An interval arithmetic-based method for parametric identification of a fuel cell equivalent circuit model. (15th May 2019)

• Record Type: Journal Article
• Authors: Petrone, Giovanni; Zamboni, Walter; Spagnuolo, Giovanni
• Is Part Of: Applied energy. Volume 242(2019)
• Page Start: 1226
• Page End: 1236
• Publication Date: 2019-05-15
• Subjects: Fuel cell -- Interval arithmetic -- Parameter identification; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.03.136
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Parametric identification of a Fuel Cell stack based on the Interval Arithmetic. Robustness with respect to the uncertainties affecting the EIS measurements. Smart Branch and Bound algorithm for reducing computational burden and memory. Suitable for the on line diagnosis of electrochemical systems as FC and batteries. Abstract: In this paper, the identification of the equivalent circuit parameters of a polymer electrolyte fuel cell stack is performed for diagnostic and monitoring purposes. An interval arithmetic branch and bound method is developed for the identification of parameters of the Fouquet model, frequently used for fuel cell modeling in the frequency domain. The proposed method allows to bound each parameter by an interval of real values. It also provides the model sensitivity with respect to the parameters. The method is also able to account for uncertainties affecting the impedance measurements at the assigned frequency values. For the specific application to fuel cells, the approach overcomes the limitations, in terms of interval contraction capability, characterising standard interval analysis-based techniques. The features of the proposed approach, shown with various examples also involving experimental measurements, are useful in monitoring the stack performance, to the final aim of improving its lifetime, and ensuring the expected electrical power production. The proposed results allow to envisage an application of the method also in real time conditions, when the fuel cell model parametric identification has to be run by using an embedded system instead of a personal computer.