Comparative analysis of various modelling techniques for emission prediction of diesel engine fueled by diesel fuel with nanoparticle additives

Authors : Erdi Tosun, Tayfun Ozgur, Ceyla Ozgur, Mustafa Ozcanli, Hasan Serin, Kadir Aydin

Pages : 15-23

Doi:10.26701/ems.320490

View : 17 | Download : 5

Publication Date : 2017-03-20

Article Type : Research Paper

Abstract :In this study, emissions of compression ignition engine fueled by diesel fuel with nanoparticle  additives  was  modeled  by  regression  analysis,  artificial  neural  network  insert ignore into journalissuearticles values(ANN);  and  adaptive  neuro  fuzzy  inference  system  insert ignore into journalissuearticles values(ANFIS);  methods.  Cetane  number  insert ignore into journalissuearticles values(CN);  and  engine  speed  insert ignore into journalissuearticles values(rpm); were selected as input parameters for estimation of carbon monoxide insert ignore into journalissuearticles values(CO);, oxides of  nitrogen insert ignore into journalissuearticles values(NOx);, and carbon dioxide insert ignore into journalissuearticles values(CO2); emissions. The results of estimation techniques were  compared with each other and they showed that regression analysis was not accurate enough  for prediction. On the other hand, ANN and ANFIS modelling techniques gave more accurate  results with respect to regression analysis; linear and non-linear. Especially ANFIS models can  be suggested as estimation method with minimum error compared to experimental results. 
Keywords : Adaptive neuro fuzzy inference system, Artificial neural network, Diesel engine, Regression analysis