Enhanced EKF and SVSF for state of charge estimation of Li‐ion battery in electric vehicle using a fuzzy parameters model
Author:
Affiliation:
1. Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS‐Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/els2.12056
Reference38 articles.
1. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations
2. Critical Review on the Battery State of Charge Estimation Methods for Electric Vehicles
3. State-of-the-Art and Energy Management System of Lithium-Ion Batteries in Electric Vehicle Applications: Issues and Recommendations
4. SoC Estimation of Li-Ion Battery Pack for Light Electric Vehicles using Enhanced Coulomb Counting Algorithm
5. Lithium-ion battery pack modeling using accurate OCV model: Application for SoC and SoH estimation
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1. High-precision state of charge estimation of electric vehicle lithium-ion battery energy storage system based on multi-scale optimized time-varying bounded smoothing variable structure filtering algorithm;Ionics;2024-07-04
2. On-line parameter identification and SOC estimation of nonlinear model of lithium-ion battery based on Wiener structure;Journal of Energy Storage;2024-07
3. A Review of the Resourceful Utilization Status for Decommissioned Power Batteries;Energies;2023-12-01
4. Enhanced SVSF for SoC Estimation of Lithium Ion Batteries;2023 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE);2023-10-12
5. An improved genetic-backpropagation neural network for state of charge estimation of lithium-ion batteries;2023 3rd New Energy and Energy Storage System Control Summit Forum (NEESSC);2023-09-26
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