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In an effort to support design and testing activities at product development lifecycle of the engine, proper duty cycle is required. However, to collect data and develop accurate duty cycles, there are not any vehicles equipped with prototype engines at customers. Therefore, in this paper, discrete duty cycle development methodology is studied to generate trailer truck engine usage profile which represents driving conditions in Turkey for engines in development phase. Cycles are generated using several vehicles equipped with prototype engines and professional drivers that can mimic customer usage. Methodology is based on defining real-world customer driving profile, discretizing real-world drives into separate events, collecting vehicle data from each discrete drive, determining the weight of events by conducting customer surveys and creating a representative reference usage profile with data analysis.

In recent years, due to the growing problem of environmental pollution and climate change internal combustion engine stroke volume size has been reduced. The use of down-sized engines provides benefit for reducing emissions and fuel consumption especially at the inner city driving conditions. However, when the engine demands additional power, utilizing a turbocharging system is required. This study is a joint work of Istituto Motori CNR with Automotive Laboratory of Mechanical Engineering Faculty of Istanbul Technical University (ITU) and the objective of this study was devoted to increase the understanding of various engine operating conditions on emissions, especially at low load. The trade-off between Nitrogen Oxide (NOx) and Particulate Matter (PM) emissions in a Diesel engine has been examined depending on turbocharging rates and the rate of Exhaust Gas Recirculation (EGR) applied.

With the advent of the KIVA-4 code which employs an unstructured mesh to represent the engine geometry, the gap in flexibility between commercial and research modeling software becomes more narrow. In this study, we tried to perform a full cycle simulation of a 4-stroke HD diesel engine represented by a highly boosted research IF (Isotta Fraschini) engine using the KIVA-4 code. The engine mesh including the combustion chamber, intake and exhaust valves and helical manifolds was constructed using optional O-Grids catching a complex geometry of the engine parts with the help of the ANSYS ICEM CFD software. The KIVA-4 mesh input was obtained by a homemade mesh converter which can read STAR-CD and CFX outputs. The simulations were performed on a full 360 deg mesh consisting of 300,000 unstructured hexahedral cells at BDC. The physical properties of the liquid fuel were taken corresponding to those of real diesel #2 oil.

A method for automatic reduction of detailed reaction mechanisms using simultaneous sensitivity, reaction flow and lifetime analysis has been developed and applied to a two-zone model of an SI engine fuelled with Primary Reference Fuel (PRF). Species which are less relevant for the occurrence of autoignition in the end gas are declared redundant. They are identified and eliminated for different pre-set minimum levels of reaction flow and sensitivity. The resulting skeletal mechanism is valid in the ranges of initial and boundary values for which the analyses have been performed. A measure of species lifetime is calculated from the chemical source terms, and the species with the lifetime shorter than and mass-fraction less than specified limits are selected for removal.

A method for automatic reduction of detailed kinetic to skeletal mechanisms for complex fuels is proposed. The method is based on the simultaneous use of sensitivity and reaction-flow analysis. The resulting skeletal mechanism is valid for the parameter range of initial and boundary values, the analysis have been performed for. The gas-phase chemistry is analyzed in the end gas of an SI-engine, using a two-zone model. Species, not relevant for the occurrence of autoignition in the end gas, are defined as redundant. They are identified and eliminated for different pre-set levels of minimum reaction flow and sensitivity. The error in the mechanism increases monotony with increasing pre-set level of minimum reaction flow.