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.