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Research Papers

Modeling and Control of Combustion Phasing in Dual-Fuel Compression Ignition Engines

[+] Author and Article Information
Wenbo Sui, Jorge Pulpeiro González, Carrie M. Hall

Illinois Institute of Technology,
10 W. 32nd St.,
Chicago, IL 60616

Manuscript received April 23, 2018; final manuscript received October 24, 2018; published online November 28, 2018. Assoc. Editor: Alessandro Ferrari.

J. Eng. Gas Turbines Power 141(5), 051005 (Nov 28, 2018) (12 pages) Paper No: GTP-18-1181; doi: 10.1115/1.4041871 History: Received April 23, 2018; Revised October 24, 2018

Dual-fuel engines can achieve high efficiencies and low emissions but also can encounter high cylinder-to-cylinder variations on multicylinder engines. In order to avoid these variations, they require a more complex method for combustion phasing control such as model-based control. Since the combustion process in these engines is complex, typical models of the system are complex as well and there is a need for simpler, computationally efficient, control-oriented models of the dual-fuel combustion process. In this paper, a mean-value combustion phasing model is designed and calibrated, and two control strategies are proposed. Combustion phasing is predicted using a knock integral model (KIM), burn duration (BD) model, and a Wiebe function, and this model is used in both an adaptive closed loop controller and an open loop controller. These two control methodologies are tested and compared in simulations. Both control strategies are able to reach steady-state in five cycles after a transient and have steady-state errors in CA50 that are less than ±0.1 CA deg (CAD) with the adaptive control strategy and less than ±1.5 CAD with the model-based feedforward control method.

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Figures

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Fig. 1

Schematic of dual-fuel engine system

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Fig. 2

Block diagram of combustion phasing in dual-fuel engines

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Fig. 3

Model calibration procedure

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Fig. 4

Comparison of model predicted: (a) SOC and (b) CA50 with GT-ISE simulation

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Fig. 5

Block diagram of CA50 adaptive feedback control system

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Fig. 6

Block diagram of CA50 model-based open-loop control system

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Fig. 7

Controller performance for all simulation cases: (a) reference CA50 change, (b) engine speed change, (c) natural gas equivalence ratio change, (d) EGR fraction change, (e) combined natural gas equivalence ratio and engine speed change, and (f) combined change in EGR fraction, engine speed, and natural gas equivalence ratio

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Fig. 8

Simulation result of error response in adaptive controller

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