A Trip-Based Model for Prediction of Truck Fuel Consumption: Application to Natural Gas Trucks

Natural Gas Vehicles (NGV) have received increasing interest in recent years. To anticipate the NGV expansion, a large-scale demonstration project, called Equilibre was launched with the support of the French Environment Agency (ADEME), two gas distribution companies (GrDF & ENGIE) and six Freight Logistics Operators (Equilibre Association).The main objective of this project is to evaluate the potential benefit of the NGV in real driving conditions. To achieve this, the authors built a decision support system that predicts energy consumption for both Diesel and NGV. In this paper the authors present the construction of a mesoscopic trip-based consumption model whose inputs are the vehicle, the trip and the total laden weight. In this case, a mesocopic modeling means that a road is divided into a sequence of mid-length sections (kilometer scale); these sections are determined by reference to a section categorization based on the presumed effect on the fuel consumption. This model was calibrated and validated with the data of a real drive experiment for NGV. Over a six-month period the accuracy of the fuel consumption prediction is better than 2 %.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADC70 Standing Committee on Transportation Energy.
• Authors:
  • Schnetzler, Bernard
  • Baouche, Fouad
  • Jeanneret, Bruno
  • Trigui, Rochdi
  • El Faouzi, Nour-Eddin
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 17p

Subject/Index Terms

• TRT Terms: Fuel consumption; Heavy duty vehicles; Mathematical prediction; Natural gas vehicles; Trucks
• Subject Areas: Energy; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01657381
• Record Type: Publication
• Report/Paper Numbers: 18-01031
• Files: TRIS, TRB, ATRI
• Created Date: Jan 24 2018 9:24AM