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Battery system modeling /

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....

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Wang, Shunli (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, 2021.
Temas:
Acceso en línea:Texto completo

MARC

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082 0 4 |a 621.312424  |2 23 
100 1 |a Wang, Shunli,  |e author. 
245 1 0 |a Battery system modeling /  |c Shunli Wang [and six others]. 
264 1 |a Amsterdam :  |b Elsevier,  |c 2021. 
300 |a 1 online resource :  |b illustrations 
336 |a text  |2 rdacontent 
336 |a still image  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
520 |a 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. 
505 0 |a Intro -- Battery System Modeling -- Copyright -- Contents -- Chapter 1: Lithium-ion battery characteristics and applications -- 1.1. Introduction to lithium-ion battery technology -- 1.1.1. Development history -- 1.1.2. Energy storage technologies -- 1.2. Battery working mechanism -- 1.2.1. Characteristic analysis -- 1.2.2. Components and working principle -- 1.2.3. Lithium-ion battery construction -- 1.2.4. Charge-discharge strategies -- 1.3. Lithium-ion battery chemistries -- 1.3.1. Lithium-ion battery family -- 1.3.2. Battery with different materials 
505 8 |a 1.3.3. Solid-state lithium-ion battery -- 1.3.4. Comparative battery types analysis -- 1.4. Lithium-ion battery characteristics -- 1.4.1. Internal parameter relationship -- 1.4.2. Capacity characteristics -- 1.4.3. Open-circuit voltage -- 1.4.4. Internal resistance characteristic -- 1.4.5. Power capability variation -- 1.4.6. Coulombic efficiency -- 1.5. Battery aging behavior -- 1.5.1. Aging mechanisms -- 1.5.2. Calendar aging process -- 1.5.3. Temperature effect on aging process -- 1.6. Lithium-ion battery applications -- 1.6.1. Applications -- 1.6.2. System state estimation 
505 8 |a 1.6.3. Battery safety protection -- 1.6.4. Battery life guarantee -- 1.6.5. Status and trends -- 1.7. Conclusion -- Acknowledgments -- Conflict of interest -- References -- Chapter 2: Electrical equivalent circuit modeling -- 2.1. Modeling method overview -- 2.1.1. Modeling types and concepts -- 2.1.2. Comparative equivalent models -- 2.1.3. Commercial circuit models -- 2.1.4. Electrochemical model -- 2.1.5. Equivalent circuit model -- 2.1.6. Principle description -- Modeling steps -- Model selection -- 2.1.7. Parameter identification -- 2.2. Improved internal resistance modeling 
505 8 |a 2.2.1. Theoretical resistance modeling -- 2.2.2. Battery model establishment -- 2.2.3. Internal resistance description -- 2.2.4. Open-circuit voltage characteristics -- 2.3. Thevenin modeling -- 2.3.1. Construction of Thevenin model -- 2.3.2. Charge-discharge characteristics -- 2.3.3. State equation establishment -- 2.3.4. Mathematical description -- 2.4. High-order modeling -- 2.4.1. Second-order circuit modeling -- 2.4.2. Internal resistance description -- 2.4.3. Splice equivalent modeling -- 2.5. Parameter identification algorithms -- 2.5.1. Identification overview 
505 8 |a 2.5.2. Least-square functional fitting -- 2.5.3. Forgetting factor correction -- 2.6. Experimental analysis -- 2.6.1. Exponential curve fitting -- 2.6.2. Polynomial relationship description -- 2.6.3. Identified parameter variation -- 2.6.4. Pulse voltage tracking effect -- 2.6.5. Modeling accuracy verification -- 2.7. Conclusion -- Acknowledgments -- Conflict of interest -- References -- Chapter 3: Electrochemical Nernst modeling -- 3.1. Nernst modeling and improvement -- 3.1.1. Model building process -- 3.1.2. Parameter identification strategies -- 3.1.3. State-space description 
650 0 |a Lithium ion batteries  |x Design and construction. 
650 0 |a Lithium ion batteries  |x Mathematical models. 
650 6 |a Batteries au lithium-ion  |0 (CaQQLa)000276316  |x Mod�eles math�ematiques.  |0 (CaQQLa)201-0379082 
650 7 |a Lithium ion batteries.  |2 fast  |0 https://id.worldcat.org/fast/1764640 
650 7 |a Mathematical models.  |2 fast  |0 https://id.worldcat.org/fast/1012085 
776 0 8 |i Print version:  |z 0323904726 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780323904728  |z Texto completo