Abstract
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.
Highlights
The world is presently confronted with a twin crisis of fossil fuel depletion and environmental degradation
In a study carried out by Alonso et al [18], Artificial Neural Networks (ANNs) were employed as predicting tools for prediction of brake specific fuel consumption (BSFC), NOx, and carbon monoxide (CO) emissions
Load percentage, compression ratio, blend percentage, injection timing, and injection pressure were taken as the input parameters and brake thermal efficiency, brake specific energy consumption, exhaust gas temperature and engine emissions NOx, smoke, and CO and unburnt hydrocarbon (UBHC) were used as the output parameters
Summary
The world is presently confronted with a twin crisis of fossil fuel depletion and environmental degradation. 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 [1,2,3]. The biodiesel produced from vegetable oil or animal fat is usually more expensive than petroleum-based diesel fuel from 10 to 50%. Manufacturers and engine application engineers usually want to know the performance of a C.I engine for various proportions of blends, for various compression ratios, and at different injection timings and injection pressures This requirement can be met either by conducting comprehensive tests or by modeling the engine operation. Single cylinder, water cooled, and constant speed diesel engine
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