Passenger cars equipped with diesel engines will meet
challenging emission legislation for the coming decade, with
introduction of Euro6 and Euro7, which comprises reduced NOX
emissions and possibly new driving cycles including off-cycle
limits. The technology measures to meet these legislative limits
comprise a broad spectrum of engine and aftertreatment, i.e.,
engine measures such as improved fuel injection with respect to
mass and timing, improved exhaust gas recirculation, improved
warm-up and reduced friction, as well as aftertreatment measures
such as selective catalytic reduction and lean NOX trap in
combination with diesel particulate filter, and the thereby
associated engine control. The resulting technology matrix is
therefore large, and calls for a multidisciplinary simulation
approach for appropriate selection and optimization of technology
and control with the objectives and constraints of emissions, fuel
consumption, performance and cost.
The idea behind multidisciplinary simulation is to include all
subcomponents of the powertrain into a complete system simulation
model, in order to study the influence of and interaction between
subsystems on emissions, fuel consumption and cost of the complete
powertrain. This approach requires simplified models on a subsystem
level for reasonable simulation times on a system level. The
subcomponents models mainly consist of a vehicle and road load
model, engine model with tunable EGR and aftertreatment models for
the appropriate system to be considered. The complete system model,
which is programmed in MATLAB Simulink, with variability in
component choice and engine calibration, is then coupled to an
external optimization routine in order to find the optimal
combination in terms of the objectives stated above.
The core of system simulation model consists of a semi-empirical
engine model based on engine bench test data from a design of
experiment, where appropriate engine operating parameters are
varied to span the possible engine operating states we expect. From
this, a mathematical model is derived where the input is defined as
operating state such as engine speed, load, EGR-ratio, coolant
temperature, intake temperature, boost pressure, etc., and the
results are fuel consumption, emissions, exhaust temperature and
mass flow, etc. Furthermore, the model includes full physical
models of the aftertreatment system including temperature
distribution along the exhaust line. The simplified nature of the
models results in fast execution times of roughly 1/100 of real
time.