4.7 Article

Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline-ethanol blended fuels using response surface methodology

期刊

ENERGY
卷 90, 期 -, 页码 1815-1829

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2015.07.004

关键词

Response surface methodology; Engine performance; Exhaust emissions; Ethanol-gasoline blends

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This paper studies the use of RSM (response surface methodology) to optimize the performance parameters and exhaust emissions of a SI (spark ignition) engine which operates with ethanol gasoline blends of 5%, 7.5%, 10%, 12.5% and 15% called E5, E7.5, E10, E12.5 and E15. In the experiments, the engine ran at various speeds for each test fuel and 45 different conditions were constructed. In comparison with gasoline fuel, the brake power, engine torque, increased using ethanol blends, and the bsfc (brake specific fuel consumption) decreased as well. Moreover, the concentration of CO and HC in the exhaust pipe decreased by introducing ethanol blends, but CO2 and NO emissions increased. Optimization of independent variables was performed using the desirability approach of the RSM (response surface methodology) with the goal of minimizing emissions and maximizing of performance parameters. The experiments were designed using a statistical tool known as DoE (design of experiments) based on RSM. Engine-operating parameters were optimized using the Desirability approach of RSM. The performance parameters for different biofuel-gasoline blends were found close to gasoline, and emission characteristics of the engine improved significantly. An engine speed of 3000 rpm and a blend of 10% bioethanol and 90% gasoline (E10) were found to be optimal values. The results of this study revealed that at optimal input parameters, the values of the brake power, Torque, bsfc, and CO, CO2, HC, NO were found to be 35.26 (kW), 103.66 (Nm), 0.25 (kg/kW hr), 3.5 (%Vol.), 12.8 (%Vol.), 136.6 (ppm) and 1300 (ppm) respectively. (C) 2015 Elsevier Ltd. All rights reserved.

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