On-road vehicles consume a substantial amount of fuel and emit air pollutants, including carbon monoxide, hydrocarbon, and nitrogen oxides. Increasing concern about air quality has meant increasing interest in accurate estimates of microscale vehicle energy use and emissions (EU&E). Vehicle EU&E rates are related to vehicle-specific power (VSP). For a given vehicle, VSP is a function of vehicle speed, acceleration, and grade, each of which can be categorized as an externally observable variable (EOV). However, internally observable variables (IOVs), such as manifold absolute pressure (MAP) and engine revolutions per minute (RPM), are more predictive of EU&E. Field measurements were conducted for 10 on-road vehicles using a portable emissions measurement system, an on-board diagnostic scan tool, and GPS receivers to measure exhaust concentrations and engine activity and to estimate road grade. VSP and the product of MAP and RPM ( PM×R) are useful as indicators of engine load. IOV-based models were developed to predict EU&E rates. The IOV-based models typically performed better than EOV-based models. The models demonstrated could be integrated into next-generation traffic simulation programs, as well as into vehicle engine control units, to provide feedback on real-time emissions.
Comparison of Vehicle-Specific Fuel Use and Emissions Models Based on Externally and Internally Observable Activity Data
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 2570 , 1 ; 30-38
2016-01-01
Article (Journal)
Electronic Resource
English
Are internally observable vehicle data good predictors of vehicle emissions?
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