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As part of the 1998 Consent Decrees concerning alternative ignition strategies between the six settling heavy-duty diesel engine manufacturers and the United States government, the engine manufacturers agreed to perform in-use emissions measurements of their engines. As part of the Consent Decrees, pre- (Phase III, pre-2000 engines) and post- (Phase IV, 2001 to 2003 engines) Consent Decree engines used in over-the-road vehicles were tested to examine the emissions of oxides of nitrogen (NOx) and carbon dioxide (CO2). A summary of the emissions of NOx and CO2 and fuel consumption from the Phase III and Phase IV engines are presented for 30 second “Not-to-Exceed” (NTE) window brake-specific values. There were approximately 700 Phase III tests and 850 Phase IV tests evaluated in this study, incorporating over 170 different heavy duty diesel engines spanning 1994 to 2003 model years. Test vehicles were operated over city, suburban, and highway routes.

Pollutants are a major issue of diesel engines, with oxides of nitrogen (NOx) and airborne total particulate matter (TPM) of primary concern. Current emission standards rely on laboratory testing using an engine dynamometer with a standard test procedure. Results are reported as an integrated value for emissions from a transient set of engine speed and load conditions over a length of time or a set of prescribed speed-load points. To be considered a valid test by the US EPA, the measured engine speed and load are compared to the prescribed engine speed and load and must be within prescribed regression limits.

For engine operations involving low load conditions for an extended amount of time, the exhaust temperature may be lower than that necessary to initiate the urea hydrolyzation. This would necessitate that the controller interrupt the urea supply to prevent catalyst fouling by products of ammonia decomposition. Therefore, it is necessary for the engine controller to have multiple calibrations available in regions of engine operation where the aftertreatment does not perform well, so that optimal exhaust conditions are guaranteed during the wide variety of engine operations. In this study the test engine was equipped with a catalyzed diesel particulate filter (DPF) and a selective catalytic reduction system (SCR), and programmed with two different engine calibrations, namely the low-NOx and the low fuel consumption (low-FC).

The range-extended electric vehicle (REEV) is a complex nonlinear system powered by internal combustion engine and electricity stored in battery. This research proposed a Multiple Operation Points (MOP) control strategy of REVV based on operation features of REEV and the universal characteristic curve of the engine. The switching logic rules of MOP strategy are designed for the desired transition of the operation mode, which makes the engine running at high efficiency region. A Genetic algorithm (GA) is adapted to search the optimal solution. The fuel consumption is defined as the target cost function. The demand power of engine is defined as optimal variable. The state of charge (SOC) and vehicle speed are selected as the state variables. The dynamic performance of vehicle and cycling life of battery is set as the constraints. The optimal switching parameters are obtained based on this control strategy. Finally, a dynamic simulation model of REEV is developed in Matlab/Simulink.

The aim of this investigation was to improve understanding and quantify the impact of exhaust gas recirculation (EGR) as an emissions control measure onto cyclic variability of a small-bore, single-cylinder, diesel-fueled compression-ignition (CI) power generation unit. Of special interest were how cycle-to-cycle variations of the CI engine affect steady-state voltage deviations and frequency bandwidths. Furthermore, the study strived to elucidate the impact of EGR addition onto combustion parameters, as well as gaseous and particle phase emissions along with fuel consumption. The power generation unit was operated over five discrete steady-state test modes, representative of nominal 0, 25, 50, 75, and 100% engine load (i.e. 0-484kPa BMEP), by absorbing electrical power via a resistive load bank. The engine was equipped with a passive EGR system that directly connected the exhaust and intake runners through a small passage.

Diesel Particulate Filters (DPFs) are well assessed exhaust aftertreatment devices currently equipping almost every modern diesel engine to comply with the most stringent emission standards. However, an accurate estimation of soot content (loading) is critical to managing the regeneration of DPFs in order to attain optimal behavior of the whole engine-after-treatment assembly, and minimize fuel consumption. Real-time models can be used to address challenges posed by advanced control systems, such as the integration of the DPF with the engine or other critical aftertreatment components or to develop model-based OBD sensors. One of the major hurdles in such applications is the accurate estimation of engine Particulate Matter (PM) emissions as a function of time. Such data would be required as input data for any kind of accurate models. The most accurate way consists of employing soot sensors to gather the real transient soot emissions signal, which will serve as an input to the model.

Both field research and certification data show that the lean burn natural gas powered spark ignition engines offer particulate matter (PM) reduction with respect to equivalent diesel power plants. Concerns over PM inventory make these engines attractive despite the loss of fuel economy associated with throttled operation. Early versions of the Cummins L-10 natural gas engines employed a mixer to establish air/fuel ratio. Emissions measurements by the West Virginia University Transportable Heavy Duty Emissions Testing Laboratories on Cummins L-10 powered transit buses revealed the potential to offer low emissions of PM and oxides of nitrogen, (NOx) but variations in the mixture could cause emissions of NOx, carbon monoxide and hydrocarbons to rise. This was readily corrected through mixer repair or readjustment. Newer versions of the L-10 engine employ a more sophisticated fueling scheme with feedback control from a wide range oxygen sensor.

Heavy-duty diesel (HDD) engines are the primary propulsion source for most heavy-duty vehicle freight movement and have been equipped with an array of aftertreatment devices to comply with more stringent emissions regulations. In light of concerns about the transportation sector's influence on climate change, legislators are introducing requirements calling for significant reductions in fuel consumption and thereby, greenhouse gas (GHG) emission over the coming decades. Advanced engine concepts and technologies will be needed to boost engine efficiencies. However, increasing the engine's efficiency may result in a reduction in thermal energy of the exhaust gas, thus contributing to lower exhaust temperature, potentially affecting aftertreatment activity, and consequently rate of regulated pollutants. This study investigates the possible utilization of waste heat recovered from a HDD engine as a means to offset fuel penalty incurred during thermal management of SCR system.

Transit agencies across the United States operate bus fleets primarily powered by diesel, natural gas, and hybrid drive systems. Passenger loading affects the power demanded from the engine, which in turn affects distance-specific emissions and fuel consumption. Analysis shows that the nature of bus activity, taking into account the idle time, tire rolling resistance, wind drag, and acceleration energy, influences the way in which passenger load impacts emissions. Emissions performance and fuel consumption from diesel and natural gas powered buses were characterized by the West Virginia University (WVU) Transportable Emissions Testing Laboratory. A comparison matrix for all three bus technologies included three common driving cycles (the Braunschweig Cycle, the OCTA Cycle, and the ADEME-RATP Paris Cycle). Each bus was tested at three different passenger loading conditions (empty weight, half weight, and full weight).