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Study and modeling of diesel combustion during transient operations is an important scientific objective. This is partially due to the fact that emissions under transient operations have aroused increasing attention by control groups during recent decades. The objective of this paper is to develop a combustion model to predict the peculiarities of transient combustion for developing and testing control strategies. To by-pass the complicated principles of transient combustion, the Neural Networks are applied to link the coefficients in an empirical combustion model with engine operating parameters. Finally, the Neural Networks combustion model would not only reflect the influence of turbocharge lag on combustion process during transient event, which cannot be predicted by its interpolation alternative, but also shown great potential for analyzing combustion characteristics during load increase transient event or other transient operations.

In this paper the experiments of hydraulic free piston diesel engine is described. The experimental data were obtained from measurement instruments on the free piston diesel engine that has been developed by Beijing Institute of Technology [ 1 ]. This article discusses the influences of compression pressure, injection timing, and combustion process to the free piston diesel engine principle. The compression process experiment shows that the piston velocity, the compression ratio can be controlled by adjusting the compression pressure. With the increasing of the compression pressure, there is a growing a compression ratio and piston velocity. The study on injection timing shows that the injection timing impacts the cylinder pressure peak value and the pressure peak arrival time. The combustion process is quite different from the crankshaft engine because of the unique piston movement characteristics of the hydraulic free piston engine.