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research-article

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

[+] Author and Article Information
Youngsun Nam

Graduate and Research Assistants
nys@hyundai.com

Inyoung Jang

Graduate and Research Assistants
iyjang@snu.ac.kr

Cheongyo Bahk

Undergraduate Research Assistant
stylick@snu.ac.kr

Dongjun Lee

Associate Professor, Interactive & Networked Robotics Laboratory, Department of Mechanical & Aerospace Engineering, Seoul National University, Seoul, 08826, Republic of Korea
djlee@snu.ac.kr

Jaehyun Kim

Graduate Research Assistant
jjaeh13@gmail.com

Han Ho Song

Associate Professor, Advanced Energy System Laboratory, Department of Mechanical & Aerospace Engineering, Seoul National University, Seoul, 08826, Republic of Korea
hhsong@snu.ac.kr

1Corresponding author.

ASME doi:10.1115/1.4039210 History: Received April 16, 2017; Revised January 21, 2018

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, 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, 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.

Copyright (c) 2018 by ASME
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