Citation
Abstract
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).
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Official URL or Download Paper: https://link.springer.com/article/10.1007/s11356-0...
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Engineering |
DOI Number: | https://doi.org/10.1007/s11356-024-34429-w |
Publisher: | Springer |
Keywords: | Artificial neural network; Diesel engine; Glycine max oil biofuel; Pollutant formation |
Depositing User: | Mohamad Jefri Mohamed Fauzi |
Date Deposited: | 05 Feb 2025 07:28 |
Last Modified: | 05 Feb 2025 07:28 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/s11356-024-34429-w |
URI: | http://psasir.upm.edu.my/id/eprint/113930 |
Statistic Details: | View Download Statistic |
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