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Advanced Cu-zeolite based SCR (selective catalytic reduction) catalyst technologies were evaluated in a laboratory reactor as a component of a diesel LNT (lean NOx trap) plus in-situ SCR system (i.e., NH3 generation over the LNT vs injection via urea). New-generation LNT formulations, with lower desulfation temperatures and improved durability characteristics relative to previous LNTs, were also evaluated. The combined new-generation LNT+Cu-zeolite SCR systems showed a much wider temperature window of high NOx conversion compared to either LNT catalysts alone or LNT+SCR systems utilizing Fe-zeolite SCR catalysts. The new-generation Cu-zeolite SCR catalysts retained high activity even after repeated exposure to high-temperature rich DeSOx conditions in a laboratory 3-mode aging cycle simulating 120,000 mile vehicle driving.

Fuel power consumption for light duty vehicles has previously been shown to be proportional to vehicle traction power, with an offset for overhead and accessory losses. This allows the fuel consumption for an individual powertrain to be projected across different vehicles, missions, and drive cycles. This work applies the power-based model to commercial vehicles and demonstrates its usefulness for projecting fuel consumption on both regulatory and customer use cycles. The ability to project fuel consumption to different missions is particularly useful for commercial vehicles, as they are used in a wide range of applications and with customized designs. Specific cases are investigated for Light and Medium Heavy- Duty work trucks. The average power required by a vehicle to drive the regulatory cycles varies by nearly a factor 10 between the Class 4 vehicle on the ARB Transient cycle and the loaded Class 7 vehicle at 65 mph on grade.

Medium duty vehicles come in many design variations, which makes testing them all for CO2 impractical. As a result there are multiple ways of reporting CO2 emissions. Actual tests may be performed, data substitution may be used, or CO2 values may be estimated using an analytical correction. The correction accounts for variations in road load force coefficients (f0, f1, f2), weight, and axle ratio. The EPA Analytically Derived CO2 equation (EPA ADC) was defined using a limited set of historical data. The prediction error is shown to be ±130 g/mile and the sensitivities to design variables are found to be incorrect. Since the absolute CO2 is between 500 and 1,000 g/mi, the equation has limited usefulness. Previous work on light duty vehicles has demonstrated a linear relationship between vehicle fuel consumption, powertrain properties and total vehicle work. This relationship improves the accuracy and avoids co-linearity and non-orthogonality of the input variables.