Air-Fuel-Ratio Control in a Spark-Ignition LPG Engine Using Grey Forecasting Model

In this paper, the application of grey forecasting control in a Liquefied Petroleum Gas (LPG) engine is presented. In order to meet increasingly stringent automotive exhaust emissions regulations, many innovative control methods and optimization strategies of a LPG engine have to be explored and applied. A LPG engine can be assumed as a grey system because of its incomplete information and nonlinear properties. Using the signal of an exhaust gas oxygen sensor, we establish a grey model which can predict the next state of air-fuel-ratio. The predicted value is compared with the scheduled target. According to the decination, the anticipatory control of the intake LPG is implemented. Unlike the conventional control algorithm, the model parameters of grey forecasting control are continuously updated. In consequence, it can adapt the change of conditions when the ageing effect or malfunction occurs in a LPG engine. The control performance can be sustained.

The software design of grey forecasting control is also introduced in this paper. In order to achieve better control effect, a high speed single-chip RISC microcomputer is used. The grey forecasting control algorithm is developed on a 1.46-liter 4-cylinder spark-ignition LPG engine. The experimental results show that the algorithm of grey forecasting control can improve the engine performance.