No abstract

Cost of hydrogen-fueled proton-exchange-membrane fuel cells (PEMFCs) remains a challenge for the global commercialization of the technology and needs to be reduced to meet the U.S. Department of Energy goals [1]. Cost-reduction can be achieved by incorporating efficient water management, which helps keep the electrolyte hydrated while avoiding cell flooding by product water. Dynamic liquid-water accumulation and electrolyte hydration can be studied via transient polarization [2-6] and ohmic-resistance [2,4-7] curves, in which they induce hysteresis. Analyzing the polarization and resistance data may, however, be challenging due to the overlapping transients of various physical processes occurring in the cell during the voltage and current sweeps. Electrochemical impedance spectroscopy (EIS) allows the study of the dynamic processes of different time scales separately in the frequency domain and has been widely used for fuel-cell characterization [8-11]. Fuel-cell impedance spectra often exhibit an inductive behavior at low frequencies, which has been shown to be affected by electrolyte hydration [10,12-14]. A recent experimental study [9] showed that the strength of this inductive behavior depends on the anode and cathode RH. Understanding the low-frequency inductance may help improve the water-management strategies for fuel cells. However, this inductive phenomenon has not been investigated in detail with a comprehensive numerical model. In this work, a transient 2D PEMFC model is developed in the open-source fuel-cell modeling software OpenFCST [17] with a thorough validation through dynamic polarization, resistance, and impedance-spectroscopy data at various operating conditions. Unlike other physical EIS models [13-16], the presented model does not rely on parameter fitting to reproduce the experimental impedance spectra. The model also takes the finite-rate water absorption/desorption kinetics of the electrolyte into account, which allows to investigate the effect of the interfacial transport of water on fuel-cell impedance and performance. With the presented model, water-management signatures are identified in fuel-cell impedance spectra under single-phase conditions that help elucidate electrolyte-hydration dynamics. The trends in the simulated effect of anode and cathode RH on the fuel-cell inductance are in agreement with experiments in [9], which verifies the model’s ability to correctly predict the inductive behavior. The low-frequency inductive behavior of fuel cells is shown to be related to the interfacial transport of water in the electrolyte and linked to the electrolyte-hydration and proton-conductivity dynamics in the membrane and in the catalyst layers. Additionally, an ohmic-resistance breakdown is performed with the model using the ohmic-heating-based approach proposed by Secanell et al. [18]. The high-frequency resistance obtained through EIS is shown to be comprised of the membrane resistance and the electronic resistance of other MEA components, but not the protonic resistance of the catalyst layers. Figure: Single-phase water-transport signatures in a fuel-cell-impedance spectrum. References [1] D. Papageorgopoulos. Fuel Cell R&D Overview. U.S. Department of Energy; 2019. [2] C. Ziegler et al. J. Electrochem. Soc. 152.8 (2005): A1555-A1567. [3] H. Yu and C. Ziegler. J. Electrochem. Soc. 153.3 (2006): A570-A575. [4] D. Gerteisen et al. J. Power Sources 187.1 (2009): 165-181. [5] L. Hao et al. J. Power Sources 177.2 (2008): 404-411. [6] J. Hou. Int. J. Hydrogen Energ. 36.12 (2011): 7199-7206. [7] A. Goshtasbi et al. J. Electrochem. Soc. 166.7 (2019): F3154-F3179. [8] D. Malevich et al. J. Electrochem. Soc. 156.2 (2009): B216-B224. [9] A. Schiefer et al. EFCF 2019: Low-Temperature Fuel Cells, Electrolisers, & H2 Processing, Chapter 03 (2019): 179–189. [10] I. Pivac and F. Barbir. J. Power Sources 326 (2016): 112-119. [11] S. M. R. Niya and M. Hoorfar. J. Power Sources 240 (2013): 281-293. [12] B. P. Setzler and T. F. Fuller. J. Electrochem. Soc. 162.6 (2015): F519-F530. [13] C. Bao and W. G. Bessler. J. Power Sources 278 (2015): 675-682. [14] G. A. Futter et al. J. Power Sources 391 (2018): 148-161. [15] A. Baricci et al. Fuel Cells 14.6 (2014): 926-937. [16] J. R. Vang et al. ECS Transactions 68.3 (2015): 13-34. [17] M. Secanell et al. ECS Transactions 64.3 (2014): 655-680. [18] M. Secanell et al. ECS Transactions 69.17 (2015): 157-187. Figure 1