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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.

The engine concept partially premixed combustion (PPC) has proved higher gross indicated efficiency compared to conventional diesel combustion engines. The relatively simple implementation of the concept is an advantage, however, high gas exchange losses has made its use challenging in multi-cylinder heavy duty engines. With high rates of exhaust gas recirculation (EGR) to dilute the charge and hence limit the combustion rate, the resulting exhaust temperatures are low. The selected boost system must therefore be efficient which could lead to large, complex and costly solutions. In the presented work experiments and modelling were combined to evaluate different turbocharger configurations for the PPC concept. Experiments were performed on a multi-cylinder engine. The engine was modified to incorporate long route EGR and a single-stage turbocharger, however, with compressed air from the building being optionally supplied to the compressor.

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 concept of Partially Premixed Combustion (PPC) in internal combustion engines has shown to yield high gross indicated efficiencies, but at the expense of gas exchange efficiencies. Most of the experimental research on partially premixed combustion has been conducted on compression ignition engines designed to operate on diesel fuel and relatively high exhaust temperatures. The partially premixed combustion concept on the other hand relies on dilution with high exhaust gas recirculation (EGR) rates to slow down the combustion which results in low exhaust temperatures, but also high mass flows over cylinder, valves, ports and manifolds. A careful design of the gas exchange system, EGR arrangement and heat exchangers is therefore of utter importance. Experiments were performed on a heavy-duty, compression ignition engine using a fuel consisting of 80 volume % 95 RON service station gasoline and 20 volume % n-heptane.

Partially Premixed Combustion (PPC) has shown to be a promising advanced combustion mode for future engines in terms of efficiency and emission levels. The combustion timing should be suitably phased to realize high efficiency. However, a simple constant model based predictive controller is not sufficient for controlling the combustion during transient operation. This article proposed one learning based model predictive control (LBMPC) approach to achieve controllability and feasibility. A learning model was developed to capture combustion variation. Since PPC engines could have unacceptably high pressure-rise rates at different operation points, triple injection is applied as a solvent, with the use of two pilot fuel injections. The LBMPC controller utilizes the main injection timing to manage the combustion timing. The cylinder pressure is used as the combustion feedback. The method is validated in a multi-cylinder heavy-duty PPC engine for transient control.