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Most governments of countries (or, in the case of the European Union, regions) with large auto markets regulate passenger vehicle fuel efficiency or CO2 emissions (essentially the same thing, since CO2 emissions are directly proportional to the amount of fuel consumed). But they take differing approaches to designing regulations, and use different underlying drive cycles and test procedures to certify that a vehicle complies with the standards. Converting the standard values—that is, the fuel efficiency mandates or emissions limits—between different regulations involves not just converting physical units, but also accounting for the impacts of differences in test cycles.
For years, the ICCT has maintained a ready reference to worldwide passenger vehicle fuel efficiency standards, updating the charts and data as governments adopted or modified regulations, that aimed to compare the relative stringency of regulations as accurately and fairly as possible. It’s generally seen as the best such comparison available, and is widely used by governments, industry, NGOs, and media to understand and illustrate what’s happening with vehicle efficiency globally.
But we always knew it could be better—even fairer and more accurate. And we’ve just concluded a significant research effort to make it so, by improving the test cycle conversion factors used to translate the standard values among the different regulations. Full details are available here. The following paragraphs give the summary version.
The study establishes CO2 emission conversion factors for four major test driving cycles: the Corporate Average Fuel Economy, or CAFE, test in the United States; the New European Driving Cycle (NEDC) in the European Union (EU); the JC08 in Japan; and the Worldwide Harmonized Light-duty Test Cycle (WLTC), which is not yet officially in use anywhere but will be (it is expected) adopted in the EU and Japan (and probably by other governments as well) beginning in 2017. Every government that has promulgated fuel efficiency standards uses one of these four test cycles for establishing compliance with the standards.
Compared with the previous conversion factors, the new approach reflects many improvements:
|Vehicle model data from the Modal Energy and Emissions Model (MEEM)||Vehicle model data from Ricardo’s ‘Data Visualization Tool’ (DVT), the same data used in developing US fuel economy standards and generating EU CO2 cost-benefit curves|
|Simulation results for 12 gasoline LDV (ICE only)||Simulation results for a large number of current and advanced gasoline, hybrids and diesel vehicles with automatic and manual transmissions|
|2015 projection||Vehicles simulated with both a 2008 baseline and with technologies projected for 2020|
|Multiplier logarithmic regression method||Different linear and non-linear regression approaches evaluated, higher level of technical details|
|Resulting algorithms converting CAFE [mpg], NEDC [g CO2/km] and JC08 [l/km]||Resulting g CO2/km based algorithms converting CAFE, NEDC, JC08 and WLTC|
Different types of regression analyses were developed and evaluated using the modeled CO2 emission data in order to describe the dependencies for each pair of driving cycles. The new conversion factors can evaluate gasoline and diesel data separately. Different regressions can be used based on the availability of information related to vehicle architecture, aerodynamic drag, and engine technology.
We found that there is a trade-off between making conversions more precise and making this information useable for global policymakers. As the fleet average CO2 emission targets are technology agnostic, the study establishes a “universal approach” by merging linear regression lines for gasoline and diesel vehicles. At this regressions level, the complete data set was evaluated without taking into account possible technology specifics. The only additional input required is the share of diesel vehicles in the assumed fleet.
The new conversion equation for the “universal approach” for converting regional fleet average fuel economy/CO2 emission targets is:
C2 = (a1 * DS + a2) * C1 + d1 * DS + d2
The table below summarizes the results for the coefficients for each combination of cycle pairs.
DS: Fleet diesel share (0-1)
The figures illustrate the relationship between different cycles. Each pair of cycles has separated regression parameters for each direction. The figures merely plot one-direction relationship between each cycle pair (Cycle 1 → Cycle 2). The opposite-direction conversion (Cycle 2 → Cycle 1) is not identical to the inverse results of the original direction conversion. The solid lines reflect cycles relationships for 100% gasoline fleet, while the dashed lines reflect 50% gasoline and 50% diesel fleet. The dotted line is a hypothetical baseline of no CO2 emission difference between two cycles.
Using the new conversion factors, we have updated the global LDV CO2 emission standard comparison charts . The updates alter the global rankings, especially for passenger car standards. Some major changes in the new global comparison charts are:
Historical fleet CO2 emissions performance and current or proposed passenger vehicle standards:
Historical fleet CO2 emissions performance and current or proposed light commercial vehicle/light truck standard:s
Note that the standards comparison does not account for fleet differences such as average vehicle weight, size, and power.
ICCT will continue to update the global standards comparison on a regular basis as newer and better data become available. We will also soon publish a new summary report on global passenger vehicle fuel economy and GHG standards, so stay tuned for that as well!