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[null,"1.","Record Nr.",null,"UNINA9911007155703321"]
[null,null,"Autore",null,"Wang Shunli"]
[null,null,"Titolo",null,"AI for Status Monitoring of Utility Scale Batteries"]
[null,null,"Pubbl/distr/stampa",null,"Stevenage : , : Institution of Engineering & Technology, , 2023"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"1-83724-508-8"]
[{"$nulls":4},"1-5231-5354-7"]
[{"$nulls":4},"1-83953-739-6"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (385 pages)"]
[null,null,"Collana",null,"Energy Engineering"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Machine learning"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Cover -- Halftitle Page -- Series Page -- Title Page -- Copyright -- Contents -- About the Authors -- Foreword -- Preface -- List of contributors -- 1\tIntroduction --   \t1.1\tMotivation for utility-scale battery deployment --   \t1.2\tDefinition of AI in the context of battery management --   \t1.3\tAdvantages of using AI for battery management -- 2\tUtility-­scale lithium-­ion battery system characteristics --   \t2.1\tOverview of lithium-ion batteries --     \t2.1.1\tBattery working principle --     \t2.1.2\tPrinciples of status monitoring of utility-scale batteries --   \t2.2\tLithium-ion batteries --     \t2.2.1\tLithium iron phosphate batteries --     \t2.2.2\tLithium cobaltate oxide batteries --     \t2.2.3\tLithium manganese oxide batteries --   \t2.3\tLarge capacity lithium-ion batteries --     \t2.3.1\tApplication areas of utility-scale batteries --     \t2.3.2\tCharacteristics of utility-scale battery systems --     \t2.3.3\tOperational challenges of utility-scale battery systems -- 3\tAI-­based equivalent modeling and parameter identification --   \t3.1\tOverview of battery equivalent circuit modeling --   \t3.2\tModeling types and concepts --   \t3.3\tEquivalent circuit modeling methods"]
[null,null,null,"Sommario/riassunto","Utility-scale Li-ion batteries are poised to play key roles for the clean energy system, but their failure has severe effects. AI can help with their monitoring and management. This work covers machine learning, neural networks, and deep learning, for battery modeling."]