Abstract:

For SI(Spark Ignition) engine AFR(Air-Fuel Ratio) control system, the NMPC(Nonlinear Model Predict Control) method based on the NARX (Nonlinear Auto Regressive model with eXogenous inputs)model is developed. First the algorithm of recursive least squares is used to identify the NARX model. And then use the method of non-linear model to predict control in SI engine. This method has high prediction accuracy, and the optimal control sequence. Thus it improves the SI engine AFR control performance. Finally, the control system is evaluated using a widely used SI engine benchmark model which is Mean engine model by using Matlab, and compared with the PI(Proportional Integral)controller algorithm which current widespread use of car and Volterra model. Simulation results demonstrate the effectiveness of the NARX model based nonlinear model predict control.

Key words: nonlinear auto regressive model with eXogenous inputs(NARX) model, identification of model, nonlinear model predictive control, air-fuel ratio