Stochastic air-fuel ratio MPC of spark ignition engines

Abstract

The problem of the stochastic model predictive control (MPC) of the air-fuel ratio is considered in this paper. A discrete-time dynamic model with residual gas fraction (RGF) which contains the dynamic equations of the air path and the fuel path is established. By the MPC theory of the Markovian jump linear systems, a stochastic model predictive controller is designed based on the dynamic model. Two results can be obtained from the numerical simulation: firstly, the performance of the stochastic model predictive controller is better than the one of the open-loop controller. Secondly, the stochastic model predictive controller with longer state horizon and control horizon has better performance than the one with shorter state horizon and control horizon.