Smart Safety Management of Energy Storage Batteries
Autor Shunli Wang, Yanxin Xie, Guangchen Liu, Qi Huang, Yujie Wang, Gexiang Zhang, Carlos Fernandezen Limba Engleză Paperback – sep 2025
- Contains technical references for system design and application
- Addresses battery equivalent modelling, including electrical circuit modelling and parameter identification theory
- Includes coverage of battery state estimation methods, including state of charge estimation, state of health estimation, and state-of-charge and state-of-health co-estimation
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Specificații
ISBN-13: 9780443275784
ISBN-10: 0443275785
Pagini: 541
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443275785
Pagini: 541
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE
Cuprins
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