Study of CWS/Diesel Dual Fuel Engine Emissions by Means of RBF Neural Network

In order to study and improve the emission performance of WCS/diesel DFE, an emission model for DFE based on radial basis function neural network was developed which was a black-box input-output training data model not require priori knowledge .Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. And the effect of the DFE main performance parameters , such as rotation speed ,load, pilot quantity and injection timing ,were also predicted by means of this model. An emission predict model for WCS/diesel DFE based RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx ,Smoke emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value,although it still has some limitations ,because of its high dependence on the quantity of the experimental sample data.