Fast model-based calibration of multiple injections for a CI engine using nonlinear optimal control

Abstract: Today’s internal combustion engines are subject to strict regulations of pollutant emissions and to ambitious fuel consumption reduction targets. For direct-injection compression-ignition engines, multiple injections offer additional degrees of freedom that help to achieve these goals. Thus far, the calibration of multiple injections has been based on data-driven approaches using design of experiments. However, an ever increasing number of actuators causes the calibration of the engine to require much more time. In this paper, we propose a model-based calibration method for multiple injections. The model, which is based on first principles, is identified by a low number of measurements and extrapolates well to various operating points. An optimal control problem which includes that model is then formulated to calculate the efficiency-optimal injector inputs while respecting constraints on cylinder pressure, pressure gradient, engine-out temperature, and engine-out NOx emissions. The optimal control problem is implemented on a rapid prototyping control system and is solved with the nonlinear optimal control framework acados. Due to the simple zero-dimensional formulation of the model and the fast convergence of the solver, the method allows for a fast calibration of two injections for an engine at steady-state operation. The method is used at various engine operating points to find various trade-offs of relevant engine-out quantities. An experimental validation shows that the calibration time is reduced significantly compared to an approach based on a design of experiments. When compared to a full-factorial design of experiment, a reduction in measurements of up to 60% is possible

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
Control engineering practice. - 145 (2024) , 105848, ISSN: 1873-6939

Event
Veröffentlichung
(where)
Freiburg
(who)
Universität
(when)
2024
Creator

DOI
10.1016/j.conengprac.2024.105848
URN
urn:nbn:de:bsz:25-freidok-2581392
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:25 AM CEST

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Time of origin

  • 2024

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