A study on emission reduction and combustion efficiency, analyzing oxymethylene ether (OME1-5) with diesel fuel
Abstract
Data availability: Data will be made available on request.This study investigates an optimized fuel blend comprising oxymethylene ethers (OMEn = 1–5 series) with diesel aimed at simultaneously reducing soot and NOx emissions while enhancing fuel efficiency. An optimal blend was identified through rigorous experimentation and computational fluid dynamics (CFD) modeling. The study employs the response surface method (RSM) for regression analysis and integrates machine learning techniques for predictive modeling to assess various fuel compositions and optimize the mixture for improved combustion dynamics. Experimental measurements were conducted in an optical constant volume combustion chamber (CVCC) to confirm the blend’s effectiveness in reducing both soot and NOx emissions. The investigation thoroughly analyzes spray combustion properties, including injection duration, Start of Combustion (SOC), End of Combustion (EOC), Lift-Off length of fuels, spray tip penetration, and their impact on combustion efficiency. Analysis of energy densities between the blends reveals that OMED exhibits a heating value superior to OME2-5 but inferior to diesel, striking a balance in energy output. Furthermore, OMED demonstrates superior energy density compared to OME1-3 and diesel, highlighting its potential for enhanced fuel efficiency. The optimized blend achieves a significant 78.2 % reduction in soot emissions and a 31.3 % reduction in NOx emissions compared to conventional diesel, underscoring its efficacy in mitigating harmful emissions without compromising combustion performance. This research contributes valuable insights into developing sustainable fuel solutions for diesel engines, paving the way for greener automotive technologies in the future.This research was financially supported by the College of Engineering Design and Physical Sciences at Brunel University London under grant number 11667100Similar works
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This paper was published in Brunel University Research Archive.
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