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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.

An opposed-piston two-stroke folded-cranktrain diesel engine was studied in this paper. In order to achieve asymmetric scavenging, asymmetric angle between two crank throws were designed. However asymmetric crank-throw angle has direct effect on the piston dynamic, which affects engine performance. This paper investigated the characteristics of the piston dynamic on an opposed-piston two-stroke folded-cranktrain diesel engine; effects of the asymmetric angle on the piston displacement, velocity and acceleration were analyzed; further researches were done to studied the effect of piston dynamic on the gas exchange performance and in-cylinder performance. The results show that, larger asymmetric angle is positive for the scavenging efficiency but negative for combustion.