Citation

LeBlanc DC, Saunders FM, Meyer MD, Guensler R. Transp. Res. Rec. 1995; 1472: 45-52.

Copyright

(Copyright © 1995, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

unavailable

PMID

unavailable

Abstract

An analysis of instrumented vehicle data revealed significant differences in operating mode profiles for vehicle operations in Atlanta, Georgia; Baltimore, Maryland; and Spokane, Washington. Differences in such operating mode characteristics as acceleration rates and cruise speed distributions are important in the development of new emissions models because certain vehicle and engine operating modes are proving to be significant sources of elevated emissions rates. Although not conclusive, these data indicate that the variations in operating mode fractions across cities may be related to differences in road network characteristics. A simple predictive model, based on three operating parameters (vehicle speed, engine speed, and manifold absolute pressure) was developed from the data collected from eight instrumented General Motors 3.1-L vehicles and is capable of predicting elevated carbon monoxide (CO) emission rates for various vehicle and engine activities. These emission results do not apply to hydrocarbons (HC) or oxides of nitrogen (NOx), which behave differently. The modeling technique discussed has been developed exclusively for CO. The model is used to estimate the relative CO emission differences associated with the differences in operating profiles noted from city to city (and potentially from driver to driver). This modeling approach appears capable of adequately distinguishing the CO emission effects associated with variations in engine and vehicle operations for individual vehicle makes and models. However, it should be noted that the large variability in vehicle-to-vehicle CO emission response to changes in operating modes that has been noted in ongoing studies indicates that a model based on vehicle speed and acceleration profiles alone may not provide sufficient CO emission rate predictive capabilities for the fleet.

Language: en

Keywords

Mathematical models; Speed; Vehicles; Air quality; Engines; Estimation; Computer simulation; Motor transportation; Air pollution control; Behavioral research; Carbon monoxide; Particulate emissions