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An Artificial Neural Network Model for a Diesel Engine Fuelled with Mahua Biodiesel

  • N. Acharya
  • S. Acharya
  • S. Panda
  • P. Nanda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 556)

Abstract

In this paper, an Artificial Neural Network (ANN) model is used to predict the different parameters of a diesel engine fuelled with the mixture of diesel and mahua biodiesel in different proportion. The data has been obtained from an experiment carried out in a twin cylinder diesel engine in different loading condition and different blending ratios of diesel and biodiesel. Two input data, i.e., engine load and blending ratio and five output data, i.e., Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC), Smoke level, Carbon monoxide (CO), and Nitrogen Oxides (NOx) emissions have been considered for ANN modeling. The network used is back propagation, feed forward with multilayer perceptron having ten numbers of neurons in hidden layer with trainlm training algorithm being proposed. It has been observed that the prediction ability of the model is high as there is minimum difference between the predicted and the experimentally measured values.

Keywords

Vegetable oil Transesterification Biodiesel Viscosity ANN 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Excavation DepartmentM.C.LBurlaIndia
  2. 2.Department of Computer ApplicationVSSUTBurlaIndia
  3. 3.Department of Mechanical EngineeringVSSUTBurlaIndia

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