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It is widely acknowledged that the soot particulate pollutants pose a serious threat to both the environment and human health. Reducing the emission of these soot particulate pollutants from engines is very urgent, to which a highly efficient and robust modeling tool for soot emission prediction could contribute significantly. In this work, a new and robust numerical approach to handle the detailed soot models in engine combustion simulations is presented. The new approach adopts an advanced bi-variate moment projection method to treat the complex soot particle dynamics. The bi-variate moment projection method is superior to other methods of moments in terms that it is able to solve the soot moment closure problem due to oxidation, which governs the evolution of soot particle populations inside the engine cylinder. The proposed approach has been validated by simulating the detailed evolution processes of the soot particle population inside a dual-fueled, four-cylinder compression ignition engine. It is shown to be highly efficient and robust. It is able to provide a comprehensive investigation into the soot particle dynamics inside the engine cylinder at low computational cost. The emissions of soot particles under different engine operating conditions could be predicted with high accuracy. These findings suggest that the new approach proposed in this work is a promising framework for prediction and analysis of the emission of soot particulate pollutants from internal combustion engines. It is a useful tool to explore clean combustion technology.

A highly robust numerical approach for handling the bi-variate soot population balance models in internal combustion engines