Evaluation, Transformation, and Extraction of Driving Cycles and Vehicle Operations
A driving cycle is a representation of how vehicles are driven and
is usually represented by a set of data points of vehicle speed
versus time. Driving cycles have been used to evaluate vehicles for
a long time. A traditional usage of driving cycles have been in
certification test procedures where the exhaust gas emissions from
the vehicles need to comply with legislation. Driving cycles are now
also used in product development for example to size components or
to evaluate different technologies. Driving cycles can be just a
repetition of measured data, be synthetically designed from
engineering standpoints, be a statistically equivalent
transformation of either of the two previous, or be obtained as an
inverse problem e.g. obtaining driving/operation patterns. New
methods that generate driving cycles and extract typical behavior
from large amounts of operational data have recently been proposed.
Other methods can be used for comparison of driving cycles, or to
get realistic operations from measured data.
This work addresses evaluation, transformation and extraction of
driving cycles and vehicle operations.To be able to test a vehicle
in a controlled environment, a chassis dynamometer is an
option. When the vehicle is mounted, the chassis dynamometer
simulates the road forces that the vehicle would experience if it
would be driven on a real road. A moving base simulator is a
well-established technique to evaluate driver perception of e.g. the
powertrain in a vehicle, and by connecting these two simulators the
fidelity can be enhanced in the moving base simulator and at the
same time the mounted vehicle in the chassis dynamometer is
experiencing more realistic loads. This is due to the driver's
perception in the moving base simulator is close to reality.
If only a driving cycle is considered in the optimization of a
controller there is a risk that the controllers of vehicles are
tailored to perform well in that specific driving cycle and not during
real-world driving. To avoid the sub-optimization issues, the
operating regions of the engine need to be excited differently. This
can be attained by using a novel algorithm, which is proposed in
this thesis, that alters the driving cycle while maintaining that
the driving cycle tests vehicles in a similar way. This is achieved
by keeping the mean tractive force constant during the process.
From a manufacturers standpoint it is vital to understand how your
vehicles are being used by the customers. Knowledge about the usage
can be used for design of driving cycles, component sizing and
configuration, during the product development process, and in
control algorithms. To get a clearer picture of the usage of wheel
loaders, a novel algorithm that automatically, using existing
sensors only, extracts information of the customers usage, is
suggested. The approach is found to be robust when evaluated on
measured data from wheel loaders loading gravel and shot rock.
Peter Nyberg
2013
Informationsansvarig: webmaster
Senast uppdaterad: 2021-11-10
LiU Homepage
