
Battery System Modeling
- 1st Edition - June 23, 2021
- Imprint: Elsevier
- Authors: Shunli Wang, Carlos Fernandez, Yu Chunmei, Yongcun Fan, Cao Wen, Daniel-Ioan Stroe, Zonghai Chen
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 4 7 2 - 8
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 4 3 3 - 9
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 model… Read more

Purchase options

Institutional subscription on ScienceDirect
Request a sales quoteBattery 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.
- Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling
- Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation
- Provides a dedicated chapter on active control strategies
Researchers and engineers of all levels of experience working on energy storage and batteries, specifically those related to lithium ion batteries, energy storage devices, and battery management systems. Graduate students and industry engineers involved in lithium ion batteries, energy storage devices, and battery management systems
- Cover image
- Title page
- Table of Contents
- Copyright
- Chapter 1: Lithium-ion battery characteristics and applications
- Abstract
- 1.1: Introduction to lithium-ion battery technology
- 1.2: Battery working mechanism
- 1.3: Lithium-ion battery chemistries
- 1.4: Lithium-ion battery characteristics
- 1.5: Battery aging behavior
- 1.6: Lithium-ion battery applications
- 1.7: Conclusion
- Chapter 2: Electrical equivalent circuit modeling
- Abstract
- 2.1: Modeling method overview
- 2.2: Improved internal resistance modeling
- 2.3: Thevenin modeling
- 2.4: High-order modeling
- 2.5: Parameter identification algorithms
- 2.6: Experimental analysis
- 2.7: Conclusion
- Chapter 3: Electrochemical Nernst modeling
- Abstract
- 3.1: Nernst modeling and improvement
- 3.2: Modeling realization
- 3.3: Model parameter identification
- 3.4: Experimental verification
- 3.5: Conclusion
- Chapter 4: Battery state estimation methods
- Abstract
- 4.1: State parameter identification
- 4.2: Battery state influencing factors
- 4.3: Traditional state estimation methods
- 4.4: Machine learning algorithms
- 4.5: Conclusion
- Chapter 5: Battery state-of-charge estimation methods
- Abstract
- 5.1: Introduction
- 5.2: State-of-charge estimation methods
- 5.3: Iterative calculation and modeling
- 5.4: Experimental result analysis
- 5.5: Conclusion
- Chapter 6: Battery state-of-energy prediction methods
- Abstract
- 6.1: Overview
- 6.2: Iterative algorithm and realization
- 6.3: Improved prediction and correction
- 6.4: Experimental results analysis
- 6.5: Conclusion
- Chapter 7: Battery state-of-power evaluation methods
- Abstract
- 7.1: State-space model construction
- 7.2: State estimation structural design
- 7.3: Calculation procedure design
- 7.4: Experimental analysis
- 7.5: Conclusion
- Chapter 8: Battery state-of-health estimation methods
- Abstract
- 8.1: Equivalent modeling and description
- 8.2: Particle filtering algorithm
- 8.3: Estimation modeling process
- 8.4: Whole life-cycle experiments
- 8.5: Conclusion
- Chapter 9: Battery system active control strategies
- Abstract
- 9.1: Overview of battery management systems
- 9.2: Charging strategies for capacity extension
- 9.3: Balancing control methods
- 9.4: Temperature adjustment
- 9.5: Conclusion
- Index
- Edition: 1
- Published: June 23, 2021
- Imprint: Elsevier
- No. of pages: 354
- Language: English
- Paperback ISBN: 9780323904728
- eBook ISBN: 9780323904339
SW
Shunli Wang
CF
Carlos Fernandez
YC
Yu Chunmei
YF
Yongcun Fan
CW
Cao Wen
DS
Daniel-Ioan Stroe
ZC