2011 | OriginalPaper | Buchkapitel
The Nonlinear Viscoelastic Properties of PFSA Membranes in Water-immersed and Humid Air Conditions
verfasst von : Lei Yan, Timothy A. Gray, Kshitish A. Patankar, Scott W. Case, Michael W. Ellis, Robert B. Moore, David A. Dillard, Yeh-Hung Lai, Yongqiang Li, Craig S. Gittleman
Erschienen in: Experimental Mechanics on Emerging Energy Systems and Materials, Volume 5
Verlag: Springer New York
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Proton exchange membranes (PEM) in an automotive fuel cell stack can experience significant temperature and hydration changes as the stack responds to the demanding automotive duty cycle. Since mechanical stresses resulting from the hygrothermal cycles are believed to contribute to the loss of mechanical durability that are sometimes experienced in operating PEM fuel cells, it is important to characterize the mechanical behavior of PEMs over a wide range of hygrothermal conditions. In this study, the linear and nonlinear viscoelastic properties of PEMs equilibrated with both humidified air and liquid water are characterized using a custom-built multistation stress relaxation fixture. Specifically, relaxation data of a commercially available, perfluorosulfonic acid PEM was collected over a temperature range of 30-90°C and strain levels from less than 1% to over 20% or more. A comparison of immersed data to dry conditions and a range of humidity levels is presented in this paper. Significant nonlinearity is observed in the membrane, but becomes less pronounced at longer times. Cyclic tests with various strain levels were carried out on the membranes at 70o C in immersed conditions. The nonlinearity exhibited by the PEM under the larger strain levels was represented quite accurately with a Schapery unaxial hereditary single integral model. For this initial effort, material nonlinear parameters were chosen to simulate the stress output from larger strain levels. Complex loading profiles at various rates were used to validate the model and good agreement was achieved between experimental results and numerical predictions.