BP和RBF神经网络在辨识内燃机燃烧过程中的应用

Identification of Diesel Combustion Process by BP and RBF Neural Network

分析了发动机燃烧过程的研究方式,提出了用BP和RBF网络辨识内燃机燃烧过程的方法。选定神经网络的结构、隐层神经元的作用函数和控制参数,成功地得到了发动机的辨识模型,结果由RBF网络辨识的模型给出,从这一模型可以获得任意点缸内压力和温度以延拓的参数,为排放分析、计算和结构优化提供了良好的基础。

This paper analyzes the study methods of engine combustion processes and tries to set up the ways identified by BP and RFB neural networks for diesel burning work. The structure, the functions of neural element in hidden layers and parameters are chosen and an identification model is get. The result is given out by the identified model of RBF, which can present the pressure and temperature at any crank angle and expanding parameters, to provide well base for emission analysis and calculation and the optimum of engine structure.