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.