The optimization procedure adopted in the present investigation is based on Genetic Algorithms (GA) and allows different fitness functions to be simultaneously maximized. The parameters to be optimized are related to the geometric features of the combustion chamber, which ranges of variation are very wide. For all the investigated configurations, bowl volume and squish-to-bowl volume ratio were kept constant so that the compression ratio was the same for all investigated chambers. This condition assures that changes in the emissions were caused by geometric variations only. The spray injection angle was also considered as a variable parameter. The optimization was simultaneously performed for different engine operating conditions, i.e. load and speed, and the corresponding fitness values were weighted according to their occurrence in the European Driving Test. The evaluation phase of the genetic algorithm was performed by simulating the behavior of each chamber with a modified version of the KIVA3V code. The parameters for the sprays and the combustion models were adjusted according to the experimental data of a commercial chamber geometry taken as baseline case. Three fitness functions were defined according to engine emission levels (soot, NOx and HC) and a penalty function was used to account for engine performance. The goal of the optimization process was to select a chamber giving the best compromise of the selected fitness functions. Furthermore, chambers optimizing each single fitness function were also analyzed. The influence of the geometric characteristics on emissions has also been investigated in the paper.

Optimization of the Combustion Chamber of Direct Injection Diesel Engines

DE RISI, Arturo;LAFORGIA, Domenico;DONATEO, Teresa
2003-01-01

Abstract

The optimization procedure adopted in the present investigation is based on Genetic Algorithms (GA) and allows different fitness functions to be simultaneously maximized. The parameters to be optimized are related to the geometric features of the combustion chamber, which ranges of variation are very wide. For all the investigated configurations, bowl volume and squish-to-bowl volume ratio were kept constant so that the compression ratio was the same for all investigated chambers. This condition assures that changes in the emissions were caused by geometric variations only. The spray injection angle was also considered as a variable parameter. The optimization was simultaneously performed for different engine operating conditions, i.e. load and speed, and the corresponding fitness values were weighted according to their occurrence in the European Driving Test. The evaluation phase of the genetic algorithm was performed by simulating the behavior of each chamber with a modified version of the KIVA3V code. The parameters for the sprays and the combustion models were adjusted according to the experimental data of a commercial chamber geometry taken as baseline case. Three fitness functions were defined according to engine emission levels (soot, NOx and HC) and a penalty function was used to account for engine performance. The goal of the optimization process was to select a chamber giving the best compromise of the selected fitness functions. Furthermore, chambers optimizing each single fitness function were also analyzed. The influence of the geometric characteristics on emissions has also been investigated in the paper.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/104322
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