| DOI | Trouver le DOI : https://doi.org/10.1016/j.ijhydene.2021.12.150 |
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| Auteur | Rechercher : Wang, Yunli1; Rechercher : Wang, SijiaIdentifiant ORCID : https://orcid.org/0000-0001-7334-8436; Rechercher : Decès-Petit, Cyrille2 |
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| Affiliation | - Conseil national de recherches du Canada. Technologies numériques
- Conseil national de recherches du Canada. Énergie, les mines et l'environnement
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| Format | Texte, Article |
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| Sujet | hydrogen refueling stations; measurement accuracy; Bayesian non-parametric methods |
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| Résumé | The ability to evaluate measurement error at hydrogen refueling stations plays a vital role in the sustainability of the hydrogen vehicle industry. Most previous work in this application investigates the measurement accuracy of mass flow meters in controlled experiments, using testing equipment. The focus of our work is to estimate the measurement accuracy of fueling using data from hydrogen refueling stations collected under real operation. Accuracy is estimated by comparing the observed mass count readings with reference mass counts calculated using the pressure-volume-temperature method. To quantify the measurement uncertainty, we propose using Dirichlet process mixture models, a class of Bayesian non-parametric methods. The Dirichlet process mixture model approach is tested on five hydrogen refueling stations in real operation. Our results show that the model is able to capture the complex structure of the data and successfully estimate the probability distribution of measurement uncertainty. Our work demonstrates the effectiveness of the Bayesian non-parametric approach for evaluating the measurement uncertainty of hydrogen refueling stations. |
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| Date de publication | 2022-01-05 |
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| Maison d’édition | Elsevier |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 2a45d6ef-ae0a-44b7-b696-6a123672c123 |
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| Enregistrement créé | 2022-01-18 |
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| Enregistrement modifié | 2022-03-25 |
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