model based optimal design of experiments supported by parameter sensitivity analysis
Andraž Kravos (Author), Daniel Ritzberger (Author), Christoph Hametner (Author), Stefan Jakubek (Author), Tomaž Katrašnik (Author)

Abstract

Determination of the optimal design of experiments that enables efficient parametrisation of fuel cell (FC) model with a minimum parametrisation data-set is one of the key prerequisites for minimizing costs and effort of the parametrisation procedure. To efficiently tackle this challenge, the paper present an innovative methodology based on the electrochemical FC model, parameter sensitivity analysis and application of D-optimal design plan. Relying on this consistent methodological basis the paper answers fundamental questions: a) on a minimum required data-set to optimally parametrise the FC model and b) on the impact of reduced space of operational points on identifiability of individual calibration parameters. Results reveal that application of D-optimal DoE enables enhancement of calibration parameters information resulting in up to order of magnitude lower relative standard errors on smaller data-sets. In addition, it was shown that increased information and thus identifiability, inherently leads to improved robustness of the FC electrochemical model.

Keywords

PEM fuel cells;electrochemical PEM FC model;model-based design of experiments;reduced dimensionality models;parameter sensitivity;virtual observers;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FS - Faculty of Mechanical Engineering
UDC: 621.352.6:004.9(045)
COBISS: 36716803 Link will open in a new window
ISSN: 0360-3199
Views: 53
Downloads: 24
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Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary keywords: PEM gorivne celice;elektrokemični model PEM gorivne celice;modelsko osnovan dizajn eksperimentov;modeli z zmanjšano dimenzionalnostjo;občutljivostna analiza parametrov;virtualna tipala;
Type (COBISS): Article
Pages: str. 13832-13844
Volume: ǂVol. ǂ46
Issue: ǂiss. ǂ26
Chronology: Apr. 2021
DOI: 10.1016/j.ijhydene.2020.10.146
ID: 15956614