Fuel Economy Label Research Articles

Comparison of On-Road Highway Fuel Economy and All-Electric Range to Label Values: Are the Current Label Procedures Appropriate for Battery Electric Vehicles?

<div class="section abstract"><div class="htmlview paragraph">As consumers transition from internal combustion engine (ICE)-powered vehicles to battery electric vehicles (BEV), they will expect the same fuel economy label-to-on-road correlation. Current labeling procedures for BEVs allow a 0.7 or higher multiplier to be applied to the unadjusted fuel economy and range values. For ICE-powered vehicles, the adjustment factor decreases with increasing unadjusted fuel economy and can be lower than 0.7. To better inform consumers, starting in 2016, Car and Driver added an on-road highway fuel-economy test, conducted at 120 kph (75 mph), that augments the performance metrics that it's been measuring since the 1950s. For electric vehicles, testing includes an evaluation of the all-electric range.</div><div class="htmlview paragraph">The on-road test results were aligned with the certification information for each vehicle model including unadjusted and label fuel economy and range, road load force coefficients, and labeling options. Tractive energy and kinetic energy available for regenerative braking were computed from the certification information to evaluate the differences between the on-road testing and chassis-rolls testing conducted during the certification process.</div><div class="htmlview paragraph">Based on these results, the highway fuel economy label tends to be a very good predictor of the fuel economy observed during the on-road test at real highway speeds with vehicles powered by an ICE. However, most BEVs tested to date fall short of both their electric consumption and range label values. For BEVs, the difference between the label and on-road consumption and range is further exacerbated by other factors, such as extreme temperatures and suggestions by automakers to charge to less than 100 percent to extend battery life. Consequently, these results support the need to re-evaluate the labeling procedures for this emerging technology as it continues to become increasingly prominent in the marketplace.</div></div>

A multivariable output neural network approach for simulation of plug-in hybrid electric vehicle fuel consumption

This study is laser focused on the simulation of fuel consumption and fuel economy label parameters of plug-in hybrid electric vehicles. While fuel economy is a key factor in the design of plug-in hybrid electric vehicles, a fuel economy label can educate customers about the economic advantage of purchasing a particular car. The fuel economy label of a PHEV consists of parameters like driving range, electrical energy consumption, fuel economy for city, highway, and combined use, battery recharge time, and fuel consumption rates. The study used an inverse function model of an artificial neural network to simulate and calculate the parameters of the fuel economy labels of PHEVs. Firstly, the selected parameters of the fuel economy label of plug-in hybrid electric vehicles were used to develop a single output model. The output variable of the single output model was then merged with dummy functions to form input variables for the inverse function model. The output variables simulated were engine size in litres; estimated driving range when the battery is fully charged in km, battery recharged time in hours, city fuel consumption (L/100 ​km), highway fuel consumption (L/100 ​km), combined fuel consumption (L/100 ​km), estimated driving range when the tank is full, carbon dioxide (CO2) emission in grams/km, electric motor power in kW, number of cylinders, and electrical charges consumed in kWh/100 ​km. Different cases of input variables were considered for the inverse function model. The accuracy of the model was 29.1 times greater than that of the conventional inverse artificial neural network model.

MPG, fuel costs, or savings? Exploring the role of information framing in consumer valuation of fuel economy using a choice experiment

Despite the large body of literature, there is still considerable debate and uncertainty about how consumers value fuel economy. This study explores how the presentation of fuel economy information can influence valuation using a stated choice experiment with comparative experimental conditions. We randomly assigned a nationally representative sample of 1,612 intended vehicle purchasers in the United States to one of six conditions, which varied in their presentation of fuel economy information as follows: miles per gallon, annual fuel costs, five-year fuel cost, lifetime fuel cost, amount of money saved/spent over five years compared to the average vehicle per class, and the full government-mandated fuel economy label (in the US). We find that consumer valuation of fuel economy is causally impacted by the information presented. In particular, we observe significantly higher willingness-to-pay values for participants in the condition with the full fuel economy label, relative to conditions only presented with the annual fuel cost, five-year fuel cost, and spend/save comparison. Valuation also varied with the demographic characteristics of participants: fuel economy was more highly valued among older participants and those that anticipated a relatively lower purchase price for their next vehicle. This study suggests that the observed inconsistencies in consumer valuation of fuel economy in the literature may stem in part from differences in the framing of fuel economy information across studies – at least for stated preference studies.

신형식 자동차 적용에 따른 연비 보정식 검토에 관한 연구

자동차 표시연비는 국가적으로 에너지관리 지표로서 활용되며, 자동차 제작사의 기술개발을 유도하고, 소비자 차량구매 시 정보제공의 역할을 담당하고 있다. 하지만 정부의 표시연비가 체감연비와 상이하다는 소비자 불만이 지속되어 정부는 보다 정확한 표시연비 측정을 위해 미국의 5-cycle 시험방법을 국내 차량 기준에 맞게 재설정하여 도입하였다. 본래는 다양한 환경조건 및 주행패턴이 반영된 5개의 시험모드를 모두 주행함으로써 측정된 결과 값을 표시연비로 계산하는 방법이지만 소요되는 자원의 급격한 증가에 따른 충격을 완화하기 위하여 2개의 시험모드(도심(FTP-75 mode), 고속도로(HWFET mode))의 결과 값을 5-cycle 시험법으로 계산된 연비 값과 동등한 수준으로 산출하는 5-cycle 보정식을 사용하고 있다. 이 보정식은 2011년에 30대 차량의 5-cycle 시험방법으로 산출되었으나 최근 자동차 기술의 급속한 발전으로 인한 신형식 자동차에 대한 기존 5-cycle 보정식에 대한 검토가 필요할 것으로 판단되었다. 본 연구에서는 최근 기술이 적용된 14대의 신형식 자동차를 대상으로 기존과 동일한 시험 방법을 통해 시험모드별 연비 특성을 확인하고, 기존에 개발된 보정식과 차이를 분석한 결과 기존 시험 차량 결과와 큰 차이를 보이지 않았으며 보정식 또한 최대 1.5% 이내의 오차로써 기존 연비 보정식은 현재의 자동차 기술발전에 따른 개선도에 크게 영향을 받고 있지 않음을 알 수 있었다. Fuel economy label will be used as a national indicator in energy management, leading to the development of car technology manufacturer and plays a role in providing consumer vehicle purchase information. But the government's fuel economy label is continued consumer complaint is different and diminishing fuel economy were introduced by the government to measure the exact fuel economy label than resetting the 5-cycle test method in the US for the domestic vehicle standards. Originally two test mode in order to reduce the impact of the sharp increase in the resources required but methods of calculating a measured result value by driving all of the five test mode a variety of environmental conditions and the running pattern is reflected to the fuel economy label (city( FTP-75 mode), highway(HWFET mode)) and using 5-cycle correction formula for calculating a fuel consumption value and the equivalent value to calculate the result of the 5-cycle test. The compensation was calculated expression 30s, 5-Cycle Test Method of vehicles in 2011 was considered necessary to review the existing 5-cycle correction formula for the New Type car due to the recent rapid development of automotive technology. In this study, recent technology is targeting 14 units New Type car applied over the same test method and the existing check test mode specific fuel economy properties and, as a result of analyzing the corrected expression differences that have already been developed with the existing test vehicle resulting large did not show the difference was found to correction formula also not getting the existing fuel correction expression significant effect on the improvement of the current automobile technology as a maximum error of less than 1.5%.

What is the Effect of Fuel Efficiency Information on Car Prices? Evidence from Switzerland

Inadequate information is often identified as a potential cause for the so-called “energy efficiency gap,” i.e., the sluggish pace of investment in energy efficiency technologies, which potentially affects a wide variety of energy-using goods, including road vehicles. To improve the fuel economy of vehicles, in 2003 Switzerland introduced a system of fuel economy and CO2 emissions labels for new passenger cars, based on grades from A (best) to G (worst). We have data for all cars approved for sale in Switzerland from 2000 to 2011. Hedonic regressions suggest that there is a fuel-economy premium, but do not allow us to identify whether the fuel economy label has an additional effect on car price, above and beyond the effect of fuel economy. To circumvent this problem, we turn to a sharp regression discontinuity design based on the mechanism used by the government to assign cars to the fuel economy label, which estimates the effect of the A label on price to be 6-11%. Matching estimators find this effect to be 5%.

Metric and Scale Design as Choice Architecture Tools

Interest is increasing in using behavioral decision insights to design better product labels. A specific policy target is the fuel economy label, which policy makers can use to encourage reduction in carbon dioxide emissions from transport-related fossil-fuel combustion. In two online experiments, the authors examine whether vehicle preferences can be shifted toward more fuel-efficient vehicles by manipulating the metric (consumption of gas vs. cost of gas) and scale (100 miles vs. 15,000 miles vs. 100,000 miles) on which fuel economy information is expressed. They find that preference for fuel-efficient vehicles is highest when fuel economy is expressed in terms of the cost of gas over 100,000 miles, regardless of whether the vehicle pays for its higher price in gas savings. The authors discuss the underlying psychological mechanisms for this finding, including compatibility, anchoring, and familiarity effects, and conclude that policy makers should initiate programs that communicate fuel-efficiency information in terms of costs over an expanded, lifetime scale.

Does the Swiss Car Market Reward Fuel Efficient Cars? Evidence from Hedonic Pricing Regressions, a Regression Discontinuity Design, and Matching

To correct market failures due to the presence of negative externalities associated with energy consumption, governments have adopted a variety of policies, including taxes, subsidies, regulations and standards, and information-based policies. For example, labels that clearly convey energy consumption rates, associated costs, and emissions of conventional pollutants and CO2, have been devised and used in the last two decades in several countries. In 2003, Switzerland introduced a system of fuel economy labels, based on grades ranging from A to G, where is A best and G is worst, to assist consumers in making decisions that improve the fleet’s fuel economy and lower emissions. We use a dataset documenting all passenger cars approved for sale in Switzerland each year from 2000 to 2011 to answer three key research questions. First, what is the willingness to pay for fuel economy? Second, do Swiss drivers — or Swiss auto importers on their behalf — appear to do a one-to-one tradeoff between car purchase price and savings on fuel costs over the lifetime of the car? Third, does the label have an additional effect on price, all else the same, above and beyond that of fuel efficiency alone? Hedonic pricing regressions that exploit the variation in fuel economy across make-models, and over time within make-models, suggest that there is a (modest) capitalization of fuel economy into car prices. The diesel premium, however, exceeds the future fuel cost savings made possible by diesel cars, even at zero discount rates. An alternate calculation suggests that the fuel economy premium is consistent with a very low discount rate (2.5%). We use a sharp regression discontinuity design (RDD) based on the mechanism used by the Swiss Federal Office of Energy to assign cars to the fuel economy label to see if the label has an independent effect on price, above and beyond that of the fuel economy. The RDD approach estimates the effect to be 6-11%. To broaden the fuel economy range over which we assess the effect of the A label, we also deploy matching estimators, and find that the effect of an A label on car price is approximately 5%.

Does the Swiss Car Market Reward Fuel Efficient Cars? Evidence from Hedonic Pricing Regressions, Matching and a Regression Discontinuity Design

To correct market failures due to the presence of negative externalities associated with energy consumption, governments have adopted a variety of policies, including taxes, subsidies, regulations and standards, and information-based policies. For example, labels that clearly convey energy consumption rates, associated costs, and emissions of conventional pollutants and CO2, have been devised and used in the last two decades to promote rational decisions, but it is unclear whether labeling schemes have realigned consumer and producer behaviors. In 2003, Switzerland introduced a system of fuel economy labels, based on grades ranging from A to G, where is A best and G is worst, to assist consumers in making decisions that improve the fleet’s fuel economy and lower emissions. We use a dataset documenting all passenger cars approved for sale in Switzerland each year from 2000 to 2011 to answer three key research questions. First, what is the willingness to pay for fuel economy? Second, do Swiss drivers — or Swiss auto importers — appear to do a one-to-one tradeoff between car purchase price and savings on fuel costs over the lifetime of the car? Third, does the label have an additional effect on price, all else the same, above and beyond that of fuel efficiency alone? Hedonic pricing regressions that exploit the variation in fuel economy across make-models, and over time within make-models, suggest that there is a (modest) capitalization of fuel economy into car prices. The Diesel premium, however, exceeds the future fuel cost savings made possible by Diesel cars, even at zero discount rates. An alternate calculation suggests that the fuel economy premium is consistent with a very low discount rate (2.5%). We use matching estimators and a sharp regression discontinuity design (RDD) based on the mechanism used by the Swiss Federal Office of Energy to assign cars to the fuel economy label to see if the label has an independent effect on price, above and beyond that of the fuel economy. The matching estimator indicates that the A-label effect on car price is approximately 5%. The RDD approach estimates the effect to be 6-11%.

Battery Charge Balance and Correction Issues in Hybrid Electric Vehicles for Individual Phases of Certification Dynamometer Driving Cycles as Used in EPA Fuel Economy Label Calculations

Battery Charge Balance and Correction Issues in Hybrid Electric Vehicles for Individual Phases of Certification Dynamometer Driving Cycles as Used in EPA Fuel Economy Label Calculations