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In this paper, a control-oriented soot model was developed for real-time soot prediction and combustion condition optimization in a gasoline Partially Premixed Combustion (PPC) Engine. PPC is a promising combustion concept that achieves high efficiency, low soot and NOx emissions simultaneously. However, soot emissions were found to be significantly increased with high EGR and pilot injection, therefore a predictive soot model is needed for PPC engine control. The sensitivity of soot emissions to injection events and late-cycle heat release was investigated on a multi-cylinder heavy duty gasoline PPC engine, which indicated main impact factors during soot formation and oxidation processes. The Hiroyasu empirical model was modified according to the sensitivity results, which indicated main influences during soot formation and oxidation processes. By introducing additional compensation factors, this model can be used to predict soot emissions under pilot injection.

The combustion timing in internal combustion engines affects the fuel consumption, in-cylinder peak pressure, engine noise and emission levels. The combination of an in-cylinder pressure sensor together with a direct injection fuel system lends itself well for cycle-to-cycle control of the combustion timing. This paper presents a method of controlling the combustion timing by the use of a cycle-to-cycle injection-timing algorithm. At each cycle the currently estimated heat-release rate is used to predict the in-cylinder pressure change due to a combustion-timing shift. The prediction is then used to obtain a cycle-to-cycle model that relates combustion timing to gross indicated mean effective pressure, max pressure and max pressure derivative. Then the injection timing that controls the combustion timing is decided by solving an optimization problem involving the model obtained.