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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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Clean Energy Technology and Energy Storage Systems : 8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024, Suzhou, China, September 13–15, 2024, Proceedings, Part III / / edited by Kang Li, Kailong Liu, Yukun Hu, Mao Tan, Long Zhang, Zhile Yang
| Clean Energy Technology and Energy Storage Systems : 8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024, Suzhou, China, September 13–15, 2024, Proceedings, Part III / / edited by Kang Li, Kailong Liu, Yukun Hu, Mao Tan, Long Zhang, Zhile Yang |
| Autore | Li Kang |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (404 pages) |
| Disciplina | 003.3 |
| Altri autori (Persone) |
LiuKailong
HuYukun TanMao ZhangLong YangZhile |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer simulation
Computer networks Machine learning Computers, Special purpose Computer science - Mathematics Application software Computer Modelling Computer Communication Networks Machine Learning Special Purpose and Application-Based Systems Mathematics of Computing Computer and Information Systems Applications |
| ISBN | 9789819602322 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910983395203321 |
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Li Kang
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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