The Effect of Cyclic Hygrothermal Loading on the Mechanical Fatigue Durability of PEM Fuel Cells
Bibliographic record
Abstract
The membrane electrode assembly (MEA) in polymer electrolyte membrane (PEM) fuel cells undergoes hygrothermal cyclic loading during normal operating conditions. These cyclic loadings create in plane and through plane cyclic stresses being distributed in the membrane. To understand the mechanical fatigue behavior, samples in dogbone shapes (Figure 1) are prepared and placed under the application of cyclic mechanical loadings in controlled ambient conditions [1]. Both pure PFSA membrane and catalyst coated membrane samples are used in the experiments. The tests are conducted ex-situ and the environmental conditions selected in this study cover the temperature and relative humidity levels from those of room conditions to fuel cell conditions. The experimental results are used to benchmark the effect of environmental and loading conditions on the fatigue lifetime of the membrane. Our previous studies [2,3] show that the catalyst layers play a significant role in the mechanical behavior of catalyst coated membranes. Hence, in this study the effect of catalyst layers on the mechanical durability and final elongation of the membrane before the mechanical failure is also investigated. A strain based fatigue model is then used to develop a finite element numerical scheme for simulating the membrane fatigue lifetime under hygrothermal mechanical loadings. Using the experimental results, the accuracy of the finite element simulations results are verified (Figure 1). The effects of temperature and relative humidity swings on the mechanical longevity of the pure membrane are explored. It is seen that hydration swings have a more profound effect on the fatigue lifetime of the membrane than the temperature swings. Then, using the ex-situ results for the catalyst coated membrane, the impact of the catalyst layers on the membrane/CCM fatigue lifetime is investigated. The finite element model is then used to study the in-situ mechanical stability of pure membranes and catalyst coated membranes under hygrothermal cyclic conditions. Acknowledgements: This research was supported by Ballard Power Systems and the Natural Sciences and Engineering Research Council of Canada through an Automotive Partnership Canada (APC) grant. References [1] R.M.H. Khorasany, A.S. Alavijeh, E. Kjeang, G.G. Wang, R.K.N.D. Rajapakse, J. Power Sources (2014) under review. [2] M.A. Goulet, R.M.H. Khorasany, C. De Torres, M. Lauritzen, E. Kjeang, G.G. Wang, N. Rajapakse, J. Power Sources 234 (2013) 38-47. [3] R.M.H. Khorasany, M.-A. Goulet, A.S. Alavijeh, E. Kjeang, G.G. Wang, R.K.N.D. Rajapakse, J. Power Sources 252 (2014) 176-188. Figure 1: (a) Dogbone sample used in simulations (with dimensions given in mm), membrane fatigue lifetime at room conditions (23oC, 50% RH) under cyclic mechanical loadings with a maximum force of (b) 1.16 N and (c) 0.95
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".