Highly robust co‐estimation of state of charge and state of health using recursive total least squares and unscented Kalman filter for lithium‐ion battery
Abstract State of charge (SOC) and state of health (SOH) constitute pivotal factors in the efficient and secure management of lithium‐ion batteries, particularly within the context of electric vehicles. A highly‐robust co‐estimation method is proposed in this paper to accurately assess the SOC and S...
Saved in:
Main Authors: | Xiaohui Li, Weidong Liu, Bin Liang, Qian Li, Yue Zhao, Jian Hu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2024-12-01
|
Series: | IET Renewable Power Generation |
Subjects: | |
Online Access: | https://doi.org/10.1049/rpg2.12965 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
State of charge estimation for lithium‐ion batteries based on square root sigma point Kalman filter considering temperature variations
by: Davoud Mahboubi, et al.
Published: (2022-09-01) -
A Dual Extended Kalman Filter for the State of Charge Estimation of Lithiumion Batteries
by: Ndayishimiye Christian, et al.
Published: (2023-12-01) -
Design of a Robust Unknown Input Observer for the State of Charge Estimation for Lithium-Ion Batteries
by: Omid Rezaei, et al.
Published: (2023-09-01) -
A Joint Forgetting Factor-Based Adaptive Extended Kalman Filtering Approach to Predict the State-of-Charge and Model Parameter of Lithium-Ion Battery
by: Satyaprakash Rout, et al.
Published: (2025-01-01) -
Lithium Battery Degradation and Failure Mechanisms: A State-of-the-Art Review
by: Joselyn Stephane Menye, et al.
Published: (2025-01-01)