A Control Algorithm for Low Pressure - EGR Systems Using a Smith Predictor with Intake Oxygen Sensor Feedback

Low-pressure cooled EGR (LP-cEGR) systems can provide significant improvements in spark-ignition engine efficiency and knock resistance. However, open-loop control of these systems is challenging due to low pressure differentials and the presence of pulsating flow at the EGR valve. This research describes a control structure for Low-pressure cooled EGR systems using closed loop feedback control along with internal model control. A Smith Predictor based PID controller is utilized in combination with an intake oxygen sensor for feedback control of EGR fraction. Gas transport delays are considered as dead-time delays and a Smith Predictor is one of the conventional methods to address stability concerns of such systems. However, this approach requires a plant model of the air-path from the EGR valve to the sensor. An open loop EGR mass flow model as well as a simplified plug flow based transport model are utilized to predict EGR fraction at different locations in the air system upstream of the intake oxygen sensor. A turbocharged gasoline spark ignition engine with a low-pressure EGR system is used for algorithm validation. The control algorithm is implemented and tested in real-time using a rapid prototype control system. Experiments consisting of step changes in EGR fraction are performed at steady state engine operating conditions. A clear improvement in control stability and accuracy was observed with the Smith Predictor control over a conventional PID controller.