A Balancing Current Ratio Based State-of-Health Estimation Solution for Lithium-Ion Battery Pack

Xiaopeng TANG, Furong GAO, Kailong LIU*, Qi LIU, Aoife M. FOLEY

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

31 Citations (Scopus)


The inevitable battery ageing is a bottleneck that hinders the advancement of battery-based energy storage systems. Developing a feasible health assessment strategy for battery pack is important but challenging due to the joint requirements of the computational burden, modeling cost, estimation accuracy, and battery equalization. This article proposes a balancing current ratio (BCR) based solution to achieve reliable state-of-health (SoH) estimations of all series-connected cells within a pack while significantly reduce the overall reliance on cell-level battery models. Specifically, after employing BCR to describe the properties of the balancing process, the voltage-based active balancing is combined into the SoH estimator design for the first time, leading to a weighted fusion strategy to effectively estimate SoHs of all cells within a pack. Hardware-in-the-loop experiments show that even if a parameter-fixed open-circuit-voltage-resistance model is used for modeling, the typical estimation error of our proposed solution can still be bounded by only 1.5%, which is 70% lower than that of the benchmarking algorithms. Due to the model-free nature of the integrated voltage-based balancing, the robustness and flexibility of the proposed pack SoH estimation solution are also significantly improved.

Original languageEnglish
Pages (from-to)8055-8065
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Issue number8
Early online date3 Sept 2021
Publication statusPublished - Aug 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 1982-2012 IEEE.


  • Balancing current ratio (BCR)
  • electric vehicle
  • lithium-ion battery pack
  • state-of-health (SoH) estimation


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