Experimental assessment and optimization of the performance of a biodiesel engine using response surface methodology

Abstract

BackgroundBiodiesel is a renewable and ecofriendly fuel for internal combustion engines. However, fuel standards need to be adapted for efficiency and commercial use. This paper deals with a novel process of its production using a purification step that counters the high costs of production and experimental analysis using multiresponse optimization.MethodsSoybean oil was chosen as a biodiesel of 5%, 10%, and 15% blend with common diesel fuel and is experimentally tested in a variable compression ratio compression ignition engine. The biodiesel is blended with common diesel fuel to run the engine without any modification in its setup, which also solves most of the operational problems. The functional relationship between the input parameters and the performance characteristics of the engine is evaluated by statistical response surface methodology using the Box–Behnken design model, which generates a design of experiment resulting in an optimum experimental run that reduces the overall cost of the experimental investigation. Uncertainty analysis is done to minimize the gap between the results considering the errors of each piece of equipment. Validation of the results is also carried out.ResultsThe analysis of variance is used to measure the acceptability of the model and the competency of the model to predict output performance. The optimum value of input parameters which are obtained are 4.5 kg for the load, the compression ratio of 18, and B05 for the fuel blend, which results in maximum performance of brake power of 3 kW, minimum fuel consumption and emissions of CO and NOx, which are 0.39 kg/kWh, 0.01%, and 50 ppm.ConclusionsCost analysis reveals that biodiesel produced from the novel process of transesterification is reasonable as compared with the conventional process. It is also environmentally more sustainable, which cannot be ignored. This technique can be used in future research for cost-effective production fields such as combustion parameters and biofuels produced from waste, which need to be explored.