Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine

Alternative fuels; Brakes; Carbon; Carbon monoxide; Diesel engines; Engine cylinders; Engines; Ethanol; Fuel consumption; Fuels; Gasoline; Knowledge acquisition; Learning systems; Nitrogen oxides; Speed; Brake specific fuel consumption; Coefficient of determination; Engine performance; Exhaust emiss...

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Main Authors: Sebayang A.H., Masjuki H.H., Ong H.C., Dharma S., Silitonga A.S., Kusumo F., Milano J.
Other Authors: 39262519300
Format: Article
Published: Elsevier Ltd 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-230202023-05-29T14:37:28Z Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine Sebayang A.H. Masjuki H.H. Ong H.C. Dharma S. Silitonga A.S. Kusumo F. Milano J. 39262519300 57175108000 55310784800 57217370281 39262559400 56611974900 57052617200 Alternative fuels; Brakes; Carbon; Carbon monoxide; Diesel engines; Engine cylinders; Engines; Ethanol; Fuel consumption; Fuels; Gasoline; Knowledge acquisition; Learning systems; Nitrogen oxides; Speed; Brake specific fuel consumption; Coefficient of determination; Engine performance; Exhaust emission; Extreme learning machine; Manihot glaziovii; Mean absolute percentage error; Nitrogen oxide emissions; Bioethanol Bioethanol can potentially replace gasoline because of its lower exhaust emissions. The purpose of this study was to investigate the engine performance and exhaust emissions of Manihot glaziovii bioethanol�gasoline blends at different blend ratios (5%, 10%, 15%, and 20%). Tests were performed on a single-cylinder, four-stroke spark-ignition engine with engine speed was varied from 1600 to 3400 rpm, and the properties of the Manihot glaziovii bioethanol�gasoline blends were measured and analysed. The vapour pressure increased for fuel blends with low concentrations of bioethanol due to the oxygen within the bioethanol molecules and the contribution of the flame speed which can enhance the combustion and improved the engine efficiency. In addition, the engine torque, brake power, and brake-specific fuel consumption (BSFC) were measured, as well as the carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide emissions. For a fuel blend containing 20% bioethanol at an engine speed of 3200 rpm, the BSFC decreased, with maximum values of 270.7 g/kWh. The CO and HC emissions were lower for the Manihot glaziovii bioethanol�gasoline blends. In addition, an extreme learning machine (ELM) model was developed for application in the automotive and industrial sectors. This tool reduces the cost, time, and effort associated with experimental data. The blend ratio of the bioethanol�gasoline blends and the engine speed were used as the input data of the model, and the engine performance and exhaust emissions parameters were used as the output data. The coefficient of determination (R2) was within a range of 0.980�1.000, and the mean absolute percentage error was within a range of 0.411%?2.782% for all the parameters. The results indicate that the ELM model is capable of predicting the engine performance and exhaust emissions of bioethanol�gasoline fuel blends. � 2017 Elsevier Ltd Final 2023-05-29T06:37:28Z 2023-05-29T06:37:28Z 2017 Article 10.1016/j.fuel.2017.08.102 2-s2.0-85029417416 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029417416&doi=10.1016%2fj.fuel.2017.08.102&partnerID=40&md5=c3590aab07d2a68136ff5e84fd3ab8a3 https://irepository.uniten.edu.my/handle/123456789/23020 210 914 921 Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Alternative fuels; Brakes; Carbon; Carbon monoxide; Diesel engines; Engine cylinders; Engines; Ethanol; Fuel consumption; Fuels; Gasoline; Knowledge acquisition; Learning systems; Nitrogen oxides; Speed; Brake specific fuel consumption; Coefficient of determination; Engine performance; Exhaust emission; Extreme learning machine; Manihot glaziovii; Mean absolute percentage error; Nitrogen oxide emissions; Bioethanol
author2 39262519300
author_facet 39262519300
Sebayang A.H.
Masjuki H.H.
Ong H.C.
Dharma S.
Silitonga A.S.
Kusumo F.
Milano J.
format Article
author Sebayang A.H.
Masjuki H.H.
Ong H.C.
Dharma S.
Silitonga A.S.
Kusumo F.
Milano J.
spellingShingle Sebayang A.H.
Masjuki H.H.
Ong H.C.
Dharma S.
Silitonga A.S.
Kusumo F.
Milano J.
Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
author_sort Sebayang A.H.
title Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
title_short Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
title_full Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
title_fullStr Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
title_full_unstemmed Prediction of engine performance and emissions with Manihot glaziovii bioethanol ? Gasoline blended using extreme learning machine
title_sort prediction of engine performance and emissions with manihot glaziovii bioethanol ? gasoline blended using extreme learning machine
publisher Elsevier Ltd
publishDate 2023
_version_ 1806428006007177216