Nonlinear model predictive control of lean NOx trap regenerations

This paper describes a diesel engine lean NO_x trap (LNT) regeneration control system using a nonlinear model predictive control (NMPC) technique. A two-level NMPC architecture is proposed for the LNT regenerations. The control objective is to minimize the fuel penalty caused by LNT regenerations while keeping the tailpipe NOx emissions amount under the regulation level. A physically-based and experimentally-validated nonlinear LNT dynamic model was employed to construct the NMPC control algorithms. The NMPC control system was evaluated on a vehicle simulator, cX-Emissions, with a 1.9L diesel engine model through the FTP75 driving cycle. Compared with a conventional LNT control strategy, 26.6% of fuel penalty reduction was observed during a single regeneration event, and 36.4% fuel penalty reduction was achieved for an entire FTP75 test cycle.