Application of ANN to Predict S.I. Engine Performance and Emission Characteristics Fuelled Bioethanol

1024x768 The performance of artificial neural network (ANN) to predict spark ignition (S.I) engine performance such as torque, BSFC, exhaust temperature and emissions (CO and HC) for various compression ratios was investigated. For training and testing the ANN, experimental data from a single cylinder Hydra spark ignition engine powered by various bioethanol and gasoline blends (E0, E10, E20, E40 and E60) were used. ANN performance was measured by mean squared errors and correlation coefficient. The training function used was trainbr and the training algorithm used was feed-forward back propagation. The overall correlation coefficient obtained from the prediction was 0.98526 and the mean squared error obtained was very low (9.26 E-06). Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}