Analyzing the effects of hexane and water blended diesel fuels on emissions and performance in a ceramic-coated diesel engine by Taguchi optimization method

Abstract

In this study, the effects of different hexane and water blended diesel fuel rates on CO (ppm), CO2 (%), HC (ppm), exhaust gas temperature (degrees C), NOx (%), smoke opacity (%), brake specific fuel consumption (g/kWh) and brake thermal efficiency (%) in ceramic-coated and uncoated diesel engines that were run at distinct brake loads were investigated. At first, experimental designs were obtained from the orthogonal array of the Taguchi method, and the experiments were carried out based on these designs. The results of the experiments were then tested and evaluated with ANOVA to analyze the effect of the engine, brake load and fuel factors on the experimental results of the emission and performance parameters. The diesel fuel blends employed in the experiments were 100% diesel (D), 90% diesel + 5% water + 5% hexane (D90W5H5), and 85% Diesel + 5% water + 10% hexane (D85W5H10). These fuels were utilized in ceramic-coated and uncoated diesel engines operating brake loads of 2 kW, 3 kW, and 4 kW. This experimental study was designed with the Taguchi method as a mixed level based on the orthogonal array L18 (2 boolean AND 1 3 boolean AND 2). The engine factor was defined as two levels, while the brake load and fuel factors were defined as three levels each. During the experiments, resulting values of CO, HC, smoke opacity, and brake-specific fuel consumption (BSFC) were aimed to be lower, while CO2, exhaust gas temperature (EGT), NOx (%), and brake thermal efficiency (BTE) higher to conduct the analysis. As a result of the mixed-level Taguchi analysis, while blending the hexane and water with diesel fuels provided improvements in the emission and performance parameters, only the BTE parameter gave better results in pure diesel fuel. The ceramic-coated engine was found to be the most effective factor in all parameters. Also, the 4 kW brake load gave better results in all parameters. According to the results of ANOVA the test, the factors were most statistically significant in explaining the emission and performance parameters (P < 0.05). However, the engine factor for NOx and CO2 and the fuel factor for BSFC were not statistically significant (P > 0.05). This means that these factors did not significantly affect the results of NOx, CO2 and BSFC. Also, the R2 values of models created for all emission and performance parameters were more than 90%, indicating that the accuracy was very high. According to the Taguchi analysis, the most effective factors in the results were brake load, fuel, and engine respectively for all the experiments.