Model-Based Condition Monitoring of a Vanadium Redox Flow Battery

Shujuan Meng, Binyu Xiong and Tuti Mariana Lim
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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

Energies, 2019, vol. 12, issue 15, 1-16

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.

Keywords: state of charge; capacity decay; parameter identification; condition monitoring; vanadium redox flow battery (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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