Online Tuning of Extended Kalman Filter Using Reinforcement Learning for Improved Battery State-of-Charge Estimation
Author:
Affiliation:
1. Aalborg University,AAU Energy,Aalborg,Denmark
2. McMaster University,Department of Mechanical Engineering,Hamilton,Ontario,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10540646/10540608/10540773.pdf?arnumber=10540773
Reference15 articles.
1. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations
2. State of charge estimation of lithium‐ion battery based on extended Kalman filter and unscented Kalman filter techniques
3. Lithium-ion battery state of charge estimation with a Kalman Filter based on a electrochemical model
4. A Novel Fractional Order Model for State of Charge Estimation in Lithium Ion Batteries
5. An Enhanced Equivalent Circuit Model With Real-Time Parameter Identification for Battery State-of-Charge Estimation
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