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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/25270/1/Determination%20of%20bio-diesel%20engine%20combustion%20pressure%20using.pdf
http://umpir.ump.edu.my/id/eprint/25270/
http://www.myjurnal.my/public/article-view.php?id=133314
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spelling my.ump.umpir.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
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
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/25270/1/Determination%20of%20bio-diesel%20engine%20combustion%20pressure%20using.pdf
http://umpir.ump.edu.my/id/eprint/25270/
http://www.myjurnal.my/public/article-view.php?id=133314
_version_ 1648741192622407680
score 13.211869

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