Prediction of spark ignition engine performance responses fueled with fusel oil/gasoline blends by artificial neural network

Abstract

In the present study, the performance parameters of a single-cylinder, air-cooled spark ignition (SI) engine using fusel oil-gasoline fuel blends were predicted by artificial neural network (ANN). The SI engine was operated with gasoline/fusel oil (10% and 20%) blends at different engine load (1000, 2000, 3000, 4000, 5000, 6000, 7000 and 8000 Watt) and compression ratios (8.00, 9.12 and 10.07) to obtain data essential to create the ANN model. In the constructed ANN model, brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) are chosen as output  parameters, while engine load, compression ratio (CR) and fusel oil ratio are chosen as input factors. 75% of the test results were employed to train the ANN. The performance of ANN model was determined by comparing it with the data produced from the part not used for training. According to the found data, ANN model estimated engine performance parameters such as BTE and BSFC by an overall regression coefficient (R) at 0.99384. Simultaneously, mean absolute percentage error (MAPE) were found as 5.027% and 7.847% for BTE and BSFC, respectively. When ANN results and experimental results are compared for BTE and BSFC responses, it is determined that ANN results are close to experimental results with an error rate of less than 5%.

Keywords

• Fusel oil
• artificial neural network
• performance
• gasoline engine

References

1. Biswal, A., Kale, R., Teja, G. R., Banerjee, S., Kolhe, P., Balusamy, S., “An experimental and kinetic modeling study of gasoline/lemon peel oil blends for PFI engine,” Fuel, vol. 267, 2020.
2. S. Simsek, “Effects of biodiesel obtained from Canola, sefflower oils and waste oils on the engine performance and exhaust emissions,” Fuel, vol. 265, pp. 117026, 2020.
3. Suiuay, C., Laloon, K., Katekaew, S., Senawong, K., Noisuwan, P., Sudajan, S., “Effect of gasoline-like fuel obtained from hardresin of Yang (Dipterocarpus alatus) on single cylinder gasoline engine performance and exhaust emissions,” Renew. Energy, vol. 153, pp. 634–645, 2020.
4. S. Uslu and M. B. Celik, “Prediction of engine emissions and performance with artificial neural networks in a single cylinder diesel engine using diethyl ether,” Eng. Sci. Technol. an Int. J., pp. 0–7, 2018.
5. Masum, B. M., Masjuki, H.H., Kalam, M.A., Palash, S.M., Wakil, M.A., Imtenan,S., “Tailoring the key fuel properties using different alcohols (C2–C6) and their evaluation in gasoline engine,” Energy Convers. Manag., vol. 88, pp. 382–390, 2014.
6. Solmaz, H., “A comparative study on the usage of fusel oil and reference fuels in an HCCI engine at different compression ratios,” Fuel, vol. 273, p. 117775, 2020.
7. Santhosh, K., Kumar, G.N., Radheshyam, Sanjay, P.V., “Experimental analysis of performance and emission characteristics of CRDI diesel engine fueled with 1-pentanol/diesel blends with EGR technique,” Fuel, vol. 267, 2020.
8. Cao, C., Zhang, Y., Zhang, X., Zou, J., Qi, F., Li, Y., Yang, J., “Experimental and kinetic modeling study on flow reactor pyrolysis of iso-pentanol: Understanding of iso-pentanol pyrolysis chemistry and fuel isomeric effects of pentanol,” Fuel, vol. 257, p. 116039, 2019.

9. Simsek, S. and Ozdalyan B., “Improvements to the Composition of Fusel Oil and Analysis of the Effects of Fusel Oil–Gasoline Blends on a Spark-Ignited (SI) Engine’s Performance and Emissions,” Energies, vol. 11, no. 3, p. 625, 2018.
10. Şimşek, S., Özdalyan, B., Saygın, H., “Improvement of the Properties of Sugar Factory Fusel Oil Waste and Investigation of its Effect on the Performance and Emissions of Spark Ignition Engine,” BioResources, vol. 14, no. 1, pp. 440–452, 2019.
11. Uslu, S. and Celik, M. B., “Combustion and emission characteristics of isoamyl alcoholgasoline blends in spark ignition engine,” Fuel, vol. 262, 2020.
12. H. Solmaz, “Combustion, performance and emission characteristics of fusel oil in a spark ignition engine,” Fuel Process. Technol., vol. 133, pp. 20–28, 2015.
13. O. I. Awad et al., “Using fusel oil as a blend in gasoline to improve SI engine efficiencies: A comprehensive review,” Renew. Sustain. Energy Rev., vol. 69, no. December 2016, pp. 1232–1242, 2017.
14. Simsek, S. and Uslu, S., “Experimental study of the performance and emissions characteristics of fusel oil/gasoline blends in spark ignited engine using response surface methodology,” Fuel, vol. 277, p. 118182, 2020.
15. Şimşek, S., Saygın, H., Özdalyan, B., “Improvement of Fusel Oil Features and Effect of Its Use in Different Compression Ratios for an SI Engine on Performance and Emission,” Energies, vol. 13, no. 7, p. 1824, 2020.
16. Simsek, S. and Uslu, S., “Determination of a diesel engine operating parameters powered with canola, safflower and waste vegetable oil based biodiesel combination using response surface methodology (RSM),” Fuel, vol. 270, 2020.
17. Aydın, M., Uslu, S., Çelik, M. B., “Performance and emission prediction of a compression ignition engine fueled with biodiesel-diesel blends: A combined application of ANN and RSM based optimization,” Fuel, vol. 269, 2020.
18. S. Uslu and M. B. Celik, “Prediction of engine emissions and performance with artificial neural networks in a single cylinder diesel engine using diethyl ether,” Eng. Sci. Technol. an Int. J., vol. 21, no. 6, 2018.
19. B. Ghobadian, H. Rahimi, A. M. Nikbakht, G. Najafi, and T. F. Yusaf, “Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network,” Renew. Energy, vol. 34, no. 4, pp. 976–982, 2009.
20. Taghavi, M., Gharehghani, A., Nejad, F. B. and Mirsalim, M., “Developing a model to predict the start of combustion in HCCI engine using ANN-GA approach,” Energy Convers. Manag., vol. 195, pp. 57–69, 2019.
21. R. K. Mehra, H. Duan, S. Luo, A. Rao, and F. Ma, “Experimental And Artificial Neural Network (ANN) Study Of Hydrogen Enriched Compressed Natural Gas (HCNG) Engine Under Various Ignition Timings And Excess Air Ratios,” Appl. Energy, vol. 228, pp. 736–754, 2018.
22. T. M. Kiani Deh Kiani, B. Ghobadian, A. M. Tavakoli, and G. N. Nikbakht, “Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends,” Energy, vol. 35, pp. 65–69, 2010.
23. J.P. Holman, "Experimental techniques for engineers", 7nth ed., Tata McGraw Hill, New Delhi, 2004.
24. V. Yap, W. K., Ho, T. and Karri, “Exhaust emissions control and engine parameters optimization using artificial neural network virtual sensors for a hydrogen-powered vehicle,” Int. J. Hydrogen Energy, vol. 37, no. 10, pp. 8704–8715, 2012.
25. R. Deb, M., Majumder, P., Majumder, A., Roy, S., Banerjee, “Application of artificial intelligence (AI) in characterization of the performance–emission profile of a single cylinder CI engine operating with hydrogen in dual fuel mode: An ANN approach with fuzzylogic based topology optimization,” Int. J. Hydrogen Energy, vol. 41, no. 32, pp. 14330–14350, 2016.
26. Bhowmik, S., Panua, R., Debroy, D., Paul, A., “Artificial Neural Network Prediction of Diesel Engine Performance and Emission Fueled With Diesel–Kerosene–Ethanol Blends: A Fuzzy-Based Optimization,” J. Energy Resour. Technol., vol. 139, no. 4, 2017.
27. D. P. Javed, S., Murthy, Y.V.V.S., Baig, R. U., Rao, “Development of ANN model for prediction of performance and emission characteristics of hydrogen dual fueled diesel engine with Jatropha Methyl Ester biodiesel blends,” J. Nat. Gas Sci. Eng., vol. 26, pp. 549–557, 2015.
28. Renald, C. J. T. and Somasundaram, P., “Experimental Investigation on Attenuation of Emission with Optimized LPG Jet Induction in a Dual Fuel Diesel Engine and Prediction by ANN Model,” Energy Procedia, vol. 14, pp. 1427–1438, 2012.
29. Salam, S. and Verma, T. N., “Appending empirical modelling to numerical solution for behaviour characterisation of microalgae biodiesel,” Energy Convers. Manag., vol. 180, pp. 496–510, 2019.
30. G. Najafi, B. Ghobadian, T. Tavakoli, D. R. Buttsworth, T. F. Yusaf, and M. Faizollahnejad, “Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network,” Appl. Energy, vol. 86, no. 5, pp. 630–639, 2009.
31. A. Calam, Y. İçingür, H. Solmaz, and H. Yamık, "A Comparison of Engine Performance and the Emission of Fusel Oil and Gasoline Mixtures at Different Ignition Timings", International Journal of Green Energy, vol. 12, no. 8, pp. 767–772, 2015.
32. E. Yılmaz, "Investigation of the effects of diesel-fusel oil fuel blends on combustion, engine performance and exhaust emissions in a single cylinder compression ignition engine", Fuel, vol. 255, pp. 115741, 2019.
33. O. I. Awad, R. Mamat, T. K. Ibrahim, F. Y. Hagos, M. M. Noor, I. M. Yusri, and A. M. Leman, "Calorific value enhancement of fusel oil by moisture removal and its effect on the performance and combustion of a spark ignition engine", Energy Conversion and Management, vol. 137, pp. 86–96, 2017.
34. A. N. Abdalla, H. Tao, S. A. Bagaber, O. M. Ali, M. Kamil, X. Ma, and O. I. Awad, "Prediction of emissions and performance of a gasoline engine running with fusel oil–gasoline blends using response surface methodology", Fuel, vol. 253, pp. 1–14, 2019.
35. A. Calam, H. Solmaz, A. Uyumaz, S. Polat, E. Yılmaz, Y. İçingür, "Investigation of usability of the fusel oil in a single cylinder spark ignition engine", Journal of The Energy Institute, vol. 88, no. 3, pp. 258–265, 2015.