Performance optimization of ethanol blends in diesel model using Taguchi and grey relational approach

The incorporation of biofuels, such as ethanol and biodiesel, offers a viable alternative, but it requires meticulous tuning of engine characteristics. Given their emissions of nitrogen oxides (NO_x), and particulate matter (PM), diesel engines are crucial for many applications but also pose substantial environmental and health concerns, the following important selections of alternatives: renewable sources, lower environmental impact, carbon-neutral potential, and circular economy support. This work assesses the influence of fuel injection pressure, fuel percentage (specifically ethanol-biodiesel-diesel mixtures), and engine load on the efficiency and atmospheric emissions of a direct injection diesel engine designed for light-duty applications. Variations in fuel injection pressures (220, 240, 260 bar), ethanol and waste cooking oil biodiesel fractions (10%, 20%, 30% by volume), and load circumstances (20%, 50%, 80%) were evaluated using the Taguchi L9 orthogonal array. An analysis was conducted on key performance indicators, the desirability function established the ideal parameters as 220 bar fuel injection pressure, 40% ethanol-biodiesel blend, and 80% engine load, reduced brake specific fuel consumption (BSFC) by 7.5%, carbon monoxide (CO) emissions by 15%, and smoke density by 18% when compared to traditional diesel performance. Furthermore, the levels of NO_x emissions rose by 12%, therefore emphasizing the inherent trade-off associated with emissions. Under these ideal conditions, the brake thermal efficiency (BTE) reached its maximum value of 32%. Thereby achieving a balance between performance and emissions. The present work showcases the efficacy of the Taguchi technique, and its desired function in the optimization of diesel engines, therefore promoting environmental sustainability and operational efficiency.