Search Results

Emissions testing of new heavy-duty engines is performed to ensure compliance with governmental emissions standards. This testing involves operating the engine through the heavy-duty engine transient Federal Test Procedure (FTP). While in-use engine emissions testing would be beneficial in aiding regions to meet standards dictated by the Clean Air Act, the process of removing the engine from the vehicle, fitting it to an engine dynamometer, testing, and refitting the engine in the chassis, combined with costs associated with removing the vehicle from service, is expensive. A procedure for engine emissions testing with the engine in the vehicle using a chassis dynamometer was developed to mimic the FTP. Data from two engines and vehicles (a 195 hp 1994 Navistar T 444E in a single axle straight truck and a 1995 370 hp Cummins N-14 in a tandem drive axle tractor) are presented as well as correlation between engine and chassis emissions tests.

The fuel cell bus program at Georgetown University (GU) has directed the operational development and testing of three hybrid fuel cell powered buses for transit operation. These are the world's first liquid-fueled, fuel cell powered road vehicles. This paper describes the emissions testing of one of these buses on a heavy duty chassis dynamometer at West Virginia University (WVU). The tested bus was driven by a 120 kW DC motor and utilized a 50 kW phosphoric acid fuel cell (PAFC) as an energy source with a 100 kW battery for supplemental power. A methanol/water fuel mixture was converted by a steam reformer to a hydrogen rich gas mixture for use in a fuel cell stack. Emissions from the reformer, fuel cell stack and startup burner were monitored for both transient and steady-state operation.

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.