A great part of the projects in the powertrain area is focused
on the development of more efficient thermal applications. In the
end, efficiency is pursued, since the aim is to achieve a
sustainable design with low fuel consumption. Thus, vehicles which
present lower fuel consumption are demanded by customers.
Additionally the emission standards have been reducing the limits
of CO₂ emissions to very low levels, which drive engineers to
develop vehicles with lower fuel consumption. In summary, the
product should now please a more demanding worldwide customer
profile as the global economy grows. Vehicle design processes
should consider fuel consumption sensitivity taking into account
the combined engine and drive train systems at early stages.
Frequently the actual fuel consumption can only be confirmed when
the first prototype is assembled in order to validate the adopted
solutions. On the other hand, project timing is another dominant
constraint, even when using planning of experiments (DoE) not all
proposed designs can be tested. In this sense, the use of numerical
simulation resources has been more and more utilized to reduce
project timing. A vehicle simulation of a 4-cylinder diesel
internal combustion engine (ICE) coupled with the driveline of the
vehicle, including its accessories, was developed utilizing the
numerical 1D model, built in GT-Suite, a Gamma Technologies, Inc.,
code. A multi-body dynamics method was used with explicit
consideration of accessory loads and the engine, which was
represented by its maps evaluated at the dyno, namely BMEP, FMEP
and BSFC. The model calibration was done using some route acquired
data in order to reproduce the measured fuel consumption under some
specific vehicle cruise conditions and 3 accelerations ramp
situations. The pedal position was assigned by a PID controller
representing a virtual driver's behavior. The gear shift
schedule was calculated inversely by inspection pursuing a
reasonable correlation of the simulated and measured fuel rates.
The aerodynamics features and the rolling resistance coefficient
were adopted based on information provided by the customer and the
dynamic tire radius were inversely calculated using GPS vehicle
speed data, engine speed and drive line ratios.
This paper presents a study of the impact of accessory loads in
a physically-representative way. Their loads have been considered
via their power consumption curve. Each one has been studied and
modeled in order to get a representative power curve shape over the
relevant speed range for the engine. Then, they were all included
in the 1D dynamic model. The final numerical model presented 6% of
max difference in total fuel consumption in comparison to
measurements for all 6 cruise situations without the need of any
calibration adjustment, which is a usual practice worldwide. The
acceleration behavior of the model presented a max difference of 7%
(with a minimum of 2%) in comparison to measurements in terms of
acceleration times and vehicle displacements. The aforementioned
results were considered excellent from the perspective of the
adopted 1D approach. The model has already served as a good basis
to evaluate the contribution of each accessory load on the total
fuel consumption in order to provide technical basis for a system
optimization, which might lead to an eventual modification of the
accessory design. Last but not least, it may help with the
accessory supplier competition.