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

know if the vehicle was “filled up” or only partially filled during any given fueling. This uncertainty
made it impossible to calibrate the on-board fuel consumption sensor.
Lesson Learned: In order to get accurate fuel consumption data and to be able to determine if the
on-board fuel consumption sensor can be calibrated, it is recommended that an external fuel sensor
be used, if such a sensor can be independently calibrated. This sensor should be deployed for at least
1/3 of the data collection period. If fuel tickets are to be used to calibrate the databus data, then
information about fuel time, location, odometer reading, and whether the tank was filled up or not,
needs to be collected.
7.2.2.6 Control of experimental variables
In this project, an attempt was made to maintain all relevant variables at the same level across all the
participating trucks, except for the type of tires and transmission. It was assumed that all drivers were
driving in a similar fashion (a reasonable assumption considering the extensive training and follow up
that Schrader provides to its drivers), and that other variables that could not be controlled (e.g. vehicle
weight, type of terrain, etc) would equally affect all of the vehicles in a similar manner over the yearlong
data collection effort. Nevertheless, and to eliminate any potential differences between the
participating trucks, it would have been desirable to switch tires among those trucks such that for any
given tractor half of the data would have been collected while equipped with dual tires and the other
half with the other type of tires . This would have also reduced any influence that drivers may have
had in the vehicle fuel efficiency.
Lesson Learned: Steps should be taken to eliminate driver, routing, and vehicle variability in the
experimental setup in order to reduce the influence of uncontrollable variables.
7.2.2.7 Control of external data gathered
It is impossible to collect all of the necessary information for a project like this one by just relying on
sensors and other equipment. In order to calibrate some of this information, it was necessary to
involve the participating trucking company personnel, specifically the staff dealing with the day-today
operations. Even when the staff has the best of intentions in helping the project (as was the case
for Schrader), there are operations procedures and idiosyncrasies that simply cannot be changed.
One example was the mating of instrumented tractor and trailers, which was impossible to achieve
because of the way in which the company operates (i.e., a driver- or tractor-centered operation), even
though the staff tried their best to support the project needs. Another example was the collection of
fuel tickets. ORNL asked Schrader to collect weight tickets (at random) to help assess and calibrate
the Air-Weigh devices. This worked only for a short while, but rapidly reverted back to obtaining
weight tickets when the truck was close to the legal weight limit; which is the logical operation for a
trucking company.
Lesson Learned: Requirements that are outside of normal operations for an operating fleet are likely
to be unsustainable in the long-run and can only be maintained for short period of times. If external
information needs to be gathered, the methodology to collect that information should either enroll the
collaboration of the partner for a short period of time, or it should increase the participation of the
research team in collaboration with that partner. Any methodology that requires repetitive tasks that
are outside of the partner’s normal way of operating is likely unachievable.
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