A comparative evaluation and optimization of performance and emission characteristics of a DI diesel engine fueled with n-propanol/diesel, n-butanol/diesel and n-pentanol/diesel blends using response surface methodology

Abstract

High carbon bio-alcohols have recently grabbed the attention of diesel engine researchers because of higher energy density, higher cetane number and better blend stability than their low carbon counterparts. This study utilizes three high carbon bio-alcohol/diesel blends prepared by mixing 40% by vol. of n-propanol, n-butanol and n-pentanol individually with fossil diesel in a DI diesel engine. Engine performance and emission characteristics were measured under high-load conditions based on a 3³ full-factorial experimental design matrix using exhaust gas recirculation (EGR) rate, injection-timing and alcohol type used in the blends as factors for controlling charge-dilution and combustion-phasing. A statistical investigation was then carried out to compare and analyze the effects of these factors on all measured responses like nitrogen oxides (NO_x), smoke, hydrocarbons (HC), carbon monoxide (CO), brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC). Multiple regression models were developed for all responses using a response surface methodology (RSM) and were found to be statistically significant at 99% confidence levels. Interactive effects between injection timing and EGR for all blends were compared and analyzed through response surface plots fitted using developed models with high R² values. Optimization was performed using a desirability approach with an objective to minimize NO_x, smoke and BSFC with maximum BTE. n-Propanol/diesel blend injected at 25° CA bTDC under 30% EGR with a desirability of 0.965 was predicted to be optimum for this engine. Similarly n-butanol/diesel and n-pentanol/diesel blends injected at 24° CA bTDC under 10% EGR were found to be optimum in their respective category. Confirmatory tests validated that the developed RSM models were adequate to describe the effects of injection timing and EGR on the engine characteristics as the predicted error is within 5%.