Enhancing Stability and Robustness of State-of-Charge Estimation for Lithium-Ion Batteries by Using Improved Adaptive Kalman Filter Algorithms
The traditional Kalman filter algorithms have disadvantages of poor stability (the program cannot converge or crash), robustness (sensitive to the initial errors) and accuracy, partially resulted from the fact that noise covariance matrices in the algorithms need to be set artificially. To overcome...
Main Authors: | Fan Zhang, Lele Yin, Jianqiang Kang |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-10-01
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Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/14/19/6284 |
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