The purpose of this study is to develop model-based
methodologies which employ thermo-fluid dynamic engine simulation
and multiple-objective optimization schemes for engine control and
calibration, and to validate the reliability of the method using a
dynamometer test.
In our technique, creating a total engine system model begins by
first entirely capturing the characteristics of the components
affecting the engine system's behavior, then using experimental
data to strictly adjust the tuning parameters in physical models.
Engine outputs over the full range of engine operation conditions
as determined by design of experiment (DOE) are simulated, followed
by fitting the provided dataset using a nonlinear response surface
model (RSM) to express the causal relationship among engine
operational parameters, environmental factors and engine output.
The RSM is applied to an L-jetronic® air-intake system control
logic for a turbocharged engine.
Coupling the engine simulator with a multi-objective genetic
algorithm, the optimal valve timings are investigated from the
viewpoints of fuel consumption rate, emissions, and torque. The
calibrations are made over all the operation points; the control
map is implemented in the turbocharged air-intake system control
logic.
The validation of the control logic was demonstrated using a
model-in-the-loop simulation (MILS). The logic output of the
charging efficiency transition due to the varying throttle valve
opening angle and variable valve timing was compared with the
simulator output. According to the results of the MILS, in-cylinder
air mass estimations are in good agreement with the engine
simulator under various transient operations.