A simple model to simulate cycle-by-cycle variation that is
suitable for use in Monte-Carlo approaches has been developed and
validated with a wide range of experimental data. The model is
intended to be diagnostic rather than predictive in nature, with a
goal of providing realistic in-cylinder pressures. The
individual-cycle cumulative rate of heat release was curve fit with
a four-parameter Wiebe function. It was found that the distribution
of the Wiebe b-parameter was quite small, so its value was obtained
from the ensemble-averaged condition. The remaining three Wiebe
function parameters, θig, θcomb and m were
found to be distributed over a moderate range, and were linearly
correlated to each other. Using the cumulative density function of
θig, and the linear fit of θcomb and m to
θig, with a random component added, a Monte-Carlo scheme
was developed. The resulting randomly chosen cycles were found to
adequately reproduce the observed cyclic variation at the same
condition, and can be used with higher-order models to assess the
impact of cyclic variations on other cylinder-pressure-driven
phenomena.
