Stochastic Model Predictive Control Design for Gasoline Engines with EGR

Abstract

This paper presents a stochastic model predictive control (SMPC) design scheme for gasoline engines with exhaust gas recirculation (EGR) by considering the stochastic distribution of indicated mean effective pressure (IMEP) as constraint to avoid abnormal combustion during transient conditions. Firstly, a MPC problem is formulated to minimize the system state tracking error based on a second order state space model. Then, the SMPC problem under stochastic IMEP distribution constraint is formulated. Moreover, in order to make the problem solvable, a scenario-based optimization approach is applied to transform the stochastic optimal control problem into a deterministic optimal control problem. Finally, the deterministic optimal control problem is solved by multi-shooting based sequence quadratic programming (SQP). The simulation validation shows that the proposed SMPC scheme can avoid misfire during the tip put transient condition while guaranteeing the system states tracking performance without depending on the exhaust manifold pressure sensor.