Sensorless Coestimation of Temperature and State-of-Charge for Lithium-Ion Batteries Based on a Coupled Electrothermal Model

Accurate estimations of the temperature and the state-of-charge (SOC) are of extreme importance for the safety of lithium-ion battery operation. Traditional battery temperature and SOC estimation methods often omit the relation between battery temperature and SOC, which may lead to significant error...

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Bibliographic Details
Published in:International journal of energy research 2023-02, Vol.2023, p.1-18
Main Authors: Bai, Wenyuan, Zhang, Xinhui, Gao, Zhen, Xie, Shuyu, Peng, Ke, Chen, Yu
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analytical methods
Batteries
Electric charge
Electric vehicles
Electrochemical impedance spectroscopy
Electrochemistry
Energy storage
Errors
Estimation
Extended Kalman filter
Heat
Kalman filters
Lithium
Lithium-ion batteries
Neural networks
Parameter identification
Product safety
Rechargeable batteries
Sensors
Spectroscopy
State of charge
Temperature
Temperature effects
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Summary:Accurate estimations of the temperature and the state-of-charge (SOC) are of extreme importance for the safety of lithium-ion battery operation. Traditional battery temperature and SOC estimation methods often omit the relation between battery temperature and SOC, which may lead to significant errors in the estimations. This study presents a coupled electrothermal battery model and a coestimation method for simultaneously estimating the temperature and SOC of lithium-ion batteries. The coestimation method is performed by a coupled model-based dual extended Kalman filter (DEKF). The coupled estimators utilizing electrochemical impedance spectroscopy (EIS) measurements, rather than utilizing direct battery surface measurements, are adopted to estimate the battery temperature and SOC, respectively. The information being exchanged between the temperature estimator and the SOC estimator effectively improves the estimation accuracy. Extensive experiments show that, in contrast with the EKF-based separate estimation method, the DEKF-based coestimation method is more favorable in reducing errors for estimating both the temperature and SOC even if the battery core temperature has increased by 17°C or more during the process of test.
ISSN:0363-907X
1099-114X
DOI:10.1155/2023/4021256