Design and Experimental Investigation of Temperature Control for a 10 kW SOFC System Based on an Artificial Neuronal Network

In this work the authors designed and experimentally evaluated different controller topologies for fuel cell operation (SOFC) of a reversible solid oxide cell (rSOC) system. Aim of the controller is to operate the SOFC system autonomously at a constant maximum temperature for maximum efficiency. The...

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Bibliographic Details
Published in:ECS transactions 2023-05, Vol.111 (6), p.493-501
Main Authors: Kruse, Nicolas, Tiedemann, Wilfried, Hoven, Ingo, Deja, Rober, Peters, Roland, Kunz, Felix, Eichel, Rudiger-A
Format: Article
Language:English
Online Access:Get full text
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Summary:In this work the authors designed and experimentally evaluated different controller topologies for fuel cell operation (SOFC) of a reversible solid oxide cell (rSOC) system. Aim of the controller is to operate the SOFC system autonomously at a constant maximum temperature for maximum efficiency. The controller design incorporates an artificial neuronal network (ANN) for real time state predictions. The training data for the ANN was generated by a Digital Twin of this system. The generated training data consists of about 16,000 different steady state operating conditions.
ISSN:1938-5862
1938-6737
DOI:10.1149/11106.0493ecst