Feedforward Model Predictive Control of Fuel-Air Ratio for Lean-Burn Spark-Ignition Gasoline Engines of Passenger Cars

Abstract

Precise fuel-air ratio (FAR) control on transient conditions is one of the key technologies for lean-burn spark-ignition (SI) engines. To improve fuel economy and reduce emissions, lean-burn engines must regulate their FAR immediately under different operating conditions. The precision of FAR control is limited by the large time-varying feedback delay which is caused by mixture combustion, exhaust gas transport, and lean $N{O_{x}}$ trap (LNT) module. Hence, a FAR predictive controller is proposed to track the desired FAR value precisely in the control framework of feedforward and feedback control. First of all, a feedforward predictive model for the FAR in the cylinder and a feedback predictive model for the FAR in the exhaust pipe with a time-delay characteristic are built respectively. Next, the FAR tracking requirement and the physical actuator constraints are transformed into the optimization objective function. Finally, a feedback/embedded feedforward predictive controller is designed, and the optimization problems are solved online to obtain the fuel injection quality. The simulation results based on GT-POWER illustrate that the proposed predictive control algorithm with feedforward predictive control can track the dynamic FAR precisely in a wide range. Meanwhile, the feedback controller decreases the effects of time delay and parameters uncertainty on the system dynamics.