• DocumentCode
    3009259
  • Title

    CO2 vehicular emission statistical analysis with instantaneous speed and acceleration as predictor variables

  • Author

    Oduro, Seth D. ; Metia, Santanu ; Duc, H. ; Ha, Q.P.

  • Author_Institution
    Fac. of Eng., Univ. of Technol., Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    25-28 Nov. 2013
  • Firstpage
    158
  • Lastpage
    163
  • Abstract
    Models for predicting vehicular emissions of carbon dioxide (CO2) are usually insensitive to vehicle modes of operation (such as cruise, acceleration, deceleration, and idling) as they are based on the average speed of motor vehicles. In the present study, real world on-road second-by-second data are used to improve the accuracy of air quality models by considering modal emissions of CO2 in terms of vehicles´ instantaneous speed and acceleration. A regression analysis approach is used with speed and acceleration as the predictor variables while CO2 emission factor as the outcome variable for vehicles manufactured in 2002 and 2008. The results show that there is significantly a linear relationship between CO2, speed and acceleration/deceleration in which speed, as compared to acceleration, has a stronger correlation with respect to the CO2 emission factor. Also, for 2002 and 2008 vehicles, every 1m/s increase in speed will emit respectively 0.041g/s and 0.034g/s CO2, whereas an increase in acceleration by 1m/s2 will produce 0.025g/s and 0.008g/s of CO2 emission in the case of constant predictors. While speed and acceleration are all significant predictors of CO2 emission, it is concluded from the magnitude of the t-statistics that speed has a greater impact than acceleration in predicting CO2 emission.
  • Keywords
    acceleration; air pollution; angular velocity; carbon compounds; regression analysis; road vehicles; vehicle dynamics; acceleration; carbon dioxide vehicular emission statistical analysis; deceleration; instantaneous speed; regression analysis; road vehicles; Acceleration; Atmospheric modeling; Engines; Fuels; Predictive models; Roads; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Information Sciences (ICCAIS), 2013 International Conference on
  • Conference_Location
    Nha Trang
  • Print_ISBN
    978-1-4799-0569-0
  • Type

    conf

  • DOI
    10.1109/ICCAIS.2013.6720547
  • Filename
    6720547