State estimation strategies in lithium-ion battery management systems. (2023)

• Record Type: Book
• Further Information: Note: Shunli Wang [and five others].
• Authors: Wang, Shunli, 1985-; Liu, Kailong; Wang, Yujie; Stroe, Daniel-Ioan; Fernandez, Carlos; Guerrero, Josep M
• Contents: 1. Introduction to current research in estimation strategies and prediction algorithms; 2. Characteristic analysis of power lithium-ion batteries; 3. Aging characteristics of lithium-ion batteries; 4. Lithium-ion battery hysteresis characteristics and modeling; 5. Lithium-ion battery aging mechanism and multiple regression model; 6. Equivalent modeling and parameter identification of power lithium-ion batteries; 7. Equivalent modeling study of aviation lithium-ion batteries; 8. Battery SOC measurement and control model based on Internet platforms; 9. High energy density lithium-ion battery SOC prognosis; 10. SOC estimation strategy based on fractional-order model; 11. SOC estimation method for large unmanned aerial vehicles; 12. Construction of SOC estimation method for automotive ternary batteries; 13. Estimation strategies for SOC and SOP of lithium-ion batteries; 14. Collaborative energy and peak power status estimation; 15. SOH estimation based on improved double-extended Kalman filter; 16. Collaborative SOC and SOH estimation based on improved AUKF-UPF algorithm
• Publisher Details: Amsterdam : Elsevier
• Publication Date: 2023
• Extent: 1 online resource (400 pages)
• Subjects: 621.312424; Lithium ion batteries; Lithium ion batteries -- Mathematical models
• Languages: English
• ISBNs: 9780443161612
• Related ISBNs: 9780443161605
• Notes: Note: Description based on CIP data; resource not viewed.
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