Model predictive air path control for a two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation

Innovative air path concepts for turbocharged spark-ignition engines with exhaust gas recirculation impose high demands on the control due to nonlinearities and cross-couplings. This contribution investigates the control of the air and exhaust gas recirculation paths of a two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation. Using exhaust gas recirculation at high loads, the in-cylinder temperature can be lowered, reducing the knock tendency, while at the same time preventing the need for the enrichment of the air/fuel ratio. Air and exhaust gas recirculation paths are cross-coupled and show different delay times. To tackle these challenges, a data-based two-stage model predictive controller is proposed: The target selector accounts for the overactuated system structure, while the dynamic controller adjusts the charging pressure and exhaust gas recirculation rate. The prediction model setup is based on a small amount of dyno-run measurement data. To ensure real-time capability, the model is kept as simple as possible. This allows for fast turnaround times of the algorithm, while maintaining the necessary accuracy in steady-state and transient operation. This study focuses on a two-stage control concept based on a target selector for optimal stationary control inputs and the dynamic controller considering the dynamic behavior of the air and exhaust gas recirculation paths. Subsequently, the control concept for the two-stage turbocharged spark-ignition engine with low pressure exhaust gas recirculation is validated via experimental tests under real-driving conditions on an automotive test track, using a prototype test vehicle. Results show that boost pressure as well as exhaust gas recirculation rate setpoints are met without overshoot and control deviation with settling times being close to the boundaries set by the hardware.