Biyodizel Yakıt Kullanan İçten Yanmalı Motorlarda Aşınma-Sürtünme Optimizasyonu ve Tahmini için Taguchi ve Yapay Sinir Ağı Uygulaması

Year 2023, Volume: 26 Issue: 4, 1543 - 1553, 01.12.2023

Hüseyin Kahraman , İdris Cesur , Beytullah Eren , Aslan Çoban

https://doi.org/10.2339/politeknik.1216411

Cited By: 1

Abstract

Dünyada ham petrolün azalması nedeniyle alternatif yakıt araştırmaları her geçen gün artmaktadır. Dizel motorlarda petrole alternatif yakıt kullanılmasının diğer bir amacıda çevreye daha az kirletici emisyon salmasıdır. Alternatif yakıtlarda dışarıya temiz emisyon salmasına karşın aynı zamanda motor veriminin de yüksek olması istenmektedir. Dizel motorlarında dizel yakıtına alternatif en iyi yakıt biyodizellerdir. Ayrıca motorlarda verim kaybının azaltılması segman-silinidir çifti arasındaki sürtünme ve aşınma miktarını azaltılması ile olmaktadır. Bu çalışmada; dizel motorlarda alternatif yakıt olarak yaygın kullanılan biyodizel yakıtının segman-silindir çifti arasındaki sürtünme ve aşınma davranışları dizel yakıtına göre karşılaştırılmıştır. Yapılan çalışma üç aşamadan oluşmaktadır. Çalışmanın birinci aşamasında Taguchi yöntemi kullanılarak sürtünme ve aşınma karakteristiklerinin optimum şartları verren deney parametreleri belirlenmiştir. İkinci aşamada, deneysel çalışma yapılarak dizel ve biyodizel yakıtının tribolojik özellikleri incelenmiştir. Çalışmanın son aşamasında ise segman-silindir çifti arasında oluşan aşınma mekanizması yapay sinir ağları (YSA) ile modellenmiştir. Yapılan çalışma ile; biyodizelin dizel yakıtına göre sürtünme katsayısının daha düşük olması ve bu nedenle aşınma miktarının daha düşük olduğu saptanmıştır. Aşınma miktarları karşılaştırıldığında optimum şartlar; biyodizel yakıtı, 150d/d ve 40 N yük altında elde edilmiştir. Deney sonuçlar YSA model ile tahmin edilmiştir. Bu sayede deney sayıları azaltılarak segman-silindir çifti arasındaki tribolojik özellikler incelenebilecektir.

Keywords

İçten yanmalı motorlar, biyodizel, aşınma, Taguchi yöntemi, yapay sinir ağları

An Artificial Neural Network and Taguchi Approach to the Optimization of Wear and Friction for Biodiesel Fuel

Abstract

Alternative fuel researches are increasing day by day due to the decrease in crude oil in the world. Another purpose of using alternative fuel to petroleum in diesel engines is to release fewer polluting emissions to the environment. Although it releases clean emissions in alternative fuels, it is also desirable to have high engine efficiency. Biodiesel is the best alternative to diesel fuel in diesel engines. In addition, the reduction of efficiency loss in engines is achieved by reducing the amount of friction and wear between the ring-cylinder couple. In this study; The friction and wear behavior of biodiesel fuel, which is widely used as an alternative fuel in diesel engines, between the ring-cylinder couple was compared with diesel fuel. The study consists of three stages; In the first stage of the study, the experimental parameters that give the optimum conditions of friction and wear characteristics were determined by using the Taguchi method. In the second stage, the tribological properties of diesel and biodiesel fuel were investigated by conducting an experimental study. In the last stage of the study, the wear mechanism between the ring-cylinder pair was modeled with artificial neural networks (ANN). With the work done; It has been determined that the friction coefficient of biodiesel is lower than diesel fuel and therefore the amount of wear is lower. Optimum conditions when the amount of wear is compared; biodiesel fuel was obtained under 150 rpm and 40 N load. Experimental results were predicted by the developed ANN model. In this way, the tribological properties between the ring-cylinder pair can be examined by reducing the number of experiments.

Keywords

Internal combustion engines, biodiesel, wear on engines, Taguchi method, artificial neural networks

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