A novel model predictive control scheme based observer for working conditions and reconditioning monitoring of Zinc-Nickel single flow batteries

Shawn Li, Kang Li*, Evan Xiao, Rui Xiong, Jianhua Zhang, Peter Fischer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Zinc-nickel single flow batteries (ZNBs) have been demonstrated as a promising alternative to lithium batteries for next generation grid-tied energy storage. However, due to the dendritic growth, the monitoring of working conditions in terms of the state of charge (SoC) and battery capacity is intractable. Although longer lifespan can be achieved through the periodic reconditioning maintenance, there is no mature method to identify the moment of reconditioning. Model predictive control (MPC) is a popular optimization paradigm in the process control. By incorporating the merits of model predictive control, this work presents a novel model predictive control based observer (MPCO) for the working conditions monitoring and reconditioning identification. Strong evidence from substantial experiments and simulations manifests the convergence, robustness, effectiveness and generality of the proposed method. The competitiveness is demonstrated by analytical comparisons against other three estimators. In this regard, the relationships of the proposed observer with other estimators are summarized briefly. At last, an indicator based on the capacity changes is proposed to judge the timing of reconditioning.

Original languageEnglish
Article number227282
JournalJournal of Power Sources
Volume445
DOIs
Publication statusPublished - 1 Jan 2020

Keywords

  • Capacity estimation
  • Model predictive control
  • Observer
  • Reconditioning
  • Redox flow batteries
  • State of charge estimation
  • Zinc-nickel single flow batteries

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