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A novel battery state of charge estimation method based on a super-twisting sliding mode observer

  • Northwestern Polytechnical University Xian
  • Université de technologie de Belfort Montbéliard

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

Abstract

A novel method for Li-ion battery state of charge (SOC) estimation based on a super-twisting sliding mode observer (STSMO) is proposed in this paper. To design the STSMO, the state equation of a second-order RC equivalent circuit model (SRCECM) is derived to represent the dynamic behaviors of the Li-ion battery, and the model parameters are determined by the pulse current discharge approach. The convergence of the STSMO is proven by Lyapunov stability theory. The experiments under three different discharge profiles are conducted on the Li-ion battery. Through comparisons with a conventional sliding mode observer (CSMO) and adaptive extended Kalman filter (AEKF), the superiority of the proposed observer for SOC estimation is validated.

Original languageEnglish
Article number1211
JournalEnergies
Volume11
Issue number5
DOIs
StatePublished - 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Li-ion battery
  • Second-order RC equivalent circuit model
  • Sliding mode observer
  • State of charge
  • Super-twisting algorithm

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