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Modeling and simulation of the thermodynamic cycle of the Diesel Engine using Neural Networks

Abstract: In this paper, a unique single zone combustion model is proposed to predict Diesel engine’s performance, pressure, and temperature based on the conservation of mass and energy. In order to simulate all phases of combustion, the proposed model takes in consideration the dynamics of the intake and exhaust gas through the valves, the ignition delay, the instantaneous change in gas properties, the properties of the burned fuel, and the heat losses by the walls. Validation of this model has been realized by experimental data. Important issue has been recognized that the physical model takes too much time in calculation. For this purpose, a Feed-Forward Neural Network (FFNN) model is developed and validated experimentally to predict the pressure and temperature in the cylinder in nominal and faulty operations. Finally, the influence of some possible faults that may be produced on the diesel engine cycle during the operation has been analyzed.
- Laboratoire Parole et Langage France
- Aix-Marseille University France
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
