Modeling and Optimizing Fuel Usage of On-Road Construction Equipment

Equipment operations account for more than 50% of fuel use as well as emission production in the construction industry. Currently construction firms have investigated into engine technologies and fuel attributes for reducing the fuel consumption, which may not be economical and can hardly be applied to the existing fleet of equipment. This paper aims to optimize the fuel use of on-road construction equipment through developing operational level fuel reduction strategies. Acceleration, speed, weight, and road slope have been investigated as main parameters influencing fuel use of on-road construction vehicles in this study. Field experimentations were conducted to collect real-world data from seven in-use heavy duty on-road construction trucks. Artificial neural network (ANN) analysis was applied to model the effect of investigated variables on fuel use rate. Considering operational factors and road conditions, optimal driving speed is determined to minimize the amount of fuel used per travelled distance. It is also verified quantitatively that fuel use will rise significantly by increasing the weight of vehicles and road slope. Mitigating idling time and reducing equipment stops are other effective means that are applicable to decrease the rate of fuel use. These operational level optimization measures can be readily used as a guideline for equipment operators to enhance the fuel efficiency of construction equipment while saving operational cost considerably.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 198-207
  • Monograph Title: Construction Research Congress 2018: Sustainable Design and Construction and Education

Subject/Index Terms

Filing Info

  • Accession Number: 01684811
  • Record Type: Publication
  • ISBN: 9780784481301
  • Files: TRIS, ASCE
  • Created Date: Oct 4 2018 4:49PM