Over the last decades, internal combustion engines have undergone a continuous evolution to achieve better performance, lower pollutant emissions and reduced fuel consumption. The pursuit of these often-conflicting goals involved changes in engine architecture in order to carry out advanced management strategies. Therefore, Variable Valve Actuation, Exhaust Gas Recirculation, Gasoline Direct Injection, turbocharging and powertrain hybridization have found wide application in the automotive field. However, the effective management of a such complex system is due to the contemporaneous development of the on-board Engine electronic Control Unit. In fact, the additional degrees of freedom available for the engine regulation highly increased the complexity of engine control and management, resulting in a very expensive and long calibration process. To overcome these drawbacks, an effective methodology based on the adoption of 1D thermo-fluid dynamic analysis is proposed in this study. In particular, starting from a complete experimental set of data actually used for the base calibration of a reference spark ignition engine, a novel procedure based on vector optimization approach is used to reliably calibrate a 1D engine model starting from a reduced experimental dataset. Once validated, the engine model is then used as a virtual test bench to reproduce the experimental campaign numerically, thus obtaining a detailed and complete dataset exploitable for calibration purposes, here called numerical or virtual dataset. To verify the potential of the proposed methodology, experimental and virtual dataset have been finally compared. The research clearly demonstrates the effectiveness of the proposed approach since the average errors are comparable with the measurement errors. Therefore, the methodology shows promising results concerning the use of numerical dataset obtained from reliable 1D CFD engine models as input to computer aided calibration software. This way, a significant cut to the experimental campaign required for calibration purposes is achieved, with their related times and costs.