Membrane Durability in Heavy Duty Fuel Cells for Transit Bus Applications
Notice bibliographique
Résumé
Through a concerted research agenda involving Ballard Power Systems, Simon Fraser University, and University of Victoria, we are currently developing mechanistic understanding, models, and approaches to support durable and reliable fuel cell technology for transit buses with median lifetime equal to or better than incumbent diesel engines [1]. The research focuses on mitigation of membrane degradation, which has been identified by Ballard as a potential lifetime limiting failure mode leading to stack failure under bus operating conditions. Failure modes associated with gas leaks are predominantly caused by a combination of chemical and mechanical membrane degradation [2]. Due to the stringent product lifetime requirements for heavy duty applications and the complexity of the degradation mechanisms, durability evaluations and predictions are a significant challenge. An important goal of the present research program is to develop fundamental modeling tools in order to explore and understand the degradation mechanisms and to predict the membrane durability under conditions that are relevant for automotive applications. A specialized 1-D membrane electrolyte assembly (MEA) reaction-transport model was developed and integrated with a numerical algorithm for chemical membrane degradation via hydrogen peroxide mediated hydroxyl radical attack [3]. The time-dependent membrane dimensions and transport properties were calculated by considering the material and water losses caused by the chemical degradation. The model is thereby capable of simulating the chemical degradation rate, shown to be in good agreement with fluoride release and thinning data from accelerated stress tests. Using this model, we recently discovered an iron ion redox cycle in the MEA that controls the effect of cell voltage on membrane durability. Additionally, mechanical degradation was modelled using a finite element model with an elastic-viscoplastic constitutive relation that can simulate the stress and strain distributions in the MEA during hygrothermal variations such as wet/dry cycles [4]. This model was combined with a numerical framework for membrane fatigue, supported by experimental fatigue property measurements under cyclic tensile loadings, in order to estimate the fatigue lifetime distribution as a function of operating conditions and duty cycles. In addition to the fundamental models, an empirical approach was established by utilizing a specialized accelerated membrane durability test (AMDT) [5] to predict membrane lifetime during field operation of fuel cell buses. The proposed AMDT applies enhanced levels of stress, such as elevated voltage, temperature, and humidity cycling, to ensure membrane failures consistent with those observed in historical bus field trials but in a much shorter time. Acceleration factors for each stressor were determined and employed to develop an empirical lifetime prediction model based on the general log linear - Weibull stress life distribution. The empirical model focuses on extrapolating the lifetime of membranes under AMDT conditions to a lifetime expected under actual bus conditions. The predictive ability of the model was benchmarked with recent field data from the fuel cell bus fleet in Whistler, BC, and applied to predict the bus lifetime resulting from various lifetime enhancing strategies. REFERENCES http://www.apc-hdfc.ca/. Lim, et al., J. Power Sources 257 (2014) 102. Wong, et al., J. Electrochem. Soc. 161 (2014) F823; ChemSusChem 8 (2015) 1072. Khorasany, et al., J. Power Sources 252 (2014) 176; 274 (2015) 1208; 279 (2015) 55. Macauley, et al., J. Electrochem. Soc. 162 (2015) F98.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».