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Performance, combustion and emission characteristics of a diesel engine fueled with diesel-kerosene-ethanol: A multi-objective optimization study

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  • Bhowmik, Subrata
  • Paul, Abhishek
  • Panua, Rajsekhar
  • Ghosh, Subrata Kumar

Abstract

The study explores the potential of ethanol as an additive on the performance, combustion and exhaust emission characteristics of a compression ignition engine fueled with adulterated diesel considering the environmental protection agency tier 4 emission mandates. Results showed that the inclusion of ethanol in the adulterated diesel notably reduced engine exhaust emissions along with improvement in the performance and combustion parameters. The experiential study was followed by a Pareto-based multi-objective optimization study to achieve non-dominated solutions for the performance-emission paradigms under diesel-kerosene-ethanol blends. The functional relationships for the non-dominated sorting genetic algorithm-II were acquired with the assistance of response surface methodology technique. The optimal values of the output parameters of the engine, such as brake thermal efficiency, cumulated oxide of nitrogen & unburned hydrocarbon and carbon monoxide emissions were evaluated by utilizing a multi-attribute decision making technique using input parameters, such as brake mean effective pressure, kerosene share and ethanol share. The optimization result reveals that among the different running conditions used in this study, the engine can be operated in the most optimal manner at 2.2 bar brake mean effective pressure, 2.4% kerosene share (by volume) and 10% ethanol share (by volume).

Suggested Citation

  • Bhowmik, Subrata & Paul, Abhishek & Panua, Rajsekhar & Ghosh, Subrata Kumar, 2020. "Performance, combustion and emission characteristics of a diesel engine fueled with diesel-kerosene-ethanol: A multi-objective optimization study," Energy, Elsevier, vol. 211(C).
    • Handle: RePEc:eee:energy:v:211:y:2020:i:c:s0360544220314122
    DOI: 10.1016/j.energy.2020.118305
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    4. Gharehghani, Ayat & Abbasi, Hamid Reza & Alizadeh, Pouria, 2021. "Application of machine learning tools for constrained multi-objective optimization of an HCCI engine," Energy, Elsevier, vol. 233(C).

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