Prediction on Combustion Pattern of CNG-Diesel Duel Fuel Engine Using Response Surface Methodology

Abstract

Application natural gas in dual fuel system is considered to be a potential alternative to conventional fossils fuels for vehicles application due to its lower greenhouse gas emissions and availability. However, the conversion process for duel fuel system is challenging. The main objective for this study is to predict the combustion pattern of Compress Natural Gas (CNG)-Diesel dual fuel engine using Response Surface Methodology (RSM). Two inputs, which are CNG fraction (0%, 10%, 20%, 30% and 40%) and engine speed (1500, 2000, 2500, 3000 and 3500 rpm) were used to predict engine output characteristics based on combustion pattern. The evaluation of combustion characteristic in term of ignition delay (ID), peak in-cylinder pressure (PP), heat release rate (HRR) and combustion duration (CD). 10 numbers of runs was computed using Design Expert software with average error of 0.4%. The surface response analysis showed that the rate of substitution of CNG and its characteristics influence the engine output characteristics significantly. The prediction model for ID was suggested was linear model while PP, HRR and CD was suggested 2FI model. Using a confirmation test, the prediction models were validated and showed good predictability within the 95% confidence interval. Hence, it is concluded that RSM provides prediction models with significant accuracy that predict combustion pattern, contributing to the efficiency of the conversion process for diesel-CNG dual fuel engines.