Nonlinear Fractional-Order Estimator With Guaranteed Robustness and Stability for Lithium-Ion Batteries

Changfu Zou, Xiaosong Hu, Satadru Dey, Lei Zhang, Xiaolin Tang

Research output: Contribution to journalArticlepeer-review

67 Scopus citations

Abstract

This paper proposes a new estimator design algorithm for state-of-charge (SoC) indication of lithium-ion batteries. A fractional-order model-based nonlinear estimator is first framed including a Luenberger term and a sliding mode term. The estimator gains are designed by Lyapunov's direct method, providing a guarantee for stability and robustness of the error system under certain assumptions. This generic estimation algorithm is then applied to lithium-ion batteries. A fractional-order circuit model is adopted to predict battery dynamic behaviours. Assumptions based on which the estimation algorithm is developed are justified and remarked. Experiments corresponding to electric vehicle applications are conducted to parameterize the battery model and demonstrate the estimation performance. It shows that the proposed approach is able to estimate SoC with errors less than 0.03 in the presence of initial deviation and persistent noise. Furthermore, the benefits of using the proposed estimator relative to other estimators are calculated over different cycles and conditions.

Original languageEnglish (US)
Pages (from-to)5951-5961
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume65
Issue number7
DOIs
StatePublished - Jul 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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