Prediction of performance and emission characteristics of diesel engine fuelled with waste biomass pyrolysis oil using response surface methodology

Abstract

Advanced third generation biofuels like pyrolysis oil generated from waste biomass paves way for a cleaner and sustainable environment. An experimental-cum-statistical analysis was performed with the aim of determining the optimal engine operating conditions (with respect to compression ratio, load and fuel blend) to enhance the engine operating characteristics (performance and emission) of a diesel engine. Multiple regression models designed by using response surface methodology (RSM) for the output response variables like brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), oxides of carbon (CO&CO2), hydrocarbon (HC), oxides of nitrogen (NOx) and smoke opacity were found to be statistically significant by analysis of variance. Optimization was carried out using desirability approach with a target of maximizing BTE and CO2 simultaneously by minimizing all other responses. From the results, it can be observed that the optimum conditions for bio-oil operation were 18:1 compression ratio, 20% fuel blend and 100% load. The models developed by RSM were validated through confirmatory experiments and found that the models were satisfactory to report the influence of compression ratio, load and bio-oil concentration on the operating characteristics of the diesel engine as the error in prediction is within 5%.