Power battery state of charge estimation based on extended Kalman filter
Author:
Affiliation:
1. School of Electronic and Information, Northwestern Polytechnical University, Xi'an 710072, China
2. School of Electronic Information Engineering, Xi'an Technological University, Xi'an 710032, China
Funder
Shaanxi Provincial Key Research and Development Program-General Program
Shaanxi Provincial Key Research and Development Program-Key Program
Publisher
AIP Publishing
Subject
Renewable Energy, Sustainability and the Environment
Link
http://aip.scitation.org/doi/pdf/10.1063/1.5057894
Reference13 articles.
1. Evaluation on State of Charge Estimation of Batteries With Adaptive Extended Kalman Filter by Experiment Approach
2. Battery-Management System (BMS) and SOC Development for Electrical Vehicles
3. Relaxation model of the open‐circuit voltage for state‐of‐charge estimation in lithium‐ion batteries
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4. Improved Long Short-Term Memory: Statistical Regression Model for High Precision SOC Estimation of Lithium-Ion Batteries Adaptive to Complex Current Variation Conditions;Journal of The Electrochemical Society;2023-05-01
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