Ann based prediction of engine performance and exhaust emission responses of a ci engine powered by ternary blends
Küçük Resim Yok
Tarih
2020
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Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, experimental data was collected from a single cylinder diesel engine fueled by pyrolytic oil, neat diesel and butanol fuel blends. The experimentswere conducted at various engine loads, namely from 0.25 kW to 1.25 kW by0.25 kW increment. The engine performance and exhaust emission data obtainedwere modeled using an artificial neural network (ANN) algorithm. CO, NOx,BSFC, and BTE were considered in the ANN model. The results were discussedin terms of R2, MBE, and RMSE metrics. R2 value of the performance and exhaustemission responses’ prediction were 0.986, 0.963, 0.991, and 0967 for BTE,BSFC, NOx, and CO, respectively, and in addition, all MBE value was very closeto zero and smaller than 1.14. As a conclusion, the present paper showed thatperformance and exhaust emission responses of ternary fuels can be accuratelypredicted using an artificial neural network
Açıklama
Anahtar Kelimeler
Kaynak
International Journal of Automotive Science and Technology
WoS Q Değeri
Scopus Q Değeri
Cilt
4
Sayı
3
