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Research Papers: Internal Combustion Engines

Fault Management System of LP-EGR Using In-Cylinder Pressure Information in Light-Duty Diesel Engines

[+] Author and Article Information
Junhyeong Oh

Department of Automotive Engineering,
Hanyang University,
222 Wangsimni-ro, Seongdong-gu,
Seoul 04763, South Korea
e-mail: qwerty993@hanyang.ac.kr

Kyunghan Min

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

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 IC Engine Division of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received April 13, 2017; final manuscript received July 30, 2017; published online November 7, 2017. Assoc. Editor: Nadir Yilmaz.

J. Eng. Gas Turbines Power 140(4), 042802 (Nov 07, 2017) (11 pages) Paper No: GTP-17-1140; doi: 10.1115/1.4038078 History: Received April 13, 2017; Revised July 30, 2017

Particulate matters (PM) accumulation through a low-pressure exhaust gas recirculation (LP-EGR) path may hinder to obtain the desired LP-EGR rate and thus causes an increase of nitrogen oxides (NOx). The degree of lack of the LP-EGR rate should be detected, i.e., an LP-EGR fault, and a remedy to compensate for the lack of LP-EGR rate should be a mandate to suppress NOx emission, i.e., a fault management. In order to accomplish those objectives, this paper proposes an LP-EGR fault management system, which consists of a fault diagnosis algorithm, fault-tolerant control algorithm, and an LP-EGR rate model. The model applies a combustion parameter derived from in-cylinder pressure information to the conventional orifice valve model. Consequently, the LP-EGR rate estimation was improved to the maximum error of 2.38% and root-mean-square-error (RMSE) of 1.34% at various operating conditions even under the fault condition compared to that of the conventional model with the maximum error of 7.46% and RMSE of 5.39%. Using this LP-EGR rate model as a virtual sensor, the fault diagnosis algorithm determines an LP-EGR fault state. Based on the state, the fault-tolerant control determines whether or not to generate the offset of the exhaust throttle valve (ETV) position. This offset combines with the look-up table (LUT)-based feedforward controller to control an LP-EGR rate. As a result of real-time verification of the fault management system in the fault condition, the NOx emission decreased by up to about 15%.

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References

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Figures

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Fig. 1

Different tendency of the LP-EGR differential pressure and mass flow rate

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Fig. 2

Estimation error of the orifice valve model when an LP-EGR fault occurs

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Fig. 3

Air system schematic diagram and measured sensor signal

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Fig. 4

Result of HR analysis changing the LP-EGR rate intentionally (engine speed: 1750 rpm, Injection quantity: 15 mg/str)

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Fig. 5

Process of the increase in the pumping loss caused by the decrease in the LP-EGR rate (engine speed: 1750 rpm, injection quantity: 15 mg/str): (a) LP EGR rate, (b) total EGR rate, (c) MAP, (d) MAF, (e) VGT vane position, (f) HP EGR valve position, (g) exhaust manifold pressure, (h) IMEP (kPa)

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Fig. 6

Relationship between the combustion parameter and the LP-EGR mass flow rate at the same operating conditions under the normal and fault condition

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Fig. 7

Block diagram of LP-EGR rate estimation algorithm

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Fig. 8

Engine operating conditions for modeling parameter identification

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Fig. 9

Comparison of measured LP-EGR rate in LP-EGR fault and normal condition

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Fig. 10

Modeling result of LP-EGR rate

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Fig. 11

Evaluation of linearity between the measured and modeled LP-EGR rate

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Fig. 12

Steady-state validation result in normal condition

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Fig. 13

Steady-state validation result of the proposed model in the fault condition

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Fig. 14

Structure of the proposed fault management system for LP-EGR

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Fig. 15

Structure of the proposed fault diagnosis algorithm

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Fig. 16

Structure of the proposed fault-tolerant control algorithm

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Fig. 17

Validation result of the fault management system (engine speed: 1250 rpm, injection quantity: 20 mg/str, test case 1)

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Fig. 18

Validation result of the fault management system (engine speed: 1750 rpm, injection quantity: 17.5 mg/str)[TQ2]

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Fig. 19

Validation result of the fault management system (engine speed: 2000 rpm, injection quantity: 20 mg/str)

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