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A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.

Recent 2010 emissions standards for heavy-duty engines have established a limit of oxides of nitrogen (NOX) emissions of 0.20 g/bhp-hr. However, CARB has projected that even when the entire on-road fleet of heavy-duty vehicles operating in California is compliant with 2010 emission standards, the National Ambient Air Quality Standards (NAAQS) requirement for ambient particulate matter and Ozone will not be achieved without further reduction in NOX emissions. The California Air Resources Board (ARB) funded a research program to explore the feasibility of achieving 0.02 g/bhp-hr NOX emissions. This paper details engine and aftertreatment NOX management requirements and model based control considerations for achieving Ultra-Low NOX (ULN) levels with a heavy-duty diesel engine. Data are presented for several Advanced Technology aftertreatment solutions and the integration of these solutions with the engine calibration.