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Long-Term Health State Estimation of Energy Storage Lithium-Ion Battery Packs

Description:

This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.



From the Back Cover

This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.

About the Author

Qi Huang is the president of Southwest University of Science and Technology, China. He is an IEEE fellow (Conference Secretary General). He is an authoritative expert in the field of power systems and energy internet research. He is the head of NELab. He has published 2 Wiley-IEE monographs and more than 300 academic papers. He has applied for more than 100 patents, and he has been granted more than 60 national invention patents and 1 American patent.

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 deputy head of NELab, modeling, and state estimation strategy research for lithium-ion batteries. He has undertaken more than 40 projects and 30 patents, published more than 150 research papers as well as won 20 awards such as the Young Scholar and Science & Technology Progress Awards.

Zonghai Chen is a professor at the University of Science and Technologyof China, China. His research interests include energy saving and new energy vehicle technology, complex system modeling, simulation and control, fuel cell system management, and optimal control. He has published more than 400 academic papers and applied for more than 40 patents.

Ran Xiong is a postgraduate student at Southwest University of Science and Technology, China. He is one of the group leaders of NELab. He is responsible for the electrochemical modeling and the health state estimation of energy storage batteries in NELab. He has participated in 5 projects and 6 patents, assisted in writing 3 academic monographs, and published 4 research papers as the first author or corresponding author, including 3 SCI papers.

Carlos Fernandez is a senior lecturer at Robert Gordon University, Scotland. He received his Ph.D. in Electrocatalytic Reactions from The University of Hull and then worked as a consultant technologist in Hull and in a post-doctoral position in Manchester. His research interests include Analytical Chemistry, Sensors and Materials, and Renewable Energy.

Daniel-I. Stroe is an associate professor with AAU Energy, Aalborg University, Denmark, and the leader of the Batteries research group. He received his Ph.D. degree in lifetime modeling of lithium-ion batteries from Aalborg University in 2010. He has co-authored one book and over 150 scientific peer-review publications on battery performance, modeling, and state estimation. His research interests include energy storage systems for grid and e-mobility, lithium-based battery testing, modeling, lifetime estimation, and diagnostics.


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Long-Term Health State Estimation of Energy Storage Lithium-Ion Battery Packs

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Long-Term Health State Estimation of Energy Storage Lithium-Ion Battery Packs

Product ID: K981995343K
Condition: New
Long-Term Health State Estimation of Energy Storage Lithium-Ion Battery Packs-0
Type: Paperback

AED72529

Price includes VAT & Import Duties
Availability: In Stock

Quantity:

|

Order today to get by 7-14 business days

This item qualifies for free delivery

Returns & Warranty policies

Imported From: United Kingdom

At BOLO, we work hard to ensure the products you receive are new, genuine, and sourced from reputable suppliers.

BOLO is not an authorized or official retailer for most brands, nor are we affiliated with manufacturers unless specifically stated on a product page. Instead, we source verified sellers, authorized distributors or directly from the manufacturer.

Each product undergoes thorough inspection and verification at our consolidation and fulfilment centers to ensure it meets our strict authenticity and quality standards before being shipped and delivered to you.

If you ever have concerns regarding the authenticity of a product purchased from us, please contact Bolo Support. We will review your inquiry promptly and, if necessary, provide documentation verifying authenticity or offer a suitable resolution.

Your trust is our top priority, and we are committed to maintaining transparency and integrity in every transaction.

All product information, images, descriptions, and reviews originate from the manufacturer or from trusted sellers overseas. BOLO is not affiliated with, endorsed by, or an authorized retailer for most brands listed on our website unless stated otherwise.

While we strive to display accurate information, variations in packaging, labeling, instructions, or formulation may occasionally occur due to regional differences or supplier updates. For detailed or manufacturer-specific information, please contact the brand directly or reach out to BOLO Support for assistance.

Unless otherwise stated, all prices displayed on the product page include applicable taxes and import duties.

BOLO operates in accordance with the laws and regulations of United Arab Emirates. Any items found to be restricted or prohibited for sale within the UAE will be cancelled prior to shipment. We take proactive measures to ensure that only products permitted for sale in United Arab Emirates are listed on our website.

All items are shipped by air, and any products classified as “Dangerous Goods (DG)” under IATA regulations will be removed from the order and cancelled.

All orders are processed manually, and we make every effort to process them promptly once confirmed. Products cancelled due to the above reasons will be permanently removed from listings across the website.

Description:

This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.



From the Back Cover

This book investigates in detail long-term health state estimation technology of energy storage systems, assessing its potential use to replace common filtering methods that constructs by equivalent circuit model with a data-driven method combined with electrochemical modeling, which can reflect the battery internal characteristics, the battery degradation modes, and the battery pack health state. Studies on long-term health state estimation have attracted engineers and scientists from various disciplines, such as electrical engineering, materials, automation, energy, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of extraction for health indicators and the significant influence of electrochemical modeling and data-driven issues in the design and optimization of health state estimation in energy storage systems. The book is intended for undergraduate and graduate students who are interested in new energy measurement and control technology, researchers investigating energy storage systems, and structure/circuit design engineers working on energy storage cell and pack.

About the Author

Qi Huang is the president of Southwest University of Science and Technology, China. He is an IEEE fellow (Conference Secretary General). He is an authoritative expert in the field of power systems and energy internet research. He is the head of NELab. He has published 2 Wiley-IEE monographs and more than 300 academic papers. He has applied for more than 100 patents, and he has been granted more than 60 national invention patents and 1 American patent.

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 deputy head of NELab, modeling, and state estimation strategy research for lithium-ion batteries. He has undertaken more than 40 projects and 30 patents, published more than 150 research papers as well as won 20 awards such as the Young Scholar and Science & Technology Progress Awards.

Zonghai Chen is a professor at the University of Science and Technologyof China, China. His research interests include energy saving and new energy vehicle technology, complex system modeling, simulation and control, fuel cell system management, and optimal control. He has published more than 400 academic papers and applied for more than 40 patents.

Ran Xiong is a postgraduate student at Southwest University of Science and Technology, China. He is one of the group leaders of NELab. He is responsible for the electrochemical modeling and the health state estimation of energy storage batteries in NELab. He has participated in 5 projects and 6 patents, assisted in writing 3 academic monographs, and published 4 research papers as the first author or corresponding author, including 3 SCI papers.

Carlos Fernandez is a senior lecturer at Robert Gordon University, Scotland. He received his Ph.D. in Electrocatalytic Reactions from The University of Hull and then worked as a consultant technologist in Hull and in a post-doctoral position in Manchester. His research interests include Analytical Chemistry, Sensors and Materials, and Renewable Energy.

Daniel-I. Stroe is an associate professor with AAU Energy, Aalborg University, Denmark, and the leader of the Batteries research group. He received his Ph.D. degree in lifetime modeling of lithium-ion batteries from Aalborg University in 2010. He has co-authored one book and over 150 scientific peer-review publications on battery performance, modeling, and state estimation. His research interests include energy storage systems for grid and e-mobility, lithium-based battery testing, modeling, lifetime estimation, and diagnostics.


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