The Application of RBF Neural Networks Soft-Measurement Technology in the CO Exhaust Emission of the Gasoline Engine

摘要：

It is difficult to immediately measure the CO emission of gasoline engine. The prospect of applying for neural network technique in the gasoline engine is discussed in this paper. The concept of neural network soft-measurement is advanced and the neural network control model of CO emission in the gasoline engine is also established. The neural network model is trained based on MATLAB software. The training results show that this model can measure the CO emission without the instruments, and can immediately control the CO emission.

关键词： Gasoline engine Emission Soft-measurement Neural network

作者: Huanchun Gong Yihu Wu

作者单位: Institute of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, 410076

会议类型: 国际会议

会议名称: 2007杭州国际动力工程会议(The International Conference on Power Engineering 2007)

会议地点: 杭州

会议语种:英文

在线出版日期: 2007-10-23（万方平台首次上网日期，不代表论文的发表时间）