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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.

The objective of this project, which is supported by the U.S. Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL), is to provide a comprehensive comparison of heavy-duty trucks operating on alternative fuels and diesel fuel. Data collection from up to eight sites is planned. This paper summarizes the design of the project and early results from the first two sites. Data collection is planned for operations, maintenance, truck system descriptions, emissions, duty cycle, safety incidents, and capital costs and operating costs associated with the use of alternative fuels in trucking.

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.

Biodiesel fuels benefit both from being a renewable energy source and from decreasing in carbon monoxide (CO), total hydrocarbons (THC), and particulate matter (PM) emissions relative to petroleum diesel. The oxides of nitrogen (NOx) emissions from biodiesel blended fuels reported in the literature vary relative to baseline diesel NOx, with no NOx change or a NOx decrease found by some to an increase in NOx found by others. To explore differences in NOx, two Cummins ISM engines (1999 and 2004) were operated on 20% biodiesel blends during the heavy-duty transient FTP cycle and the steady state Supplemental Emissions Test. For the 2004 Cummins ISM engine, in-cylinder pressure data were collected during the steady state and transient tests. Three types of biodiesel fuels were used in the blends: soy, tallow (animal fat), and cottonseed. The FTP integrated emissions of the B20 blends produced a 20-35% reduction in PM and no change or up to a 4.3% increase in NOx over the neat diesel.

The California Air Resources Board (ARB) developed a Medium Heavy-Duty Truck (MHDT) schedule by selecting and joining microtrips from real-world MHDT. The MHDT consisted of three modes; namely, a Lower Speed Transient, a Higher Speed Transient, and a Cruise mode. The maximum speeds of these modes were 28.9, 58.2 and 66.0 mph, respectively. Each mode represented statistically selected truck behavior patterns in California. The MHDT is intended to be applied to emissions characterization of trucks (14,001 to 33,000lb gross vehicle weight) exercised on a chassis dynamometer. This paper presents the creation of the MHDT and an examination of repeatability of emissions data from MHDT driven through this schedule. Two trucks were procured to acquire data using the MHDT schedule. The first, a GMC truck with an 8.2-liter Isuzu engine and a standard transmission, was tested at laden weight (90% GVW, 17,550lb) and at unladen weight (50% GVW, 9,750lb).

This paper summarizes the several of the studies in the Environmental Science Program being sponsored by DOE's Office of Heavy Vehicle Technologies (OHVT) through the National Renewable Energy Laboratory (NREL). The goal of the Environmental Science Program is to understand atmospheric impacts and potential health effects that may be caused by the use of petroleum-based fuels and alternative transportation fuels from mobile sources. The Program is regulatory-driven, and focuses on ozone, airborne particles, visibility and regional haze, air toxics, and health effects of air pollutants. Each project in the Program is designed to address policy-relevant objectives. Current projects in the Environmental Science Program have four areas of focus: improving technology for emissions measurements; vehicle emissions measurements; emission inventory development/improvement; ambient impacts, including health effects.

Selective Catalytic Reduction (SCR), using urea injection, is being examined as a method for substantial reduction of oxides of nitrogen (NOx) for diesel engines, but the urea injection rates must be controlled to match the NOx production which may need to be predicted during open loop control. Unfortunately NOx is usually measured in the laboratory using a full-scale dilution tunnel and chemiluminescent analyzer, which cause delay and diffusion (in time) of the true manifold NOx concentration. Similarly, delay and diffusion of measurements of all emissions cause the task of creating instantaneous emissions models for vehicle simulations more difficult. Data were obtained to relate injections of carbon dioxide (CO2) into a tunnel with analyzer measurements. The analyzer response was found to match a gamma distribution of the input pulse, so that the analyzer output could be modeled from the tunnel CO2 input.

Today's computer-based vehicle operation simulators use engine speed, engine torque, and lookup tables to predict emissions during a driving simulation [1]. This approach is used primarily for light and medium-duty vehicles, with large discrepancies inherently due to the lack of transient engine emissions data and inaccurate emissions prediction methods [2]. West Virginia University (WVU) has developed an artificial neural network (ANN) based emissions model for incorporation into the ADvanced VehIcle SimulatOR (ADVISOR) software package developed by the National Renewable Energy Laboratory (NREL). Transient engine dynamometer tests were conducted to obtain training data for the ANN. The ANN was trained to predict carbon dioxide (CO2) and oxides of nitrogen (NOx) emissions based on engine speed, torque, and their representative first and second derivatives over various time ranges.

A recently completed program was developed to evaluate ultra-low sulfur diesel fuels and passive diesel particle filters (DPF) in several different truck and bus fleets operating in Southern California. The primary test fuels, ECD and ECD-1, are produced by ARCO, a BP company, and have less than 15 ppm sulfur content. A test fleet comprised of heavy-duty trucks and buses were retrofitted with one of two types of catalyzed diesel particle filters, and operated for one year. As part of this program, a chemical characterization study was performed in the spring of 2001 to compare the exhaust emissions using the test fuels with and without aftertreatment. A detailed speciation of volatile organic hydrocarbons (VOC), polycyclic aromatic hydrocarbons (PAH), nitro-PAH, carbonyls, polychlorodibenzo-p-dioxins (PCDD) and polychlorodibenzo-p-furans (PCDF), inorganic ions, elements, PM10, and PM2.5 in diesel exhaust was performed for a select set of vehicles.

Cummins Westport Inc. (CWI) released for production the latest version of its C8.3G natural gas engine, the C Gas Plus, in July 2001. This engine has increased ratings for horsepower and torque, a full-authority engine controller, wide tolerance to natural gas fuel (the minimum methane number is 65), and improved diagnostics capability. The C Gas Plus also meets the California Air Resources Board optional low-NOx (2.0 g/bhp-h) emission standard for automotive and urban buses. Two pre-production C Gas Plus engines were operated in a Viking Freight fleet for 12 months as part of the U.S. Department of Energy's Fuels Utilization Program. In-use exhaust emissions, fuel economy, and fuel cost were collected and compared with similar 1997 Cummins C8.3 diesel tractors. CWI and the West Virginia University developed an ad-hoc test cycle to simulate the Viking Freight fleet duty cycle from in-service data collected with data loggers.

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.

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).

The recent oil crisis has once again emphasized the need to develop both fuel efficient engines and alternately fueled engines, particularly for automotive applications. Engines which burn coal or coal pyrolysis products are attractive, but ignition delay and metal erosion problems continue to limit high speed operation of such engines. Further, the throttled spark ignition engine often used with methanol and natural gas does not prove an efficient or tolerant device for the combustion of a wide range of fuel. Therefore, an novel approach must be taken in order to achieve the efficient and flexible operation of such an engine. A novel design of a fuel tolerant engine suitable for burning coal fuels separates the combustion from the piston in order to have more careful flame control and to exclude the particulate matter from the engine's piston rings.

With continuously increasing concern for the emissions from two-stroke engines including regulated hydrocarbon (HC) and oxides of nitrogen (NOx) emissions, non-road engines are implementing proven technologies from the on-road market. For example, four stroke diesel generators now include additional internal exhaust gas recirculation (EGR) via an intake/exhaust valve passage. EGR can offer benefits of reduced HC, NOx, and may even improve combustion stability and fuel efficiency. In addition, there is particular interest in use of natural gas as fuel for home power generation. This paper examines exhaust throttling applied to the Helmholtz resonator of a two-stroke, port injected, natural gas engine. The 34 cc engine was air cooled and operated at wide-open throttle (WOT) conditions at an engine speed of 5400 RPM with fueling adjusted to achieve maximum brake torque. Exhaust throttling served as a method to decrease the effective diameter of the outlet of the convergent cone.

Gaseous and particulate emissions from heavy-duty vehicles are affected by fuel types, vehicle/engine parameters, driving characteristics, and environmental conditions. Transient chassis tests were conducted on twenty-six heavy-duty vehicles fueled with methanol, compressed natural gas (CNG), #1 diesel, and #2 diesel, using West Virginia University (WVU) Transportable Heavy-Duty Vehicle Emissions Testing Laboratory. The vehicles were operated on the central business district (CBD) testing cycle, and regulated emissions of carbon monoxide (CO), total hydrocarbon (HC), nitrogen oxides (NOx), and particulate matter (PM) were measured. Comparisons of regulated emissions results revealed that the vehicles powered on methanol and CNG produced much lower particulate emissions than the conventionally fueled vehicles.

The West Virginia University (WVU) Transportable Heavy-Duty Vehicle Emissions Testing Laboratory was employed to conduct chassis dynamometer tests in the field to measure the exhaust emissions from heavy-duty buses and trucks. This laboratory began operation in the field in January, 1992. During the period January, 1992 through June, 1993, over 150 city buses, trucks, and tractors operated by 18 different authorities in 11 states were tested by the facility. The tested vehicles were powered by 14 different types of engines fueled with natural gas (CNG or LNG), methanol, ethanol, liquified petroleum gas (LPG), #2 diesel, and low sulfur diesel (#1 diesel or Jet A). Some of the tested vehicles were equipped with exhaust after-treatment systems. In this paper, a total of 12 CNG-fueled and #2 diesel-fueled transit buses equipped with Cummins L-10 engines, were chosen for investigation.

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.

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.

Emissions from trucks and buses equipped with Caterpillar dual-fuel natural gas (DFNG) engines were measured at two chassis dynamometer facilities: the West Virginia University (WVU) Transportable Emissions Laboratory and the Los Angeles Metropolitan Transportation Authority (LA MTA). Emissions were measured over four different driving cycles. The average emissions from the trucks and buses using DFNG engines operating in dual-fuel mode showed the same trends in all tests - reduced oxides of nitrogen (NOx) and particulate matter (PM) emissions and increased hydrocarbon and carbon monoxide (CO) emissions - when compared to similar diesel trucks and buses. The extent of NOx reduction was dependent on the type of test cycle used.

The objective of this project, which is supported by the U.S. Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL), is to provide a comprehensive comparison of heavy-duty trucks operating on alternative fuels and diesel fuel. Data collection from up to eight sites is planned. Currently, the project has four sites: Raley's in Sacramento, CA (Kenworth, Cummins L10-300G, liquefied natural gas - LNG); Pima Gro Systems, Inc. in Fontana, CA (White/GMC, Caterpillar 3176B Dual-Fuel, compressed natural gas - CNG); Waste Management in Washington, PA (Mack, Mack E7G, LNG); and United Parcel Service in Hartford, CT (Freightliner Custom Chassis, Cummins B5.9G, CNG). This paper summarizes current data collection and evaluation results from this project.