Diagnostic cell for large-scale battery bank
- Authors
- Liu, Alex Chun-For; Chung, Henry Shu-Hung; Wang, Wenguan; Lau, Ricky Wing-Hong; Zhang, Jun
- Issue Date
- May-2017
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Battery bank; Fault diagnosis; State of charge; State of health
- Citation
- 2017 IEEE Applied Power Electronics Conference and Exposition (APEC), pp.993 - 1000
- Indexed
- SCOPUS
- Journal Title
- 2017 IEEE Applied Power Electronics Conference and Exposition (APEC)
- Start Page
- 993
- End Page
- 1000
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115711
- DOI
- 10.1109/APEC.2017.7930817
- ISSN
- 1048-2334
- Abstract
- The battery banks in many battery storage systems, such as uninterruptible power supply (UPS) systems, are placed in unattended or remote locations. Operators have to conduct regular on-site visual inspection of the service condition of the batteries. Unexpected premature battery failure cannot be discovered easily and accurately. To ensure serviceability, those batteries are typically replaced after a few years of service, depending on the site condition and the maintenance practice and experience of the operators. This paper will present a diagnostic cell for conducting real-time estimation of the State of Charge (SOC) and State of Health (SOH) of two series connected batteries, forming a basic unit for diagnosing the health of a large-scale battery bank. Operators can monitor the SOC and SOH remotely, and conduct replacement exercise at optimal time before any failure or incident occurs. The cell could save resources on regular site inspection. As the batteries are to be replaced near the end of their life cycle, it will also reduce undesired electronic waste. © 2017 IEEE.
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