Exploring the Impact of Al 2 O 3 Additives in Gasoline on HCCI-DI Engine Performance: An Experimental, Neural Network, and Regression Analysis Approach.

This study delves into the influence of incorporating alumina (Al 2 O 3 ) nanoparticles with waste cooking oil (WCO) biofuels in a gasoline engine that employs premixed fuel. During the suction phase, gasoline blends with atmospheric air homogeneously at the location of the inlet manifold. The biodiesel, enhanced with Al 2 O 3 nanoparticles and derived from WCO, is subsequently directly infused into the combustion chamber at 23° before the top dead center. The results highlight that when gasoline operates in the homogeneous charge compression ignition with direct injection (HCCI-DI) mode, there is a notable enhancement in thermal efficiency by 4.23% in comparison to standard diesel combustion. Incorporating the Al 2 O 3 nanoparticles with the WCO biodiesel contributes to an extra rise of 6.76% in thermal efficiency. Additionally, HCCI-DI combustion paves the way for a reduction in nitrogen oxides and smoke emissions, whereas biodiesel laced with Al 2 O 3 nanoparticles notably reduces hydrocarbon and carbon monoxide discharges. Predictive tools such as artificial neural networks and regression modeling were employed to forecast engine performance variables.