Maximizing Efficiency and Environmental Benefits of an Algae Biodiesel-Hydrogen Dual Fuel Engine through Operational Parameter Optimization Using Response Surface Methodology
The utilization of clean and renewable fuels has become increasingly significant in the power generation and transportation sectors. Dual-fuel engines that employ hydrogen and algal biodiesel are potential alternatives. This study investigated the impact of pilot fuel injection pressures and engine...
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Published in | International journal of hydrogen energy Vol. 52; pp. 1395 - 1407 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
02.01.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The utilization of clean and renewable fuels has become increasingly significant in the power generation and transportation sectors. Dual-fuel engines that employ hydrogen and algal biodiesel are potential alternatives. This study investigated the impact of pilot fuel injection pressures and engine loads on the performance and emissions of an algal biodiesel-hydrogen dual-fuel engine. The engine was optimized using response surface methodology under various operating conditions. The highest brake thermal efficiency (28.71%) was obtained at 240 bar pilot fuel injection pressure and 100% engine load, significantly reducing carbon monoxide and hydrocarbon emissions. The optimum parameters were identified using response surface methodology at 67.63% engine load and 245.48 bar pilot fuel injection pressure, with a high model fit (R2) range of 88.89% to 99.59% and composite desirability of 96.1%. The potential for optimizing algal biodiesel-hydrogen dual-fuel engines to achieve greater efficiency and environmental benefits is highlighted in this work, as is the relevance of applying response surface methods to optimize engine performance.
•Algae Biodiesel-Hydrogen dual fuel resulted 28.11% highest brake thermal efficiency.•Algae Biodiesel-Hydrogen dual fuel resulted less emissions than biodiesel alone.•Response surface model achieved strong data fitting between 91-99%.•Optimal response surface found at 62% load and 246.75 bar pilot injection pressure.•96% composite desirability achieved using response surface optimization. |
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ISSN: | 0360-3199 1879-3487 |
DOI: | 10.1016/j.ijhydene.2023.10.134 |