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Research Papers

Control-Oriented Model of Molar Scavenge Oxygen Fraction for Exhaust Recirculation in Large Diesel Engines

[+] Author and Article Information
Kræn Vodder Nielsen

MAN Diesel & Turbo,
Copenhagen 2450, Denmark;
Automation and Control Group,
Department of Electrical Engineering,
Technical University of Denmark,
Kongens Lyngby 2800, Denmark
e-mail: krvni@elektro.dtu.dk

Mogens Blanke

Automation and Control Group,
Department of Electrical Engineering,
Technical University of Denmark,
Kongens Lyngby 2800, Denmark;
AMOS CoE,
Institute of Technical Cybernetics,
Norwegian University of
Science and Technology,
Trondheim 7491, Norway
e-mail: mb@elektro.dtu.dk

Lars Eriksson

Vehicular Systems,
Department of Electrical Engineering,
Linköping University,
Linköping 58183, Sweden
e-mail: larer@isy.liu.se

Morten Vejlgaard-Laursen

MAN Diesel & Turbo,
Copenhagen 2450, Denmark

Manuscript received June 8, 2016; final manuscript received September 5, 2016; published online November 10, 2016. Assoc. Editor: Ryozo Nagamune.

J. Dyn. Sys., Meas., Control 139(2), 021007 (Nov 10, 2016) (10 pages) Paper No: DS-16-1298; doi: 10.1115/1.4034750 History: Received June 08, 2016; Revised September 05, 2016

Exhaust gas recirculation (EGR) systems have been introduced to large marine engines in order to reduce NOx formation. Adequate modeling for control design is one of the bottlenecks to design EGR control that also meets emission requirements during transient loading conditions. This paper therefore focuses on deriving and validating a mean-value model of a large two-stroke crosshead diesel engine with EGR. The model introduces a number of amendments and extensions to previous, complex models and shows in theory and practice that a simplified nonlinear model captures all essential dynamics that is needed for EGR control. Our approach is to isolate and reduce the gas composition part of the more complex models using nonlinear model reduction techniques. The result is a control-oriented model (COM) of the oxygen fraction in the scavenge manifold with three molar flows being inputs to the COM, and it is shown how these flows are estimated from signals that are commonly available. The COM is validated by first comparing the output to a simulation of the full model, then by comparing with measurement series from two engines. The control-oriented nonlinear model is shown to be able to replicate the behavior of the scavenge oxygen fraction well over the entire envelope of load and blower speed range that are relevant for EGR. The simplicity of the new model makes it suitable for observer and control design, which are essential steps to meet the emission requirements for marine diesel engines that take effect from 2016.

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Figures

Grahic Jump Location
Fig. 1

Overview of main gas flows and components of the engine with exhaust gas recirculation and cylinder by-pass valve (CBV)

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Fig. 2

An example of required scavenge oxygen fraction as a function of engine load. The linearly interpolated commissioning points are specific to the engine.

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Fig. 3

The CBV flow mixes directly into the turbine flow and not the exhaust receiver

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Fig. 4

A digraph shows the couplings between states in the MVEM model. The model can be separated in two cascaded systems as the gas composition states only affect each other.

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Fig. 5

The figure shows the magnitude of the terms ψ and ã11−λ1. Both terms remain close to zero during a simulation of the MVEM in a wide range of engine loads and EGR blower speeds with realistic input rates and they can therefore be neglected in the model.

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Fig. 6

Time constants τ1 and τ2 of the gas mixing process vary slightly during simulation over a wide engine load and EGR flow range

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Fig. 7

Overview of the control-oriented model with its input estimates and the signals used

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Fig. 8

Simulation and estimation of cooler flow n˙ic with constant CBV opening and varying engine load (43 to 100%) and EGR blower speed

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Fig. 9

Simulation and estimation of cooler flow n˙ic with constant EGR blower speed opening and varying engine load (43 to 100%) and CBV opening (0 to 100%)

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Fig. 10

Simulation and estimation of cooler flow while changing engine load (43, 69, and 100%) and EGR blower speed in steps

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Fig. 11

Comparison of Osr simulated by MVEM and COM during steps of EGR blower speed at engine loads 43, 69, and 100%

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Fig. 12

Comparison of Osr simulated by MVEM and COM during steps of engine load (43, 69, 100, 69, and 43%) at different EGR blower speeds

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Fig. 13

Comparison of Osr measured on test engine and estimated by COM during steps of EGR blower speed at engine loads 50, 75, and 100%

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Fig. 14

Comparison of Osr measured on test engine and estimated by COM during a series of engine RPM setpoint changes

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Fig. 15

Comparison of Osr measured on vessel engine and estimated by COM during steps of EGR blower speed at engine loads 40, 60, and 80%

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Fig. 16

Comparison of Osr measured on vessel engine and estimated by COM during a series of engine RPM setpoint changes

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