Cylinder pressure based calibration model for engines using ethanol, hydrogen and natural gas as alternative fuels


This paper proposes a novel virtual engine calibration method for alternative fuels using thermodynamic simulation for in-cylinder pressure prediction. Based on known engine data, including the crank angle of the peak cylinder pressure, the optimization problem is defined for a desired indicated mean effective pressure. The decision variables are the combustion and heat transfer model parameters The method was tested for three different engines of different sizes, operating with ethanol, hydrogen and natural gas, and different equivalence ratios. The Wiebe model and a quasi-dimensional fractal combustion model were compared. The results showed that the method was able to successfully predict the in-cylinder pressure curve, with a coefficient of determination higher than 0.99. Furthermore, the method predicted the peak pressure and the crank angle corresponding to 50% of mass fraction burned with a maximum deviation of 2.5% and 1.5 °CA, respectively.

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Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences > Energy and Bioproducts Research Institute (EBRI)
College of Engineering & Physical Sciences
Additional Information: © 2021 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license Funding Information: This study was financed in part by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil . The authors would like to thank the colleagues at the Engines, Emissions and Fuels Research Centre (CPMEC) at PUC Minas for their support and kindness.
Uncontrolled Keywords: Alternative fuels,Calibration model,Cylinder pressure,Engine simulation,Ethanol conversion,Hydrogen energy,Energy(all)
Publication ISSN: 2352-4847
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 3772?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2021-11
Published Online Date: 2021-07-08
Accepted Date: 2021-06-01
Authors: Ayad, Sami Massalami Mohammed Elmassalami
Vago, Carolina Locatelli
Belchior, Carlos Rodrigues Pereira
Sodré, José Ricardo (ORCID Profile 0000-0003-2243-8719)

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