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Common rail injection system iterative learning control based parameter calibration for accurate fuel injection quantity control

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Abstract

This paper presents an accurate engine fuel injection quantity control technique for high pressure common rail (HPCR) injection systems by an iterative learning control (ILC)-based, on-line calibration method. Accurate fuel injection quantity control is of importance in improving engine combustion efficiency and reducing engine-out emissions. Current Diesel engine fuel injection quantity control algorithms are either based on pre-calibrated tables or injector models, which may not adequately handle the effects of disturbances from fuel pressure oscillation in HPCR, rail pressure sensor reading inaccuracy, and the injector aging on injection quantity control. In this paper, by using an exhaust oxygen fraction dynamic model, an on-line parameter calibration method for accurate fuel injection quantity control was developed based on an enhanced iterative learning control (EILC) technique in conjunction with HPCR injection system. A high-fidelity, GT-Power engine model, with parametric uncertainties and measurement disturbances, was utilized to validate such a methodology. Through simulations at different engine operating conditions, the effectiveness of the proposed method in rejecting the effects of uncertainties and disturbance on fuel injection quantity control was demonstrated.

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Abbreviations

k :

index of engine cycle

{ie}:

piston surface area effective parameter

{ie}:

piston surface area effective parameter

φ :

engine crank angle

ην :

engine volumetric efficiency

λ s :

Stoichiometric oxygen fuel mass ratio for complete combustion

ρ fuel :

fuel density

ΔP :

pressure difference between common rail and incylinder pressures

θ(t):

uncertainty parameter to be calculated

A cyl :

area of the total outflow section

c d,cyl :

fuel flow discharge coefficient

d :

in-cylinder charge density during valve overlapping

ET :

injection duration

F i :

oxygen fractions of the gases in intake manifold at IVC

F e :

oxygen fractions of the gases in exhaust manifold at IVC

F c :

oxygen fractions of the gases in cylinder at IVC

F ec :

oxygen fractions of the gases out of cylinder

k :

index of engine cycle

m c :

mass of gas in the cylinder at IVC

m e :

mass of gas in exhaust manifold at IVC

m ic :

mass of gas from intake manifold to cylinder per cycle

m ec :

mass of gas from exhaust manifold to cylinder per cycle

m ce :

mass of gas from cylinder to exhaust manifold per cycle

m f :

fuel mass quantity per cylinder per cycle

Δm restV :

mass from exhaust manifold to cylinder caused by the volume change

Δm restB :

mass from exhaust manifold to cylinder caused by the pressure difference

N :

engine speed (rpm)

p i :

pressure in intake manifold

p e :

pressure in exhaust manifold

R :

ideal gas constant

T i :

temperature in intake manifold

T e :

temperature in exhaust manifold

V i :

volume of intake manifold

V e :

volume of exhaust manifold

W c :

mass flow rate through cylinder

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Authors and Affiliations

  1. Department of Mechanical Engineering, The Ohio State University, Columbus, Ohio, 43210, USA

    F. Yan & J. Wang

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  1. F. Yan
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  2. J. Wang
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Correspondence to J. Wang.

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Yan, F., Wang, J. Common rail injection system iterative learning control based parameter calibration for accurate fuel injection quantity control. Int.J Automot. Technol. 12, 149–157 (2011). https://doi.org/10.1007/s12239-011-0019-7

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  • DOI: https://doi.org/10.1007/s12239-011-0019-7

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