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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.

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.

A multi-year technology validation program was completed in 2001 to evaluate ultra-low sulfur diesel fuels and passive diesel particle filters (DPF) in several different diesel fleets operating in Southern California. The fuels used throughout the validation program were diesel fuels with less than 15-ppm sulfur content. Trucks and buses were retrofitted with two types of passive DPFs. Two rounds of emissions testing were performed to determine if there was any degradation in the emissions reduction. The results demonstrated robust emissions performance for each of the DPF technologies over a one-year period. Detailed descriptions of the overall program and results have been described in previous SAE publications [2, 3, 4, 5]. In 2002, a third round of emission testing was performed by NREL on a small subset of vehicles in the Ralphs Grocery Truck fleet that demonstrated continued robust emissions performance after two years of operation and over 220,000 miles.

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).

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).

Emissions tests for heavy -duty diesel-fueled engines and vehicles are normally performed using engine dynamometers and chassis dynamometers, respectively, with laboratory grade gaseous concentration measurement analyzers and supporting test equipment. However, a considerable effort has been recently expended on developing in-use, on-board tools to measure brake-specific emissions from heavy -duty vehicles with the highest degree of accuracy and precision. This alternative testing methodology would supplement the emissions data that is collected from engine and chassis dynamometer tests. The on-board emissions testing methodology entails actively recording emissions and vehicle operating parameters (engine speed and load, vehicle speed etc.) from vehicles while they are operating on the road. This paper focuses on in-use measurements of NOX with zirconium oxide sensors and other portable NOX detectors.

In characterizing the emissions from mobile sources, it is essential that the vehicle be exercised in a way that reasonably represents typical in-use behavior. A heavy-heavy duty diesel truck (HHDDT) test schedule was developed from speed-time data gathered during two Air Resources Board-sponsored truck activity programs. The data were divided into four modes, termed Idle, Creep, Transient and Cruise Modes, in order of increasing speed. For the last three modes, speed-time schedules were created that represented all the data in that mode. Statistical parameters such as average speed, stops per unit distance, kinetic energy, maximum speed and acceleration and deceleration values were considered in arriving at these schedules. The schedules were evaluated using two Class 8 over-the-road tractors on a chassis dynamometer. Emissions were measured using a full-scale dilution tunnel, filtration for particulate matter (PM), and research grade analyzers for the gases.

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.

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.

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.

West Virginia University evaluated diesel oxidation catalysts (DOC) and lean-NOX catalysts as part of Diesel Emissions Control-Sulfur Effects (DECSE) project. In order to perform thermal aging of the DOC and lean-NOX catalysts simultaneously and economically, each catalyst was sized to accommodate half of the engine exhaust flow. Simultaneous catalyst aging was then achieved by splitting the engine exhaust into two streams such that approximately half of the total exhaust flowed through the DOC and half through the lean-NOX catalyst. This necessitated splitting the engine exhaust into two streams during emissions measurements. Throttling valves installed in each branch of the split exhaust were adjusted so that approximately half the engine exhaust passed though the active catalyst under evaluation and into a full flow dilution tunnel for emissions measurement.

Particulate emission control from diesel engines is one of the major concerns in the urban areas in California. Recently, regulations have been proposed for stringent PM emission requirements from both existing and new diesel engines. As a result, particulate emission control from urban diesel engines using advanced particulate filter technology is being evaluated at several locations in California. Although ceramic based particle filters are well known for high PM reductions, the lack of effective and durable regeneration system has limited their applications. The continuously regenerated diesel particulate filter (CRDPF) technology discussed in this presentation, solves this problem by catalytically oxidizing NO present in the diesel exhaust to NO2 which is utilized to continuously combust the engine soot under the typical diesel engine operating condition.

Hybrid diesel electric buses offer the advantage of superior fuel economy through use of regenerative braking and lowered transient emissions by reducing the need of the engine to follow load as closely as in a conventional bus. With the support of the Department of Energy (DOE), five Lockheed Martin-Orion hybrid diesel-electric buses were operated on the West Virginia University Transportable Laboratory in Brooklyn, New York. The buses were exercised through a new cycle, termed the Manhattan cycle, that was representative of today's bus use as well as the accepted Central Business District Cycle and New York Bus Cycle. Emissions data were corrected for the state of charge of the batteries. The emissions can be expressed in units of grams/mile, grams/axle hp-hr and grams/gallon fuel. The role of improved fuel economy in reducing oxides of nitrogen relative to conventional automatic buses is evident in the data.

Emissions from heavy-duty vehicles may be reduced through the introduction of clean diesel formulations, and through the use of catalyzed particulate matter filters that can enjoy increased longevity and performance if ultra-low sulfur diesel is used. Twenty over-the-road tractors with Detroit Diesel Series 60 engines were selected for this study. Five trucks were operated on California (CA) specification diesel (CARB), five were operated on ARCO (now BP Amoco) EC diesel (ECD), five were operated on ARCO ECD with a Johnson-Matthey Continuously Regenerating Technology (CRT) filter and five were operated on ARCO ECD with an Engelhard Diesel Particulate Filter (DPX). The truck emissions were characterized using a transportable chassis dynamometer, full-scale dilution tunnel, research grade gas analyzers and filters for particulate matter (PM) mass collection. Two test schedules, the 5 mile route and the city-suburban (heavy vehicle) route (CSR), were employed.

Hybrid-electric transit buses offer benefits over conventional transit buses of comparable capacity. These benefits include reduced fuel consumption, reduced emissions and the utilization of smaller engines. Factors allowing for these benefits are the use of regenerative braking and reductions in engine transient operation through sophisticated power management systems. However, characterization of emissions from these buses represents new territory: the whole vehicle must be tested to estimate real world tailpipe emissions levels and fuel economy. The West Virginia University Transportable Heavy Duty Emissions Testing Laboratories were used to characterize emissions from diesel hybrid-electric powered as well as diesel and natural gas powered transit buses in Boston, MA and New York City.

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.