Advanced Search
DSpace@MIT

A Statistical Model of Vehicle Emissions and Fuel Consumption

Research and Teaching Output of the MIT Community

Show simple item record

dc.contributor.author Cappiello, Alessandra
dc.contributor.author Chabini, Ismail
dc.contributor.author Nam, Edward K.
dc.contributor.author Lue, Alessandro
dc.contributor.author Zeid, Maya Abou
dc.date.accessioned 2002-09-17T19:49:06Z
dc.date.available 2002-09-17T19:49:06Z
dc.date.issued 2002-09-17T19:49:06Z
dc.identifier.uri http://hdl.handle.net/1721.1/1675
dc.description.abstract A number of vehicle emission models are overly simple, such as static speed-dependent models widely used in practice, and other models are sophisticated as to require excessive inputs and calculations, which can slow down computational time. We develop and implement an instantaneous statistical model of emissions (CO2, CO, HC, and NOx) and fuel consumption for light-duty vehicles, which is derived from the physical loadbased 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 assess 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. en
dc.format.extent 739550 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject vehicle emission models en
dc.subject fuel consumption en
dc.title A Statistical Model of Vehicle Emissions and Fuel Consumption en


Files in this item

Name Size Format Description
A_Statistical_Mod ... 722.2Kb PDF

This item appears in the following Collection(s)

  • Ford-MIT Alliance
    Institute-wide collaboration focusing on statistical engineering, virtual education, and the environment

Show simple item record

MIT-Mirage