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Reduced emissions, improved fuel economy, and improved performance are a priority for manufacturers of internal combustion engines. However, these three goals are normally interrelated and difficult to optimize simultaneously. Studying the experimental heat release provides a useful tool for combustion optimization. Heavy-duty diesel engines are inherently transient, even during steady state operation engine controls can vary due to exhaust gas recirculation (EGR) or aftertreatment requirements. This paper examines the heat release and the derived combustion characteristics during steady state and transient operation for a 1992 DDC series 60 engine and a 2004 Cummins ISM 370 engine. In-cylinder pressure was collected during repeat steady state SET and the heavy-duty transient FTP test cycles.

A program has been completed to evaluate ultra-low sulfur diesel fuels and passive diesel particulate filters (DPFs) in truck and bus fleets operating in southern California. The fuels, ECD and ECD-1, are produced by ARCO (a BP Company) and have less than 15 ppm sulfur content. Vehicles were retrofitted with two types of catalyzed DPFs, and operated on ultra-low sulfur diesel fuel for over one year. Exhaust emissions, fuel economy and operating cost data were collected for the test vehicles, and compared with baseline control vehicles. Regulated emissions are presented from two rounds of tests. The first round emissions tests were conducted shortly after the vehicles were retrofitted with the DPFs. The second round emissions tests were conducted following approximately one year of operation. Several of the vehicles retrofitted with DPFs accumulated well over 100,000 miles of operation between test rounds.

The use of Artificial Neural Networks (ANNs) as a predictive tool has been shown to have a broad range of applications. Earlier work by the authors using ANN models to predict carbon dioxide (CO2), carbon monoxide (CO), oxides of nitrogen (NOx), and particulate matter (PM) from heavy-duty diesel engines and vehicles yielded marginal to excellent results. These ANN models can be a useful tool in inventory prediction, hybrid vehicle design optimization, and incorporated into a feedback loop of an on-board, active fuel injection management system. In this research, the ANN models were trained on continuous engine and emissions data. The engine data were used as inputs to the ANN models and consisted of engine speed, torque, and their respective first and second derivatives over a one, five, and ten second time range. The continuous emissions data were the desired output that the ANN models learned to predict through an iterative training process.

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).

When preparing inventory models, it is desirable to obtain representative distance-specific emissions factors that truthfully represent the vehicle activity on a particular road (facility) type. Unfortunately, emissions values are often measured using only one test schedule, which represents a single average speed and a specific type of activity. This paper investigated the accuracy of predicting the emissions for a test schedule based on measurements from a different test schedule for the case of a medium heavy-duty truck. First, the traditional Speed Correction Factor (SCF) approach was examined, followed by the use of a power-based model derived from continuous data, followed by an artificial neural network (ANN) approach. The SCF modeling used distance-averaged emissions and cycle-averaged vehicle speed to predict distance-averaged NOx. The power-based modeling was based on linear and polynomial correlations between continuous axle power and NOx.

The effects of fuel composition on emissions levels from compression ignition engines can be profound, and this understanding has led to mandated reductions in both sulfur and aromatic content of automotive diesel fuels. A Navistar T444E (V8, 7.3 liter) engine was installed on an engine dynamometer and subjected to transient emissions measurement using a variety of fuels, namely federal low sulfur pump diesel; California pump diesel; Malaysian Fischer-Tropsch fuel with very low sulfur and aromatic content; various blends of soy-derived biodiesel; a Fischer-Tropsch fuel with very low sulfur and 10% aromatics; and the same Fischer-Tropsch fuel with 10% isobutanol by volume. The biodiesel blends showed their ability to reduce particulate matter, but at the expense of increasing oxides of nitrogen (NOx), following the simple argument that cetane enhancement led to earlier ignition. However, the Fischer-Tropsch fuels showed their ability to reduce all of the regulated emissions.

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.

The Quarter Wave Coaxial Cavity Resonator (QWCCR) plasma igniter is designed, from previous theoretical work, as an ignition source for an internal combustion engine. The present research has explored the implementation of the QWCCR into an internal combustion (IC) engine. The QWCCR design parameters of inner conductor length, loop geometry, and loop position were varied for two igniters of differing operating frequency. Variations of the QWCCR radio frequency (RF) parameters, as a function of engine geometry, were studied by placing the igniter in a combustion chamber and manually varying the crank position. Three identical igniters were fitted with dielectric inserts and the parameters were studied before and after ignition was sustained in a twin-cylinder engine. Optimal resonator geometries were determined. Radio frequency parameter invariance was found with respect to crank angle and piston distance. The first successful IC engine ignition using a QWCCR was achieved.

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.

A study was performed in the spring of 2001 to chemically characterize exhaust emissions from trucks and buses fueled by various test fuels and operated with and without diesel particle filters. This study was part of a multi-year technology validation program designed to evaluate the emissions impact of ultra-low sulfur diesel fuels and passive diesel particle filters (DPF) in several different heavy-duty vehicle fleets operating in Southern California. The overall study of exhaust chemical composition included organic compounds, inorganic ions, individual elements, and particulate matter in various size-cuts. Detailed descriptions of the overall technology validation program and chemical speciation methodology have been provided in previous SAE publications (2002-01-0432 and 2002-01-0433).

Linear engine alternator (LEA) design optimization traditionally has been difficult because each independent variable alters the motion with respect to time, and therefore alters the engine and alternator response to other governing variables. An analogy is drawn to a conventional engine with a very light flywheel, where the rotational speed effectively is not constant. However, when springs are used in conjunction with an LEA, the motion becomes more consistent and more sinusoidal with increasing spring stiffness. This avoids some attractive features, such as variable compression ratio HCCI operation, but aids in reducing cycle-to-cycle variation for conventional combustion modes. To understand the cycle-to-cycle variations, we have developed a comprehensive model of an LEA with a 1kW target power in MATLAB®/Simulink, and an LEA corresponding to that model has been operated in the laboratory.

Techniques have been developed to sample and speciate dilute heavy duty diesel exhaust to determine the specific reactivities and the ozone forming potential. While the Auto/Oil Air Quality Improvement Research Program (AQIRP) has conducted a comprehensive investigation to develop data on potential improvements in vehicle emissions and air quality from reformulated gasoline and various other alternative fuels. However, the development of sampling protocols and speciation of heavy duty diesel exhaust is still in its infancy [1, 2, 3, 4, 5 and 6]. This paper focuses on the first phase of the heavy duty diesel speciation program, that involves the development of a unique set of sampling protocols for the gas phase, semi-volatile and particulate matter from the exhaust of engines operating on different types of diesel fuel. Effects of sampling trains, sampling temperatures, semi-volatile adsorbents and driving cycles are being investigated.

The basic design of a purely rotary motion engine has potentially many advantages over the conventional piston-crank internal combustion engine. Although only one rotary engine has been successfully placed into production, rotary mechanisms still show promise in the market place. A comprehensive review of rotary engine concepts is presented with an emphasis placed on the last 30 years. Suggestions are made as to where research concentrations should be placed to improve the progress of a rotary engine.

The goal of the Diesel Emissions Control-Sulfur Effects (DECSE) program was to determine the impact of diesel fuel sulfur levels on emissions control devices that could lower emissions of oxides of nitrogen (NOX) and particulate matter (PM) from on-highway trucks and buses. West Virginia University (WVU) performed evaluations of lean-NOx catalysts to determine the effects of fuel sulfur content on emissions reduction efficiency and catalyst durability in the first 250 hours of operation. A Cummins ISM370 engine (10.8 liter, 370 horsepower), typical of heavy -duty truck applications, was utilized to evaluate high-temperature lean-NOX catalyst while a Navistar T444E (7.3 liter, 210 horsepower), typical of medium-duty applications, was used to evaluate low-temperature catalyst. Catalysts were evaluated periodically during the first 250 hours of exposure to exhaust from engines operated on 3ppm, 30ppm, 150ppm and 350ppm sulfur content diesel fuel.

This paper examines the energy pathways of a 29cc air-cooled two-stroke engine operating on natural gas with different exhaust geometries. The engine was operated at wide-open-throttle at a constant speed of 5400 RPM with ignition adjusted to yield maximum brake torque while the fueling was adjusted to examine both rich and lean combustion. The exhaust configurations examined included an off-the-shelf (OTS) model and two other custom models designed on Helmholtz resonance theory. The custom designs included both single and multi-cone features. Out of the three exhaust systems tested, the model with maximum trapping efficiency showed a higher overall efficiency due to lower fuel short-circuiting and heat transfer. The heat transfer rate was shown to be 10% lower on the new designs relative to OTS model.

Heavy-Duty Diesel (HDD) engines' particulate matter (PM) emissions are most often measured quantitatively by weighing filters that collect diluted exhaust samples pre- and post-test. PM sampling systems that dilute exhaust gas and collect PM samples have different effects on measured PM data. Those effects usually contribute to inter-laboratory variance. The U.S. Environmental Protection Agency (EPA)'s 2007 PM emission measurement regulations for the test of HDD engines should reduce variability, but must also cope with PM mass that is an order of magnitude lower than legacy engine testing. To support the design of a 2007 US standard HDD PM emission sampling system, a parametric study based on a systematic Simulink® model was performed. This model acted as an auxiliary design tool when setting up a new 2007 HDD PM emission sampling system in a heavy-duty test cell at West Virginia University (WVU). It was also designed to provide assistance in post-test data processing.

Alternative compression ignition engine fuels are of interest both to reduce emissions and to reduce U.S. petroleum fuel demand. A Malaysian Fischer-Tropsch gas-to-liquid fuel was compared with California #2 diesel by characterizing emissions from over the road Class 8 tractors with Caterpillar 3176 engines, using a chassis dynamometer and full scale dilution tunnel. The 5-Mile route was employed as the test schedule, with a test weight of 42,000 lb. Levels of oxides of nitrogen (NOx) were reduced by an average of 12% and particulate matter (PM) by 25% for the Fischer-Tropsch fuel over the California diesel fuel. Another distillate fuel produced catalytically from Fischer-Tropsch products originally derived from natural gas by Mossgas was also compared with 49-state #2 diesel by characterizing emissions from Detroit Diesel 6V-92 powered transit buses, three of them equipped with catalytic converters and rebuilt engines, and three without.

Understanding the nitric oxide (NO) conversion process plays a major role in optimizing the Selective NOX Recirculation (SNR) technique. SNR has been proven in gasoline and diesel engines, with up to 90% NOX conversion rates being achieved. This technique involves adsorbing NOX from an exhaust stream, then selectively desorbing the NOX into a concentrated NOX stream, which is fed back into the engine's intake, thereby converting a percentage of the concentrated NOX stream into harmless gases. The emphasis of this paper is on the unique chemical kinetic modeling problem that occurs with high concentrations of NOX in the intake air of a spark ignited natural gas engine with SNR. CHEMKIN, a chemical kinetic solver software package, was used to perform the reaction modeling. A closed homogeneous batch reactor model was used to model the fraction of NOX versus time for varying initial conditions and constants.

West Virginia University has conducted research to characterize the emissions from medium-duty vehicles operating on Fischer-Tropsch synthetic gas-to-liquid compression ignition fuel. The West Virginia University Transportable Heavy Vehicle Emissions Testing Laboratory was used to collect data for gaseous emissions (carbon dioxide, carbon monoxide, oxides of nitrogen, and total hydrocarbon) while the vehicles were exercised through a representative driving schedule, the New York City Bus Cycle (NYCB). Artificial neural networks were used to model emissions to enhance the capabilities of computer-based vehicle operation simulators. This modeling process is presented in this paper. Vehicle velocity, acceleration, torque at rear axel, and exhaust temperature were used as inputs to the neural networks. For each of the four gaseous emissions considered, one set of training data and one set of validating data were used, both based on the New York City Bus Cycle.

Selective NOX Recirculation (SNR) involves three main steps in NOX reduction. The first step adsorbs NOX from the exhaust stream, followed by periodic desorption from the aftertreatment medium. The final step passes the desorbed NOX gas into the intake air stream and feeds into the engine. A percentage of the NOX is expected to be decomposed during the combustion process. The motivation for this research was to clarify the reduction of NOX from large stationary engines. The objective of this paper is to report the NOX decomposition phenomenon during the combustion process from three test engines. The results will be used to develop an optimal system for the conversion of NOX with a NOX adsorbtion system. A 1993 Cummins L10G natural gas engine, a 1992 Detroit Diesel series 60 engine and a 13hp Honda gasoline engine were used in the experiments. Commercially available nitric oxide (NO) was injected into the engine intake to mimic the NOX stream from the desorption process.