Predictive correlations for NOx and smoke emission of DI CI engine fuelled with diesel-biodiesel-higher alcohol blends-response surface methodology approach

By Saravanan Subramani, Ravi Govindasamy, G. L. N. Rao. 2020

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Abstract This study explore the application of Taguchi design and Response surface methodology for optimizing the NOx and smoke emission of a diesel engine with minimum penalty in brake specific fuel consumption (BSFC). A single cylinder 4.4 kW Direct Injection stationary engine was used for the investigation. Eight parameters (percentage of Biodiesel, percentage of Butanol, percentage of propanol, percentage of pentanol, Piston Geometry, Retarded injection Timing, Injection pressure. Percentage EGR) which have significant effects on engine emissions and performance were selected as factors and NOx, smoke and BSFC were selected as variables for the present investigation. Three levels were chosen in each factor and tests were conducted with different levels of the chosen factors by selecting suitable orthogonal array. ANOVA was employed to obtain the most influencing factor for the chosen variables. Taguchi design was employed for screening the significant factors and optimal custom design under Response Surface Methodology (RSM) was used for optimizing the level of the factors. A predictive correlation was developed for the chosen engine variables as a function of tested factors through regression analysis.

Subfields: Biomedical Engineering, Computational Mechanics, Fluid Flow and Transfer Processes

View Paper: https://www.semanticscholar.org/paper/ffe509510019722b27d4cf876b876c1f55d2cd88