Nonlinear Model Predictive Control of a Variable Valve Timing System in a Turbocharged Spark Ignition Engine

This paper presents a practical demonstration of Nonlinear Model Predictive Control (NMPC) applied to the variable valve timing system of a 1 liter gasoline direct injection turbocharged engine over a transient maneuver. The nonlinear dynamic model utilized in the NMPC controller is a Takagi-Sugeno Neuro-Fuzzy model. The control problem has been formulated as a two-input-two-output multivariable control system with intake valve phase and exhaust valve phase angles as the two manipulated variables and engine fuel consumption and engine out NOx emissions as the two controlled variables. Two implementation methods were evaluated on the engine. In the first method, the NMPC using a sequential quadratic programming algorithm executed on a PC which was connected to the engine control unit over a controller area network. In the second method, the NMPC using a quasi-newton based optimization algorithm was deployed to and executed on the engine control unit. Results show the potential for >10% improvement in NOx emissions compared to the original engine strategy.