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Prediction of engine performance and exhaust emissions for gasoline and methanol using artificial neural network

Author

Listed:
  • Çay, Yusuf
  • Korkmaz, Ibrahim
  • Çiçek, Adem
  • Kara, Fuat
Abstract
This study investigates the use of ANN (artificial neural networks) modelling to predict BSFC (break specific fuel consumption), exhaust emissions that are CO (carbon monoxide) and HC (unburned hydrocarbon), and AFR (air–fuel ratio) of a spark ignition engine which operates with methanol and gasoline. To obtain training and testing data, a number of experiments were performed with a four-cylinder, four-stroke test engine operated at different engine speeds and torques. The experimental results reveal that the methanol improved the emission characteristics compared with the gasoline. For the ANN modelling, the standard back-propagation algorithm was found to be the optimum choice for training the model. In the building of the network structure, four different learning algorithms were used such as BFGS (Quasi-Newton back propagation), LM (Levenberg–Marquardt learning algorithm). It was found that the ANN model is able to predict the engine performance and exhaust emissions with a correlation coefficient of 0.998621, 0.977654, 0.998382 and 0.996075 for the BSFC, CO, HC and AFR for testing data, respectively. It was obvious that the developed ANN model is fairly powerful for predicting the brake specific fuel consumption and exhaust emissions of internal combustion engines.

Suggested Citation

  • Çay, Yusuf & Korkmaz, Ibrahim & Çiçek, Adem & Kara, Fuat, 2013. "Prediction of engine performance and exhaust emissions for gasoline and methanol using artificial neural network," Energy, Elsevier, vol. 50(C), pages 177-186.
    • Handle: RePEc:eee:energy:v:50:y:2013:i:c:p:177-186
    DOI: 10.1016/j.energy.2012.10.052
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    References listed on IDEAS

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    1. Najafi, G. & Ghobadian, B. & Tavakoli, T. & Buttsworth, D.R. & Yusaf, T.F. & Faizollahnejad, M., 2009. "Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network," Applied Energy, Elsevier, vol. 86(5), pages 630-639, May.
    2. Chauhan, Bhupendra Singh & Kumar, Naveen & Cho, Haeng Muk, 2012. "A study on the performance and emission of a diesel engine fueled with Jatropha biodiesel oil and its blends," Energy, Elsevier, vol. 37(1), pages 616-622.
    3. Mohamed Ismail, Harun & Ng, Hoon Kiat & Queck, Cheen Wei & Gan, Suyin, 2012. "Artificial neural networks modelling of engine-out responses for a light-duty diesel engine fuelled with biodiesel blends," Applied Energy, Elsevier, vol. 92(C), pages 769-777.
    4. Yilmaz, Nadir & Sanchez, Tomas M., 2012. "Analysis of operating a diesel engine on biodiesel-ethanol and biodiesel-methanol blends," Energy, Elsevier, vol. 46(1), pages 126-129.
    5. Yilmaz, Nadir, 2012. "Comparative analysis of biodiesel–ethanol–diesel and biodiesel–methanol–diesel blends in a diesel engine," Energy, Elsevier, vol. 40(1), pages 210-213.
    6. Deh Kiani, M. Kiani & Ghobadian, B. & Tavakoli, T. & Nikbakht, A.M. & Najafi, G., 2010. "Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends," Energy, Elsevier, vol. 35(1), pages 65-69.
    7. Ghobadian, B. & Rahimi, H. & Nikbakht, A.M. & Najafi, G. & Yusaf, T.F., 2009. "Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network," Renewable Energy, Elsevier, vol. 34(4), pages 976-982.
    8. Adnan, R. & Masjuki, H.H. & Mahlia, T.M.I., 2012. "Performance and emission analysis of hydrogen fueled compression ignition engine with variable water injection timing," Energy, Elsevier, vol. 43(1), pages 416-426.
    9. Gong, Chang-Ming & Huang, Kuo & Jia, Jing-Long & Su, Yan & Gao, Qing & Liu, Xun-Jun, 2011. "Regulated emissions from a direct-injection spark-ignition methanol engine," Energy, Elsevier, vol. 36(5), pages 3379-3387.
    10. Masi, Massimo, 2012. "Experimental analysis on a spark ignition petrol engine fuelled with LPG (liquefied petroleum gas)," Energy, Elsevier, vol. 41(1), pages 252-260.
    11. Ozsezen, Ahmet Necati & Canakci, Mustafa, 2011. "Performance and combustion characteristics of alcohol–gasoline blends at wide-open throttle," Energy, Elsevier, vol. 36(5), pages 2747-2752.
    12. Mohammadi, Pouya & Nikbakht, Ali M. & Tabatabaei, Meisam & Farhadi, Khalil & Mohebbi, Arash & Khatami far, Mehdi, 2012. "Experimental investigation of performance and emission characteristics of DI diesel engine fueled with polymer waste dissolved in biodiesel-blended diesel fuel," Energy, Elsevier, vol. 46(1), pages 596-605.
    13. Yusaf, T.F. & Yousif, B.F. & Elawad, M.M., 2011. "Crude palm oil fuel for diesel-engines: Experimental and ANN simulation approaches," Energy, Elsevier, vol. 36(8), pages 4871-4878.
    14. Rakopoulos, Dimitrios C. & Rakopoulos, Constantine D. & Giakoumis, Evangelos G. & Dimaratos, Athanasios M., 2012. "Characteristics of performance and emissions in high-speed direct injection diesel engine fueled with diethyl ether/diesel fuel blends," Energy, Elsevier, vol. 43(1), pages 214-224.
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