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Bi-fuel SI engine model for analysis and optimization

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posted on 2019-03-26, 14:11 authored by K. Rezapour, Byron Mason, A.S. Wood, M.K. Ebrahimi
The natural gas as an alternative fuel has economical and environmental benefits. Bi-fuel engines powered by gasoline and compressed natural gas (CNG) are an intermediate and alternative step to dedicated CNG engines. The conversion to bi-fuel CNG engine could be a short-term solution to air pollution problem in many developing countries. In this paper a mathematical model of a bi-fuel four-stroke spark ignition (SI) engine is presented for comparative studies and analysis. It is based on the two-zone combustion model, and it has the ability to simulate turbulent combustion. The model is capable of predicting the cylinder temperature and pressure, heat transfer, brake work , brake thermal and volumetric efficiency, brake torque, brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), concentration of CO2, brake specific CO (BSCO) and brake specific NOx (BSNOx). The effect of engine speed, equivalence ratio and performance parameters using gasoline and CNG fuels are analysed. The model has been validated by experimental data using the results obtained from a bi-fuel engine. The results show the capability of the model in terms of engine performance optimization and minimization of the emissions. The engine used in this study is a typical example of a modified bi-fuel engine conversion, which could benefit the researchers in the field.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Universal Journal of Mechanical Engineering

Volume

2

Pages

71 - 82

Citation

REZAPOUR, K. ... et al., 2017. Bi-fuel SI engine model for analysis and optimization. Universal Journal of Mechanical Engineering, 2(2), pp. 71-82.

Publisher

© Horizon Research Publishing Corporation

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by-nc/4.0/

Publication date

2017

Notes

This is an Open Access Article. It is published by Horizon Research Publishing under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by-nc/4.0/

ISSN

2332-3353

Language

  • en

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