Optimization of automotive diesel engine calibration using genetic algorithm techniques

Federico Millo, Pranav Arya and Fabio Mallamo

Energy, 2018, vol. 158, issue C, 807-819

Abstract: Although the advancements in automotive diesel engines in the last two decades have resulted in the possibility of achieving better performance with lower pollutant emissions and fuel consumption, the increased complexity of the system and the high number of control parameters require the solution of optimization problems of high dimensionality. It is of crucial importance to identify suitable methodologies, which allow achieving the full exploitation of the potential of these powertrains. In this paper, an original methodology for optimizing the latest generation of common rail automotive diesel engines has been presented.

Keywords: Diesel engine calibration; Genetic algorithm; Surrogate models; Multi objective optimization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:158:y:2018:i:c:p:807-819

DOI: 10.1016/j.energy.2018.06.044

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