Optimization of Train Diesel Engine for Maximizing Efficiency and Driving Quality Using Modified Parameterized Level-Set Method

Introduction Progress in air and fuel management has greatly increased the efficiency of modern automotive train diesel engines, also achieving significant reductions of pollutant emissions. The increased flexibility of the air and fuel management systems also means a higher number of control parame...

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Published inJournal of Vibration Engineering & Technologies Vol. 11; no. 1; pp. 43 - 52
Main Authors Stojicic, Srdjan, Milovančević, Miloš, Milčić, Dragan, Andjelkovic, Boban, Vračar, Ljubomir
Format Journal Article
LanguageEnglish
Published Singapore Springer Nature Singapore 01.01.2023
Springer Nature B.V
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ISSN2523-3920
2523-3939
DOI10.1007/s42417-022-00557-1

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Summary:Introduction Progress in air and fuel management has greatly increased the efficiency of modern automotive train diesel engines, also achieving significant reductions of pollutant emissions. The increased flexibility of the air and fuel management systems also means a higher number of control parameters and complex interactions between different parameters. Materials and methods The task of tuning the engine control parameters to find the right combination to maximize the efficiency and reduce pollutant emissions is referred to as engine calibration. The task of engine calibration for modern automotive diesel engine has become extremely challenging, requiring large amount of time and money to be spent on engine test bench. Results The main aim of the study was to test and evaluate driving quality of train diesel engine. For the accessibility study of these issues with regard to the implementation of the engine control approach, level-set approaches were used in this study. Conclusion The subject of this test is a diesel engine train. The diesel engine train series with respect to running safety and Adynamic behavior, under the test conditions fulfilled, it meets the prescribed requirements of the standard EN 14363: 2005.
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ISSN:2523-3920
2523-3939
DOI:10.1007/s42417-022-00557-1