Octavio Armas

This paper presents a fuel injection rate predictive model based on zero-dimensional correlations from experimental results. This model estimates the fuel injection rate behavior with varying parameters such as fuel injection pressure-injector energizing, the injection nozzle geometrical characteristics, and fuel viscosity. The model approach was carried out with diesel fuel. Then, the model was applied to the use of two alternative low-carbon fuels without diesel. An experimental methodology was used under controlled conditions, employing an injection rate indicator to measure the injection parameters in real time. The setup was carried out on a pump test bench using a common rail injection system. The results show that the model can be adapted to different injection conditions and fuels.