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Model-based experimental screening for DOC parameter estimation

Björn Lundberg (Institutionen för kemi och kemiteknik, Kemisk reaktionsteknik) ; Jonas Sjöblom (Institutionen för tillämpad mekanik, Förbränning) ; Åsa Johansson ; Björn Westerberg ; Derek Creaser (Institutionen för kemi och kemiteknik, Kemisk reaktionsteknik)
Computers and Chemical Engineering (0098-1354). Vol. 74 (2015), p. 144-157.
[Artikel, refereegranskad vetenskaplig]

In the current study a parameter estimation method based on data screening by sensitivity analysis is presented. The method applied Multivariate Data Analysis (MVDA) on a large transient data set to select different subsets on which parameters estimation was performed. The subset was continuously updated as the parameter values developed using Principal Component Analysis (PCA) and D-optimal onion design. The measurement data was taken from a Diesel Oxidation Catalyst (DOC) connected to a full scale engine rig and both kinetic and mass transport parameters were estimated. The methodology was compared to a conventional parameter estimation method and it was concluded that the proposed method achieved a 32% lower residual sum of squares but also that it displayed less tendencies to converge to a local minima. The computational time was however significantly longer for the evaluated method.

Nyckelord: Parameter estimation, D-optimal design, Diesel Oxidation Catalyst, Multivariate Data Analysis, Engine rig experiments

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Denna post skapades 2015-03-23. Senast ändrad 2015-04-13.
CPL Pubid: 214182


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