Performance analysis of a turbocharged diesel engine using biodiesel with back propagation artificial neural network
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Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
SILA SCIENCE
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
This paper determines, using artificial neural network (ANN), performance of a turbocharged diesel engine using biodiesel produced from cotton and rapeseed oils through transesterification. To acquire data for training and testing of the proposed ANN, a three-cylinder, four-stroke test engine was fuelled with biodiesel-eurodiesel blended fuels with various percentages of biodiesel (B2, B5%), and operated at different engine speeds and loads. Backpropagation algorithms for the engine was developed using some of the experimental data for training. The performance of the ANN was validated by comparing the prediction dataset with the experimental results.It was observed that the ANN model can predict the engine performance quite well with correlation coefficient (R) 0.99, 0.98, 0.92 and 0.98 for the engine power, the engine torque, the specific fuel consumption (SFC) and exhaust gas temperature, respectively. The prediction MSE (Mean Square Error) error was between the desired outputs as measured values and the simulated values were obtained as 0.0004 by the model.
Description
Keywords
Biodiesel, Diesel engine, Engine performance, Exhaust emission
Journal or Series
ENERGY EDUCATION SCIENCE AND TECHNOLOGY PART A-ENERGY SCIENCE AND RESEARCH
WoS Q Value
N/A
Scopus Q Value
N/A
Volume
28
Issue
1
