Optimization of application of 2-ethyl-hexyl-nitrate on partial substitution of ethanol in CI engine for fuel economy and emission control using MADM method

Abstract

The present study is performed to identify the blending proportion of cetane improver for partial substitution of ethanol with diesel to achieve fuel economy and emission control. This is case of multiple attribute decision making problem which is solved using Taguchi GRA. Taguchi method is used to decide the proportion of blend in fuel sample to achieve maximum improvement with minimum number of fuel sample and grey relation analysis is done to identify the significant factor along with optimize fuel proportion. Using Taguchi method, nine different fuel samples containing mixture of ethanol, 2 ethyl hexyl-nitrates and diesel were prepared. Each sample was tested on computerized single cylinder CI engine test rig at constant speed and variable compression ratio at 16, 17 and 18 and variable load conditions. After Grey relation analysis of performance and emission results of experimentation, it is observed that D80E20EH3 by ranking method and D80E10EH3 by mean method are optimum fuel sample sequence. Confirmatory experimentation also shows that experimental GRG is close to predicted GRG of 0.8387 hence optimum sequences is acceptable. The optimum sequence shows improvement in fuel economy and lesser NOx emission with little increases in smoke. Keywords Ethanol • Cetane improver • MADM • Taguchi GRA • CI engine Abbreviations CR Compression ration BSFC Brake specific fuel consumption NOx Nitrogen oxide PM Particulate matter CR Compression ration kW Kilo watt CO Carbon monoxide HC Hydro carbon ANNOVA Analysis of variance 2EHN 2 Ethyl hexyl nitrate DF Degree of freedom

Optimization of Material Composition and Compression Molding Process Parameters to Maximize Mechanical Properties of Recycled Polypropylene (r-PP) Composite Reinforced with Ironwood Powder

“…The Taguchi method uses rigorous experimental design to optimize process parameters [39][40][41]. This method can also be used to minimize the number of experiments.…”