Abstract
Reports on the optimum brake-power, surrogate fuel, engine emissions, and efficiency using hybrid model on high compression ratio diesel engines are very imperative for effective application of biodiesel in power and renewable energy generation. This study presents Dyacrodes edulis biodiesel engine performance and combustion release optimization using response surface methodology-genetic algorithm (RSM-GA) as well as the variation of key engine efficiency and exhaust release indices with brake power and fuel blend in a high compression ratio (CR) diesel engine. Combustion emission impacts of the blends with respect to petro-diesel decreased in values except for NOX. Brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), volumetric efficiency, and exhaust temperature increased with brake power while specific energies decreased with load. Optimum conditions obtained using integrated RSM-GA were 40.03%, 0.05 kg/kW-h, 0.03%, 132.30 ppm, and 18.84 ppm for BTE, BSFC, CO, NOx, and HC respectively at low factor (engine load, engine speed, and fuel blend) conditions. At the optimum conditions, the experimental validation results were 44.01%, 0.05 kg/kW-h, 0.04%, 130.05 ppm, and 20.33 ppm for BTE, BSFC, CO, NOx, and HC respectively. The application of the feedstock in compression ignition engine is viable.
Highlights
The fuel combustion process in the transportation sector is the second largest energy consuming after industrial sector and it accounts for about 30% of the world’s total delivered energy of which 80% is on road transport
The brake specific energy consumption (BSEC) of the blends with biodiesel was found to be lower than that of diesel. It indicates that energy released by biodiesel to develop unit power is more than that of petrodiesel fuel[46] Similar to the changes observed on the brake specific fuel consumption (BSFC) with increase in brake powers, BSEC decreased with increase in power, while there was no significant difference in the BSEC between 30 and 40 Nm
The value of the percentage change of Carbon (II) oxide (CO) emission at 30 Nm was highest for B25 followed by B75 and least for B100
Summary
The fuel combustion process in the transportation sector is the second largest energy consuming after industrial sector and it accounts for about 30% of the world’s total delivered energy of which 80% is on road transport. The application of artificial neural network (ANN) for predicting the brake power, torque, and emissions of CO, CO2, HC, and NOx in relation to engine speed, load, and fuel blends has been developed and the result showed high correlation coefficients[23] while backpropagation training algorithm of ANN is observed as appropriate to predict performance and exhaust emissions of engine for different speeds and different fuel blends.[24] Recently, the optimization of biodiesel combustion through parametric approach using response surface methodology (RSM) and the simulation analyses of indicated specific fuel consumption (ISFC), NOx and soot using design of experiments (DOE) is reported.[25] More importantly, the main advantage of response surface methodology (RSM) is its capability to minimize the number of experimental runs needed to give adequate evidence for statistically acceptable result.[26,27] This makes it possible to predict the conditions required to obtain optimum responses through its robustness.[28] the effects of engine parameters on power, static injection pressure (SIP), injection timing, fuel fraction and compression ratio characteristics of karanja oil biodiesel with petrodiesel using Taguchi based design of experiment in a single cylinder 5.2 kW diesel engine has been investigated.[29]. The variations of extensive engine performance and emissions characteristics with brake power and diesel surrogate fuels which have not been previously reported are investigated and presented in details
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