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Enregistrement W4285398173 · doi:10.1149/ma2022-01412456mtgabs

Simulation of Cathode Catalyst Durability Under Fuel Cell Vehicle Operation - the Effect of Fuel Cell Stack Size

2022· article· en· W4285398173 sur OpenAlexaffabout
Mohammad Shojayian, Erik Kjeang

Notice bibliographique

RevueECS Meeting Abstracts · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésProton exchange membrane fuel cellDurabilityStack (abstract data type)CathodeProcess engineeringElectrolyteAutomotive engineeringMembrane electrode assemblyMaterials scienceDuty cycleHydrogen fuelAnodeEnvironmental scienceVoltageComputer scienceChemical engineeringNuclear engineeringFuel cellsEngineeringElectrical engineeringChemistryComposite materialElectrode

Résumé

récupéré en direct d'OpenAlex

The concerns regarding climate change have made the researchers seek a clean alternative for the fossil fuel vehicles. Fuel cell vehicles (FCVs) are considered to be promising candidates owing to their efficient energy conversion and zero-carbon emission. However, a number of obstacles such as high cost and limited hydrogen infrastructure have made the FCVs commercialization process challenging. Polymer electrolyte membrane fuel cells (PEMFCs) have been proven promising for transportation applications. For heavy duty transportation applications, the PEMFC durability is also not yet proven, and extrapolating from lab data to real-world field operating conditions remains a significant challenge [1]. In this work, the cathode catalyst degradation in PEMFC is studied to estimate the effect of stack size on fuel cell durability in the FCV application. Platinum dissolution and redeposition, platinum oxidation and platinum ion formation during the fuel cell operation are modeled using the Butler-Volmer approach presented in [2]. A drive cycle recorded based on a real-life transit bus operation in the city of Victoria is utilized to calculate the input fuel cell voltage profile based on the methodology presented by Ahmadi and Kjeang [3]. According to this methodology, the required cell power density is calculated using Newton’s second law considering the air flow drag force as a counteracting force against the vehicle movement. Then, the required voltage cycle is obtained by employing a polarization curve characterizing the fuel cell performance. Finally, the change of remaining electrochemically active surface area (ECSA) with time is calculated as the output of the model. The fuel cell is assumed to operate at 80 ℃ and the cell active area is considered to be 500 cm2. Simple Tafel kinetics is then used to determine the fuel cell voltage loss. A 10% voltage drop at 0.6 A/cm2 is considered as the failure criterion for the cathode lifetime. Moreover, the effect of the fuel cell stack size is studied. By increasing fuel cell stack size, the required cell power density drops, leading to a decrease in the voltage cycle amplitude while the voltage cycle period remains the same. According to the empirical kinetic rate equation, the catalyst degradation exponentially increases with increasing the voltage. Therefore, a higher degradation rate is observed for a catalyst operating on a voltage cycle with a lower amplitude while the period and the upper potential limit (UPL) are maintained the same, causing a significant platinum ion generation. Fig. 1 shows the change of remaining ECSA over time and resulting fuel cell lifetime for three stack sizes which are represented by the stack nominal powers. The results show that the fuel cell lifetime will be roughly doubled when the stack size is reduced by half. Stack sizing is thus an important consideration for fuel cell durability in the FCV application. In this regard, predicting fuel cell lifetime is a crucial step in commercializing FCVs. The present modeling framework could be utilized by FCV developers to predict lifetime for new products instead of carrying out time-consuming lifetime experiments. The factors influencing fuel cell durability can also be investigated using the present model framework to develop durables cells and stacks for a targeted FCV application. Acknowledgements This research was supported by the Natural Sciences and Engineering Research Council of Canada, Canada Research Chairs, and Simon Fraser University Community Trust Endowment Fund. References [1] S. D. Knights, K. M. Colbow, J. St-Pierre and D. P. Wilkinson, "Aging mechanisms and lifetime of PEFC and DMFC," Journal of power sources, vol. 127, no. 1-2, pp. 127-134, 2004. [2] H. A. Baroody and E. Kjeang, "Predicting Platinum Dissolution and Performance Degradation under Drive Cycle Operation of Polymer Electrolyte Fuel Cells," Journal of The Electrochemical Society, vol. 168, no. 4, p. 044524, 2021. [3] P. Ahmadi and E. Kjeang, "Realistic simulation of fuel economy and life cycle metrics for hydrogen fuel cell vehicles," International Journal of Energy Research, vol. 41, no. 5, pp. 714-727, 2017. Figure 1

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,023
Score d'incertitude au seuil0,045

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,008
Tête enseignante GPT0,215
Écart entre enseignants0,207 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission2
Résumé présentoui

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