New car test and actual fuel economy: yet another gap?

New car test and actual fuel economy: yet another gap?

Transport Policy 1994 l(4)257-265 New car test and actual fuel economy: yet another gap? Lee Schipper and Wienke Tax Energy Analysis Program, Califor...

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Transport Policy 1994 l(4)257-265

New car test and actual fuel economy: yet another gap? Lee Schipper and Wienke Tax Energy Analysis Program, California,



CA 94720,

and Environment

Division, Lawrence



University of


Automobile fuel economy derived from tests varies greatly from that obtained from actual daily use. This ‘gap’ appears to be growing because tests do not reflect real-world driving and because driving is increasingly becoming less fuel-efficient. Comparisons among the US, Canada and four European countries find that automobile fuel economy tests tend to understate fuel use by 1525%. Since automobile fuel use is at the center of much environmental concern, the present analysis of new-car fuel economy suggests some mitigation techniques to close the test/actual fuel economy gap. Keywords:

new automobile

fuel economy,


fuel use, fuel economy tests

Automobiles are significant sources of air pollution, including carbon dioxide, a major greenhouse gas. They use as much as two-thirds of the liquid fuels consumed by the transportation sector. Not surprisingly, then, automobile fuel use is subject to scrutiny by a wide range of energy analysts and policy makers. Unfortunately, obtaining data that accurately reflect fuel consumed in transportation is one of the most serious problems in analyzing international energy use in automobiles (Schipper er al., 1993a; 1993b). There is a relatively significant gap between tested fuel economy and that actually achieved by consumers on the road in all countries, and it appears to be increasing over time in some. In 1977, the US Department of Energy (DOE) began studying the shortfall between the predicted US Environmental Protection Agency (EPA) fuel economy and in-use fuel economy by consumers. Between 1977 and 1985, a large body of information was accumulated by DOE, EPA, car manufacturers and oil companies on this shortfall, or gap, issue. When real energy prices stabilized and even declined in the mid-1980s interest in the gap declined. As fuel use and carbon dioxide emissions have reentered the science and policy debates due to concerns about global warming, a renewed interest in the gap has arisen both in the USA and in Europe. We surveyed the literature in several countries to see what the gap experience is and have discovered that despite differences in test measurement methods, data collection and analysis techniques, significant gap similarities exist across the countries we studied. The problem of measuring fuel economy is particularly difficult for new cars, due to the gap between test and actual fuel economy. Part of the problem is how the components of the driving cycle are weighted, part is intrinsic 0967-070X/94/04025749

0 1994 Butteworth-Heinemann


to the tests, and part can be attributed to driver behavior. The test is carried out in a fully-warmed up car on a predetermined driving cycle (for the EEC), or on a machine (the USA, the Deutsches Institut fur Normung (DIN)). A figure is then calculated by weighting the results for various parts of the cycle representing different speeds and driving conditions. It is widely known that, while useful indicators of the relative fuel economy of different new cars (Deutsches Institut fur Wirtschaftsforchung (DIW), 1987), new-car fuel economy tests are a poor measure of actual fuel use. Our survey of the literature suggests that real consumption per kilometer is 15-25% more than test consumption as reported by national authorities (Bosseboeuf, 1988; Mintz et al,. 1993; Watson, 1989; Maples, 1993; Westbrook and Patterson, 1989). The clear exception to this general rule is Sweden, where the gap is significantly lower (KOV, 1989). This exception will be discussed in a later section. Figure 1 shows the sales-weighted new-car intensities for a variety of OECD countries. Changes in new-car fuel economy are an important indicator of future fuel economy. They should reveal the short-term reactions of car manufacturers and buyers to changes in fuel prices or new policies. Since a change in new-car fuel economy may be a policy goal stimulated by changes in fuel prices, new car taxation, or standards such as the CAFE standards in the USA (Greene and Duleep, 1991), observers must see a change in order to judge the effectiveness of the policies. The Appendix summarizes the gap between test fuel economy and actual use. This gap arises for several reasons. The effects of these variations tend to cause test values to deviate further and further from actual conditions. 257

New car test and actualfuel

economy: yet another gap?: L Schipper and W Tax


s-4 + -t8



us* G. Britain Japan Sweden+ W. Germany+ Norway+ Italy* Denmark


fi i973

Figure 1


New car fuel economy,




test values

*Including diesel; USA includes light trucks. +Excluding diesel.

The formulae used to construct the ‘real’ cycle from road test data typically underrepresent the proportion of city (i.e. congested and stop-and-start) to urban highway (i.e. uncongested, steady, high-speed) driving. The actual conditions in all parts of the cycle, including hills, weather, road curvature, road surface, etc., are themselves worse than modeled, leading to increased actual fuel consumption. Generally, these factors cannot be accounted for by adjusting the dynamometer tests, although road tests could be adjusted. Driver behavior, i.e. speed, acceleration, frequency of cold starts, reflects patterns that themselves are more fuel-intensive than the patterns used in tests. Lack of maintenance of the vehicle may also decrease fuel economy. The tests often do not reflect seasonal differences in fuel consumption; this was noted particularly in Sweden, Canada and France. The test values do not represent cars actually sold, either because the cars tested are somehow optimized for testing or because cars actually bought contain more fuel-intensive features (larger engines, turbocharging, more accessories) than is reflected in either the tests or the sales-weightings. Additionally, the gap may be large if the vehicles counted in the weightings do not accurately represent the entire new-car fleet. In Denmark, for example, authorities publish values based on only the top 10 models sold, formerly the top 20. Our tabulation of the entire new-car fleet in 1990 shows that this practice introduces a small inaccuracy. The top 10 car models sold had a weighted fuel intensity of 7.67 litres/lOO km; the top 20, one of 7.47 l/100 km, and the entire run of models, 7.61 l/lOOkm.’ ‘Based on analysis Finance. 258

of sales data supplied by the Danish Ministry


Switching from 20 to only 10 models (between 1988 and 1990) to produce the weightings introduced inaccuracies that were as large as the actual changes in weighted fuel economy over several years. The Swedish practice of performing the weightings by brand name, not by individual model, allows for the influence of larger engines or fuel-intensive options that raise fuel intensity to escape the figures calculated using ‘base models’. Thus, even the weighting procedures can be inaccurate. Since power, size and performance have increased in recent years, these procedural issues will tend to increase the gap between actual and test fuel economy. There are other compelling reasons to believe that this gap may be growing (Westbrook and Patterson, 1989; Bosseboeuf, 1991; DIW, 1987). The exception to this general rule is Sweden, where the gap is significantly lower. Possible increases in the size of the gap make this problem even more contentious: the real-world achievement, a specified level of fuel economy, diverges significantly from what was promised. Fuel efficiency goals may be chosen which all parties think can be met, given the indicators used to measure progress. Obviously, for West Germany the ‘real world’ saw little progress towards improved fuel efficiency as implied by static test results. By contrast, the pledges of the auto industry in Sweden to bring the weighted average fuel intensity down to 8.5 l/100 km were more closely achieved since the sales-weighted average in the late 1980s lay in the interval 8.2-8.3 l/100 km and the Swedish test values themselves lay close to ‘reality’. On the other hand, the overall stock showed only about a 10% improvement. Was this because the tests and surveys were incorrect indicators of real fuel economy, or because the approach taken to estimate real fuel economy of the fleet was flawed? Resolving this uncertainty over the fuel economy gap is particularly important for West Germany and France, where overall improvement in fleet fuel economy between 1973 and 1989 appears to be less than 15%, although the changes in new-car fuel economy, as published by national authorities, are apparently much larger. Which version is correct? In Sweden and the UK, by contrast, the changes in reported new-car fuel intensity figures between 1978 and 1990 are less than 18%, and the apparent changes in the intensity of the fleet even smaller. What really happened? Clearly, if the elements of the four factors used to determine actual fuel economy are fraught with uncertainties, these changes in fuel economy might have to accumulate in the stock over several years before anything definite can be said about the real impact of changes in new-car fuel economy. Since the fleet fuel economy itself is uncertain, this leads to even more delays until results are clear. Additionally, not all changes in new-car fuel economy in recent years fit the trend towards lower fuel consumption; Sorrel1 explores this factor in his study (1992). Below we review how leading experts assess this gap in six countries. The review confirms the problems set Tmspo,_r Policy 1994

Volume I Number 4

Nemocar- test and actual fuel economy: yet another-gap?: L Schipper and W Tax

out above. First, the gap seems to be worsening in most countries. Secondly, the influence of driver behavior is probably more important than previously thought. Thirdly, actual surveys (or on-board metering) can indicate the magnitude of the gap, but these surveys only reveal but cannot resolve, the very real gap between what fuel-using technology promises to save and what drivers manage to use. Finally, there is anecdotal evidence of the worsening of actual fuel economy in a given car over time. To these issues we add a fifth. It is clear from our reading of the various studies that the fuel economy gap can be reduced through the use of a good set of weightin2 factors for fractions of city, highway and road travel, as the data from Great Britain show. But these weighting factors vary over time and, according to the British and French sources, they vary between individual drivers and even car models. For the purposes of predicting actual fuel economy for any individual driver, the tests still perform poorly, although they can be re-weighted to do a better job than current test weightings. The fuel use of the entire new-car fleet or stock can still be modeled from the results for each car. Clearly, both available technology and driver behavior affect fuel efficiency in cars. Because of the influence of dr:ver behavior, differences between actual road conditions and test conditions, and differences in weighting text cycles, authorities should consider issuing two figures for new-car fuel economy: (1) test results, reflecting changes in technology, and (2) driver-based survey results, reflecting behavior and actual use conditions. The surveys could cover the entire stock, but should particularly reflect driver experience with recent model-year cars, as in the Canadian survey. The presence of the gap even suggests that further efforts to improve fuel use technology may suffer from decreasing returns because of the impact of driver behavior. It may become necessary to restrain behavior which leads to fuel-intensive driving before pushing on to stimulate further technological progress. In other words, speed limits, fuel taxes, and other policies that discourage fuel-intensive driving styles may be a more important next step than unleashing new fuel-efficient technologies.

Review of country experience Below we review the experience tries.

from six major coun-


In France, ‘actual’ fuel intensity is determined in two ways. Surveys are used to measure fuel use and driving distances per year in a large number of vehicles. These results are multiplied to give total gasoline and total diesel fuel use for automobiles. The figures are checked against top-down calculations carried out by first estimating uses of these fuels for other vehicles and then dividing the residual by the total number of cars and yearly distances driven. These two figures are in turn buttressed by a wide variety of indicators and surveys,

including consumer expenditure surveys, travel surveys, and even surveys of the odometer readings of used cars. Analysts in France are constantly revising both the diesel and the gasoline series. Rapid growth in the popularity of diesel-fueled cars for use other than as taxis or for commercial purposes has driven down the average yearly driving distances for diesel cars and has forced authorities to change their methods of accounting for diesel fuel. Additionally, a variety of factors introduce uncertainty into the driving distance determination used to measure fleet fuel economy. When these uncertainties are worked through the calculations, the results tend to reduce the improvement of fuel economy in the fleet as a whole. Carefully designed surveys are required to separate real changes from the noise in the data. The Observatoire d’Energie and the Agence d’Environment et Maitrise d’Energie (ADEME) has published data that show that the sales-weighted fuel intensities of new cars dropped by nearly 30% between 1975 and 1989 (Figure 2), while the intensity of the whole fleet dropped by no more than 10%. Figure 2 also shows an estimate by ADEME of the unit consumption of the stock in each year as if each year’s new cars had the same real consumption as measured by tests. The divergences are striking. According to this analysis, the stock consumption should have fallen from 8.55 l/lOOkm slowly to 8.33 l/100 km in 1980, then tumbled to 7.4 l/100 km by 1986. The ‘actual’ consumption was carefully measured at 9.75 l/100 km in 1982. Other estimates of the ‘actual’ consumption point to about 8.5 l/lOOkm in 1976, rising to nearly 9 l/lOOkm in 1979, then falling to about 8.65 l/100 km in 1986 (and continuing to fall slowly thereafter). Clearly, there is a large fuel economy gap. While measurement of ‘actual’ consumption is subject to all the uncertainties discussed in the previous section, there is clearly something also wrong with ‘test’ fuel use of cars. Accordingly, ADEME (actually its predecessor, AFME) initiated a series of investigations in the mid1980s into fuel use in new automobiles under real driving conditions (Bosseboeuf, 1988). Travel diaries were kept for a sample of 1674 drivers and vehicles from the 1984 model year, each of whom made at least four tank fillings. Drivers estimated their driving over the three components of the standard Economic Commission for Europe (ECE) driving cycle, namely 90 kph (road), 120 kph (freeway) and urban (stop and go). Diesel and gasoline models of the most popular cars sold in France were studied. In all, roughly 30 drivers of each of 52 models were found and asked to participate. Results for each part of the cycle were found by regression, using total distance and consumption as a control. The aggregate indications were consistent with results from most other countries: actual consumption lay a full 26% over ‘test’ results. The deviation was larger for French-made than for foreign-made cars (29% vs. 21% respectively) although the number of foreign vehicles in the sample was quite small. The deviation from test was 40% on roads, 16% in the true urban cycle, but only 12% on freeways. Gasoline cars showed 259

New car-test and actual,fuel economy: yet another-gap?: L Schipper

and W Ta.y

behavior, which lead to opposite trends in fuel intensity. West Get-maq




z =.


kc 2 7.5 7 7.0 6.5 1970








Figure 2 The automobile fuel economy gap: France Source: ADEME,


Gasoline only.

a slightly greater deviation than did diesels. Many explanations were offered including the fact that the test cycles themselves only roughly approximate the total driving cycle, particularly when aggregated. The combined cycles tend to hide variations between cycles. Also, the presence of hills, speeds in excess of 130 km/hr, cold starts and other aspects of driver behavior all contribute to worsening of actual fuel economy relative to test. Looking further, however, the study found that the gap is greater for large cars than for small cars, and less than 20% for diesels. On the highway, diesels show only -x 4% gap. The French attribute much of this difference to behavior: drivers of the larger cars accelerate more and drive faster than those in small cars. Small cars show the smallest gap in cities, but the largest gap on open roads. Apparently, the type of car and the driving for which it was optimized play an important role in defining the gap between test and actual fuel economy. The gap in France is worsening over time. Using data from a different source which represented driving each year between 1978 and 1984 (but limited to only 10 models in each year), AFME found a marked increase in the gap after 1981, from about 20% (over all cycles) to over 30% based on this new data set. While there has been a real gain in fuel economy since 1981, the gain is smaller than that implied by succeeding model years’ test values. AFME suspected that the cars supplied for tests during the later years were ‘better’ than the average car and provided some comparisons of tests of the cars supplied and cars tested at random to support this position. Additionally, driver behavior may have changed in ways that worsened fuel economy. A fifth gear has become common which lowers the nominal fuel consumption, but this gear may not be properly used. Turbocharging adds a power boosting option that, through ineffective use by drivers, may draw more fuel than may be reflected in tests. And those thousands who switched from gasoline to diesel in the late 1980s were not fully familiar with the optimum way to drive a diesel car. Also, traffic itself worsened as the 1980s rolled on. In the final analysis, AFME notes that the gap represents a kind of conflict between possible fuel economy improvements due to new technology and driver 260

In West Germany, there are two figures for ‘test’ fuel economy. Each year the Deutsches Institute fiir Wirtschaftsforschung tabulates both indicators (DIW, 1987; 1992). DIW (Rielke, 1991) made available its more recent calculations, particularly those concerning new cars. One is a DIN standard that is based on a static machine test. The second is from actual road tests using the ECE 90/120/urban test, which DIW cites in its yearly fuel economy report. The gap in West Germany arises because of the divergence in these two tests; the gap between ‘test’ values reported for fuel economy and on-the-road values implied by DIW’s analysis of fuel use is actually much smaller than the gap between the DIN-estimated fuel economy and the ‘real’ fuel economy implied by the DIW analysis. Figure 3 shows these two ‘test’ values for gasoline cars, as well as the implied on-the-road average for the gasoline-powered fleet. The DIN tests were those used by the auto industry in tabulating theoretical improvements in weighted fleet efficiency, using static tests that imitate the ECE cycle of 90 kph/l20 kph/city traffic, which are then weighted l/3, l/3, l/3. The road test results resemble more closely those of the French survey, lying 21% above the DIN values in 1978, rising to a full 30% above these values in 198.5 and settling back to 26% in 1987. The differences for diesel rose as well, but were always smaller than those for gasoline, also similar to the French results. Since the gaps increase over time, the ‘real’ fuel economy improvements, as calculated by DIW, are significantly smaller than the theoretical ones as measured by static tests. Again, the gap increases with increasing vehicle and engine size. The reason is simple: even at 120 kph, the larger cars are running above their optimal speeds, hence wasting fuel. Unfortunately, there are no surveys of fuel economy carried out by actual drivers for West Germany in the manner of the Swedish or French surveys. So neither of the values quoted here reflect ‘real driving’. This is particularly a problem when high Autobahn speeds are considered. But the coincidence between road test values and values of fuel intensity for the fleet (see Figure 3) is striking. In particular, the ‘road test’ figures lie above those of the fleet until 1982, reflecting the observed increase in fuel intensity during most of the previous decade. The fall in new-car intensity below that of the stock in 1982 is first reflected in a slight decline in fleet intensity, which deepens after 1986. These gaps and time lags create a credible picture suggesting that the West German road tests leave only a small gap compared with ‘real’ fuel economy, as implied from DIW’s estimates of stock-wide fuel efficiency. Since ‘real’ fuel efficiency for the stock has changed so little, we infer that ‘real’ fuel efficiency for new cars must have been close to this figure all along! Clearly the gap between road tests and static tests is enormous, leaving the latter only as potential indicators of relative fuel economy.

New car test and actual fuel economy: yet another gap?: L Schipper and W Tax

the most accurate of these three equations in predicting actual fuel consumption. But when TRRL fit the three tests to results from the Consumers’ Association by regression analysis they found Fuel Consumption (in Miles per Imperial Gallon) = 0.6 X Urban + 0.26 X 90 kph + 0.14 X 120 kph,

1970 1973 1976 1979





Figure 3 The automobile fuel economy gap: Germany Siww: DIW. 1992.

In West Germany, fleet fuel intensity is generally an input assumption to calculations of fuel use. DIW uses fuel use, fuel intensity and the number of cars to estimate driving distance, so there is an uncertainty in the stock consumption figures. At the same time, the driving distances match well those revealed in the KONTIV travel surveys of 1976, 1982 and 1989 (Kloas and Kuhfeld, 1987). DIW uses information on almost 2000 car models to estimate fuel intensity, fuel use and driving distance and is careful to lay out all of its ajsumptions (numbers of vehicles and distances driven by type and fuel). There is some suggestion that the DIW driving distances for cars in the fleet are too low (Gorissen, 1992), but it is also likely that the number of cars used to estimate total fuel use is too high (e.g. includes cars registered but not in use) (Rielke, 1991; 1992) In all, we believe that the DIW analyses, which now span a 40-year time interval (DIW, 1992) shows satisfactory consistency. Great Britain

Analysts have previously pointed to the existence of a fuel economy gap in British data (Watson, 1989; Sorrell, 1992; Hughes, 1992). Unfortunately, British authorities do not widely publish sales-weighted fuel economy data for new cars nor a long-term time series containing the four determinants, including fuel intensity. Instead, the major government publications, Digest of UK Energy Statistics and Digest of UK Transport Statistics, show only total fuel consumption for automobiles, offering a partial explanation of how the figure is derived in a footnote. Figure 4 shows the fleet fuel economy figures and the figure for new cars from two sources - Hughes (1992) and Sorrel1 (1992). The Transport and Road Research Laboratory (TRRL) (Watson, 1989) has previously pointed to the existence of a mileage gap between test values and those reported to the Consumers’ Association by their members, who keep diaries. TRRL notes that the ECE Tests (90 kph/l20 kph/urban driving) uses the l/3, l/3, l/3 weighting, while the European Legislative Average (ELA) uses 0.5 urban, 0.25 90 kph, and 0.25 120 kph. The British auto industry actually uses 0.5/0.1/0.4 in weighting test figures. The ELA predictive equation was 7ransportPolicy 1994 Volume I Number 4

to be a better predictor of actual fuel economy. Such coefficients predicted the fuel economy of 90% of the stock to within 10%. This equation also matched actual use in Great Britain at the time, according to Department of Transport statistics (64% urban driving, 10% highway and 26% road). TRRL suggests that adding additional variables, such as engine size, increases the accuracy of the prediction of fuel economy. The equation then becomes: Fuel Consumption (in Miles per Imperial Gallon) = 0.24 X Urban + 0.308 X 90 kph -5.47 X ENG + 20.615. This equation predicted the actual fuel economy of 98% of cars in the tests to within 10% and a full 72% to within 5%. Watson expressed concern, however, with the rate at which engine design changes would require changes to this equation. However, travel mix also changes over time, so even the equation with only travel mix variables would have to be adjusted over time. Hughes, in his Ph.D. thesis (1992), and Potter (1992, based on Hughes’ work) offered further comments on the gap. They found that the average fuel intensity for the entire fleet, as predicted by tests, was about 17% below what they derived for the fleet. They point to the usual sources of discrepancy: Traffic conditions are worse than those reflected in tests and the real weightings of the components of the test cycle do not reflect the actual weightings in practice. This element of the gap appears to be worsening over time. Driver behavior raises actual fuel consumption. We know from our own experience of driving in the UK that actual motorway speeds are considerably in excess of 120 kph except when congestion slows traffic to a crawl. In either case, real fuel economy on motorways is less than that derived from tests. Potter also claims that the 70% of the people who drive new cars bought by their employers drive faster than the average and more often in congested city centers than average. These factors act to worsen fuel economy somewhat. Cars have different engine sizes from those used in the tests. The fuel economy figures the government provides that represent the entire new-car sales for a year are not weighted by the share of each kind of new car in total sales, but are a simple average of each model available. Since the heaviest and most fuel-intensive cars are the most expensive, this procedure tends to 261

New car- test and actual,fuel

economy: yet another gap?: L Schipper- and W TU.Y

have both served to dampen expected improvements in sales-weighted new-car figures, although the change in fuel efficiency due to catalytic converter introduction is small compared to that between model variation or technical potential. He concludes that government figures on fuel consumption are at best an adequate relative indicator of actual fuel use.


7 1970



Figure 4 The automobile SOUIUJ: Sorrell. 1992.

overestimate in a year.



fuel economy


gap: Great

‘average’ fuel economy




of all cars sold

This last problem is explored, but not resolved, by Sorrel1 (1992). His analysis implies that government calculations average the test consumption of all new models equally each year. Weighting these by registration instead yields nearly 5% lower fuel intensities for small and medium-sized cars and nearly 12% lower intensities for large cars.’ This ‘weighting gap’ was larger in the early 198Os, presumably because fuel prices were much higher and actual cars bought were smaller or less powerful, a fact confirmed by Sorrell’s tabulation of average engine size in cars sold over the 1983-89 period. Sorrell’s study estimates that the 1990 fleet required 9.26 l/100 km. Yet his data for the registration-weighted gasoline cars sold between 1983 and 1990 show test values starting at 7.55 l/100 km in 1983 and falling slightly to 7.22 l/100 km by 1989. Taking other data he presents for the model-weighted new-car average, we adjust the 1978-82 data downward by the same abovementioned model/sales-weighted gap of approximately 8%. When this entire new-car series (1978-90) is examined, it is found that, on average, gasoline cars sold in the UK after 1979 had lower test intensities than the fleet figure for 1989. By 1989, these post-1979 cars made up the great majority of vehicles in the fleet. We would expect, therefore, to see a significant decline in fleet fuel intensity. Yet as Figure 4 shows, fleet fuel intensity declined by only 10% between 1980 and 1989. The model-weighted new-car tests are consistent with the observed changes in the fuel intensity of the fleet, but the sales-weighted new-car figures appear too low. The wide difference between the sales-weighted newcar figures and the fleet estimates implies that actual new-car fuel economy is roughly l&20% higher than that given by sales-weighted new-car figures, close to what TRRL and Hughes themselves find. Sorrel1 suggests that increased purchases of larger vehicles (with larger engines) and the addition of catalytic converters %rrell used information from the 1989 stock to make these weightings for new cars sold in the years 1983 through 1989. This is acceptable if few of the cars sold in these years were scrapped by 1989.

Figure 5 shows the evolution of fleet and new-car weighted fuel economy in Sweden. The most important fact for Sweden is that there does not appear to be a significant mileage gap in new-car fuel intensity figures published by authorities there! The reason is that the published test values follow approximately the ‘American’ weightings of a rural and urban test, 45% highway and 55% urban, while actual driving in Sweden follows more closely the proportions 60%/40%. The evidence for the small gap is in a series of surveys on car ownership and maintenance conducted every few years by the National Swedish Board of Consumer Affairs (Konsumentverket or KOV). KOV collects over 10 000 survey forms in which drivers report on various characteristics of their cars, including fuel use and distances driven (KOV, 1989, and various previous years). KOV tabulated these results for three different periods. They compared the newest cars to test values for those cars. In each period, the test values lay within a few percentage of the actual values. The gap, measured as the unweighted difference between test and reported fuel economy by car type, was typically l-2% in summer and as much as 8% in winter. Since far more driving occurs in summer, the overall gap is closer to 2-3%. KOV compared the fuel economy of older cars to the test values of those cars when they were new and found a progressive worsening of actual fuel economy over time. In other words, the gap itself grows with time for an individual car. This change in fuel economy may reflect different use patterns with age (of both car and driver) or lower fuel economy of all use patterns with age.

8.0’ 1970



Figure 5 The automobile



fuel economy

SOWW: Ministry of Trade, LBL. *Survey by Konsumentverket, actual drivers.



gap: Sweden

I 1991

New car test and actual fuel economy: yet another- gap?: L Schipper and W Tax

The Swedish surveys suggest that a simple re-weighting of figures from tests could reduce the mileage gap. This re-weighting would have to be carried out using both observations and statistical techniques, as Watson (1989) showed (see above) for Great Britain. This manipulation would make the gap disappear, but require that figures for a given year be ‘deflated’ or ‘inflated’ to match driving behavior in other years. That notion reinforces the French finding, namely, that the gap itself represents a fundamental confrontation between technology (fuel-saving) and behavior (fuel-using). Unfortunately, Swedish authorities do not attempt to weight the results of the KOV surveys to make up a sample representing the fuel intensity of the entire fleet. And just enough light trucks and buses use gasoline so that ‘total gasoline’ is not a reliable measure of the consumption in the fleet. As a result, the Swedish data for new-car fuel intensity may actually be more accurate than estimates for the entire fleet; fleet estimates range from 9 to 10 l/l00 km for gasoline cars in 1989 (Schipper et al., 1993~). Our calculations, part of an ongoing study of energy use in Sweden, and various Swedish sources (Wajsman, 1989; SIND, 1977) indicate that the higher value reflects the actual intensity of the fleet. This suggests that the real gap between test and actual fuel economy is closer to 10%. In comparison with results from other countries, this is indeed a relatively small error. Canada

Transport Canada has published a yearly Fuel Consumption Guide since 1977 to provide laboratorytested fuel consumption rates for different makes and models of vehicles. These guides also explain some of the reasons why actual fuel efficiency differs and provide a rough estimate of the difference. Since 1979, Statistics Canada has conducted a Fuel Consumption Survey on operating vehicles to monitor voluntary fuel efficiency standards. The types of information collected by Statistics Canada include the number of vehicles in operation and vehicle characteristics such as make, model, number of cylinders, distance traveled and amount of fuel consumed. Strategy, Organization, and Method (SOM, Inc. 1988) compared laboratory-tested rates based on ideal conditions and actual in-use fuel consumption for 34 466 passenger vehicles and 14 021 light trucks and vans in Canada. Figure 6 compares the results from SOM with data from Energy, Mines, and Resources (1992). Overall, 1977 to 1985 model-year passenger cars consumed 26.6% more fuel than the laboratory data would indicate. Light trucks and vans consumed 34.5% more fuel, on average, than test data would indicate. The SOM study found differences from make to make, but generally the 1984 and 1985 modelyear vehicles exhibited smaller gaps than the older vehicles. This finding contrasts with the findings in studies in other countries. However, 1980 to 1983 model-year vehicles were subject to more stringent fuel economy standards, which seem to have exacerbated the gap problem. The study also found that over time, larger Tsanspor-tPolky 1994 Volume I Number 4

engines and an increase in the fraction of automatic transmissions counteracted some technical advances in fuel efficiency. Through regression analysis, the two factors modeled indicating the greatest influence on the gap were the distance traveled and the fraction of summer driving. Winter fuel consumption was estimated to be 22% higher than in summer. The difference in fuel consumption between light trucks and vans and passenger vehicles was attributed to the fact that laboratory testing did not take into account possible loads carried by the light trucks and that laboratory testing may not properly allocate the urban/highway travel mix, which may be different for light trucks than for passenger cars. United States

The US EPA has been aware of the gap and began adjusting for it in published mileage results in the late 1970s. The EPA composite fuel efficiency rating is a weighted average of 55% city and 45% highway driving, and is adjusted downward 15%, since EPA noted a 10% shortfall between its test estimates and in-use estimates for city driving and a 22% shortfall in highway driving. The gap was found to be larger than this 15% adjustment in later years and EPA did realize that its adjustment did not fully account for the gap. EPA also adjusted the Federal Test Procedure (FTP) starting with the 1979 test for some known mal-simulations such as tire type and percentage of manual transmissions, as well as non-uniform distributions of vehicle weights in EPA weight classes. These adjustments resulted in a somewhat smaller average gap between EPA test mpg and consumer in-use mpg ratings. In addition, some of the gap in the 1975 and 1976 model year tests could be explained by the relatively sudden application of emissions control technology, a trend which was noted by some European analysts in the mid- to late 1980s as catalytic converters were added to European vehicles. Some of the results of the early studies included the following: l

EPA fuel economy



actual in-


+ m x

Actual fleet SOM tests 1 yr old survey SOM survey Sales wtd model


Figure 6 The automobile fuel economy gap: Canada Sourcv: Energy, Mines, and Resources,

1992; SOM, Inc., 1988. 263

New car test and actual fuel economy: yet another gap.?: L Chipper

use fuel economy; within-model variation was quite large (US EPA, 1980); for higher-mpg cars which were expected to dominate the fleet in later years, the gap was increasing in the late 1970s; as fleet average fuel efficiency increased, so did the gap (it was about 2 mpg for a 15 mpg rating and up to 7-8 mpg for a 27.5 mpg rating); based on limited data, the diesel gap seemed to be smaller than that for gasoline engines. More recent research into the gap problem in the USA also explores the weighting of travel mix and the increase in congestion. While the 55% urban, 45% highway weighting used by EPA seems to have appropriately reflected driving conditions in the late 1960s and early 1970s a 65%/35% urban/highway travel mix is considered more appropriate for today (Mintz et al., 1993). This finding is confirmed by Maples (1993), who predicts that by 2010, urban travel in the USA will make up 67-76% of the travel mix for passenger cars and 60-70% of light duty truck travel. Both Mintz and Maples feel that increased congestion over time has added to the gap problem, since tests do not reflect this change. The more recent analyses of the US gap confirm many of the results of earlier studies, including that the gap is increasing over time, that lowuse vehicles have larger gaps, and, as in Canada, light trucks have greater shortfalls than passenger cars. Mintz concludes that EPA’s adjustment factor should be revised to reflect more adequately the gap today.

Conclusions It is clear that the gap between new-car test fuel economy and actual fuel consumption is a problem in the countries where it has been studied. The gap seems to be increasing over time in most countries, with the exception of Canada, and exhibits seasonal differences. In general, the diesel gap is smaller than that for gasoline-fueled vehicles. The gap is not consistent over vehicle technologies. It does appear to increase with vehicle age, and is larger for light trucks than for passenger cars. The weightings of test cycles in many countries may not reflect the current travel mix. We do know many of the factors that influence the gap, and can suggest some ways to adjust test values to reflect more adequately in-use fuel consumption; however, many of the factors cannot be adjusted for. Those factors which can be adjusted for, such as the weighting of travel mix, are precisely those that change over time, requiring iterative changes to travel mix equations. We are also hesitant to suggest any adjustments to test fuel economy values across countries, since the results of the different country studies are not strictly comparable due to differences in testing, data collection and analysis methodologies. At best, fuel economy values derived from tests can indicate relative (rather than absolute) changes in fuel economy over time. International experience suggests that there are three 264

and W Tax


to the new-car test/road mpg gap:

1. Technical components, such as the poor match between the test cycle (or its weighted composition) and the typical real-world driving cycle, the failure to test cars with the same power and features as those sold, and the failure to test under the same weather conditions as faced by the average driver. 2. Traffic components, such as the continual evolution of the ‘real-world driving cycle’ and ‘worsening’ of congestion. 3. Behavior-related components such as changes in actual driver behavior over a given driving cycle that influence fuel use (speeding, fast acceleration, increasing number of cold starts). Changing the way in which the components of the tests are weighted can compensate for some of these problems, but it appears that the only truly accurate way to represent automobile fuel economy is to provide two figures for each car, one from a standard series of tests that are weighted to represent some ‘average’ driver, and driver surveys that measure actual fuel economy from individual models of cars over a very large sample. The former give the driver important information about relative fuel economy of tested cars, with the limitation that the gap is not independent of the driver herself. The latter are necessary to show authorities in the public and private sector how real fuel economy is changing, which, after all, is what influences emissions and energy use, the source of our concern in the first place. The French results suggest that a large survey could provide enough information about the sources of the gap to permit authorities to identify a range of ‘gaps’ for a given car, important information for consumer car purchase decision making, since real driver behavior in the real world might influence fuel use.


for policy

As we noted, most countries consider limiting the growth of fuel use for environmental reasons a worthy policy goal. Restraining automobile fuel use through improved technology is one important means to achieving this goal. Whether the goal is supported by pricing measures (Sweden), mandatory standards (USA), voluntary fuel efficiency agreements (Germany, Sweden, France), or publicly-funded research on new fuel-saving technologies (France), policy-makers and observers want to know the immediate impacts on limiting fuel use. Our review suggests observers are not able to measure the impact of efforts very well until the passage of several years of improvements to new cars, allowing these improvements to accumulate to levels larger than the intrinsic uncertainty in test measurements of fuel economy. Moreover, it is clear that some of the measurement problem arises because the ways in which cars are used have changed and these changes themselves reduce the impact of new technology on fuel saving. Finally, the measurement of overall fleet fuel economy

New car test und actual fuel

References D (1988) Les Consommafions




Uniraires des Voitures in private automobiles] AFME

(Agence Francaise pour la Maitrise de L’Energie), Ilosseboeuf, D (1991) L’Evolution de L’Efjcacite France (1973-1988) [The evolution (1973%1988)] AFME, Paris


Enrrgetique en of energy efficiency in France

DIW (Deutsches Institut fur Wirtschaftsforschung) [German Institute for Economic Research] (1987) ‘Gesamtfahrleistungen und Kraftstoffverbrauch im Strassenverkehr weiter deutlich gestiegen’ [‘Total road traffic and fuel use has increased significantly’] DlW Wochenhericht

DIW (1992, [Trafjc

yet another

gap?: L Schipper

and W Tax

potential impact in the future’ draft report. University of Tennessee, Transportation Center, Knoxville, TN Mintz, M M, A R D Vyas and L Conley (1993) ‘Differences between EPA-test and in-use fuel economy: are the correction factors correct’?’ Transportation Research Board. 72nd Annual Meeting, January 10-14, 1993, Washington, DC Potter, S (1992) Private communication, The Open University, Milton Keynes Rielke, H (1992, 1991) Private communication, DIW (Deutsches Institut fur Wirtschaftsforschung), Berlin Schipper, L, M F Figueroa, L Price and M Espey (1993a) ‘Mind the gap: the vicious circle of measuring automobile fuel use’ Energy Policy 21 (12) 1173 Schipper, L, R Steiner, M F Figueroa and K Dolan (1993b) ‘Fuel prices and economy - factors effecting land travel’ Transport Policy 1 ( I ) 6-20 Schipper, L, F Johnson, R Howarth, B Andersson, B Andersson and L Price (1993~) Energy Use in Sweden: An International Perspective Lawrence Berkeley Laboratory, LBL-33819, Berkeley, CA SIND (Statens Industriverk) [State Board for Industrial Issues] (1977) under 1980och 1990.mien. Sveriges Energianvandning

is itself fraught with uncertainties (Schipper et al., 1993a). Given these problems, policy makers should support efforts to improve our ability to track real progress towards the goal of fuel-saving through improved automotive technology and to account for the deviations from expectations arising because of the foibles of human behavior.




[SHaedish energy


the 1980s



SIND PM 1977:9, Stockholm SOM, Inc. (Strategy, Organization, and Method) (1988) ‘Differences between laboratory-tested and on-the-road fuel consumption rates’ report prepared for Transport Canada, Road Safety, Montreal Sorrell, S (1992) ‘Fuel efficiency in the UK vehicle stock’ Energy


and various

previous years) Verkehr in Zahlen 1991 19911 Bundesminister fur Verkehr, Berlin Mines, and Resources (1992)Transport Dam Book Ottawa datafor

Energy, Gorissen, N (1992) Private communication, Umweltbundesamt, Berlin Greene, D and K Duleep (1991) Costs and Benefits of Automotive Fuel Economy Improvements: A Partial Analysis Oak Ridge National Laboratory, Oak Ridge, TN Hughes, P S (1992) ‘A strategy for reducing emissions of greenhouse gases from personal travel in Britain’ Ph.D. thesis, The Open University, Milton Keynes Kloas, .I and H Kuhfeld (1987) Verkehrsverhalten im VergIeich (KONTIV) [Comparative travel behavior] Duncker and Humbolt, Berlin KOV (Konsumentverket) [National Swedish Board of Consumer Affairs] (1989 and previous years) ‘Bilunderhall’ [‘Car maintenance’] KOV Rapport 11 Vallingby, Sweden Maples, J (1993) ‘The light duty vehicle MPG gap: its size today and

Policy 20 (8) 766-780


Canada (1990 and previous years) Fuel Survey, Passenger Cars Statistics Canada, Ottawa


US Environmental Protection Agency (EPA), Motor Vehicle Emission Laboratory (1980) Passenger Cur Fuel Economy: EPA and Road EPA 460/3-80-010, Ann Arbor, Ml Wajsman, J ( 1989) Private communication, Transportradet, Solna, Sweden Watson, R L (1989) Car Fuel Consumption: Its Relationship to Transport and Road Research Ofjcial List Consumptions Laboratory, Digest of Research Report 155, Crowthome, UK Westbrook, F and P Patterson (1989) ‘Changing driving patterns and their effect on fuel economy’ paper presented at the 1989 SAE Government/Industry Meeting, May 2, 1989, Washington, DC

Appendix Fuel economy gap, test/actual, various countries (l/100 km) Country Canada” Individual car modelsh FranceC Germanyd Sweden’ ITS’ Cars Trucks UK8


% Gap







1985 1988 1987 1987 1985

8.6 6.5 7.7 8.2

10.7 8.4 9.8 8.5

2.1 1.9 2.1 0.3

19.6 23 21.4 3.5

9.7 11.6 7.2

11.9 14.5 9.3

2.2 2.9 2.1

18.5 20 22.6




Sources: a Statistics Canada 1990 b SOM, Inc 1988; Energy, Mines, and Resources c Bosseboeuf 1988 d DIW 1987 e KOV 1987 f Mintz et al 1993 g Sorrel1 1992



Year of Cf.

Policy 1994 Volume 1 Number 4

Actual fuel efficiency from drivers surveys. Test from laboratory test

Travel diaries compared to r/1city, ‘/? highway, ‘/3road test values DIN (test) vs DIW (actual) KOV compared with consumer reported survey data RTECS survey vs EPA fleet average from dynamometer Test value for registration-weighted