Class-8 Heavy Truck Duty Cycle Project Final Report - Center for ...

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Truck Weight [lb]
Fig. 61. Truck Total Weight (All Trucks, AirWeight Devices on Both the Tractor and Trailer)
6.2.2 Fuel Information
The main objective of the data analysis for this project was to determine the effect of the different
types of tires (i.e., regular duals vs. NGSWBTs) on the fuel efficiency of Class-8 trucks. In order to
accomplish this objective, fuel consumption needed to be measured; moreover, to determine fuel
efficiency under different conditions (e.g., peak-hour vs. off-peak, urban vs. rural, etc.) it was
necessary to determine fuel consumption instantaneously. As described elsewhere in this report, the
vehicle databus provided this type of information (i.e., the instantaneous fuel consumption rate,
measured in liters/hour) which was captured through one of the data channels (see Table 5) and saved
every 0.2 seconds into the collected information database.
It is obvious that to determine the absolute fuel efficiency of any vehicle, the fuel consumption needs
to be measured accurately. At the beginning of the project, it was decided to collect fuel tickets every
time one of the participating tractors was fueled. The fuel ticket information (i.e., total number of
gallons of fuel) was to be used to calibrate the observed fuel consumption as reported by the vehicle
databus. The calibration methodology consisted of a comparison of the total fuel consumed obtained
by adding the fuel reported in the fuel tickets against the total fuel consumed obtained from the
collected information database for the same trip, or series of trips.
Three assumptions were made when this fuel consumption calibration methodology was adopted: 1)
there would not be any gaps in the data collected; 2) the date and time at which the vehicle was fueled
would be recorded; and 3) every time a vehicle was fueled the tank would be completely filled. None
of these assumptions were valid. As described elsewhere in this report, there were instances in which
a participating tractor was not at the company’s parking lot when the researchers were there to
download the data collected and to clear the storage capacity of the on-board data collection
equipment. For such instances, if the DAS’s memory became full, then no more collected data could
be saved, and part of the information was lost, thus creating a gap in the information. On other
occasions, a sensor (e.g., GPS device) may have malfunctioned for some period of time, resulting in
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