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Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries
by
Mahmoud, Karar
, Dawson, James A.
, Al-Gabalawy, Mostafa
, Lehtonen, Matti
, Darwish, Mohamed M.F.
, Hosny, Nesreen S.
in
Accuracy
/ Aging
/ Algorithms
/ Artificial intelligence
/ batteries modeling
/ dual extend Kalman filter (DEKF)
/ Heat
/ lithium-iron-phosphate battery
/ Mathematical models
/ Optimization techniques
/ Parameter identification
/ state of charge (SOC)
/ state of health (SOH)
/ Temperature effects
/ Variables
2021
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Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries
by
Mahmoud, Karar
, Dawson, James A.
, Al-Gabalawy, Mostafa
, Lehtonen, Matti
, Darwish, Mohamed M.F.
, Hosny, Nesreen S.
in
Accuracy
/ Aging
/ Algorithms
/ Artificial intelligence
/ batteries modeling
/ dual extend Kalman filter (DEKF)
/ Heat
/ lithium-iron-phosphate battery
/ Mathematical models
/ Optimization techniques
/ Parameter identification
/ state of charge (SOC)
/ state of health (SOH)
/ Temperature effects
/ Variables
2021
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Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries
by
Mahmoud, Karar
, Dawson, James A.
, Al-Gabalawy, Mostafa
, Lehtonen, Matti
, Darwish, Mohamed M.F.
, Hosny, Nesreen S.
in
Accuracy
/ Aging
/ Algorithms
/ Artificial intelligence
/ batteries modeling
/ dual extend Kalman filter (DEKF)
/ Heat
/ lithium-iron-phosphate battery
/ Mathematical models
/ Optimization techniques
/ Parameter identification
/ state of charge (SOC)
/ state of health (SOH)
/ Temperature effects
/ Variables
2021
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Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries
Journal Article
Reliable and Robust Observer for Simultaneously Estimating State-of-Charge and State-of-Health of LiFePO4 Batteries
2021
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Overview
Batteries are everywhere, in all forms of transportation, electronics, and constitute a method to store clean energy. Among the diverse types available, the lithium-iron-phosphate (LiFePO4) battery stands out for its common usage in many applications. For the battery’s safe operation, the state of charge (SOC) and state of health (SOH) estimations are essential. Therefore, a reliable and robust observer is proposed in this paper which could estimate the SOC and SOH of LiFePO4 batteries simultaneously with high accuracy rates. For this purpose, a battery model was developed by establishing an equivalent-circuit model with the ambient temperature and the current as inputs, while the measured output was adopted to be the voltage where current and terminal voltage sensors are utilized. Another vital contribution is formulating a comprehensive model that combines three parts: a thermal model, an electrical model, and an aging model. To ensure high accuracy rates of the proposed observer, we adopt the use of the dual extend Kalman filter (DEKF) for the SOC and SOH estimation of LiFePO4 batteries. To test the effectiveness of the proposed observer, various simulations and test cases were performed where the construction of the battery system and the simulation were done using MATLAB. The findings confirm that the best observer was a voltage-temperature (VT) observer, which could observe SOC accurately with great robustness, while an open-loop observer was used to observe the SOH. Furthermore, the robustness of the designed observer was proved by simulating ill-conditions that involve wrong initial estimates and wrong model parameters. The results demonstrate the reliability and robustness of the proposed observer for simultaneously estimating the SOC and SOH of LiFePO4 batteries.
Publisher
MDPI AG
Subject
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