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Cover: 9780323904728 | Battery System Modeling | Shunli Wang (u. a.) | Taschenbuch | Englisch
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Battery System Modeling
Taschenbuch von Cao Wen (u. a.)
Sprache: Englisch

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Beschreibung
Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates.
Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates.
Über den Autor
Shunli Wang is a professor at the Southwest University of Science and Technology, China. He is an authoritative expert in the field of new energy research. He is the head of DTlab, modeling, and state estimation strategy research for lithium-ion batteries. He has undertaken more than 40 projects and 30 patents, published more than 100 research papers as well as won 20 awards such as the Young Scholar, and Science & Technology Progress Awards.
Inhaltsverzeichnis

1. Li-ion Battery Characteristics and Applications 2. Electrical Equivalent Circuit Modeling 3. Electrochemical Nernst Modeling 4. Battery State Estimation Methods 5. Battery State-of-charge Estimation Methods 6. Battery State-of-energy Prediction Methods 7. Battery State-of-power Evaluation Methods 8. Battery State-of-health Estimation Methods 9. Battery System Active Control Strategies

Details
Erscheinungsjahr: 2021
Fachbereich: Kraftwerktechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780323904728
ISBN-10: 0323904726
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Wen, Cao
Fernandez, Carlos
Stroe, Daniel-Ioan
Wang, Shunli
Fan, Yongcun
Chunmei, Yu
Chen, Zonghai
Hersteller: Elsevier - Health Sciences Division
Maße: 201 x 231 x 22 mm
Von/Mit: Cao Wen (u. a.)
Erscheinungsdatum: 25.06.2021
Gewicht: 0,714 kg
Artikel-ID: 119696528
Über den Autor
Shunli Wang is a professor at the Southwest University of Science and Technology, China. He is an authoritative expert in the field of new energy research. He is the head of DTlab, modeling, and state estimation strategy research for lithium-ion batteries. He has undertaken more than 40 projects and 30 patents, published more than 100 research papers as well as won 20 awards such as the Young Scholar, and Science & Technology Progress Awards.
Inhaltsverzeichnis

1. Li-ion Battery Characteristics and Applications 2. Electrical Equivalent Circuit Modeling 3. Electrochemical Nernst Modeling 4. Battery State Estimation Methods 5. Battery State-of-charge Estimation Methods 6. Battery State-of-energy Prediction Methods 7. Battery State-of-power Evaluation Methods 8. Battery State-of-health Estimation Methods 9. Battery System Active Control Strategies

Details
Erscheinungsjahr: 2021
Fachbereich: Kraftwerktechnik
Genre: Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780323904728
ISBN-10: 0323904726
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Wen, Cao
Fernandez, Carlos
Stroe, Daniel-Ioan
Wang, Shunli
Fan, Yongcun
Chunmei, Yu
Chen, Zonghai
Hersteller: Elsevier - Health Sciences Division
Maße: 201 x 231 x 22 mm
Von/Mit: Cao Wen (u. a.)
Erscheinungsdatum: 25.06.2021
Gewicht: 0,714 kg
Artikel-ID: 119696528
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