Real-time Air/Fuel Ratio Model Predictive Control of a Spark Ignition Engine

The following paper describes the control of air/fuel ratio (AFR) of a spark ignition engine utilizing the analytical model predictive controller based on the multi-model approach. The multi-model approach employs the autoregressive model (ARX) network, using the weighting of local models, coming from the sugeno-type fuzzy logic. The weighted ARX models are identified in the particular working points and are creating a global engine model, covering its nonlinearity. Awaited improvement of a proper air/fuel mixture combusted in a cylinder is mostly gained in the transient working regimes of an engine. In these regimes, the traditional control approach looses its quality, compared to steady state working regimes of an engine. This leads to higher fuel consumption and level of emissions from an engine. Presented results of the air/fuel ratio control are acquired from the real-time control of the VW Polo 1390 ccm engine, at which the original electronic control unit (ECU) has been replaced by a dSpace system executing the model predictive controller. It has been proven, that the proposed controller is suitable for the air/fuel ratio control giving sufficiently good and steady system output.