Nonlinear model predictive control of a GDI engine

A model predictive approach to the control of a GDI engine is presented. Fuzzy Takagi-Sugeno type models are used to predict the future engine behaviour. The optimization algorithm is based on instantaneous linearization of the nonlinear prediction model at the current operating point. Special mode switching strategies are designed to minimize the torque bumps during combustion mode changes. The performance of the controller has been evaluated on the European driving cycle using a dynamic simulation model, including powertrain, chassis and driver´s submodels. Results have been achieved that show the applicability of the approach to the control of GDI engines.