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The Power State Estimation Method for High Energy Ternary Lithium-ion Batteries Based on the Online Collaborative Equivalent Modeling and Adaptive Correction - Unscented Kalman Filter

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Shunli Wang at Smart Energy Storage Institute
Shunli Wang
  • Smart Energy Storage Institute
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Abstract

Accurate power state estimation plays an important role in the real-time working state monitoring and safety control of high energy lithium-ion batteries. To solve the difficulty and low accuracy problems in its real-time power state estimation under various operating conditions, the working characteristics of the lithium cobalt oxide batteries are analyzed comprehensively under various operating conditions. An improved collaborative equivalent model is established to characterize its working characteristics and then the initial power state value is calibrated by using the experimental relationship between open circuit voltage and state of charge considering the importance of the precious estimation accuracy for the later iterate calculation and correction. And then, an adaptive correction - Unscented Kalman Filter algorithm is put forward and applied for the state of charge estimation and output voltage tracking so as to realize the real-time high-precision lithium-ion battery power state estimation. The experimental results show that the established model can predict the power state of high energy lithium-ion batteries conveniently with high convergency speed within 30 seconds, accurate output voltage tracking effect within 32 mV and high accuracy, the max estimation error of which is 3.87%, providing an effective working state monitoring and safety protection method in the cleaner production and power supply processes of the high energy lithium-ion batteries. © 2021. The Authors. Published by ESG (www.electrochemsci.org). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
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The Power State Estimation Method for High Energy Ternary Lithium-ion Batteries Based on the Online Collaborative Equivalent Modeling and Adaptive Correction - Unscented Kalman Filt
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Int. J. Electrochem. Sci., 16 (2021) 151020
International Journal of
ELECTROCHEMICAL
SCIENCE
www.electrochemsci.org
The Power State Estimation Method for High Energy Ternary
Lithium-ion Batteries Based on the Online Collaborative
Equivalent Modeling and Adaptive Correction - Unscented
Kalman Filter
Yongcun Fan1, Shunli Wang1,*, Cong Jiang1, Carlos Fernandez2
1 School of Information Engineering, Southwest University of Science and Technology, Mianyang,
621010, China
2 School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen AB17GJ, UK.
*E-mail: 497420789@qq.com
doi: 10.20964/2021.01.70
Received: 19 September 2020 / Accepted: 5 November 2020 / Published: 30 November 2020
Accurate power state estimation plays an important role in the real-time working state monitoring and
safety control of high energy lithium-ion batteries. To solve the difficulty and low accuracy problems in
its real-time power state estimation under various operating conditions, the working characteristics of
the lithium cobalt oxide batteries are analyzed comprehensively under various operating conditions. An
improved collaborative equivalent model is established to characterize its working characteristics and
then the initial power state value is calibrated by using the experimental relationship between open circuit
voltage and state of charge considering the importance of the precious estimation accuracy for the later
iterate calculation and correction. And then, an adaptive correction - Unscented Kalman Filter algorithm
is put forward and applied for the state of charge estimation and output voltage tracking so as to realize
the real-time high-precision lithium-ion battery power state estimation. The experimental results show
that the established model can predict the power state of high energy lithium-ion batteries conveniently
with high convergency speed within 30 seconds, accurate output voltage tracking effect within 32 mV
and high accuracy, the max estimation error of which is 3.87%, providing an effective working state
monitoring and safety protection method in the cleaner production and power supply processes of the
high energy lithium-ion batteries.
Keywords: high energy lithium-ion battery; collaborative equivalent model; power state estimation;
adaptive correction - Unscented Kalman Filter; output voltage tracking
FULL TEXT
Int. J. Electrochem. Sci., Vol. 16, 2021
2
© 2021 The Authors. Published by ESG (www.electrochemsci.org). This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/).
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