Bütanol-Diesel yakıtı kullanılan bir sıkıştırma ateşlemeli motorda motor performansı ve egzoz emisyonlarının yapay sinir ağları ile tahmini

Öz

Bu çalışmada saf Diesel yakıtı ve 5 farklı bütanol-Diesel yakıt karışımları (%3, 6, 9, 12 ve 15) kullanılan bir Diesel motorunda (SA) farklı devir sayılarında ve tam yük durumunda motor performansı ve egzoz emisyonları yapay sinir ağları (YSA) ile modellenmiştir. Deneysel çalışmalarda; tek silindirli bir Diesel motoru kullanılmıştır. Sunulan YSA modelinde; Scaled Conjugate Gradient ve Levenberg–Marquardt algoritmaları, tek katman ve sigmoid transfer fonksiyonu kullanılmıştır. Girdi katmanı devir sayısı ve karışım oranını içermektedir. Çıktı katmanı ise özgül yakıt tüketimi, efektif verim, NOx emisyonu ve CO emisyonu parametrelerini içermektedir. Ağın performansı için ortalama mutlak yüzde hata (MAPE) değerleri ve ortalama hata kareleri (MSE) hesaplanmıştır. Geliştirilen YSA modelin, deneysel sonuçlarla uyum içinde olduğu görülmüştür.

Anahtar Kelimeler

• Diesel motorlar,Yapay sinir ağları,Motor performansı ve egzoz emisyonları

Prediction of engine performance and exhaust emissions using artificial neural network in a compression ignition engine fueled with butanol-diesel fuel

Abstract

In this study, engine performance and exhaust emission of a Diesel engine (CI) at full load and various speeds conditions using only Diesel fuel and five different blends with butanol (3, 6, 9, 12 and 15 v/v %) were modeled by using Artificial Neural Network (ANN). A single-cylinder diesel engine was used in the experimental studies. Single layer, logistic sigmoid transfer function Scaled Conjugate Gradient and Levenberg–Marquardt algorithms were used in the presented ANN model. Input layer includes engine speed and blending ratio. Output layer includes parameters of brake specific fuel consumption, effective efficiency, NOx emission and CO emission. Mean absolute percentage error (MAPE) data and mean square error (MSE) and were calculated for performance of the networks. It was obtained that there was a consistency among the presented ANN model and the data obtained from experiments.

Keywords

• Diesel engines,Artificial neural networks,Engine performance and exhaust emissions

Kaynakça

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