumer attitudes on electric cars was conducted in Manitoba from late 2011 to early 2012. It utilizes two price assessment methods. The van Westendorp price sensitivity method (PSM) shows the acceptable price range for EVs to be $22,000–27,500. This range closely matches average price range for sales of conventional cars during the same period. The willingness-to-pay method reveals consumers are unwilling to pay large premiums for EVs, even when given information on future fuel savings. A consumer group with experience or exposure to EVs is somewhat different. Nearly 25% of these people are willing to pay a premium of up to $10,000. Different interpretations can be drawn from these responses, calling for further research. An apparent policy opportunity involves consumer education to enhance knowledge and facilitate EV purchase decisions. Survey results also support the hypothesis that EV rollout has focused too much on technology, and not enough on consumers.     

Heavy commercial vehicles‐following behavior and interactions with different vehicle classes

This work investigates the effect of heavy commercial vehicles on the capacity and overall performance of congested freeway sections. Furthermore, the following behaviors of heavy commercial vehicles and its comparison with passenger cars are presented. Freeways are designed to facilitate the flow of traffic including passenger cars and trucks. The impact of these different vehicle types is not uniform, creating problems in freeway operations and safety particularly under heavy demand with a high proportion of heavy vehicles. There have been very few studies concerned with the traffic behavior and characteristics of heavy vehicles in these situations. This study draws on extensive data collected over a long stretch of freeway using videotaping and surveys at several sites. The collected data were firstly used to study the interaction between heavy vehicles and passenger cars. Through a detailed trajectory analysis, the following behaviors of 120 heavy vehicles were then analyzed to provide a thorough understanding of heavy vehicles‐following behavior mechanism. The results showed a significant difference in the following behavior of heavy vehicles compared with other vehicles. Copyright © 2011 John Wiley & Sons, Ltd.     

Testing electric vehicle demand in ‘hybrid households’ using a reflexive survey

The debate over electric vehicles (EVs) pivots largely on issues of market demand: will consumers purchase a vehicle that provides substantially less driving range, yet can be refueled at home, than an otherwise comparable gasoline vehicle? Also, what role do other unique attributes of EVs play in the purchase decision? Most previous studies find that limited driving range is a serious market barrier; many of those same studies ignore or under-value other novel attributes. To probe these future consumer decision processes deeply and robustly, we first devised and conducted detailed, interactive and experiment-oriented interviews. Then, incorporating what we learned, we designed an innovative mail survey and administered it to 454 multi-car households in California. The four-stage mail survey included a video of EV use and recharging and other informational material, completion of a 3-day trip diary and map of activity locations, and vehicle choice experiments. In addition to propulsion systems, respondents made choices of body styles, driving ranges, and other features. We formalized and tested what we call the hybrid household hypothesis: households who choose EVs will be purposefully diversifying their vehicle holdings to achieve the unique advantages of different propulsion systems. The hypothesis is supported, given the assumptions in our experimental design. In fact, a significantly larger number of EVs are chosen than the minimum number that would support our hypothesis. We find that purchases of battery-powered EVs by hybrid households would account for between 7 and 18% of annual light duty vehicle sales in California. EVs sold to fleets and other households would be in addition to those identified by this study.     

Optimal development of alternative fuel station networks considering node capacity restrictions

A potential solution to reduce greenhouse gas (GHG) emissions in the transport sector is the use of alternative fuel vehicles (AFV). As global GHG emission standards have been in place for passenger cars for several years, infrastructure modelling for new AFV is an established topic. However, as the regulatory focus shifts towards heavy-duty vehicles (HDV), the market diffusion of AFV-HDV will increase as will planning the relevant AFV infrastructure for HDV. Existing modelling approaches need to be adapted, because the energy demand per individual refill increases significantly for HDV and there are regulatory as well as technical limitations for alternative fuel station (AFS) capacities at the same time. While the current research takes capacity restrictions for single stations into account, capacity limits for locations (i.e. nodes) – the places where refuelling stations are built such as highway entries, exits or intersections – are not yet considered. We extend existing models in this respect and introduce an optimal development for AFS considering (station) location capacity restrictions. The proposed method is applied to a case study of a potential fuel cell heavy-duty vehicle AFS network. We find that the location capacity limit has a major impact on the number of stations required, station utilization and station portfolio variety.     

Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China

We model consumer preferences for conventional, hybrid electric, plug-in hybrid electric (PHEV), and battery electric (BEV) vehicle technologies in China and the U.S. using data from choice-based conjoint surveys fielded in 2012–2013 in both countries. We find that with the combined bundle of attributes offered by vehicles available today, gasoline vehicles continue in both countries to be most attractive to consumers, and American respondents have significantly lower relative willingness-to-pay for BEV technology than Chinese respondents. While U.S. and Chinese subsidies are similar, favoring vehicles with larger battery packs, differences in consumer preferences lead to different outcomes. Our results suggest that with or without each country’s 2012–2013 subsidies, Chinese consumers are willing to adopt today’s BEVs and mid-range PHEVs at similar rates relative to their respective gasoline counterparts, whereas American consumers prefer low-range PHEVs despite subsidies. This implies potential for earlier BEV adoption in China, given adequate supply. While there are clear national security benefits for adoption of BEVs in China, the local and global social impact is unclear: With higher electricity generation emissions in China, a transition to BEVs may reduce oil consumption at the expense of increased air pollution and/or greenhouse gas emissions. On the other hand, demand from China could increase global incentives for electric vehicle technology development with the potential to reduce emissions in countries where electricity generation is associated with lower emissions.     

Heterogeneous consumer preferences for alternative fuel cars in China

This paper models consumer preferences for alternative fuel cars and conventional, petrol fueled cars in China. It compares discrete choice model specifications where each specification reflects how consumers choose between alternative fuel cars and conventional types of cars. We find that, in China, consumers differentiate between the types of alternative fuel cars and are more likely to consider switching from petrol fuel vehicles to hybrid than to electric cars. Segmentation analysis is used to explore groups of consumers and their likelihood of adopting alternative fuel cars.     

Electric vehicles: How much range is required for a day’s driving?

One full year of high-resolution driving data from 484 instrumented gasoline vehicles in the US is used to analyze daily driving patterns, and from those infer the range requirements of electric vehicles (EVs). We conservatively assume that EV drivers would not change their current gasoline-fueled driving patterns and that they would charge only once daily, typically at home overnight. Next, the market is segmented into those drivers for whom a limited-range vehicle would meet every day’s range need, and those who could meet their daily range need only if they make adaptations on some days. Adaptations, for example, could mean they have to either recharge during the day, borrow a liquid-fueled vehicle, or save some errands for the subsequent day. From this analysis, with the stated assumptions, we infer the potential market share for limited-range vehicles. For example, we find that 9% of the vehicles in the sample never exceeded 100 miles in one day, and 21% never exceeded 150 miles in one day. These drivers presumably could substitute a limited-range vehicle, like electric vehicles now on the market, for their current gasoline vehicle without any adaptation in their driving at all. For drivers who are willing to make adaptations on 2 days a year, the same 100 mile range EV would meet the needs of 17% of drivers, and if they are willing to adapt every other month (six times a year), it would work for 32% of drivers. Thus, it appears that even modest electric vehicles with today’s limited battery range, if marketed correctly to segments with appropriate driving behavior, comprise a large enough market for substantial vehicle sales. An additional analysis examines driving versus parking by time of day. On the average weekday at 5 pm, only 15% of the vehicles in the sample are on the road; at no time during the year are fewer than 75% of vehicles parked. Also, because the return trip home is widely spread in time, even if all cars plug in and begin charging immediately when they arrive home and park, the increased demand on the electric system is less problematic than prior analyses have suggested.