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Technical Paper

Effects of Average Driving Cycle Speed on Lean-Burn Natural Gas Bus Emissions and Fuel Economy

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.
Technical Paper

The DOE/NREL Environmental Science Program

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.
Technical Paper

Neural Network Modeling of Emissions from Medium-Duty Vehicles Operating on Fisher-Tropsch Synthetic Fuel

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.
Technical Paper

Weight Effect on Emissions and Fuel Consumption from Diesel and Lean-Burn Natural Gas Transit Buses

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).
Technical Paper

Weighting of Parameters in Artificial Neural Network Prediction of Heavy-Duty Diesel Engine Emissions

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.
Technical Paper

Speciation of Organic Compounds from the Exhaust of Trucks and Buses: Effect of Fuel and After-Treatment on Vehicle Emission Profiles

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).
Technical Paper

Operating Envelopes of Hybrid Bus Engines

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.
Technical Paper

Performance and Durability Evaluation of Continuously Regenerating Particulate Filters on Diesel Powered Urban Buses at NY City Transit

Particulate emission from diesel engines is one of the most important pollutants in urban areas. As a result, particulate emission control from urban bus diesel engines using particle filter technology is being evaluated at several locations in the US. A project entitled “Clean Diesel Demonstration Program” has been initiated by NY City Transit under the supervision of NY State DEC and with active participation from several industrial partners. Under this program, several NY City transit buses with DDC Series 50 engines have been equipped with continuously regenerating diesel particulate filter system and are operating with ultra low sulfur diesel (< 30 ppm S) in transit service in Manhattan since February 2000. These buses are being evaluated over a 8-9 month period for operations, maintainability and durability of the particulate filter.
Technical Paper

Emission Reductions and Operational Experiences With Heavy Duty Diesel Fleet Vehicles Retrofitted with Continuously Regenerated Diesel Particulate Filters in Southern California

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.
Technical Paper

Class 8 Trucks Operating On Ultra-Low Sulfur Diesel With Particulate Filter Systems: Regulated Emissions

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.
Technical Paper

Effect on Emissions of Multiple Driving Test Schedules Performed on Two Heavy-Duty Vehicles

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.
Technical Paper

Comparative Toxicity of Gasoline and Diesel Engine Emissions

Better information on the comparative toxicity of airborne emissions from different types of engines is needed to guide the development of heavy vehicle engine, fuel, lubricant, and exhaust after-treatment technologies, and to place the health hazards of current heavy vehicle emissions in their proper perspective. To help fill this information gap, samples of vehicle exhaust particles and semi-volatile organic compounds (SVOC) were collected and analyzed. The biological activity of the combined particle-SVOC samples is being tested using standardized toxicity assays. This report provides an update on the design of experiments to test the relative toxicity of engine emissions from various sources.
Technical Paper

Characterization of Emissions from Hybrid-Electric and Conventional Transit Buses

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.
Technical Paper

Development of a Driving Schedule to Mimic Transit Bus Behavior in Mexico City

It is difficult to project the emissions performance of a vehicle on a route unless the test cycle used to gain the emissions data reasonably represents that route. A chassis dynamometer emissions measurement test schedule consisting of three modes (congested, non-congested and bus rapid transit (BRT) operation) was developed for use in a program to evaluate transit bus technologies in Mexico City. Existing buses were fitted with global positioning system (GPS) data loggers and, between September 2nd and 8th of 2004, 54 hours of speed-time data were collected while the buses were operated over several bus routes in Mexico City. The data set was then broken down into individual micro-trips, each consisting of an idle period followed by the bus traveling some distance, followed by a final deceleration to idle.
Technical Paper

Final Operability and Chassis Emissions Results from a Fleet of Class 6 Trucks Operating on Gas-to-Liquid Fuel and Catalyzed Diesel Particle Filters

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).
Technical Paper

Hybrid Diesel-Electric Heavy Duty Bus Emissions: Benefits Of Regeneration And Need For State Of Charge Correction

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.
Technical Paper

Chassis Dynamometer Emissions Characterization of a Urea-SCR Transit Bus

West Virginia University characterized the emissions and fuel economy performance of a 30-foot 2010 transit bus equipped with urea selective catalytic reduction (u-SCR) exhaust aftertreatment. The bus was exercised over speed-time driving schedules representative of both urban and on-highway activity using a chassis dynamometer while the exhaust was routed to a full-scale dilution tunnel with research grade emissions analyzers. The Paris speed-time driving schedule was used to represent slow urban transit bus activity while the Cruise driving schedule was used to represent on-highway activity. Vehicle weights representative of both one-half and empty passenger loading were evaluated. Fuel economy observed during testing with the urban driving schedule was significantly lower (55%) than testing performed with the on-highway driving schedule.
Technical Paper

Multidimensional Correlation Study Using Linear Regression of PM and NOX for Heavy Duty Diesel Vehicles

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.
Technical Paper

Emissions Modeling of Heavy-Duty Conventional and Hybrid Electric Vehicles

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.
Technical Paper

Quantification of Energy Pathways and Gas Exchange of a Small Port Injection SI Two-Stroke Natural Gas Engine Operating on Different Exhaust Configurations

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.