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A statistical model of vehicle emissions and fuel consumption
Many vehicle emission models am overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO/sub 2/, CO, HC, and NOx) and fuel consumption for light duty vehicles, which is simplified from the physical load-based approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to, test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.
A statistical model of vehicle emissions and fuel consumption
Many vehicle emission models am overly simple, such as the speed dependent models used widely, and other models are sufficiently complicated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO/sub 2/, CO, HC, and NOx) and fuel consumption for light duty vehicles, which is simplified from the physical load-based approaches that are gaining in popularity. The model is calibrated for a set of vehicles driven on standard as well as aggressive driving cycles. The model is validated on another driving cycle in order to, test its estimation capabilities. The preliminary results indicate that the model gives reasonable results compared to actual measurements as well as to results obtained with CMEM, a well-known load-based emission model. Furthermore, the results indicate that the model runs fast and is relatively simple to calibrate. The model presented can be integrated with a variety of traffic models to predict the spatial and temporal distribution of traffic emissions and assess the impact of ITS traffic management strategies on travel times, emissions, and fuel consumption.
A statistical model of vehicle emissions and fuel consumption
Cappiello, A. (author) / Chabini, I. (author) / Nam, E.K. (author) / Lue, A. (author) / Abou Zeid, M. (author)
2002-01-01
550664 byte
Conference paper
Electronic Resource
English
A STATISTICAL MODEL OF VEHICLE EMISSIONS AND FUEL CONSUMPTION
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