Smart Safety Management of Energy Storage Batteries
- 1st Edition - September 1, 2025
- Imprint: Elsevier
- Authors: Shunli Wang, Yanxin Xie, Guangchen Liu, Qi Huang, Yujie Wang, Gexiang Zhang, Carlos Fernandez
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 7 5 7 8 - 4
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 7 5 7 9 - 1
Smart Safety Management of Energy Storage Batteries addresses battery management in new power systems which is an important component of the new generation of information techno… Read more
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Request a sales quoteSmart Safety Management of Energy Storage Batteries addresses battery management in new power systems which is an important component of the new generation of information technology and power systems. This book covers the application of this new type of power storage as well as power system identification modeling, intelligent energy storage battery status evaluation, and key technologies in intelligent management monitoring. Written for researchers, engineers, and students studying related areas, this book supports research in control science and control, automation, and electrical engineering, and serves as a technical reference for the application of new electric energy storage battery science and technology.
- Contains technical references for system design and application
- Addresses battery equivalent modeling, including electrical circuit modeling and parameter identification theory
- Includes coverage of battery state estimation methods such as state of charge estimation, state of health estimation, and state-of-charge and state-of-health co-estimation
Researchers, engineers, and students studying related areas
1. Introduction
2. Power Storage Battery Testing
3. Smart Energy Modeling Analysis
4. Intelligent Core Algorithm for Predicting the State of Energy Storage Batteries
5. SOC Estimation of Energy Storage Battery Based on LSTM Neural Network
6. Data-driven SOH Estimation for Energy Storage Battery Clusters
7. Battery Peak Power Eestimation Based on Long and Short Term Memory Networks
8. Design and Optimization of Energy State Assessment Algorithms for Energy Storage Batteries
9. Improved Firefly Optimized Method for Lithium-ion Batteries of the Co-Estimation of SOC and SOH
10. Joint Estimation of SOC and SOP for Lithium-ion Battery Based on H∞ Filtering
11. Battery RUL Prediction Based on Multicore Correlation Vector Machine
12. Intelligent Balancing Management of New Power Storage Batteries
2. Power Storage Battery Testing
3. Smart Energy Modeling Analysis
4. Intelligent Core Algorithm for Predicting the State of Energy Storage Batteries
5. SOC Estimation of Energy Storage Battery Based on LSTM Neural Network
6. Data-driven SOH Estimation for Energy Storage Battery Clusters
7. Battery Peak Power Eestimation Based on Long and Short Term Memory Networks
8. Design and Optimization of Energy State Assessment Algorithms for Energy Storage Batteries
9. Improved Firefly Optimized Method for Lithium-ion Batteries of the Co-Estimation of SOC and SOH
10. Joint Estimation of SOC and SOP for Lithium-ion Battery Based on H∞ Filtering
11. Battery RUL Prediction Based on Multicore Correlation Vector Machine
12. Intelligent Balancing Management of New Power Storage Batteries
- Edition: 1
- Published: September 1, 2025
- No. of pages (Paperback): 541
- No. of pages (eBook): 541
- Imprint: Elsevier
- Language: English
- Paperback ISBN: 9780443275784
- eBook ISBN: 9780443275791
SW
Shunli Wang
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.
Affiliations and expertise
Southwest University of Science and Technology, ChinaYX
Yanxin Xie
Yanxin Xie is a PhD student of Southwest University of Science and Technology, China. Her research direction is new energy measurement and control, and she has long been engaged in modeling, and state estimation strategy research for lithium-ion batteries. She has published 4 papers, applied for 6 intellectual property rights, granted 4 authorizations, participated in 6 projects, won 1 national scholarship, 1 first-class scholarship, and 1 second-class scholarship.
Affiliations and expertise
PhD Student, Southwest University of Science and Technology, ChinaGL
Guangchen Liu
Guangchen Liu is a professor at the Inner Mongolia University of Technology, China. He is an expert in power converter for renewable energy and energy storage. He is the director of Engineering Research Center of Large Energy Storage Technology, Ministry of Education (LEST), materials and devices, detection , control and safe operation of large energy Storage. He has undertaken 6 projects, published 73 research articles.
Previous Publications.Affiliations and expertise
Professor, Inner Mongolia University of Technology, ChinaQH
Qi Huang
Qi Huang is the president of Southwest University of Science and Technology, China. He is a professor, IEEE Fellow, IET Fellow. He is an authoritative expert in the field of new energy research. He is the head of NELab. He has undertaken more than 20 projects, published more than 300 academic papers, applied for more than 100 patents. He has won 1 first prize of China Instrument Society, 1 second prize of Sichuan Province Science and Technology Progress Award and 1 second prize of Ministry of Education Excellent scientific and Technological achievements.
Affiliations and expertise
President of Southwest University of Science and Technology, ChinaYW
Yujie Wang
Yujie Wang is an associate professor at the Department of Automation, University of Science and Technology of China. His research interests include new energy vehicle technology, battery safety management, digital twin and AI application in energy system. He received his Ph.D. degree in Control science and engineering from the University of Science and Technology of China in 2017. He has co-authored over 60 SCI journal papers on battery-related topics. His research interests include energy-saving and new energy vehicle technology, complex system modeling, simulation and control, fuel cell system management, and optimal control.
Affiliations and expertise
Department of Automation, University of Science and Technology of China, ChinaGZ
Gexiang Zhang
Gexiang Zhang is Foreign Academician of the Russian Academy of Natural Sciences, IET Fellow, and President of the International Membrane Computing Society. He mainly engages in research work in artificial intelligence, intelligent robots, smart grids, and intelligent control. He pioneered the establishment of multiple research platforms such as IMCS and JMC; The publication of 'Application of Membrane Computing in Real Life' fills the gap in practical works in the field of membrane computing worldwide.
Affiliations and expertise
Professor, Chengdu University of Information Engineering, ChinaCF
Carlos Fernandez
Carlos Fernandez is a senior lecturer at Robert Gordon University, Scotland, UK. He received his Ph.D. in Electrocatalytic Reactions from The University of Hull and then worked as a Consultant Technologist in Hull and a post-doctoral position in Manchester. His research interests include Analytical Chemistry, Sensors and Materials, and Renewable Energy.
Affiliations and expertise
Robert Gordon University, Aberdeen, UK