Experimental investigation of performance, emission, and combustion characteristics of a diesel engine using blends of waste cooking oil-ethanol biodiesel with MWCNT nanoparticles

Abstract

In this study, blends of 5 % and 10 % ethanol with waste cooking oil biodiesel are mixed with Multi-Walled Carbon Nanotubes (MWCNT) at a concentration of 30 ppm. MWCNTs, known for their high surface area and unique properties, are added to potentially enhance combustion efficiency and reduce emissions. These blends are then tested in a diesel engine to evaluate their performance, emission and combustion characteristics using Design of experiment technique. After conducting various experiments and analyses, the blend of 20 % biodiesel, 10 % ethanol, and 30 ppm MWCNT was identified as the most optimal due to its favorable engine characteristics. Brake Thermal Efficiency (BTE) was increased from 3.1 % to 3.4 % with the addition of MWCNTs, indicating enhanced fuel efficiency. Moreover, average Fuel Consumption is decreased from 2.2 % to 2.5 %, suggesting improved fuel utilization. Using MWCNT 30 ppm in B20 ethanol blends (MWCNT 30 ppm B20+E10) resulted in 35 % reduction in nitrogen oxide (NOx) emissions, 37 % reduction in CO emissions and 39 % reduction in HC emissions. Hence MWCNTs demonstrated effectiveness in mitigating harmful exhaust emissions The optimized values for all parameters fall within acceptable ranges, indicated successful optimization using Response surface methodology. Additionally, statistical analysis reveals that the machine learning- XGBoost model outperformed all other advanced machine learning models across all tested metrics, including MSE, MAE, and R-square.

Keywords

• Waste cooking oil
• Multi-walled carbon nanotubes (mwcnt)
• Ethanol
• Diesel engine
• ML-RSM