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Crude palm oil fuel for diesel-engines: Experimental and ANN simulation approaches

Author

Listed:
  • Yusaf, T.F.
  • Yousif, B.F.
  • Elawad, M.M.

Abstract

In the current work, the effect of using CPO (crude palm oil)–OD (ordinary diesel) blends as fuel on the performance of CI (compression ignition) engine is studied. Three different blends of CPO–OD (25%, 50% and 75%) were investigated using direct-injection, stationary diesel engine. The CPO–OD blends were preheated to about 60 °C before the injection to reduce the viscosity of the blends. The experiments were conducted at variable engine speeds (1000 rpm through 3000 rpm) under fixed throttle opening. The results revealed that the CPO–OD exhibited higher torque and power output at engine speeds lower than 2000 rpm, while the BSFC (brake specific fuel consumption) was found to be higher than the OD at the same engine speeds. CPO enhanced the BSFC at higher engine speeds (above 2000 rpm). The CPO–OD blends exhibited lower emissions of NOx and higher emission of CO compared to the OD.

Suggested Citation

  • Yusaf, T.F. & Yousif, B.F. & Elawad, M.M., 2011. "Crude palm oil fuel for diesel-engines: Experimental and ANN simulation approaches," Energy, Elsevier, vol. 36(8), pages 4871-4878.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:8:p:4871-4878
    DOI: 10.1016/j.energy.2011.05.032
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    References listed on IDEAS

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    1. Najafi, G. & Ghobadian, B. & Tavakoli, T. & Buttsworth, D.R. & Yusaf, T.F. & Faizollahnejad, M., 2009. "Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network," Applied Energy, Elsevier, vol. 86(5), pages 630-639, May.
    2. Fassinou, Wanignon Ferdinand & Sako, Aboubakar & Fofana, Alhassane & Koua, Kamenan Blaise & Toure, Siaka, 2010. "Fatty acids composition as a means to estimate the high heating value (HHV) of vegetable oils and biodiesel fuels," Energy, Elsevier, vol. 35(12), pages 4949-4954.
    3. Bari, S. & Lim, T.H. & Yu, C.W., 2002. "Effects of preheating of crude palm oil (CPO) on injection system, performance and emission of a diesel engine," Renewable Energy, Elsevier, vol. 27(3), pages 339-351.
    4. Ghobadian, B. & Rahimi, H. & Nikbakht, A.M. & Najafi, G. & Yusaf, T.F., 2009. "Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network," Renewable Energy, Elsevier, vol. 34(4), pages 976-982.
    5. Yusaf, Talal F. & Buttsworth, D.R. & Saleh, Khalid H. & Yousif, B.F., 2010. "CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network," Applied Energy, Elsevier, vol. 87(5), pages 1661-1669, May.
    6. Kalam, M.A & Husnawan, M & Masjuki, H.H, 2003. "Exhaust emission and combustion evaluation of coconut oil-powered indirect injection diesel engine," Renewable Energy, Elsevier, vol. 28(15), pages 2405-2415.
    7. Szklo, Alexandre & Schaeffer, Roberto, 2006. "Alternative energy sources or integrated alternative energy systems? Oil as a modern lance of Peleus for the energy transition," Energy, Elsevier, vol. 31(14), pages 2513-2522.
    8. Deh Kiani, M. Kiani & Ghobadian, B. & Tavakoli, T. & Nikbakht, A.M. & Najafi, G., 2010. "Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends," Energy, Elsevier, vol. 35(1), pages 65-69.
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