Model Predictive Control for Intersubmodule State-of-Charge Balancing in Cascaded H-Bridge Converter-Based Battery Energy Storage Systems

Gaowen Liang*, Ezequiel Rodriguez, Glen G. Farivar, Enrique Nunes, Georgios Konstantinou, Christopher D. Townsend, Ramon Leyva, Josep Pou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In the operation of battery energy storage systems based on the cascaded H-bridge converter, it is beneficial to balance the state of charge of batteries in different submodules within the converter phase-arm. This is achieved by distributing the active power among the submodules. Although multiple methods have been proposed for this purpose, they face the challenge of rendering optimal active power distributions that maximize balancing speed while meeting power constraints in the battery energy storage system. To overcome this challenge, a model predictive control scheme is developed in this article. The proposed method is remarkably robust against parametric uncertainties (battery voltage, capacity, etc.), as evidenced by its ability to tolerate a substantial 50% uncertainty in the parameters, resulting in a mere 0.05% steady-state error. Furthermore, because the predictive control can be executed at a low frequency, the computational burden is comparable to other existing methods.

Original languageEnglish
Pages (from-to)5777-5786
Number of pages10
JournalIEEE Transactions on Industrial Electronics
Volume71
Issue number6
DOIs
Publication statusPublished - Jun 1 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1982-2012 IEEE.

ASJC Scopus Subject Areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Battery energy storage
  • cascaded H-bridge
  • model predictive control
  • optimization
  • state-of-charge

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