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Research Papers

Estimation of Intake Oxygen Concentration Using a Dynamic Correction State With Extended Kalman Filter 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
e-mail: sturm@hanyang.ac.kr

Jaewook Shin

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

Donghyuk Jung

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

Manbae Han

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

Myoungho Sunwoo

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

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 22, 2016; final manuscript received July 21, 2017; published online September 8, 2017. Assoc. Editor: Ryozo Nagamune.

J. Dyn. Sys., Meas., Control 140(1), 011013 (Sep 08, 2017) (15 pages) Paper No: DS-16-1567; doi: 10.1115/1.4037390 History: Received November 22, 2016; Revised July 21, 2017

An accurate estimation of 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 (EKF) 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.

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Figures

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Fig. 1

Correlation between NOx emissions and the control indicators

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Fig. 2

Modeling error of the effective area for the EGR mass flow model

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Fig. 3

Experimental apparatus

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Fig. 4

Engine schematic and measurement configuration

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Fig. 5

Model structure of the air system

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Fig. 6

Engine operating conditions for the air system model

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Fig. 7

Modeling results about the empirical models

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Fig. 8

Overall structure of the correction algorithm

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Fig. 9

Estimation results of the EGR mass flow depending on covariance gain (engine speed: 1500 rpm)

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Fig. 10

Covariance gain matrix for the correction state: (a) covariance matrix for one model input and (b) merged covariance matrix for all the modeling points

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Fig. 11

Merging process of covariance gain matrix

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Fig. 12

Online validation results of the air system model

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Fig. 13

Estimation results of air system model at load step change (engine speed: 1500 rpm and injected fuel quantity: 12.5–27.5 (2.5) mg/str)

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Fig. 14

Estimation results of oxygen concentration at load step change (engine speed: 1500 rpm and injected fuel quantity: 12.5–27.5 (2.5) mg/str)

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Fig. 15

Estimation results of air system model at actuator step change (engine speed: 1500 rpm, injected fuel quantity: 20 mg/str, and EGR valve position: 16.5–24.5 (2) %)

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Fig. 16

Estimation results of oxygen concentration at load step change (engine speed: 1500 rpm, injected fuel quantity: 20 mg/str, and EGR valve position: 16.5–24.5 (2) %)

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Fig. 17

Estimation results under the UDC engine experiment

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Fig. 18

Estimation results of oxygen concentration under the UDC engine experiment

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Fig. 19

Estimation results under the EUDC engine experiment

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Fig. 20

Estimation results of oxygen concentration under the EUDC engine experiment

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