Determination of bio-diesel engine combustion pressure using neural network based model

Combustion pressure analysis is an important aspect to be studied in the research and development of internal combustion engines. However, measurements of incylinder combustion pressure for a complete range of testing are time-consuming and costly, as it required high accuracy pressure sensor system...

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Main Authors:	Che Wan, Mohd Noor, R., Mamat, Najafi, G., Anuar, Abu Bakar, Samo, Khalid
Format:	Article
Language:	English
Published:	Taylor's University 2019
Subjects:	QA Mathematics TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics
Online Access:	http://umpir.ump.edu.my/id/eprint/25270/ http://umpir.ump.edu.my/id/eprint/25270/ http://umpir.ump.edu.my/id/eprint/25270/1/Determination%20of%20bio-diesel%20engine%20combustion%20pressure%20using.pdf

id	ump-25270
recordtype	eprints
spelling	ump-252702019-10-25T02:10:17Z http://umpir.ump.edu.my/id/eprint/25270/ Determination of bio-diesel engine combustion pressure using neural network based model Che Wan, Mohd Noor R., Mamat Najafi, G. Anuar, Abu Bakar Samo, Khalid QA Mathematics TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics Combustion pressure analysis is an important aspect to be studied in the research and development of internal combustion engines. However, measurements of incylinder combustion pressure for a complete range of testing are time-consuming and costly, as it required high accuracy pressure sensor systems. Alternatively, a simulation model based on the computer program can be used to retrieve those parameters. This study focused on developing the prediction model to determine the combustion pressure of diesel engines by employing artificial neural network methods. Input data for training, testing, and validation of the model were obtained from laboratory engine testing. The biodiesel blends percentage, engine loads, engine speeds and crank angle position were selected as the input parameters. The performance of the ANN model was validated against the experimental data. The results show that the developed model successfully predicted the engine combustion pressure with a higher correlation coefficient (R-value) between 0.99968-0.99973, means that the model produces 99% of prediction accuracy. In addition, the prediction errors occurred within a small range of values. This study revealed that the neural network approach is able to predict the combustion pressure of the diesel engine with high accuracy. Taylor's University 2019-04 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25270/1/Determination%20of%20bio-diesel%20engine%20combustion%20pressure%20using.pdf Che Wan, Mohd Noor and R., Mamat and Najafi, G. and Anuar, Abu Bakar and Samo, Khalid (2019) Determination of bio-diesel engine combustion pressure using neural network based model. Journal of Engineering Science and Technology, 14 (2). pp. 909-921. ISSN 1823-4690 http://www.myjurnal.my/public/article-view.php?id=133314
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA Mathematics TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics
spellingShingle	QA Mathematics TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering TL Motor vehicles. Aeronautics. Astronautics Che Wan, Mohd Noor R., Mamat Najafi, G. Anuar, Abu Bakar Samo, Khalid Determination of bio-diesel engine combustion pressure using neural network based model
description	Combustion pressure analysis is an important aspect to be studied in the research and development of internal combustion engines. However, measurements of incylinder combustion pressure for a complete range of testing are time-consuming and costly, as it required high accuracy pressure sensor systems. Alternatively, a simulation model based on the computer program can be used to retrieve those parameters. This study focused on developing the prediction model to determine the combustion pressure of diesel engines by employing artificial neural network methods. Input data for training, testing, and validation of the model were obtained from laboratory engine testing. The biodiesel blends percentage, engine loads, engine speeds and crank angle position were selected as the input parameters. The performance of the ANN model was validated against the experimental data. The results show that the developed model successfully predicted the engine combustion pressure with a higher correlation coefficient (R-value) between 0.99968-0.99973, means that the model produces 99% of prediction accuracy. In addition, the prediction errors occurred within a small range of values. This study revealed that the neural network approach is able to predict the combustion pressure of the diesel engine with high accuracy.
format	Article
author	Che Wan, Mohd Noor R., Mamat Najafi, G. Anuar, Abu Bakar Samo, Khalid
author_facet	Che Wan, Mohd Noor R., Mamat Najafi, G. Anuar, Abu Bakar Samo, Khalid
author_sort	Che Wan, Mohd Noor
title	Determination of bio-diesel engine combustion pressure using neural network based model
title_short	Determination of bio-diesel engine combustion pressure using neural network based model
title_full	Determination of bio-diesel engine combustion pressure using neural network based model
title_fullStr	Determination of bio-diesel engine combustion pressure using neural network based model
title_full_unstemmed	Determination of bio-diesel engine combustion pressure using neural network based model
title_sort	determination of bio-diesel engine combustion pressure using neural network based model
publisher	Taylor's University
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/25270/ http://umpir.ump.edu.my/id/eprint/25270/ http://umpir.ump.edu.my/id/eprint/25270/1/Determination%20of%20bio-diesel%20engine%20combustion%20pressure%20using.pdf
first_indexed	2023-09-18T22:38:43Z
last_indexed	2023-09-18T22:38:43Z
_version_	1777416770213117952

Determination of bio-diesel engine combustion pressure using neural network based model

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