A Comprehensive Single-Phase, Non-Isothermal Mathematical MEA Model and Analysis of Non-Isothermal Effects
Notice bibliographique
Résumé
A comprehensive single-phase non-isothermal MEA model, which accounts for all applicable heat sources, viz., entropic and irreversible heating associated with electrochemical reactions, protonic and electronic ohmic heating, phase change, and heat release/absorption due to sorption/desorption of water in electrolyte is presented. Starting from a general energy transport equation, layer-specific thermal transport equations are derived. The model expands upon the isothermal model by Secanell et al. [1] and accounts for multi-step reaction kinetics for the oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR) [2]. The model accounts for water management in two phases, viz., vapour and sorbed phase, and accounts for thermal effects on water transport such as temperature driven vapour diffusion, and thermal osmosis. The model is integrated into openFCST, a finite element based, open-source, fuel cell simulation framework, which is available for download online at http://www.openfcst.mece.ualberta.ca/. The non-isothermal model is used to estimate the maximum temperature inside the membrane electrode assembly under different operating conditions such as hot and dry, and cold and wet. At low humidity conditions, the mathematical model predicts a significant performance drop in the cell due to drying out of ionomer. The cathode catalyst layer is found to be the hottest, with temperatures rising by more than 10ºC at high current densities (Figure 1). A detailed breakdown of various heat sources inside the cell at different current densities is also provided (Figure 2). It is observed that heat of sorption, which has generally been ignored in previous non-isothermal models, is more significant than protonic ohmic heating at medium current densities, and causes a shift in temperature distribution in the in-plane direction. At high current densities, heat of sorption accounts for roughly 15% of the overall heat generated in the cell, and it is concluded that this term cannot be ignored. There is ambiguity in the literature regarding reversible heat distribution between the half-cell reactions of the ORR and HOR [3]. Based on the data by Ramousse et al. [3], the HOR should be exothermic. This is contrary to the general practice of assuming the HOR to be athermic. Using the non-isothermal model with an exothermic HOR, it is shown that the assumption causes a cell performance drop and the maximum temperature of the cell to shift from the cathode catalyst layer (CCL) to anode catalyst layer (ACL). Thermal management strongly affects water transport in the cell. Therefore, the thermal transport equation is solved with a detailed water management model including thermal-osmosis. The non-isothermal model predicts higher sorbed water movement from the ACL to CCL due to drying out of ionomer in the CCL when compared to an isothermal model (Figure 3). The contribution of thermal osmosis to sorbed water flux is as much as 15% as shown in Figure 3. The thermal conductivity of microporous layer is found to significantly influence the cell performance predictions. If reduced considerably, the model predicts self-heating of the MEA and a complete dryout of the cell (Figure 4). In summary, a detailed single-phase non-isothermal MEA model is developed. The non-isothermal fuel cell model governing equations include a thermal transport equation, a sorbed water transport equation, the mass and charge transport of all species, and multi-step kinetics for HOR and ORR electrochemical reactions. Using the model, the importance of several critical physical phenomena is analyzed. References [1] M. Secanell et al., Energy and Environmental Science, 1(3):378-388, 2008. [2] M. Moore et al., Journal of the Electrochemical Society, 161(8), 2014. [3] J. Ramousse et al., Journal of Power Sources, 192(2):435-441, 2009.
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) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
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 ».