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The optimization of biodiesel production by using response surface methodology and its effect on compression ignition engine

Abuhabaya, Abdullah, Fieldhouse, John D. and Brown, David .R. (2013) The optimization of biodiesel production by using response surface methodology and its effect on compression ignition engine. Fuel Processing Technology, 113. pp. 57-62. ISSN 0378-3820

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Abstract

Bio-fuel production provides an alternative non-fossil fuel without the need to redesign current engine technology. This study presents an experimental investigation into the effects of using biodiesel blends on diesel engine performance and its emissions. The biodiesel fuels were produced from sunflower oil using the transesterification process with low molecular weight alcohols and sodium hydroxide then tested on a steady state engine test rig using a Euro 4 four cylinder compression ignition (CI) engine. This study also shows how by blending biodiesel with diesel fuel at intervals of B5, B10, B15, and B20 can decrease harmful gas emissions significantly while maintaining similar performance output and efficiency. Production optimization was achieved by changing the variables which included methanol/oil molar ratio, NaOH catalyst concentration, reaction time, reaction temperature, and the rate of mixing to maximize biodiesel yield. The technique used was the response surface methodology (RSM). In addition, a second-order model was developed to predict the biodiesel yield if the production criteria is known. The model was validated using additional experimental testing. It was determined that the catalyst concentration and molar ratio of methanol to sunflower oil were the most influential variables affecting percentage conversion to fuel and percentage initial absorbance.

Item Type: Article
Subjects: T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
School of Computing and Engineering > Automotive Engineering Research Group
School of Computing and Engineering > High-Performance Intelligent Computing > High Performance Computing Research Group
School of Computing and Engineering > Pedagogical Research Group
Related URLs:
Depositing User: Cherry Edmunds
Date Deposited: 05 Jul 2013 15:26
Last Modified: 05 Jul 2013 15:26
URI: http://eprints.hud.ac.uk/id/eprint/17911

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