Buji ile ateşlemeli bir motorun ideal hava-yakıt çevrim analizi ile performans hesabı

Bilgisayar teknolojisindeki gelişmelere paralel olarak içten yanmalı motorların tasarımında teorik modellerin kullanılması ile farklı çalışma ve tasarım parametrelerinin motor performansına etkileri ve gerçek bir motorun performans karakteristikleri daha az maliyetle ve daha kısa sürede tahmin edilebilmektedir. Bu çalışmada, tek silindirli, 4-zamanlı, doğal emişli buji ile ateşlemeli bir motorun ideal hava-yakıt çevrim analizini incelemek üzere matematiksel bir simülasyon modeli geliştirilmiştir. FORTRAN programlama dilinde yazılmış bir bilgisayar programı yardımıyla farklı sıkıştırma oranı, motor hızı ve hava fazlalık katsayıları (HFK) için krank mili açısı (KMA)'na bağlı olarak silindir basınç ve sıcaklık değişimleri elde edilerek ortalama indike basınç,- yakıt ve hava tüketimi, indike güç, termik verim gibi motor performans parametreleri hesaplanmıştır. Nümerik hesap metodunda yakıt olarak izo-Oktan ($C_8H_{18}$) kullanılmış olup, ($C_8H_{18}$) ve türlere ait iç enerji ve özgül ısılar ile ayrışma denge sabitlerinin hesabı sıcaklığa bağlı amprik fonksiyonlarla gerçekleştirilmiştir. Yanma ve egzoz proseslerinin sabit hacimde ve sıkıştırma, yanma ve genişleme proseslerinin ise adyabatik olarak gerçekleştiği kabul edilmiştir. Sonuç olarak, matematiksel modellerin içten yanmalı motorlarda performans karakteristiklerinin belirlenmesinde uygun bir metot olarak kullanılabilmektedir.Depending on the development in computer technologies by using theoretical models in the design of internal combustion engines, the effects of different operating and design parameters on engine performance and performance characteristics of a real engine can be estimated with shorter time and lower cost. In this study, a mathematical simulation model is developed to investigate ideal air-fuel cycle analysis of a single cylinder, four-stroke and natural aspirated spark ignition engine. Obtained the variations of cylinder temperature and pressure with crankshaft angle (CA) depending on different compression ratio, engine speed and air excess coefficient (AEC), engine performance parameters such as indicated mean effective pressure, fuel and air consumptions, indicated power, thermal efficiency were calculated using computer program written in FORTRAN. Iso-Octane ($C_8H_{18}$) is used as a fuel in the numerical calculation method, and calculation of internal energy and specific heats belong to ($C_8H_{18}$) and species and calculation of considered two basic dissociation equilibrium constants were determined as the empiric functions of temperature. It is assumed that combustion and exhaust processes are done at constant volume and compression, combustion and expansion processes are adiabatic. With these results, it is believed that the mathematical model can be used for determination of engine performance characteristics as an appropriate method in internal combustion engines

The investigation of the effect of injection pressure and maximum fuel quantity on engine performance and smoke emissions in diesel engines

Yakıt enjeksiyon basıncı ve maksimum yakıt miktarı dizel motorlarında performans ve emisyonları etkileyen önemli çalışma parametrelerindendir. Bu çalışmada, 4 zamanlı, tek silindirli ve direkt enjeksiyonlu bir dizel motorunda enjeksiyon basıncı ve maksimum yakıt miktarının performans ve duman emisyonlarına etkileri deneysel olarak araştırılmıştır. Farklı enjeksiyon basıncı ve maksimum yakıt miktarı için motor hızına bağlı olarak, moment, motor gücü, özgül yakıt tüketimi ve duman emisyonları belirlenmiştir. Enjeksiyon basıncının artması ile moment ve güçte bir miktar artış, yakıt ekonomisinde iyileşme ve duman emisyonlarında azalma gözlenmiştir. Ancak, enjeksiyon basıncının belirli bir değerden daha fazla artırılması motor performansını olumsuz etkilemektedir. Maksimum yakıt miktarının artışı moment ve güçte artış sağlarken duman emisyonlarını ve özgül yakıt tüketimini artırmaktadır. Maksimum yakıt miktarının %75 artışı duman koyuluğunu oldukça fazla artırmakta ve tüm motor hızları için sınır değerin üzerine çıkılmaktadır.Fuel injection pressure and maximum fuel quantity are significant operating parameters affecting the performance and emissions in diesel engines. In this experimental study, the effects of injection pressure and maximum fuel quantity on engine performance and smoke emissions were investigated in a four-stroke, single cylinder direct injection diesel engine. Engine torque, engine power, specific fuel consumption and smoke emissions depending on engine speed for various injection pressure and maximum fuel quantity were determined. It was obtained that increasing the injection pressure slightly increases the torque, power and fuel economy and reduces smoke emissions. On the other hand, decreasing the injection pressure causes some reduction in engine performance and increases smoke emissions. However, increasing the injection pressure to a value higher than a certain value may contribute adverse effect on engine performance in diesel engine. Increasing maximum fuel quantity increases in torque and power while it causes increasing in smoke emissions and specific fuel consumption. Also, smoke limit was exceeded by operating excessive fuel quantity of %75 for all engine speeds

Prediction of Performance and Smoke Emission Using Artificial Neural Network in a Diesel Engine

The fuel injection pressure is one of the significant operating parameters affects atomization of fuel and mixture formation; therefore, it determines the performance and emissions of a diesel engine. Increasing the fuel injection pressure decrease the particle diameter and caused the diesel fuel spray to vaporize quickly. However, with decreasing fuel particles their inertia will also decrease and for this reason fuel can not penetrate deeply into the combustion chamber. In this study, artificial neural-networks (ANNs) are used to determine the effects of injection pressure on smoke emissions and engine performance in a diesel engine. Experimental studies were used to obtain training and test data. Injection pressure was changed from 100bar to 300bar in experiment (standard injection pressure of test engine is 150bar). Injection pressure and engine speed have been used as the input layer; smoke emission, engine torque and specific fuel consumption have been used as the output layer. Two different training algorithms were studied. The best results were obtained from Levenberg-Marquardt (LM) and Scaled Conjugate gradient (SCG) algorithms with 11 neurons. However, The LM algorithm is faster than the SCG algorithm, and its error values are smaller than those of the SCGs. For the torque with LM algorithm, fraction of variance (R2) and mean absolute percentage error (MAPE) were found to be 0.9927 and 7.2108%, respectively. Similarly, for the specific fuel consumption (SFC), R2 and MAPE were calculated as 0.9872 and 6.0261%, respectively. For the torque with SCG algorithm, R2 and MAPE were found to be 0.9879 and 9.0026%, respectively. Similarly, for the specific fuel consumption (SFC), R2 and MAPE were calculated as 0.9793 and 8.7974%, respectively. So, these ANN predicted results can be considered within acceptable limits and the results show good agreement between predicted and experimental values