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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).

As emission regulations become increasingly strict, the need for more accurate sampling systems becomes essential. When calculating emissions from a dilution system, a correction is made to remove the effects of contaminants in the dilution air. The dilution air correction was explored to determine why this correction is needed, when this correction is important, and what methods are available for calculating the dilution factor (DF). An experimental and error analysis investigation into the standard and recently proposed methods for calculating the DF was conducted. Five steady state modes were run on a 1992 Detroit Diesel engine series 60 and the DF from eleven different equations were investigated. The effects of an inaccurate dilution air correction on calculated fuel flow from a carbon balance and the mass emissions was analyzed. The dilution air correction was shown to be important only for hydrocarbons, particulate matter (PM), and CO2.

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.

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.

Although diesel engines still power most of the heavy-duty transit buses in the United States, many major cities are also operating fleets where a significant percentage of buses is powered by lean-burn natural gas engines. Emissions from these buses are often expressed in distance-specific units of grams per mile (g/mile) or grams per kilometer (g/km), but the driving cycle or route employed during emissions measurement has a strong influence on the reported results. A driving cycle that demands less energy per unit distance than others results in higher fuel economy and lower distance-specific oxides of nitrogen emissions. In addition to energy per unit distance, the degree to which the driving cycle is transient in nature can also affect emissions.

The 1998 Consent Decrees between the United States Government and the settling heavy-duty diesel engine manufacturers require in-use emissions testing from post 2000 model year engines. The emissions gathered from these engines must be reported on a brake-specific mass basis. To report brake-specific mass emissions, three primary parameters must be measured. These are the concentration of each emission constituent, the exhaust mass flow rate, and the engine power output. The measurement of the concentration level and exhaust mass flow rate can be (and are generally) measured directly with instrumentation installed in the exhaust transfer tube. However, engine power cannot be measured directly for in-use emissions testing due to the direct coupling of the engine output shaft to the vehicle's transmission. Engine power can be inferred from the electronic control unit (ECU) broadcast of engine speed and engine torque.

Heavy duty diesel vehicle (HDDV) emissions are known to affect air quality, but few studies have quantified the real-world contribution to the inventory. The objective of this study was to provide data that may enable ambient emissions investigators to m,odel the air quality more accurately. The 25 vehicles reported in this paper are from the first phase of a program to determine representative regulated emissions from Heavy Heavy-Duty Diesel Trucks (HHDDT) operating in Southern California. Emissions data were gathered using a chassis dynamometer, full flow dilution tunnel, and research grade analyzers. The subject program employed two truck test weights and four new test modes (one was idle operation), in addition to the Urban Dynamometer Driving Schedule (UDDS), and the AC50/80 cycle. The reason for such a broad test cycle scope was to determine thoroughly how HHDDT emissions are influenced by operating cycle to improve accuracy of models.

The 1998 Consent Decrees between the settling heavy-duty diesel engine manufacturers and the United States Government require the engine manufacturer to perform in-use emissions testing to evaluate their engine designs and emissions when the vehicle is placed into service. This additional requirement will oblige the manufacturer to account for real-world conditions when designing engines and engine control algorithms and include driving conditions, ambient conditions, and fuel properties in addition to the engine certification test procedures. Engine operation and ambient conditions can be designed into the engine control algorithm. However, there will most likely be no on-board determination of fuel properties or composition in the near future. Therefore, the engine manufacturer will need to account for varying fuel properties when developing the engine control algorithm for when in-use testing is performed.

In 2007, the Environmental Protection Agency will begin measuring not only exhaust emissions from diesel engines, but also emissions from the crankcase if it is not vented into the engine intake. The 2007 government standards for emissions of carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NOx) and particulate matter (PM) will also become more restrictive. There is the additional concern that crankcase emissions from present day trucks and buses may impact the quality of air inside the vehicle. This paper presents data to characterize crankcase emissions and examines a crankcase emissions abatement system (CEAS), the New Condensator®, manufactured by World NCI. Rather than allowing crankcase emissions to leave via a vent tube, a CEAS re-circulates the emissions to the intake of the engine.

Six 2001 International Class 6 trucks participated in a project to determine the impact of gas-to-liquid (GTL) fuel and catalyzed diesel particle filters (DPFs) on emissions and operations from December 2003 through August 2004. The vehicles operated in Southern California and were nominally identical. Three vehicles operated “as-is” on California Air Resources Board (CARB) specification diesel fuel and no emission control devices. Three vehicles were retrofit with Johnson Matthey CCRT® (Catalyzed Continuously Regenerating Technology) filters and fueled with Shell GTL Fuel. Two rounds of emissions tests were conducted on a chassis dynamometer over the City Suburban Heavy Vehicle Route (CSHVR) and the New York City Bus (NYCB) cycle. The CARB-fueled vehicles served as the baseline, while the GTL-fueled vehicles were tested with and without the CCRT filters. Results from the first round of testing have been reported previously (see 2004-01-2959).

When heavy-duty truck emissions rates are expressed in distance-specific units (such as g/mile), average speed and the degree of transient behavior of the vehicle activity can affect the emissions rate. Previous one-dimensional studies have shown some correlation of distance-specific emissions rates between cycles. This paper reviews emissions data sets from the 5-mode CARB Heavy Heavy-Duty Diesel Truck (HHDDT) Schedule, the Heavy Duty Urban Dynamometer Driving Schedule (UDDS) and an inspection and maintenance cycle, known as the AC5080. A heavy-duty chassis dynamometer was used for emissions characterization along with a full-scale dilution tunnel. The vehicle test weights were simulated at 56,000 lbs. Two-dimensional correlations were used to predict the emissions rate on one mode or cycle from the rates of two other modes or cycles.

Increasingly stringent oxides of nitrogen (NOx) and particulate matter (PM) regulations worldwide have prompted considerable activity in developing emission control technology to reduce the emissions of these two constituents from heavy-duty diesel engines. NOx has come under particular scrutiny by regulators in the US and in Europe with the promulgation of very stringent regulation by both the US Environmental Protection Agency (EPA) and the European Union (EU). In response, heavy-duty engine manufacturers are considering Selective Catalytic Reduction (SCR) as a potential NOx reduction option. While SCR performance has been well established through engine dynamometer evaluation under laboratory conditions, there exists little data characterizing SCR performance under real-world operating conditions over time. This project evaluated the field performance of ten SCR units installed on heavy-duty Class 8 highway and refuse trucks.

Emissions from diesel engines, particularly NOx and TPM emissions are harmful to the environment. Reduction of NOx emissions from diesel engines is of increasing concern. In 1998, a novel approach called Selective NOx Recirculation (SNR) was used to reduce NOx emissions in diesel engines. The SNR concept relies on two major parts, one to collect the NOx emissions from the exhaust by an adsorber, and another to decompose NOx using the in-cylinder combustion process by injecting the collected NOx emissions into the intake manifold at an elevated concentration. This paper deals with the destruction rates during the combustion process. A 1992 DDC series 60, 350 hp, 12.7 liter engine was connected to a 500 hp DC dynamometer. A full-scale dilution tunnel and analyzers capable of measuring continuous NOx, CO2, CO, HC, and PM in the exhaust were used.

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.

When heavy-duty truck emissions are expressed in distance-specific units (such as g/mile), the values may depend strongly on the nature of the test cycle or schedule. Prior studies have compared emissions gained using different schedules and have proposed techniques for translating emissions factor rates between schedules. This paper reviews emissions data from the 5-mode CARB HHDDT Schedule, UDDS Schedule, and a steady-state cycle (AC5080), with reference to each other. NOX and PM emissions are the two components of emissions which are reviewed. A heavy-duty chassis dynamometer was used for emissions characterization along with a full scale dilution tunnel. The vehicle test weights were simulated at 30,000 lbs, 56,000 lbs, and 66,000 lbs. For each vehicle, average data from one mode or cycle have been compared with average data for a different mode or cycle.

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).

West Virginia University redesigned a 2002 Ford Explorer and created a diesel electric hybrid vehicle to satisfy the goals of the 2002 FutureTruck competition. These goals were to demonstrate a 25% improvement in fuel economy, to reduce greenhouse gas emissions, to achieve California ULEV emissions, to demonstrate 1/8-mile acceleration of 11.5 seconds or less, and to maintain vehicular comforts and performance. West Virginia University's 2002 hybrid sport utility vehicle (SUV), the Exclaim!, meets or exceeds these goals. Using a post-transmission parallel configuration, WVU integrated a 2.5L Detroit Diesel Corporation engine along with a Unique Mobility 75kW electric motor to replace the stock drivetrain. With an emphasis on maintaining performance, WVU strived to improve areas where SUVs have traditionally performed poorly: fuel economy and emissions. Using regenerative braking, fuel economy has been significantly improved.

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).