Modeling, Estimation, and Control of HCCI Engine With In-Cylinder Pressure Sensing

Abstract

We propose a novel modeling, estimation, and control framework for homogeneous charge compression ignition (HCCI) engines, which, by utilizing direct in-cylinder pressure sensing, can detect, and react to, the wide spectrum of combustion, thereby allowing for the prevention or even recovery from partial burn or misfire, while significantly improving the stability of transition control. For this, we first develop a discrete-time cyclic control-oriented model of the HCCI process, for which we completely replace the Arrhenius integral by quantities based on the in-cylinder pressure sensing. We then propose a nonlinear state feedback control based on the exact feedback linearization and the switching linear quadratic regulators (LQRs), and also present how the state and other quantities necessary for this control can be estimated by using the in-cylinder pressure sensing. We also provide a new modeling approach for heat transfer, which, through principal component analysis (PCA), can systematically allow us to choose most significant variables, thereby substantially improving control and estimation precision. Simulation studies using a continuous-time detailed HCCI engine model built on matlab/simulink and Cantera Toolbox are also performed to demonstrate the efficacy of our proposed framework for the scenarios of engine load transition and partial burn recovery with the enlarged regions-of-attraction with less stringent actuation limitation also shown.