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The Advanced Collaborative Emissions Study (ACES) program required the use of representative heavy-duty diesel engine activity. This need resulted in an engine test schedule creation program, and a schedule of engine modes representative of modern truck usage was developed based on data collected from engines in trucks operated through the heavy heavy-duty diesel truck (HHDDT) chassis schedule. The ACES test schedule included four active modes of truck operation including creep, transient, cruise, and high-speed cruise (HHDDT_S). This paper focuses on Phase 2 of the program, which was to validate and demonstrate the use of the ACES modes in a test cell. Preliminary testing was performed using a 1992 Detroit Diesel Corporation heavy heavy-duty diesel engine (HHDDE) on only the transient mode. On the basis of these results, each mode was modified slightly to suit implementation in a test cell. The locations of "closed throttle" points in the modes were determined through careful examination of the data. These closed throttle points were simulated during testing by adding negative set point torque values to the input file. After modification, all modes were tested during a final ACES modes demonstration period using a 2004 Cummins ISM HHDDE, obtaining three runs for each mode. During testing, carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), particulate matter (PM), and hydrocarbon (HC) emissions were measured, and engine control unit (ECU) data were recorded. The new ACES modes did not adopt the Federal Test Procedure (FTP) regression criteria. New regression criteria for acceptability of a run were determined for each mode using the data obtained during testing. [ABSTRACT FROM AUTHOR]

The Advanced Collaborative Emissions Study (ACES) has the objective of characterizing the emissions and assessing the possible health impacts of the 2007-2010 heavyduty diesel engines and their control systems. The program seeks to examine emissions from engines operated in a realistic duty cycle and requires the development of an engine test schedule described in this paper. Field data on engine operation were available from Engine Control Unit (ECU) broadcasts from seven heavy heavy-duty trucks (HHDDT) tested during the Coordinating Research Council (CRC) E-55/59 study. These trucks were exercised at three weights (30,000 lb [13,610 kg], 56,000 lb [25,400 kg], and 66,000 lb [29,940 kg]) through four different active modes of a chassis test schedule that were developed from the data of in-use HHDDT operation in the state of California. The trucks were equipped with heavyduty engines made by three major U.S. engine manufacturers with a range of model years from 1998 to 2003. This paper reports on the development of four engine test modes, termed creep, transient, cruise, and high-speed cruise (HHDDT_S), which correspond to the E-55/59 HHDDT chassis test modes. The creep and transient modes represent urban travel, and the cruise and HHDDT_S modes represent freeway operation. The test mode creation used the method of joining selected truck trips together while ensuring that they offered a reasonable statistical representation of the whole database by using a least-square errors method. Least-square errors between test modes and the database are less than 5%. The four test modes are presented in normalized engine speed and torque according to the definitions presented in the Code of Federal Regulations, Title 40, Part 86. [ABSTRACT FROM AUTHOR]

Idle emissions data from 19 medium heavy-duty diesel and gasoline trucks are presented in this paper. Emissions from these trucks were characterized using full-flow exhaust dilution as part of the Coordinating Research Council (CRC) Project E-55/59. Idle emissions data were not available from dedicated measurements, but were extracted from the continuous emissions data on the low-speed transient mode of the medium heavy-duty truck (MHDTLO) cycle. The four gasoline trucks produced very low oxides of nitrogen (NOx) and negligible particulate matter (PM) during idle. However, carbon monoxide (CO) and hydrocarbons (HCs) from these four trucks were approximately 285 and 153 g/hr on average, respectively. The gasoline trucks consumed substantially more fuel at an hourly rate (0.84 gal/hr) than their diesel counterparts (0.44 gal/hr) during idling. The diesel trucks, on the other hand, emitted higher NOx (79 g/hr) and comparatively higher PM (4.1 g/hr), on average, than the gasoline trucks (3.8 g/hr of NOx and 0.9 g/hr of PM, on average). Idle NOx emissions from diesel trucks were high for post-1992 model year engines, but no trends were observed for fuel consumption. Idle emissions and fuel consumption from the medium heavy-duty diesel trucks (MHDDTs) were marginally lower than those from the heavy heavy-duty diesel trucks (HHDDTs), previously reported in the literature. [ABSTRACT FROM AUTHOR]

The two main propulsion engines on Staten Island Ferry Alice Austen (Caterpillar 3516A, 1550 hp each) were fitted with selective catalytic reduction (SCR) aftertreatment technology to reduce emissions of oxides of nitrogen (NOx). After the installation of the SCR system, emissions from the ferry were characterized both pre- and postaftertreatment. Prior research has shown that the ferry operates in four modes, namely idle, acceleration, cruise, and maneuvering modes. Emissions were measured for both engines (designated NY and SI) and for travel in both directions between Manhattan and Staten Island. The emissions characterization used an analyzer system, a data logger, and a filter-based particulate matter (PM) measurement system. The measurement of NOx, carbon monoxide (CO), and carbon dioxide (CO2) were based on federal reference methods. With the existing control strategy for the SCR urea injection, the SCR provided approximately 64% reduction of NOx for engine NY and 36% reduction for engine SI for a complete round trip with less than 6.5 parts per million by volume (ppmv) of ammonia slip during urea injection. Average reductions during the cruise mode were 75% for engine NY and 47% for engine SI, which was operating differently than engine NY. Reductions for the cruise mode during urea injection typically exceeded 94% from both engines, but urea was injected only when the catalyst temperature reached a 300 °C threshold pre- and postcatalyst. Data analysis showed a total NOx mass emission split with 80% produced during cruise, and the remaining 20% spread across idle, acceleration, and maneuvering. Examination of continuous NOx data showed that higher reductions of NOx could be achieved on both engines by initiating the urea injection at an earlier point (lower exhaust temperature) in the acceleration and cruise modes of operation. The oxidation catalyst reduced the CO production 94% for engine NY and 82% for engine SI, although the high CO levels during acceleration did cause analyzers to overrange. No clear, quantitative conclusions could be made regarding the effects of the SCR on PM. [ABSTRACT FROM AUTHOR]

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NOx), particulate matter (PM), and carbon dioxide (CO2) have been reported. Idle CO2 emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted ∼20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NOx, 1 g/hr of PM, and 4636 g/hr of CO2 during idle. MFI equipped vehicles emitted ∼35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NOx, 4 g/hr of PM, and 4484 g/hr of CO2, on average, during idle. Vehicles with EFI emitted less idle CO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NOx, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO2 and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO2, NOx, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO2 and NOx emissions and fuel consumption increased by <150%, whereas PM and HC emissions increased by ∼100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NOx, and PM emissions and consumed fuel at only 75% of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell. [ABSTRACT FROM AUTHOR]

In-use emissions from vehicles using heavy-duty diesel engines can be significantly higher than the levels obtained during engine certification. These higher levels may be caused by a combination of degradation of engine components, poor engine maintenance, degradation or failure of emissions after-treatment devices, and engine and emissions system tampering. A direct comparison of in-use vehicle emissions with engine certification levels, however, is not possible without removing an engine from the vehicle in order to perform engine dynamometer emissions testing. The goal of this research was to develop a chassis test procedure that mimics the engine performance, and as such the expected emissions levels, from the engine certification emissions test prescribed in the U.S. Code of Federal Regulations. Emissions measurements were taken from two engines during testing on an engine dynamometer using the transient heavy-duty Federal Test Procedure (FTP). Additionally, each engine was installed in an appropriate vehicle, and emissions measurements were taken using a chassis dynamometer while employing a vehicle driving schedule intended to match closely the instantaneous torque and speed schedule of the engine FTP. Engine and chassis testing was performed with the engines in stock (unmodified) condition as well as in several modes to simulate either tampered or poorly maintained conditions. The use of a chassis test as a predictive tool for determining whether an engine in a vehicle would pass the engine certification test has proven to be worthwhile. Analysis of the data shows that identification of chassis-mounted engines with NO[subx] emissions above certification levels is possible by employing engine-specific correction factors. In the case of PM emissions, significant data scatter allowed only the identification of gross PM emitters. Engine tampering and poor maintenance can raise PM and NO[subx] emissions, and these increase can be correctly... [ABSTRACT FROM AUTHOR]

Diesel particulate matter (PM) is a significant contributor to ambient air PM[sub10] and PM[sub2.5] particulate levels. In addition, recent literature argues that submicron diesel PM is a pulmonary health hazard. There is difficulty in attributing PM emissions to specific operating modes of a diesel engine, although it is acknowledged that PM production rises dramatically with load and that high PM emissions occur during rapid load increases on turbocharged engines. Snap-acceleration tests generally identify PM associated with rapid transient operating conditions, but not with high load. To quantify the origin of PM during transient engine operation, continuous opacity measurements have been made using a Wager 650CP full flow exhaust opacity meter. Opacity measurements were taken while the vehicles were operated over transient driving cycles on a chassis dynamometer using the West Virginia University (WVU) Transportable Heavy Duty Vehicle Emissions Testing Laboratories. Data were gathered from Detroit Diesel, Cummins, Caterpillar, and Navistar heavy-duty (HD) diesel engines. Driving cycles used were the Central Business District (CBD) cycle, the WVU 5-Peak Truck cycle, the WVU 5-Mile route, and the New York City Bus (NYCB) cycle. Continuous opacity measurements, integrated over the entire driving cycle, were compared to total integrated PM mass. In addition, the truck was subjected to repeat snap-acceleration tests, and PM was collected for a composite of these snap-acceleration tests. Additional data were obtained from a fleet of 1996 New Flyer buses in Flint, MI, equipped with electronically controlled Detroit Diesel Series 50 engines. Again, continuous opacity, regulated gaseous emissions, and PM were measured. The relationship between continuous carbon monoxide (CO) emissions and continuous opacity was noted. In identifying the level of PM emissions in transient diesel engine operation, it is suggested that CO emissions may... [ABSTRACT FROM AUTHOR]

Enumerates factors affecting heavy-duty diesel vehicle emissions. Parameters that affect emissions from compression ignition engine-powered vehicles; Utility of the knowledge of each aspects of engine on the emission level; Documentation status of vehicle emission in case of heavy duty vehicles.

Models of diesel engine emissions such as oxides of nitrogen (NOx) are valuable when they can predict instantaneous values because they can be incorporated into whole vehicle models, support inventory predictions, and assist in developing superior engine and aftertreatment control strategies. Recent model-year diesel engines using multiple injection strategies, exhaust gas recirculation, and variable geometry turbocharging may have more transient sensitivity and demand more sophisticated modeling than for legacy engines. Emissions data from 1992, 1999, and 2004 model-year U.S. truck engines were modeled separately using a linear approach (with transient terms) and multivariate adaptive regression splines (MARS), an adaptive piece-wise regression approach that has limited prior use for emissions prediction. Six input variables based on torque, speed, power, and their derivatives were used for MARS. Emissions time delay was considered for both models. Manifold air temperature (MAT) and manifold air pressure (MAP) were further used in NOx modeling to build a plug-in model. The predictive performance for instantaneous NOx on part of the certification transient test procedure (Federal Test Procedure [FTP]) of the 2004 engine MARS was lower (R2 = 0.949) than the performance for the 1992 (R2 = 0.981) and 1999 (R2 = 0.988) engines. Linear regression performed similarly for the 1992 and 1999 engines but performed poorly (R2 = 0.896) for the 2004 engine. The MARS performance varied substantially when data from different cycles were used. Overall, the MAP and MAT plug-in model trained by MARS was the best, but the performance differences between LR and MARS were not substantial. [ABSTRACT FROM AUTHOR]

As part of the Gasoline/Diesel PM Split Study, relatively large fleets of gasoline vehicles and diesel vehicles were tested on a chassis dynamometer to develop chemical source profiles for source attribution of atmospheric particulate matter in California's South Coast Air Basin. Gasoline vehicles were tested in cold-start and warm-start conditions, and diesel vehicles were tested through several driving cycles. Tailpipe emissions of particulate matter were analyzed for organic tracer compounds, including hopanes, steranes, and polycyclic aromatic hydrocarbons. Large intervehicle variation was seen in emission rate and composition, and results were averaged to examine the impacts of vehicle ages, weight classes, and driving cycles on the variation. Average profiles, weighted by mass emission rate, had much lower uncertainty than that associated with intervehicle variation. Mass emission rates and elemental carbon/organic carbon (EC/OC) ratios for gasoline vehicle age classes were influenced most by use of cold-start or warm-start driving cycle (factor of 2-7). Individual smoker vehicles had a large range of mass and EC/OC (factors of 40 and 625, respectively). Gasoline vehicle age averages, data on vehicle ages and miles traveled in the area, and several assumptions about smoker contributions were used to create emissions profiles representative of on-road vehicle fleets in the Los Angeles area in 2001. In the representative gasoline fleet profiles, variation was further reduced, with coldstart or warm-start and the representation of smoker vehicles making a difference of approximately a factor of two in mass emission rate and EC/OC. Diesel vehicle profiles were created on the basis of vehicle age, weight class, and driving cycle. Mass emission rate and EC/OC for diesel averages were influenced by vehicle age (factor of 2-5), weight class (factor of 2-7), and driving cycle (factor of 10-20). Absolute and relative emissions of molecular marker compounds showed levels of variation similar to those of mass and EC/OC. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy Gasoline/Diesel PM Split Study examined the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the contributions of spark-ignition (SI) and compression-ignition (CI) engine exhaust to ambient fine particulate matter (PM2.5). This paper presents the chemical composition profiles of SI and CI engine exhaust from the vehicle-testing portion of the study. Chemical analysis of source samples consisted of gravimetric mass, elements, ions, organic carbon (OC), and elemental carbon (EC) by the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciation Trends Network (STN) thermal/optical methods, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, alkanes, and polar organic compounds. More than half of the mass of carbonaceous particles emitted by heavy-duty diesel trucks was EC (IMPROVE) and emissions from SI vehicles contained predominantly OC. Although total carbon (TC) by the IMPROVE and STN protocols agreed well for all of the samples, the STN/IMPROVE ratios for EC from SI exhaust decreased with decreasing sample loading. SI vehicles, whether low or high emitters, emitted greater amounts of high-molecular-weight particulate PAHs (benzo[ghi]perylene, indeno[1,2,3-cd]pyrene, and coronene) than did CI vehicles. Diesel emissions contained higher abundances of two- to four-ring semivolatile PAHs. Diacids were emitted by CI vehicles but are also prevalent in secondary organic aerosols, so they cannot be considered unique tracers. Hopanes and steranes were present in lubricating oil with similar composition for both gasoline and diesel vehicles and were negligible in gasoline or diesel fuels. CI vehicles emitted greater total amounts of hopanes and steranes on a mass per mile basis, but abundances were comparable to SI exhaust normalized to TC emissions within measurement uncertainty. The combustion-produced high-molecular-weight PAHs were found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil. The contributions of lubrication oils to abundances of these PAHs in the exhaust were large in some cases and were variable with the age and consumption rate of the oil. These factors contributed to the observed variations in their abundances to total carbon or PM2.5 among the SI composition profiles. [ABSTRACT FROM AUTHOR]

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NOx]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NOx in the case of a class-8 truck but were more accurate as the truck weight increased. [ABSTRACT FROM AUTHOR]