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Design of a decision support methodology using response surface for torque comparison: An empirical study on an engine fueled with waste plastic pyrolysis oil

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  • Poompipatpong, Chedthawut
  • Kengpol, Athakorn

Abstract

Current energy and environmental situations have been driving the development of new alternative energies, especially in transportation sector. The objective of this research is to present a decision support methodology to compare engine torques between using the average value and the new approach called response surface. This research investigates the engine torques from neat diesel fuel (WPO (waste plastic pyrolysis oil) 0%) and blend 25% of waste plastic pyrolysis oil by volume in diesel (WPO 25%) at wide range of engine load (20%, 40%, 60%, and 100%) and speed (800 rpm, 1200 rpm, 1500 rpm, 1800 rpm, and 2000 rpm). A heavy-duty multi-cylinder diesel engine was installed on an engine dynamometer and the torque data were recorded. The contribution of this research is to present a more accurate methodology to perform an engine torque comparison. The value of this research lies in the development of a new approach, which is applicable to decision makers in obtaining an engine torque comparison. Consequently, the benefit of the research is that the empirical data from a heavy-duty diesel engine fueled with waste plastic oil blends are revealed. The number of experimentations can be reduced and this leads to lower costs and less time usage for future research.

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  • Poompipatpong, Chedthawut & Kengpol, Athakorn, 2015. "Design of a decision support methodology using response surface for torque comparison: An empirical study on an engine fueled with waste plastic pyrolysis oil," Energy, Elsevier, vol. 82(C), pages 850-856.
    • Handle: RePEc:eee:energy:v:82:y:2015:i:c:p:850-856
    DOI: 10.1016/j.energy.2015.01.095
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    References listed on IDEAS

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    Cited by:

    1. Yusri, I.M. & Abdul Majeed, A.P.P. & Mamat, R. & Ghazali, M.F. & Awad, Omar I. & Azmi, W.H., 2018. "A review on the application of response surface method and artificial neural network in engine performance and exhaust emissions characteristics in alternative fuel," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 665-686.
    2. Najafi, Gholamhassan & Ghobadian, Barat & Yusaf, Talal & Safieddin Ardebili, Seyed Mohammad & Mamat, Rizalman, 2015. "Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline–ethanol blended fuels using response surface methodology," Energy, Elsevier, vol. 90(P2), pages 1815-1829.

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