Cylinder pressure based calibration model for engines using ethanol, hydrogen and natural gas as alternative fuels

Abstract

This paper proposes a novel virtual engine calibration method for alternative fuels using thermodynamic simulation for in-cylinder pressure prediction. Based on known engine data, including the crank angle of the peak cylinder pressure, the optimization problem is defined for a desired indicated mean effective pressure. The decision variables are the combustion and heat transfer model parameters The method was tested for three different engines of different sizes, operating with ethanol, hydrogen and natural gas, and different equivalence ratios. The Wiebe model and a quasi-dimensional fractal combustion model were compared. The results showed that the method was able to successfully predict the in-cylinder pressure curve, with a coefficient of determination higher than 0.99. Furthermore, the method predicted the peak pressure and the crank angle corresponding to 50% of mass fraction burned with a maximum deviation of 2.5% and 1.5 °CA, respectively.