Steigerung der Effizienz in der modellbasierten Motoren-applikation durch die neue CAMEO Online DoE-Toolbox

Gschweitl, Kurt; Pfluegl, Horst; Fortuna, Tiziana; Leithgoeb, Rainer

doi:10.1007/bf03226227

Cited by 17 publications

(7 citation statements)

References 4 publications

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“…With the presented method, the high dimensional problem is reduced to an order of two. Although the optimization of a working point like in (Gschweitl, et al, 2001) or in (Hagena, et al, 2006) is not the objective for this transformation, it can be used for an online optimization, too. However it is not intended to be used for ECU calibration, but as mentioned before for a later online control.…”

Section: Discussionmentioning

confidence: 99%

Optimal Selection of Control Inputs for Diesel Engines

Alberer

Hirsch

2008

IFAC Proceedings Volumes

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Section: Discussionmentioning

confidence: 99%

Optimal Selection of Control Inputs for Diesel Engines

Alberer

Hirsch

2008

IFAC Proceedings Volumes

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“…be the discrete analogue of the curve ϕ describing how long the curve ϕ stays in OP f t . Again, Φ may coincide with DC from (6) or be chosen to optimize fuel consumption on a larger part of the operation field. The optimization objective is now to find a solution map SOL ∈ Ω k by picking for each stack S f t a single representative…”

Section: Discrete Optimization Problemmentioning

confidence: 99%

Semi-automatically optimized calibration of internal combustion engines

Burggraf¹,

Joswig

Pfetsch

et al. 2019

Optim Eng

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Modern combustion engines incorporate a number of actuators and sensors that can be used to control and optimize the performance and emissions. We describe a semi-automatic method to simultaneously measure and calibrate the actuator settings and the resulting behavior of the engine. The method includes an adaptive process for refining the measurements, a data cleaning step, and an optimization procedure. The optimization works in a discretized space and incorporates the conditions to describe the dependence between the actuators and the engine behavior as well as emission bounds. We demonstrate our method on practical examples. Internal Cumbustion Engines and Calibration and Mixed Integer Nonlinear OptimizationThe work of T. Burggraf, M. Pfetsch and S. Ulbrich has been supported by Deutsche Forschungsgemeinschaft within GSC 233 "Computational Engineering". M. Pfetsch and S.

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“…The first modelling algorithms which were used in modelbased engine calibration, were polynomial models (e.g. see Mitterer (2000) and Gschweitl et al (2001)). As polynomial regression suffers from some drawbacks, which are discussed in chapter 5, more sophisticated models were developed and used.…”

Section: Overview Of Modelling-typesmentioning

confidence: 99%