Differential Resistance Analysis – a New Tool for Evaluation of Solid Oxide Fuel Cells Degradation. (9th November 2017)

• Record Type: Journal Article
• Authors: Stoynov, Zdravko B.; Vladikova, Daria E.; Burdin, Blagoy G.; Laurencin, Jerome; Montinaro, Dario; Nakajo, Arata; Piccardo, Paolo; Thorel, Alain; Hubert, Maxime; Spotorno, Roberto; Chesnaud, Anthony
• Is Part Of: MRS advances. Volume 2:Number 64(2017)
• Page Start: 3991
• Page End: 4003
• Publication Date: 2017-11-09
• Subjects: electrical properties, -- energy generation, -- energy storage, -- ionic conductor; Electrical engineering -- Congresses; Physics -- Congresses; Materials -- Research -- Congresses; Materials science -- Congresses; 620.11
• DOI: 10.1557/adv.2017.592
• Languages: English
• ISSNs: 2059-8521

Abstract

ABSTRACT: Solid Oxide Fuel Cells (SOFCs) are a promising technology that can provide efficient and clean energy production. The general barriers hindering their market entry are durability, i.e. resistance to aging, and costs. In parallel to the deeper insight into the different degradation sources and improved understanding of ageing factors and their interactions, work towards higher accuracy for the assessment and monitoring of real-world fuel cell ageing in necessary. The requirements for operational stability formulate the parameter "degradation rate" (DR). Most often long term durability tests are performed at constant current load and the decrease of the voltage is used for its definition. In this work a new approach based on analysis of the volt-ampere characteristics, named Differential Resistance Analysis (DRA), is presented. It operates with the differential resistance, i.e. with the derivative of the voltage in respect to the current (dU/dI = Rd ) which is more sensitive to small deviations and thus increases the sensitivity of the analysis. Two performance indicators are derived (Rd, min and ∆U*) with differing selectivity: ∆U* is more sensitive to activation losses and Rd, min - to transport hindrances. The application of the DRA is demonstrated on examples from measurements in fuel cell and in reverse (fuel cell/electrolyzer) mode, as well as on modeling data. The results show that the method is at least 10 times more sensitive to DR evaluation in comparison with the classical approach.