Prediction of engine performance, combustion and emission for canola oil biodiesel blends using artificial neural network

Year 2019, Volume: 7 Issue: 3, 2045 - 2056, 31.07.2019

Mehmet Şen

https://doi.org/10.29130/dubited.551230

Cited By: 2

Abstract

In this study, the results of emission, performance and combustion
experimental data of diesel fuel and canola oil biodiesel blends used in a
diesel engine and the results of the model created by artificial neural
networks were compared. For construct the model 44 different engine test
results were used. The feedback algorithm was used in the training of the
network. The trainlm was selected as the learning algorithm. The logsig function
was used in the hidden layer while the purelin function was used in the output
layer. The input variables in network training were fuel blend ratios, engine
speeds and engine loads. At the output of network a separate model was created
for each of the specific fuel consumption, exhaust temperature, combustion
efficiency, start of injection, start of combustion, ignition delay, combustion
duration, smoke opacity and NO_x values. The R² values of
the ANN models were calculated to be higher than 0.99 for the performance and
combustion parameters and higher than 0.98 for the emissions value.

Keywords

Keywords: ANN, emission, combustion, performance

Yapay Sinir Ağı Kullanarak Kanola Yağı Biyodizel Karışımları İçin Motor Performansı, Yanma ve Emisyon Tahmini

Abstract

Bu
çalışmada bir dizel motorda kullanılan dizel yakıtı ve kanola yağından üretilen
biyodizel karışımlarının; emisyon, performans ve yanma deneysel verileri ile
yapay sinir ağları ile oluşturulan modelin sonuçları karşılaştırılmıştır.
Modelin oluşturulması için 44 farklı motor deney sonuçları kullanılmıştır. Ağın
eğitiminde geri beslemeli algoritma kullanılmıştır. Öğrenme algoritması olarak
trainlm, gizli katmanda logsig ve çıkış katmanında ise purelin fonksiyonları
kullanılmıştır. Ağ eğitiminde
giriş değişkenleri: karışımdaki dizel yakıt oranı, kanola yağı biyodizel oranı,
motor devri ve motor momentidir. Çıkışta ise özgül yakıt tüketimi (ÖYT), egzoz
sıcaklığı, yanma verimi, püskürtme başlangıcı, yanma başlangıcı, tutuşma
gecikmesi, yanma süresi, duman koyuluğu ve NOx değerlerinin her biri için ayrı
model oluşturulmuştur. YSA modellerinin R² değerleri tutuşma
gecikmesi için 0,998, yanma süresi için 0,992, duman koyuluğu için 0,984, NOx
için ise 0,990 olarak hesaplanmıştır. R² değerleri ÖYT, egzoz
sıcaklığı, yanma verimi, püskürtme başlangıcı ve yanma başlangıcı değerleri
için ise 0,999‘dan yüksek bulunmuştur.

Keywords

YSA, emisyon, yanma, performans

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