Experimental investigation and ANN modelling of the effects of diesel/gasoline premixing in a waste cooking oil-fuelled
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Experimental investigation and ANN modelling of the effects of diesel/ gasoline premixing in a waste cooking oil‑fuelled HCCI‑DI engine G. M. Lionus Leo1 · S. Sekar2 · S. Arivazhagan1 Received: 25 October 2019 / Accepted: 4 February 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract This paper intends to study the combustion, performance and emission characteristics of the HCCI-DI engine with waste cooking oil (WCO) biodiesel as direct injection fuel and diesel/gasoline as the premixed fuel. 20% of fuel (gasoline/diesel) was injected at inlet manifold along with the intake air during the suction stroke. Balance 80% of the fuel (diesel, B50 and WCO) was injected into the cylinder at 23 °CA before TDC. The outcomes observed from the experimentations showed that the HCCI-DI engine was resulted increased brake thermal efficiency (ηbth) than conventional DI engine. Increase in the ηbth up to 4.23% was found form the gasoline-premixed HCCI-DI operation compared to DI operation. During HCCI-DI, 14.81% and 4.3% drop in oxides of nitrogen (NOx) were observed for the diesel and gasoline premixing, respectively, compared to conventional engine. A decrease in the hydrocarbon up to 54.17% was noted for the WCO-fuelled DI engine compared with diesel-fuelled DI engine. 50.66% and 39.21% reduction in the smoke emissions were found for the diesel and gasolinepremixed HCCI-DI, respectively, compared to diesel-fuelled DI engine. Artificial neural network modelling was proposed to forecast the emissions and ηbth of the HCCI-DI engine. Keywords Artificial neural network · HCCI-DI · Waste cooking oil · Gasoline premixing · Diesel premixing List of symbols P Cylinder pressure (bar) m Number of data set R Correlation coefficient R2 Coefficient of determination O2 Oxygen Greek symbols ηbth Brake thermal efficiency θRoHRmax Crank angle corresponding RoHRmax θpmax Crank angle corresponding Pmax Subscripts t Actual observation n Crank angle interval (°CA) o Predicted output value max Maximum
* G. M. Lionus Leo [email protected] 1
Department of Mechanical Engineering, St. Joseph’s College of Engineering, Chennai 600119, India
Department of Mechanical Engineering, Rajalakshmi Engineering College, Chennai 602105, India
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Abbreviations ANN Artificial neural network ASTM American society for testing and materials standard CI Compression ignition CO Carbon monoxide CZO Copper-doped zinc oxide DI Direct injection HC Hydrocarbon HCCI Homogeneous charge compression ignition RoHR Rate of heat release IC Internal combustion MAPE Mean absolute percentage error NOx Oxides of nitrogen NRMSE Normalized root-mean-square error RPR Rate of pressure rise (bar °CA−1) SFC Specific fuel consumption SI Spark ignition SOC Start of combustion
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Introduction Rapid industrialization and population have increased the rate of energy consumption. Gasoline and diesel are the two major fuels used in the transportation sector. The primary energy consumption of India is the third biggest after China
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