Modeling, optimization and environmental assessment of electrified marine vessels
Notice bibliographique
Résumé
Electrified Vehicles (EVs), including Hybrid Electric Vehicles (HEVs) and Pure Electric Vehicles (PEVs), can provide substantial improvements in energy efficiency, emission reduction, and lifecycle cost over conventional vehicles solely powered by Internal Combustion Engines (ICE). Progress on electrification of marine vessels has been made, but the pace has been impacted by factors such as the different operational load profile of vessels, relatively small production levels and longer or varied lifetimes. In this dissertation, hybrid electric and pure electric propulsion system designs for fishing boats and passenger ferries are studied based on in-field acquired operational data. A new integrated marine propulsion system modeling and simulation method and a dedicated mobile data acquisition system have been introduced to analyze the energy efficiency, emission reduction, and lifecycle costs of new or retrofitted fishing boats and passenger ferries with hybrid electric and pure electric powertrains. Following the automotive industry Model Based Design (MBD) approach, modeling and simulation of electrified vessels using the acquired operation profile have been carried out using backward and forward-facing methods. Series hybrid electric and pure electric powertrain system designs with powertrain component models and rule-based system control, including a properly sized electric Energy Storage System (ESS) with a Supercapacitor (SC) or battery, have been studied. The total CO2 equivalent (CO2e) or Greenhouse Gas (GHG) emissions and lifecycle costs of various new, electrified vessel propulsion system designs have been evaluated. Clean propulsion system solutions for fishing boats and passenger ferries with detailed powertrain system and control system designs are given which provide a foundation for further research and development. \nThis dissertation also addresses the environmental impact of Natural Gas (NG) as a transportation fuel, particularly for marine transportation use. A systematic evaluation of GHG emissions is provided for the upstream fuel supply chain of natural gas fuel in British Columbia (BC), Canada. The Liquefied Natural Gas (LNG) lifecycle GHG emissions produced in both the upstream supply chain and the downstream vessel propulsion are estimated quantitatively using manufacturer data and propulsion system models of marine vessels. Extensive data have been collected from oil and gas companies that have active operations in BC to determine the upstream supply chain GHG emissions of the NG fuel under three scenarios. The energy efficiency and emissions of natural gas engines are compared with traditional diesel fuel marine engines and generators. The results obtained indicate that LNG fuel can lower CO2e by 10% to 28% with reduced local air pollutants such as sulfur oxides and particulates, compared to conventional diesel fuel. However, engine methane slip during combustion should be monitored as it can have a significant impact on the GHG emissions and so offset the environmental benefits of LNG.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 tête enseignante, 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 ».