Fuzzy Filter-Based State of Energy Estimation for Lithium-Ion Batteries
Innbundet /
2024
/ Engelsk
Product details
ISBN
9781527570665
Published
2024-03-22
Publisher
Cambridge Scholars Publishing; Cambridge Scholars Publishing
Height
212 mm
Width
148 mm
Age
P, 06
Language
Product language
Engelsk
Format
Product format
Innbundet
Number of pages
140
Biographical note
Shunli Wang is a professor at Southwest University of Science and Technology, China. His research largely focuses on green and low-carbon energy storage in smart grids, and has won 13 awards including the second prize of the Automation Association, China.Yujie Wang is an associate professor at the University of Science and Technology of China. Wang specializes in research areas such as energy conservation and new energy vehicle technology, battery safety control, and digital twins. Xiao Yang is a doctoral student at Southwest Jiaotong University, China. His research focuses on battery safety management.Carlos Fernandez is a senior lecturer at Robert Gordon University, Scotland. His research interests include analytical chemistry, sensors and materials, and renewable energy.Josep M. Guerrero is a professor at the University of Aalborg, Denmark. His research interests include artificial intelligence based on neuroscience, digital twins, cybersecurity, blockchain and traded energy in maritime, aerospace, and space electrification.
Awareness of the safety issues of lithium-ion batteries is crucial in the development of new energy technologies, and real-time and high-precision State of Energy (SOE) estimation is not only a prerequisite for battery safety, but also serves as the basis for predicting the remaining driving range of electric vehicles and aircrafts. In order to achieve real-time and accurate estimation of the energy state of lithium-ion batteries, this book improves the calculation method of the open-circuit voltage in the traditional second-order RC equivalent circuit model. It also combines a fuzzy controller and a dual-weighted multi-innovation algorithm to optimize the traditional Centralized Kalman Filter (CKF) algorithm in terms of the aspects of convergence speed, estimation accuracy, and algorithm robustness. This enables the precise estimation of SOE and the maximum available energy. The content of this book provides theoretical support for the development of new energy initiatives.
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Product details
ISBN
9781527570665
Published
2024-03-22
Publisher
Cambridge Scholars Publishing; Cambridge Scholars Publishing
Height
212 mm
Width
148 mm
Age
P, 06
Language
Product language
Engelsk
Format
Product format
Innbundet
Number of pages
140