State of Charge Estimation of Power Lithium-ion Battery Based on a Variable Forgetting Factor Adaptive Kalman Filter
Author:
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
Reference44 articles.
1. An Overview and Comparison of Online Implementable SoC Estimation Methods for Lithium-Ion Battery;Meng;IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS,2018
2. Research on Modeling, State Estimation and Management Strategy of Power Lithium-ion Batteries;Wang,2017
3. Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries;Shrivastava;Renew. Sustain. Energy Rev.,2019
4. A brief review on key technologies in the battery management system of electric vehicles;Liu;Front. Mech. Eng.,2019
5. An Improved Coulomb Counting Approach Based on Numerical Iteration for SoC Estimation With Real-Time Error Correction Ability;He;IEEE ACCESS,2019
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