Parameter Estimation of a DOC from Engine Rig Experiments with a Discretized Catalyst Washcoat Model
Journal article, 2014

Parameter tuning was performed against data from a full scale engine rig with a Diesel Oxidation Catalysts (DOC). Several different catalyst configurations were used with varying Pt loading, washcoat thickness and volume. To illustrate the interplay between kinetics and mass transport, engine operating points were chosen with a wide variation in variables (inlet conditions) and both transient and stationary operation was used. A catalyst model was developed where the catalyst washcoat was discretized as tanks in series both radially and axially. Three different model configurations were used for parameter tuning, evaluating three different approaches to modeling of internal transport resistance. It was concluded that for a catalyst model with internal transport resistance the best fit could be achieved if some parameters affecting the internal mass transport were tuned in addition to the kinetic parameters. However it was also shown that a model with negligible internal transport resistance still could obtain a good fit since kinetic parameters could compensate for transport limitations. This highlighted the inherent difficulties using kinetic models with high parameter correlation and also showed the importance of using a kinetic model with a structure that is capable of describing exclusively intrinsic kinetics.

Diesel exhaust emissions control

Simulation and Modeling

Catalysts

Author

Björn Lundberg

Chalmers, Chemical and Biological Engineering, Chemical Reaction Engineering

Jonas Sjöblom

Chalmers, Applied Mechanics, Combustion and Propulsion Systems

Åsa Johansson

Johnson Matthey

Björn Westerberg

Scania CV AB

Derek Creaser

Chalmers, Chemical and Biological Engineering, Chemical Reaction Engineering

SAE International Journal of Engines

1946-3936 (ISSN) 19463944 (eISSN)

Vol. 7 2 1093-1112

Areas of Advance

Transport

Subject Categories

Chemical Process Engineering

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.4271/2014-01-9049

More information

Latest update

8/8/2023 6