Reducing vehicle fuel consumption while respecting pollutants emission standards has been a major concern over the last decades in the automotive industry. Consequently, Spark Ignition (SI) engine air-paths can now incorporate devices such as Exhaust Gas Recirculation (EGR), Variable Valve Timing (VVT) or Actuation (VVA), Variable Geometry Turbocharger (VGT) or even Variable Compression Ratio (VCR). Optimizing the settings for all these devices made engine development more complex and challenging. The development of engine control strategy can be efficiently performed through system simulation with a complete engine simulator, as it allows describing the phenomenological process occurring in the engine while requiring reasonable quantity of measurement data. CPU time is also a constraint, therefore 0-dimensional models are commonly used, particularly to represent in-cylinder combustion process. Still, the combustion model has to account for the influence of air-path settings, as they strongly impact turbulence in chamber and the resulting combustion speed. This paper focuses on the system simulation version of the Coherent Flame Model (CFM1D), more precisely on its development to make it more predictive to different air path settings variations. Based on previous work, the equations of a K-k family turbulence model are introduced to replace the simplified turbulence model, on which CFM1D lies during closed valve operation to determine the increase of the flame front speed compared to laminar case. In the same time, the initialisation of turbulence variable at the intake valve closure (IVC) is modified to better take into account VVT effects. Additionally, an optional equation accounting for the physical description of the laminar to turbulent transition is proposed and discussed, allowing to further simplify the calibration process. The improved model is calibrated to fit measurements on reference engine operating points, and played on different settings including variations on spark advance VVT, VVA, VCR and EGR. The achieved results bring out the advantage of the new approach in terms model sensitivity and robustness, while pointing out further areas of improvement.
Dr.-Ing. Guillaume ALIX, IFPEN, FRANCE Dr. Alessio DULBECCO, IFPEN, FRANCE