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The advent of digitalization opens up new avenues for advances in large internal combustion engine technology. Key engine components are becoming "intelligent" through advanced instrumentation and data analytics. By generating value-added data, they provide deeper insight into processes related to the components. An intelligent common rail diesel fuel injection valve for large engine applications in combination with machine learning allows reliable prediction of key combustion parameters such as maximum cylinder pressure, combustion phasing and indicated mean effective pressure. However, fault-related changes to the injection valve also have to be considered. Based on experiments on a medium-speed four-stroke single-cylinder research engine with a displacement of approximately 15.7 liter, this study investigates the extent to which the intelligent injection valve can improve the reliability of combustion parameter predictions in the presence of injection valve faults.

The incorporation of a detailed engine process calculation that takes into account thermal behavior of the engine and exhaust system is essential for a realistic simulation of transient vehicle operation. This is the only possible way to have a precise preliminary calculation of fuel consumption and emissions. Therefore, a comprehensive thermal network of the engine based on the lumped capacity method has been developed. The model allows the computation of component temperatures in steady state operation as well as in transient engine studies, e.g. investigations of engine warm-up. The model is integrated in a co-simulation environment consisting of a detailed vehicle and engine cycle simulation code. The paper describes the procedure of the co-simulation and presents several examples of warm-up simulations.

This paper summarizes the results of several investigations on in-cylinder heat transfer during high-pressure and gas exchange phases as well as heat transfer in the inlet and outlet ports for a number of different engine types (DI Diesel, SI and gaseous fueled engine). The paper contains a comparision of simulation results and experimental data derived from heat flux measurements. Numerical results were obtained from zero-, one- and three-dimensional simulation methods. Time and spatially resolved heat fluxes were measured applying the surface temperature method and special heat flux sensors. The paper also includes an assessment of different sensor types with respect to accuracy and applicability.