Online Estimation of Open Circuit Voltage Based on Extended Kalman Filter with Self-Evaluation Criterion

Open circuit voltage (OCV) is crucial for battery degradation analysis. However, high-precision OCV is usually obtained offline. To this end, this paper proposes a novel self-evaluation criterion based on the capacity difference of State of Charge (SoC) unit interval. The criterion is integrated int...

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Bibliographic Details
Published inEnergies (Basel) Vol. 15; no. 12; p. 4373
Main Authors Qiao, Xin, Wang, Zhixue, Hou, Enguang, Liu, Guangmin, Cai, Yinghao
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2022
Subjects
Accuracy
Aging
Algorithms
Criteria
Electrodes
Energy storage
Extended Kalman filter
incremental capacity and differential voltage curves
Lithium
lithium-ion battery
Mean square errors
Open circuit voltage
Parameter identification
Phase transitions
Self evaluation
self-evaluation criterion
State of charge
Voltage
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Summary:Open circuit voltage (OCV) is crucial for battery degradation analysis. However, high-precision OCV is usually obtained offline. To this end, this paper proposes a novel self-evaluation criterion based on the capacity difference of State of Charge (SoC) unit interval. The criterion is integrated into extended Kalman filter (EKF) for joint estimations of OCV and SoC. The proposed method is evaluated in a typical application scenario, energy storage system (ESS), using a LiFePO4 (LFP) battery. Extensive experimental results show that a more accurate OCV and incremental capacity and differential voltage (IC-DV) can be achieved online with the proposed method. Our method also greatly improves the accuracy of SoC estimation at each SoC point where the maximum estimation error of SoC is less than 0.3%.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15124373