Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks

Glycine max oil biofuel (GMOB) is a product of the transesterification of soybean oil. It contains a substantial amount of thermal energy. In this study, the result of varying fuel injection timings on the performance, ignition, and exhaust parameters of a research engine with single-cylinder, four-...

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Main Authors: Rajak, Upendra, Panchal, Manoj, Dasore, Abhishek, Verma, Tikendra Nath, Chaurasiya, Prem Kumar
Format: Article
Published: Springer 2024
Online Access:http://psasir.upm.edu.my/id/eprint/113930/
https://link.springer.com/article/10.1007/s11356-024-34429-w?error=cookies_not_supported&code=d1f4e543-d828-48bd-95fb-442e7212c504
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Institution: Universiti Putra Malaysia
id my.upm.eprints.113930
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spelling my.upm.eprints.1139302025-02-05T07:28:56Z http://psasir.upm.edu.my/id/eprint/113930/ Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks Rajak, Upendra Panchal, Manoj Dasore, Abhishek Verma, Tikendra Nath Chaurasiya, Prem Kumar Glycine max oil biofuel (GMOB) is a product of the transesterification of soybean oil. It contains a substantial amount of thermal energy. In this study, the result of varying fuel injection timings on the performance, ignition, and exhaust parameters of a research engine with single-cylinder, four-stroke with direct injection (DI) diesel was experimentally investigated and optimised using artificial neural networks (ANN). The results demonstrated that a 20% fuel blend with 24.5° before top dead centre (b TDC) decreased brake thermal efficiency (BTE), NOx emissions, and exhaust cylinder temperature but improved fuel consumption, carbon dioxide emissions (CDE), and smoke emissions. With 26.5° b TDC, the BTE was found to be approximately 5.0% higher while the fuel consumption was approximately 2.0% lower than with the original injection timing of 24.5° b TDC. At 26.5° b TDC, the NOx emission was approximately 8.6% higher, and the smoke emission was approximately 4.07% lower than at the original injection timing (24.5° b TDC). Springer 2024-07-25 Article PeerReviewed Rajak, Upendra and Panchal, Manoj and Dasore, Abhishek and Verma, Tikendra Nath and Chaurasiya, Prem Kumar (2024) Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks. Environmental Science and Pollution Research. ISSN 0944-1344; eISSN: 1614-7499 https://link.springer.com/article/10.1007/s11356-024-34429-w?error=cookies_not_supported&code=d1f4e543-d828-48bd-95fb-442e7212c504 10.1007/s11356-024-34429-w
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Glycine max oil biofuel (GMOB) is a product of the transesterification of soybean oil. It contains a substantial amount of thermal energy. In this study, the result of varying fuel injection timings on the performance, ignition, and exhaust parameters of a research engine with single-cylinder, four-stroke with direct injection (DI) diesel was experimentally investigated and optimised using artificial neural networks (ANN). The results demonstrated that a 20% fuel blend with 24.5° before top dead centre (b TDC) decreased brake thermal efficiency (BTE), NOx emissions, and exhaust cylinder temperature but improved fuel consumption, carbon dioxide emissions (CDE), and smoke emissions. With 26.5° b TDC, the BTE was found to be approximately 5.0% higher while the fuel consumption was approximately 2.0% lower than with the original injection timing of 24.5° b TDC. At 26.5° b TDC, the NOx emission was approximately 8.6% higher, and the smoke emission was approximately 4.07% lower than at the original injection timing (24.5° b TDC).
format Article
author Rajak, Upendra
Panchal, Manoj
Dasore, Abhishek
Verma, Tikendra Nath
Chaurasiya, Prem Kumar
spellingShingle Rajak, Upendra
Panchal, Manoj
Dasore, Abhishek
Verma, Tikendra Nath
Chaurasiya, Prem Kumar
Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
author_facet Rajak, Upendra
Panchal, Manoj
Dasore, Abhishek
Verma, Tikendra Nath
Chaurasiya, Prem Kumar
author_sort Rajak, Upendra
title Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
title_short Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
title_full Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
title_fullStr Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
title_full_unstemmed Predict the characteristics of the DI engine with various injection timings by Glycine max oil biofuel using artificial neural networks
title_sort predict the characteristics of the di engine with various injection timings by glycine max oil biofuel using artificial neural networks
publisher Springer
publishDate 2024
url http://psasir.upm.edu.my/id/eprint/113930/
https://link.springer.com/article/10.1007/s11356-024-34429-w?error=cookies_not_supported&code=d1f4e543-d828-48bd-95fb-442e7212c504
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