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research-article

Estimation of Intake Oxygen Concentration Using a Dynamic Correction State with EKF for Light-duty Diesel Engines

[+] Author and Article Information
Kyunghan Min

Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea
sturm@hanyang.ac.kr

Jaewook Shin

Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea
jaeuk321@gmail.com

Donghyuk Jung

Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea
dh1776@naver.com

Manbae Han

Department of Mechanical and Automotive Engineering, Keimyung University, 1095 Dalgubeol-daero, Daegu 42601, South Korea
mbhan2002@kmu.ac.kr

Myoungho Sunwoo

Professor, Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, South Korea
msunwoo@hanyang.ac.kr

1Corresponding author.

ASME doi:10.1115/1.4037390 History: Received November 22, 2016; Revised July 21, 2017

Abstract

An accurate estimating the intake oxygen concentration (IOC) is a prerequisite to develop the optimal control strategy because it directly affects the combustion and emissions. Since the IOC is determined based on the mass conservation law in the intake manifold, estimating the mass flow rate of the exhaust gas recirculation (EGR) is most critical. However, to estimate the EGR mass flow rate the conventional orifice valve model causes extrapolation error or inaccurate estimation results under transient operating conditions. In order to improve the estimation performance, this study proposes a correction algorithm for estimating IOC. A dynamic correction state is determined for the orifice valve model. In addition, the intake pressure dynamics is also derived based on the energy conservation law in the intake manifold. Using these dynamic models, a nonlinear parameter varying model is determined and an extended Kalman filter is applied to derive the value of correction state. Furthermore, unmeasurable physical states of the nonlinear parameter varying model are estimated from an air system model that only requires the engine equipped sensors of mass production engines. The correction algorithm is validated through the engine experiments that clearly demonstrate high accuracy of the IOC estimation during transient conditions, which may apply for the vehicle application.

Copyright (c) 2017 by ASME
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