This study aims to optimize the engine parameters using response surface methodology to achieve fewer pollutants in the exhaust of a spark-ignition engine mounted with a commercial catalytic converter and a sucrolite-catalyst coated converter
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study aims to optimize the engine parameters using response surface methodology to achieve fewer pollutants in the exhaust of a spark-ignition engine mounted with a commercial catalytic converter and a modified catalytic converter. In this research, a sucrose-doped alumina was used as a catalyst as a novel technique to reduce the harmful pollutants present in the exhaust gas. The experiment allowed exhaust gas to pass axially through the converters. The experimental parameters employed were used to develop a numerical model to predict emission levels concerning catalytic converters. The numerical model was developed using brake power, actual to the theoretical air-fuel ratio, and engine exhaust gas pollutants measured before being treated by the catalytic converter as input variables, and primary toxic pollutants treated by the catalytic converters output parameters. The developed model showed superior performance, with higher R-2 values over 0.987 for all cases. The experimental results validated the predicted optimum responses, and the measured error percentage was less than 3% for most cases. The optimized parameters yielded a desirability factor of 0.831 for the commercial catalytic converter and 0.9 for the modified catalytic converter. Thus, the developed response surface methodology model can highly predict the emission characteristics. [GRAPHICS] .
Açıklama
Anahtar Kelimeler
Gasoline engine, Numerical model, Emission reduction, Emission prediction, Low light-off temperature, Exhaust gas treatment, Performance test
Kaynak
International Journal of Environmental Science and Technology
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
20
Sayı
2
