Nowadays numerical simulations play a major role in the development of future sustainable powertrain thanks to their capability of investigating a wide spectrum of innovative technologies with times and costs significantly lower than a campaign of experimental tests. In such a framework, this paper aims to assess the predictive capabilities of an 1D-CFD engine model developed to support the design and the calibration of the innovative highly efficient spark ignition engine of the PHOENICE (PHev towards zerO EmissioNs & ultimate ICE efficiency) EU H2020 project. As a matter of fact, the availability of a reliable simulation platform is crucial to achieve the project target of 47% peak indicating efficiency, by synergistically exploiting the combination of innovative in-cylinder charge motion, Miller cycle with high compression ratio, lean mixture with cooled Exhaust Gas Recirculation (EGR) and electrified turbocharger. Since the engine is expected to operate in highly diluted conditions, particular attention was paid to the definition of a reliable combustion model to accurately predict the burn duration and the occurrence of abnormal combustion phenomena. A preliminary set of experimental data measured at 3000 RPM and 7 bar BMEP, including both EGR and λ variations, was used to assess the predictive capabilities of the model. Afterwards, the developed virtual test rig was exploited to perform a calibration of the engine in terms of optimal λ and EGR combinations and the results obtained for two operating points, a low load 1500 RPM and 5.5 bar BMEP and a high load 3000 RPM and 13 bar BMEP, were presented and discussed. Findings showed that best efficiency values, well above 40% indicated efficiency, could be obtained with moderate dilution and EGR rates thanks to knock suppression capability for the high load point and de-throttling for the low load point.