A Novel Multiple Correction Approach for Fast Open Circuit Voltage Prediction of Lithium-ion Battery

Meng Jinhao, Daniel-Ioan Stroe, Mattia Ricco, Luo Guangzhao, Swierczynski Maciej, Remus Teodorescu

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

2 Citationer (Scopus)
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Resumé

This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).
OriginalsprogEngelsk
Artikelnummer8528545
TidsskriftI E E E Transactions on Energy Conversion
Vol/bind34
Udgave nummer2
Sider (fra-til)1115-1123
Antal sider9
ISSN0885-8969
DOI
StatusUdgivet - jun. 2019

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Open circuit voltage
Voltage measurement
Relaxation time
Curve fitting
Electric potential
State estimation
Control theory
Energy storage
Feedback control
Lithium-ion batteries
Thermodynamics
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abstract = "This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).",
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A Novel Multiple Correction Approach for Fast Open Circuit Voltage Prediction of Lithium-ion Battery. / Jinhao, Meng; Stroe, Daniel-Ioan; Ricco, Mattia; Guangzhao, Luo; Maciej, Swierczynski; Teodorescu, Remus.

I: I E E E Transactions on Energy Conversion, Bind 34, Nr. 2, 8528545, 06.2019, s. 1115-1123.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

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AU - Ricco, Mattia

AU - Guangzhao, Luo

AU - Maciej, Swierczynski

AU - Teodorescu, Remus

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AB - This paper proposes a novel fast open circuit voltage prediction approach for Lithium-ion battery, which is potential to facilitate a convenient battery modeling and states estimation in the energy storage system. Open circuit voltage measurement suffers from a long relaxation time (several hours, even days) to reach the thermodynamic equilibrium of the battery. On the basis of the feedback control theory, the proposed multiple correction approach utilizes the constrained nonlinear optimization of the power function in each curve fitting step. The voltage measurement in a short period is divided into several segments to correct the voltage prediction multiple times with the feedback errors after each curve fitting. The similarity between the shape of the power function and the variation of the terminal voltage during the relaxation time is utilized. The proposed method can speed up the time-consuming open circuit voltage measurement and predict the open circuit voltage with high accuracy. Experimental tests on a LiFePO4 battery prove the validation and effectiveness of the proposed method in accurately predicting the open circuit voltage within a very short relaxation time (less than 15 min).

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