Linearized Neural Predictive Control A Turbocharged SI Engine Application

Nowadays, (engine) downsizing using turbocharging appears as a major way for reducing fuel consumption. With this aim in view, the air actuators (throttle, Turbo WasteGate) control is needed for an efficient engine torque control especially to reduce pumping losses and to increase efficiency. This work proposes Nonlinear Model Predictive Control (NMPC) of the air actuators for turbocharged SI engines where the predictions are achieved by a neural model. The results obtained from a test bench of a Smart MCC engine show the real time applicability of the proposed method based on on-line linearization and the good control performances (good tracking, no overshoot) for various engine speeds.