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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 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.

The historical lack of continuous data for PM emissions from heavy-duty diesel engines hampers advanced inventory approaches and hampers second-by-second engine control optimization. Continuos PM data can be obtained using a Tapered Element Oscillating Microbalance (TEOM), but moisture correction of data is needed to remove unwanted transient components of the mass. Reasonable correlation can be found between TEOM data integrated over the cycle and conventional PM filter data. Considerable scatter was evident when continuous TEOM data were plotted against instantaneous power, but by dispersing the power in time a clearer relationship was evident. Continuous TEOM data showed the same gross trends as PM filter mass distributed over a cycle in proportion to instantaneous CO, but it was evident that this CO proportioning technique is at best approximate. Binning of PM mass rate as a function of vehicle speed and acceleration were also evaluated for inventory purposes.

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.

Results of a research effort directed towards identifying and measuring the genotoxic properties of respirable particulate matter involved in mining exposures, especially those which may synergistically affect genotoxic hazard, are presented. Particulate matter emissions from a direct injection diesel engine have been sampled and assayed to determine the genotoxic potential as a function of engine operating conditions. Diesel exhaust from a Caterpillar 3304 diesel engine, representative of the ones found in underground mines, rated 100 hp at 2200 rpm is diluted in a multi-tube mini-dilution tunnel and the particulate matter is collected on 70 mm fluorocarbon coated glass fiber filters as well as on 8″ x 10″ hi-volume filters. A six mode steady state duty cycle was used to relate engine operating conditions to the genotoxic potential.

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.