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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.

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.

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).

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.

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.