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Model-Based Condition Monitoring of a Vanadium Redox Flow Battery

Author

Listed:
  • Shujuan Meng

    (School of Space and Environment, Beihang University, Beijing 100191, China)

  • Binyu Xiong

    (School of Automation, Wuhan University of Technology, Wuhan 430072, China)

  • Tuti Mariana Lim

    (School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore)

Abstract

The safe, efficient and durable utilization of a vanadium redox flow battery (VRB) requires accurate monitoring of its state of charge (SOC) and capacity decay. This paper focuses on the unbiased model parameter identification and model-based monitoring of both the SOC and capacity decay of a VRB. Specifically, a first-order resistor-capacitance (RC) model was used to simulate the dynamics of the VRB. A recursive total least squares (RTLS) method was exploited to attenuate the impact of external disturbances and accurately track the change of model parameters in realtime. The RTLS-based identification method was further integrated with an H-infinity filter (HIF)-based state estimator to monitor the SOC and capacity decay of the VRB in real-time. Experiments were carried out to validate the proposed method. The results suggested that the proposed method can achieve unbiased model parameter identification when unexpected noises corrupt the current and voltage measurements. SOC and capacity decay can also be estimated accurately in real-time without requiring additional open-circuit cells.

Suggested Citation

  • Shujuan Meng & Binyu Xiong & Tuti Mariana Lim, 2019. "Model-Based Condition Monitoring of a Vanadium Redox Flow Battery," Energies, MDPI, vol. 12(15), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:3005-:d:254634
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    References listed on IDEAS

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    1. Xinan Zhang & Yifeng Li & Maria Skyllas-Kazacos & Jie Bao, 2016. "Optimal Sizing of Vanadium Redox Flow Battery Systems for Residential Applications Based on Battery Electrochemical Characteristics," Energies, MDPI, vol. 9(10), pages 1-20, October.
    2. Wei, Zhongbao & Meng, Shujuan & Xiong, Binyu & Ji, Dongxu & Tseng, King Jet, 2016. "Enhanced online model identification and state of charge estimation for lithium-ion battery with a FBCRLS based observer," Applied Energy, Elsevier, vol. 181(C), pages 332-341.
    3. Wei, Zhongbao & Lim, Tuti Mariana & Skyllas-Kazacos, Maria & Wai, Nyunt & Tseng, King Jet, 2016. "Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery," Applied Energy, Elsevier, vol. 172(C), pages 169-179.
    4. Shi, Yu & Eze, Chika & Xiong, Binyu & He, Weidong & Zhang, Han & Lim, T.M. & Ukil, A. & Zhao, Jiyun, 2019. "Recent development of membrane for vanadium redox flow battery applications: A review," Applied Energy, Elsevier, vol. 238(C), pages 202-224.
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    Cited by:

    1. Muhammed Samil Yesilyurt & Huseyin Ayhan Yavasoglu, 2023. "An All-Vanadium Redox Flow Battery: A Comprehensive Equivalent Circuit Model," Energies, MDPI, vol. 16(4), pages 1-14, February.
    2. Alejandro Clemente & Ramon Costa-Castelló, 2020. "Redox Flow Batteries: A Literature Review Oriented to Automatic Control," Energies, MDPI, vol. 13(17), pages 1-31, September.

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