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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).

This paper reviews fuel-saving technologies for commercial trailers, provides an overview of the trailer market in the U.S., and explores options for policy measures at the federal level that can promote the development and deployment of trailers with improved efficiency. For trailer aerodynamics, there are many technologies that exist and are in development to target each of the three primary areas where drag occurs: 1) the tractor-trailer gap, 2) the side and underbody of the trailer, and 3) the rear end of the trailer. In addition, there are tire technologies and weight reduction opportunities for trailers, which can lead to reduced rolling resistance and inertial loss. As with the commercial vehicle sector, the trailer market is diverse, and there are a variety of sizes and configurations that are employed to meet a wide range of freight demands.

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).

Yard hostlers are tractors (switchers) used to move containers at ports and storage facilities. While many speed-time driving cycles for assessing emissions and performance from heavy-duty vehicles exist, a driving cycle representative of yard hostler activity at Port of Long Beach, CA was not available. Activity data were collected from in-use yard hostlers as they performed ship loading/unloading, rail loading/unloading and other yard routines, primarily moving containers on trailers or carts. The activity data were then used to develop four speed-time driving cycles with durations of 1200 seconds, representing light and heavy ship activities and light and heavy load rail activities. These cycles were constructed using actual speed-time data collected during activity logging and the cycles created were statistically comparable to each subset of activity data.

Recent chassis testing of hybrid buses demonstrated the potential of hybrid technology to reduce emissions and raise fuel economy relative to conventional buses. However, hybrid buses represent a certification quandary because the engines must be certified using the accepted Federal Test Procedure (FTP), without regard for benefits that may arise from less transient engine operation. Actual engine operating data from series configuration hybrid buses were analyzed to determine the envelopes of torque and speeds covered by the engine. Transient engine operation was also considered in terms of rates of change of torque, power and speed. These measures did not compare closely with similar measures computed from the FTP because the series hybrid engines explored a more structured zone of operation than the FTP implied and because the FTP represented more transient operation.

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.

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.

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.

Heavy-duty trucks are an important sector to evaluate when seeking fuel consumption savings and emissions reductions. With fuel costs on the rise and emissions regulations becoming stringent, vehicle manufacturers find themselves spending large amounts of capital improving their products in order to be compliant with regulations. The Powertrain System Analysis Toolkits (PSAT), developed by the Argonne National Laboratory (ANL), is a simulation tool that helps mitigate costs associated with research and automotive system design. While PSAT has been widely used to predict the fuel consumption and exhaust emissions of conventional and hybrid light-duty vehicles, it also may be employed to test heavy-duty vehicles. The intent of this study was to develop an accurate model that predicts emissions and fuel economy for heavy-duty vehicles for use within PSAT.

Heavy duty tractor-trailers under freeway operations consume about 65% of the total engine shaft energy to overcome aerodynamic drag force. Vehicles are exposed to on-road crosswinds which cause change in pressure distribution with a relative wind speed and yaw angle. The objective of this study was to analyze the drag losses as a function of on-road wind conditions, on-road vehicle position and trajectory. Using coefficient of drag (CD) data available from a study conducted at NASA Ames, Geographical Information Systems model, time-varying weather data and road data, a generic model was built to identify the yaw angles and the relative magnitude of wind speed on a given route over a given time period. A region-based analysis was conducted for a study on interstate trucking operation by employing I-79 running through West Virginia as a case study by initiating a run starting at 12am, 03/03/2012 out to 12am, 03/05/2012.

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.

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.

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).

Repeatable measurement of real-world heavy-duty diesel truck emissions requires the use of a chassis dynamometer with a test schedule that reasonably represents actual truck use. A new Heavy Heavy-Duty Diesel Truck (HHDDT) schedule has been created that consists of four modes, termed Idle, Creep, Transient and Cruise. The effect of driving style on emissions from the Transient Mode was studied by driving a 400 hp Mack tractor at 56,000 lbs. test weight in fashions termed “Medium”, “Good”, “Bad”, “Casual” and “Aggressive”. Although there were noticeable differences in the actual speed vs. time trace for these five styles, emissions of the important species oxides of nitrogen (NOx) and particulate matter (PM), varied little with a coefficient of variation (COV) of 5.13% on NOX and 10.68% on PM. Typical NOx values for the HHDDT Transient mode ranged from 19.9 g/mile to 22.75 g/mile. The Transient mode which was the most difficult mode to drive, proved to be repeatable.

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.

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.

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.

Chassis based emissions characterization of heavy-duty vehicles has advanced over the last decade, but the understanding of the effect of test schedule on measured emissions is still poor. However, this is an important issue because the test schedule should closely mimic actual vehicle operation or vocation. A wide variety of test schedules was reviewed and these cycles were classified as cycles or routes and as geometric or realistic. With support from the U.S. Department of Energy Office of Transportation Technologies (DOE/OTT), a GMC box truck with a Caterpillar 3116 engine and a Peterbilt over the road tractor-trailer with a Caterpillar 3406 engine were exercised through a large number of cycles and routes. Test weight for the GMC was 9,980 kg and for the Peterbilt was 19,050 kg. Emissions characterization was performed using a heavy-duty chassis dynamometer, with a full-scale dilution tunnel, analyzers for gaseous emissions, and filters for PM emissions.