Predicting the Effects of Direct-Injected Fuels Co-Powered by High-CO2 Biogas on RCCI Engine Emissions Using Kinetic Mechanisms and Multi-Objective Optimization
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Date
2024
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Publisher
Elsevier
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
High inert gas content in biogas resulted in poor burning and emissions attributes, though scarcely investigated in reactivity controlled compression ignition (RCCI). Established kinetic mechanisms were combined with multiobjective optimization to investigate, predict, and analyze emissions occurrence and trade-offs for reduced environmental impacts. The work examined the impact of direct-injected high reactivity fuels (HRF) and portinjected Biogas at various inert gas (carbon dioxide, CO2) rates (25 - 45% vol), biogas fractions (40 - 70%), speeds (1600 - 2000 rpm), and loads (4.5 - 6.5 bar IMEP) on emissions of RCCI engine, experimentally. The findings revealed that while engine speeds greatly decreased CO (carbon monoxide) and NOx (nitrate oxide) emissions with rising unburned hydrocarbon (UHC) regardless of HRF employed, higher engine load significantly reduced UHC emissions. Diesel-biogas reduces NOx emissions and performs better in reducing CO and UHC emissions at lower speeds than B5-biogas, except in low-level loads. Although increasing CO2 impact led to a reduction in UHC and CO emissions, the biogas proportion was the most significant variable. The main factor influencing increased NOx emissions was engine load, which is inversely correlated with reduced NOx and increased particulate emissions owing to high CO2 content and biogas proportion. The premixed mode's optimisation outcome confirms the trade -off reduction at 5.5 bar IMEP, 35.586% CO2, and 50% fraction. As a result, running the RCCI engine with direct-injected diesel co-powered in equal proportion with high-CO2 biogas cuts the emissions trade -off dramatically, limiting the environmental repercussions of the emissions.
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Keywords
RCCI, High-Co 2 Content, Biogas, Emission Trade -Off, Kinetic Mechanisms, Multi-Objective Optimization
Turkish CoHE Thesis Center URL
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WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
N/A
Source
Process Safety and Environmental Protection
Volume
184
Issue
Start Page
747
End Page
765
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CrossRef : 5
Scopus : 14
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