with the collaboration of Iranian Society of Mechanical Engineers (ISME)

Document Type : Research Article-en

Authors

1 Department of Mechanical Biosystems Engineering, Faculty of Agriculture, College of Agriculture and Natural Science, Razi University, Kermanshah, Iran

2 Biosystems Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

3 Department of Mechanical Biosystems Engineering, University of Tehran, Karaj, Iran

Abstract

The vibrations generated by the use of different fuel mixtures in tractor engines can lead to accelerated wear of engine components, significant increases in maintenance costs, and reduced comfort and safety for operators. Nowadays, renewable fuels, namely biodiesel and bioethanol, have been of great interest to many researchers. In the present study, vibrations of the engine of MF285 tractor were measured in three directions, at speeds of 1000, 1600, and 2000 rpm for ten different fuel levels obtained from different compositions of biodiesel, bioethanol, and diesel fuels. To analyze the effects of the concerned parameters on engine vibrations, the response surface methodology (RSM) and artificial neural network fuzzy inference system (ANFIS) were applied. The obtained results demonstrated that increasing the engine speeds was in direct proportion to the vibrations increase. Furthermore, pure diesel fuel accounted for the major portion of vibrations, and B5E4D91 had the highest vibrations among the fuel compositions. Moreover, vibrations were meaningfully reduced with the increase of biodiesel in fuel compositions. The optimization analysis revealed that the most effective fuels, exhibiting the lowest vibration levels, were identified as B25E6D69 through RSM and B25E4D71 via ANFIS.

Keywords

Main Subjects

©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

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