A low order model of SCR-in-DPF systems with proper orthogonal decomposition
conference contributionposted on 06.08.2018 by Seun Olowojebutu, Thomas Steffen
Any type of content contributed to an academic conference, such as papers, presentations, lectures or proceedings.
© 2018 SAE International. All Rights Reserved. This paper presents a method to achieve a low order system model of the urea-based SCR catalyst coated filter (SCR-in-DPF or SCRF or SDPF), while preserving a high degree of fidelity. Proper orthogonal decomposition (POD), also known as principal component analysis (PCA), or Karhunen-Loéve decomposition (KLD), is a statistical method which achieves model order reduction by extracting the dominant characteristic modes of the system and devises a low-dimensional approximation on that basis. The motivation for using the POD approach is that the low-order model directly derives from the high-fidelity model (or experimental data) thereby retains the physics of the system. POD, with Galerkin projection, is applied to the 1D + 1D SCR-in-DPF model using ammonia surface coverage and wall temperature as the dominant system states to achieve model order reduction. The performance of the low-order POD model (with only a few basis modes) shows good agreement with the high fidelity model in steady and transient states analyses. This shows the promise of the application of POD in exhaust after-treatment system (EATS) modelling to achieve high fidelity low order models. In addition system control design is easier for the reduced order model using a modern approach. We demonstrate the performance of a model-based controller applied to the low-order POD model to minimize ammonia slip for a transient test cycle.
This work was funded by Engineering and Physical Sciences Research Council (EPSRC), UK and Eminox Ltd.
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