Comparative evaluation of fuel consumption estimation models

Edward Jastrzembski, Byungkyu Park, Joonwoo Son

Research output: Contribution to conferencePaperpeer-review

Abstract

Increased fossil fuel consumptions present a huge environmental challenge to the world. In order to meet the consumers' demands for transportation and at the same time to provide more fuel efficient vehicles, scientists are constantly searching for effective emissions and fuel consumption estimation models to protect the environment, especially to design more efficient control algorithms at traffic signalized intersections (e.g., eco-adaptive control) and promote environmentally friendly driving behaviors (e.g., eco-driving). The purpose of this research was to assess three existing fuel consumption estimation models using actual fuel consumption rates based on field measurements. The three models are the Virginia Tech Microscopic Energy and Emissions Model (VT-Micro), the Comprehensive Modal Emission Model (CMEM) and the Motor Vehicle Emission Simulator (MOVES) Model, and the field measured fuel consumptions are from instantaneous light duty vehicle (LDV) fuel consumption (FC) rate data collected by the Daegu Gyeongbuk Institute of Science and Technology of Korea (DGIST). Both the VT-Micro and the CMEM explained DGIST data reasonably well. All three models adequately tracked DGIST total fuel consumption over a fixed time interval.

Original languageEnglish
StatePublished - 2014
Event21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014 - Detroit, United States
Duration: 7 Sep 201411 Sep 2014

Conference

Conference21st World Congress on Intelligent Transport Systems: Reinventing Transportation in Our Connected World, ITSWC 2014
Country/TerritoryUnited States
CityDetroit
Period7/09/1411/09/14

Keywords

  • CMEM model
  • Fuel consumption
  • MOVES model
  • VT-Micro model

Fingerprint

Dive into the research topics of 'Comparative evaluation of fuel consumption estimation models'. Together they form a unique fingerprint.

Cite this