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AI for Status Monitoring of Utility Scale Batteries
| AI for Status Monitoring of Utility Scale Batteries |
| Autore | Wang Shunli |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Stevenage : , : Institution of Engineering & Technology, , 2023 |
| Descrizione fisica | 1 online resource (385 pages) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
LiuKailong
WangYujie StroeDaniel-Ioan FernándezCarlos (Lecturer in Analytical Chemistry) GuerreroJosep M |
| Collana | Energy Engineering |
| Soggetto topico | Machine learning |
| ISBN |
1-83724-508-8
1-5231-5354-7 1-83953-739-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cover -- Halftitle Page -- Series Page -- Title Page -- Copyright -- Contents -- About the Authors -- Foreword -- Preface -- List of contributors -- 1 Introduction -- 1.1 Motivation for utility-scale battery deployment -- 1.2 Definition of AI in the context of battery management -- 1.3 Advantages of using AI for battery management -- 2 Utility-scale lithium-ion battery system characteristics -- 2.1 Overview of lithium-ion batteries -- 2.1.1 Battery working principle -- 2.1.2 Principles of status monitoring of utility-scale batteries -- 2.2 Lithium-ion batteries -- 2.2.1 Lithium iron phosphate batteries -- 2.2.2 Lithium cobaltate oxide batteries -- 2.2.3 Lithium manganese oxide batteries -- 2.3 Large capacity lithium-ion batteries -- 2.3.1 Application areas of utility-scale batteries -- 2.3.2 Characteristics of utility-scale battery systems -- 2.3.3 Operational challenges of utility-scale battery systems -- 3 AI-based equivalent modeling and parameter identification -- 3.1 Overview of battery equivalent circuit modeling -- 3.2 Modeling types and concepts -- 3.3 Equivalent circuit modeling methods |
| Record Nr. | UNINA-9911007155703321 |
Wang Shunli
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| Stevenage : , : Institution of Engineering & Technology, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization / / Kailong Liu, Yujie Wang, Xin Lai
| Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization / / Kailong Liu, Yujie Wang, Xin Lai |
| Autore | Liu Kailong |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2022 |
| Descrizione fisica | 1 online resource (277 p.) : illustrations (chiefly color) |
| Altri autori (Persone) |
WangYujie
LaiXin |
| Collana | Green Energy and Technology |
| Soggetto topico |
Battery management systems
Lithium ion batteries |
| ISBN | 3-031-01340-9 |
| Classificazione | COM018000TEC021000TEC031000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction to Battery Full-Lifespan Management --Chapter 2. Key Stages for Battery Full-Lifespan Management --Chapter 3. Data Science-based Battery Manufacturing Management --Chapter 4. Data Science-based Battery Operation Management I --Chapter 5. Data Science-based Battery Operation Management II --Chapter 6. Data Science-based Battery Reutilization Management --Chapter 7. The Ways Ahead. |
| Record Nr. | UNINA-9910558694203321 |
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Liu Kailong
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| Cham, : Springer International Publishing AG, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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