Cascaded Use and Sustainable Management of Lithium-ion Batteries in Mobility and Stationary Power
Notice bibliographique
Résumé
The purpose of this thesis is to assess —from a life cycle perspective — the environmental benefits of re-purposing electric vehicle Li-ion batteries to re-use in stationary applications. \nThe thesis consists of three separate papers arranged in as chapters. The main objectives are threefold: to develop and analyze a parameterized life cycle model of Li-ion battery first use in EV and extended usage to incorporate the re-purposing and re-use in grid storage for a utility application (Chapter 3), to evaluate effective factors on the feasibility of re-purposing used EV Li-ion batteries and the effect of factors on the cumulative energy use and greenhouse gas (GHG) emissions of the re-purposed batteries life cycle (Chapter 4)., and to assess potential environmental impacts of re-purposing and re-using of EV Li-ion batteries into stationary applications from a life cycle perspective and compare with natural gas stationary power generation (Chapter 5). \nAccording to the study, it is found that the magnitude of CO2 mitigation associated with battery re-use is similar to that of switching from using a conventional vehicle to an electric vehicle, meaning that the GHG benefits of vehicle electrification could be doubled by extending the life of EV batteries, and better using off-peak low-cost clean electricity. \nthe effects of capacity fade, energy efficiency fade, failure rate, and charge/discharge profile are investigated for Li-ion batteries based on first use in EVs and second-use in ESS. It is estimated that the re-purposed EV battery loses a further 15% of its capacity after its second use in the energy storage system (ESS) over 10 years. As energy efficiency decreases with increased charge/discharge cycles, a capacity fade model is used to approximate the effect of the relationship between cycles and capacity fade over the life of the battery. The performance of the \niiii \nbattery in its second use is represented using a model of degradation modes, assuming a 0.01% cell failure rate and a non-symmetric charge/discharge profile. Finally, an accurate modeling of battery performance is used to examine energy savings and GHG emission reduction benefits from using a Li-ion battery first in an EV and then in an ESS connected to the Ontario electrical grid. \nA cradle-to-grave life cycle assessment (LCA) of the Li-ion battery pack is conducted and six environmental impact categories are assessed including global warming potential, particulate matter formation, freshwater eutrophication, photochemical oxidant formation potential, metal depletion, and fossil depletion. It is concluded that the manufacturing phase of the Li-ion battery has the main environmental impacts during the life cycle of the battery as concluded from. Utilizing the re-purposed Li-ion battery in contrast with natural gas source in the stationary application powering causes more savings from an environmental standpoint. The assessed environmental impacts highlight the importance of electricity mix used in the processes of the product systems. Finally, the effect of the battery degradation is analyzed through energy efficiency fade effect on the battery performance and it is found that the use phase of the battery in the EV during 8 years is more sensitive to this phenomenon than the re-using of the Li-ion batteries in the stationary application during additional 10 years.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».