Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7049611 | Applied Thermal Engineering | 2013 | 9 Pages |
Abstract
This study investigates the applicability of adaptive neuro-fuzzy inference system (ANFIS) approach for modelling the performance parameters and exhaust emissions of a diesel engine employing various fuels. In order to gather data for developing the proposed ANFIS model, a single-cylinder direct injection diesel engine was fuelled with diesel fuel, biodiesel and their blends, and steady-state tests were performed by varying the biodiesel content, engine speed and engine load. Then, using experimental data, engine performance parameters, namely engine power, brake specific fuel consumption, brake thermal efficiency, exhaust gas temperature, and emissions of HC, CO and NO were determined. After an ANFIS model for the prediction of the performance parameters and exhaust emissions of the engine was developed using some of the data acquired in the experiments, the model results were compared with experimental ones for determining the accuracy of the ANFIS predictions. It was determined that the predictions usually agreed well with the experimental results with correlation coefficients in the range of 0.940-1.000 and mean relative errors in the range of 1.40-27.40%. The results suggest that the ANFIS approach can be used successfully for predicting the performance and emissions of diesel engines using various fuels.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Fluid Flow and Transfer Processes
Authors
Murat Hosoz, Huseyin Metin Ertunc, Murat Karabektas, Gokhan Ergen,