Biogas engine performance estimation using ANN
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier - Division Reed Elsevier India Pvt Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Artificial neural network (ANN) method was used to estimate the thermal efficiency (TE), brake specific fuel consumption (BSFC) and volumetric efficiency (VE) values of a biogas engine with spark ignition at different methane (CH4) ratios and engine load values. For this purpose, the biogas used in the biogas engine was produced by the anaerobic fermentation method from bovine manure and different CH4 contents (51%, 57%, 87%) were obtained by purification of CO2 and H2S. The data used in the ANN models were obtained experimentally from a 4-stroke four-cylinder, spark ignition engine, at constant speed for different load and CH4 ratios. Using some of the obtained experimental data, ANN models were developed, and the rest was used to test the developed models. In the ANN models, the CH4 ratio of the fuel, engine load, inlet air temperature (T-in), air fuel ratio and the maximum cylinder pressure are chosen as the input parameters. TE, BSFC and VE are used as the output parameters. Root mean square error (RMSE), mean absolute percentage error (MAPE) and correlation coefficient (R) performance indicators are used to compare measured and predicted values. It has been shown that ANN models give good results in spark ignition biogas engines with high correlation and low error rates for TE, BSFC and VE values. (C) 2017 Karabuk University. Publishing services by Elsevier B.V.
Açıklama
Anahtar Kelimeler
Estimating engine performance, Biogas, BSFC, ANN
Kaynak
Engineering Science and Technology-An International Journal-Jestech
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
20
Sayı
6
