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Oxides of nitrogen (NOx) emissions, produced by engines that burn fuels with atmospheric air, are known to cause negative health and environmental effects. Increasingly stringent emissions regulations for marine engines have caused newer engines to be developed with inherent NOx reduction technologies. Older marine engines typically have a useful life of over 20 years and produce a disproportionate amount of NOx emissions when compared with their newer counterparts. Wet scrubbing as an aftertreatment method for emissions reduction was applied to ocean-going marine vessels for the reduction of sulfur oxides (SOx) and particulate matter (PM) emissions. The gaseous absorption process was explored in the laboratory as an option for reducing NOx emissions from older diesel engines of harbor craft operating in ports of Houston and Galveston. A scrubber system was designed, constructed, and evaluated to provide the basis for a real-world design.

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.

Biodiesel may be derived from either plant or animal sources, and is usually employed as a compression ignition fuel in a blend with petroleum diesel (PD). Emissions differences between vehicles operated on biodiesel blends and on diesel have been published previously, but data do not cover the latest engine technologies. Prior studies have shown that biodiesel offers advantages in reducing particulate matter, with either no advantage or a slight disadvantage for oxides of nitrogen emissions. This paper describes a recent study on the emissions impact of two biodiesel blends B20A, made from 20% animal fat (tallow) biodiesel and 80% PD, and B20B, obtained from 20% soybean biodiesel and 80% PD. These blends used the same PD fuel for blending and were contrasted with the same PD fuel as a reference. The research was conducted on a 2007 medium heavy-duty diesel truck (MHDDT), with an engine equipped with Exhaust Gas Recirculation (EGR) and a Diesel Particulate Filter (DPF).

Biodiesel fuels benefit both from being a renewable energy source and from decreasing in carbon monoxide (CO), total hydrocarbons (THC), and particulate matter (PM) emissions relative to petroleum diesel. The oxides of nitrogen (NOx) emissions from biodiesel blended fuels reported in the literature vary relative to baseline diesel NOx, with no NOx change or a NOx decrease found by some to an increase in NOx found by others. To explore differences in NOx, two Cummins ISM engines (1999 and 2004) were operated on 20% biodiesel blends during the heavy-duty transient FTP cycle and the steady state Supplemental Emissions Test. For the 2004 Cummins ISM engine, in-cylinder pressure data were collected during the steady state and transient tests. Three types of biodiesel fuels were used in the blends: soy, tallow (animal fat), and cottonseed. The FTP integrated emissions of the B20 blends produced a 20-35% reduction in PM and no change or up to a 4.3% increase in NOx over the neat diesel.

The key to overcoming Low Temperature Combustion (LTC) load range limitations is based on suitable control over the thermo-chemical properties of the in-cylinder charge. The proposed alternative to achieve the required control of LTC is the use of two separate fuel streams to regulate timing and heat release at specific operational points, where the secondary fuel, with different autoignition characteristics, is a reformed product of the primary fuel in the tank. It is proposed in this paper that the secondary fuel is produced using Thermo-Chemical Recuperation (TCR) with steam/fuel reforming. The steam/fuel mixture is heated by sensible heat from the engine exhaust gases in the recuperative reformer, where the original hydrocarbon reacts with water to form a hydrogen rich gas mixture. An equilibrium model developed by Gas Technology Institute (GTI) for n-heptane steam reforming was applied to estimate reformed fuel composition at different reforming temperatures.

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).

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.

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.

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.

Beginning 2007, heavy-duty engine certification would require that in-use emissions from vehicles be measured under ‘real-world’ operating conditions using on-board measurement devices. An on-board portable emissions measurement system called Mobile Emissions Measurement System (MEMS) was developed at West Virginia University (WVU) to record in-use, continuous and brake-specific emissions from heavy-duty diesel-powered vehicles. The objective of this paper is to present a preliminary development of a test data quality assurance methodology for emissions measured using the any portable emissions measurement system (PEMS). The first stage of the methodology requires ensuring the proper operation of the different sensors and transducers during data collection. The second stage is data synchronization and pre-processing. The next stage is systematic checking of possible errors from transducers and sensors.

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).

Continuously variable transmissions (CVTs) are usually used in small vehicles due to power limitations on the variable elements. Continuously variable power-split transmissions (CVPST) were developed in order to reduce the fraction of power passing through the variable elements [1,2]. The configuration presented in this paper includes a planetary gear train (PGT), which in combination with the CVT allows the power to be split and therefore increase the power envelope of the system. The PGT also provides a branch that can be used in a hybrid electric vehicle (HEV) operation through an electric motor. A conceptual design of a CVPST for a HEV is presented in this paper. The objectives are to show the different operational modes, with diagrams, perform a power analysis, develop the velocity and force equations and finally show the performance of the system with an example application.

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).

In an effort to develop engine/vehicle test methods that will reflect real-world emission characteristics, West Virginia University (WVU) designed and conducted a study on a Class-8 tractor with an electronically controlled diesel engine that was mounted on a chassis dynamometer in the Old Dominion University Langley full-scale wind tunnel. With wind speeds set at 88 km/hr in the tunnel, and the tractor operating at 88 km/hr on the chassis dynamometer, a Scanning Mobility Particle Sizer (SMPS) was employed for measuring PM size distributions and concentrations. The SMPS was housed in a container that was attached to a three-axis gantry in the wind tunnel. Background PM size-distributions were measured with another SMPS unit that was located upstream of the truck plume. Ambient temperatures were recorded at each of the sampling locations. The truck was also operated through transient tests with vehicle speeds varying from 65 to 88 km/hr, with a wind speed of 76 km/hr.

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.

When preparing inventory models, it is desirable to obtain representative distance-specific emissions factors that truthfully represent the vehicle activity on a particular road (facility) type. Unfortunately, emissions values are often measured using only one test schedule, which represents a single average speed and a specific type of activity. This paper investigated the accuracy of predicting the emissions for a test schedule based on measurements from a different test schedule for the case of a medium heavy-duty truck. First, the traditional Speed Correction Factor (SCF) approach was examined, followed by the use of a power-based model derived from continuous data, followed by an artificial neural network (ANN) approach. The SCF modeling used distance-averaged emissions and cycle-averaged vehicle speed to predict distance-averaged NOx. The power-based modeling was based on linear and polynomial correlations between continuous axle power and NOx.

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.

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.

Emissions tests for heavy-duty diesel-fueled vehicles are normally performed using an engine dynamometer or a chassis dynamometer. Both of these methods generally entail the use of laboratory-grade emissions measurement instrumentation, a CVS system, an environment control system, a dynamometer, and associated data acquisition and control systems. The results obtained from such tests provide a means by which engines may be compared to the emissions standards, but may not be truly indicative of an engine's in-vehicle performance while operating on the road. An alternative to such a testing methodology would be to actively record the emissions from a vehicle while it was operating on-road. A considerable amount of discussion has been focused on the development of on-road emissions measurement systems (OREMS) that would provide for such in-use emissions data collection.