%0 Journal Article
%T Radial-Basis-Function-Network-Based Prediction of Performance and Emission Characteristics in a Bio Diesel Engine Run on WCO Ester
%A Shiva Kumar
%A P. Srinivasa Pai
%A B. R. Shrinivasa Rao
%J Advances in Artificial Intelligence
%D 2012
%I Hindawi Publishing Corporation
%R 10.1155/2012/610487
%X Radial basis function neural networks (RBFNNs), which is a relatively new class of neural networks, have been investigated for their applicability for prediction of performance and emission characteristics of a diesel engine fuelled with waste cooking oil (WCO). The RBF networks were trained using the experimental data, where in load percentage, compression ratio, blend percentage, injection timing, and injection pressure were taken as the input parameters, and brake thermal efficiency (BTE), brake specific energy consumption (BSEC), exhaust gas temperature ( ), and engine emissions were used as the output parameters. The number of RBF centers was selected randomly. The network was initially trained using variable width values for the RBF units using a heuristic and then was trained by using fixed width values. Studies showed that RBFNN predicted results matched well with the experimental results over a wide range of operating conditions. Prediction accuracy for all the output parameters was above 90% in case of performance parameters and above 70% in case of emission parameters. 1. Introduction The world is presently confronted with a twin crisis of fossil fuel depletion and environmental degradation. Indiscriminate extraction and lavish consumption of fossil fuels have led to a reduction in underground-based carbon resources. The search for an alternative fuel which promises a harmonious correlation with the sustainable development, energy conservation, and management has become highly pronounced in the present context. The fuels of bio-origin like vegetable oils can provide a feasible solution to this crisis. The energy density, cetane number, and heat of vaporization of vegetable oils are comparable to diesel values. It is renewable, available everywhere, and has proved to be a cleaner fuel and more environment friendly than the fossil fuels [1¨C3]. Also from the literature, it is revealed that the emissions from the biodiesel engines are comparatively lesser from the engines with the petroleum-based fuels [4¨C6]. But the higher viscosity of vegetable oils affects the flow properties of fuel such as spray, atomization, and consequent vaporization and air fuel mixing. Heating and blending of vegetable oils may reduce the viscosity and improve the volatility of the vegetable oils, but its molecular structure remains unchanged. Literature survey revealed that converting vegetable oils into methyl esters will overcome all problems related with vegetable oils [7, 8]. However, high cost of biodiesel is the major obstacle for its commercialization. The
%U http://www.hindawi.com/journals/aai/2012/610487/