Evaluation and optimization of engine performance and exhaust emissions of a diesel engine fueled with diestrol blends

Shahin Rafiee*, Zeinab Shabani, Benyamin Khoshnevisan, Barat Ghobadian, Amin Nasiri


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Biofuel is a nontoxic and renewable fuel and could be used in diesel engines in combination with diesel to reduce emissions. The effects of various biodiesel–ethanol–diesel (BED) blends were investigated on the engine power, specific fuel consumption (SFC), engine vibration, and pollutant emissions. The engine experiments were performed using nine castor biodiesel and ethanol blends under five different engine speeds. The engine power was not influenced by different BED blends while B5E4, and B5E6 fuel blends had the highest SFC. The engine vibration slightly increased when fueled with BED blends. Hydrocarbon emission diminished by increasing biodiesel percentage in the blends, whereas it increased by substituting more ethanol in BED blends. NOx emission was increased by adding more biodiesel into BED blends, while ethanol performed vice versa. The results showed that CO emission was enhanced by increasing ethanol percentage, while it decreased with more biodiesel addition. There was not a remarkable difference in CO2 emissions between different treatments. A novel combination of an Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling and Honeybee Mating Optimization (HBMO) method was adopted to find a global optimum BED blend considering various output parameters. The selected ANFIS model satisfactorily predicted the engine efficiency and exhaust emissions with R2, mean absolute percentage error (MAPE), and root-mean-squared error (RMSE) of 0.99, 0.02, and 0.11, respectively. Consequently, using the HBMO algorithm, the BED blend with 15% of biodiesel, 6% of ethanol, and 79% of pure diesel was found to be the most optimal BED blend for a diesel engine at an engine speed of 950 rpm.

TidsskriftEnvironmental Progress and Sustainable Energy
Udgave nummer1
Antal sider15
StatusUdgivet - jan. 2023

Bibliografisk note

Funding Information:
The authors would like to acknowledge the financial supports provided by the University of Tehran and the Iran National Science Foundation under project numbers 7313285/1/10 and 91059668, respectively.

Funding Information:
Iran National Science Foundation, Grant/Award Number: 91059668; University of Tehran, Grant/Award Number: 7313285/1/10 Funding information

Publisher Copyright:
© 2022 American Institute of Chemical Engineers.


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