OPTIMIZATION OF PERFORMANCE AND EMISSION CHARACTERISTICS OF GASOLINE-ALCOHOL-BASED NANOFUELS USING TEACHING LEARNING-BASED OPTIMIZATION METHOD FOR SUSTAINABLE FUTURE

Zinc Oxide and Aluminum oxide nanoparticles (14 nm) were added to E20 (Ethanol 20% +80% Gasoline) and E20 based iso-stoichiometric ternary fuel blends of gasoline, ethanol, methanol (GEM) by means of ultrasonication technique at the concentrations of 5ppm and 10 ppm to formulate different nano fuel blends. All the test samples were tested on Spark-Ignition engine. Teaching-Learning based optimization technique (TLBO) is employed to optimize the results and identify the best performing blend. The parameters such as brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), carbondioxide (CO2), carbonmonoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx) were optimized. The optimum results were obtained for nanoparticle concentration of 5ppm and engine speed of 2900 rpm for the ZnO fuel blends. The performance and the emission characteristics obtained at the optimum operating parameters were 36.5 % BTE, 0.22 kg/kWh of BSFC, 41ppm of HC, 788 ppm of NOx, 0.29% CO, 13.26% CO2.