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This paper investigates the performance, emission and combustion of a four cylinder common-rail turbocharged diesel engine using jatropha curcas biodiesel blends (JCB). The test was performed with various ratios of jatropha curcas methyl ester (JCME) in the blends (JCB10, JCB20, JCB30, and JCB50). An artificial neural networks (ANN) model based on standard back-propagation algorithm was used to predict combustion, performance and emissions characteristics of the engine using MATLAB. To acquire data for training and testing of the proposed ANN, the different engine speeds (1500-3500 rpm) was selected as the input parameter, whereas combustion, performance and emissions were chosen as the output parameters for ANN modeling of a common-rail turbocharged diesel engine. The performance, emissions and combustion of the ANN were validated by comparing the prediction dataset with the experimental results.

Nowadays, engine problems such as higher NOx, increase in smoke content and low brake power output due to biofuel fueled engine have been reduced by several improvements by using additives or modifications on engine itself. This paper presents a type of compositions and proper combination of selected chemical components which may be used in palm olein-diesel blends namely “Envo-Diesel”. The blended component was designed as an additive package which was blended with diesel-biofuel at 99:1 up to 95:5 percent ratios. Blended fuels with additive have been used in the single cylinder engine which operated under 2000 rpm for 100 hours. Engine performance and emissions tests were conducted as well as engine deposit analysis was done after 100 hours engine operation time.