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Experimental and computational analysis of combustion characteristics of a diesel engine fueled with diesel-tomato seed oil biodiesel blends

journal contribution
posted on 07.06.2022, 00:08 authored by Rahim Karami, Mohammad RasulMohammad Rasul, Mohammad KhanMohammad Khan, Mohammad Mahdi Salahi, Mohammad AnwarMohammad Anwar
Diesel engines are the main sources of fuel consumption due to their wide use in various sectors such as transportation, agriculture, and industry, however they produce huge greenhouse gas (GHG) emissions. Therefore, the use of biodiesel has attracted considerable attention of researchers and engine manufacturers because it can significantly reduce GHG emissions with only a small penalty of engine performance. Tomato seeds oil (TSO) can be used as a cheap and non-edible source of biodiesel. This study presents combustion analysis of a four-cylinder diesel engine fueled with four diesel-TSO biodiesel blends. The experiments were carried out with B0 (pure diesel), B5 (5% biodiesel + 95% diesel), B10 and B20 at different engine loads and speeds. The combustion parameters, namely Ignition Delay (ID), Combustion Duration (CD), Heat Release Rate (HRR), Cylinder Pressure (CP) and Indicated Work (Wi) are investigated. An artificial neural network (ANN) model was developed to predict engine combustion characteristics. The numerical simulation was also done using AVL FIRE software. Results show that, (i) the smallest and largest ID values were found for B20 at about 8°–9° CA and for B10 at about 13° CA; (ii) the highest of peak HRR CA occurs at 1400 rpm at about 20.5° CA; and (iii) the highest and lowest CPs were found at 2000 rpm at about 69 MPas and 1600 rpm at about 65 MPas respectively. Based on the amount of Wi generation, B10 was found to be the optimal mixture of biodiesel with diesel. Both ANN model and AVL simulation model results agrees quite satisfactorily with experimental values.

History

Volume

285

Start Page

1

End Page

13

Number of Pages

13

eISSN

1873-7153

ISSN

0016-2361

Publisher

Elsevier

Language

en

Peer Reviewed

Yes

Open Access

No

Acceptance Date

11/09/2020

External Author Affiliations

Shiraz University, Iran

Era Eligible

Yes

Journal

Fuel

Article Number

119243