State of Charge Estimation of LiFePO4 Battery Based on a Gain-classifier Observer

Xiaopeng TANG, Boyang LIU, Furong GAO*

*Corresponding author for this work

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

18 Citations (Scopus)

Abstract

A state of charge (SOC) estimation is required to work well over a wide range of conditions. In this study, a multi-gain observer based on classified conditions is proposed in order to estimate SOC efficiently. The feedback gain in the observer is switched by a proposed geometry classifier to categorize the voltage error into different groups so that the observing strategies can be designed for different error sources, and thereby robust and accurate SOC estimations. Different load conditions (including QC/T 897-2011 standard suggested condition) are tested to verify the proposed method. The results show that the proposed method is effective and accurate. It is possible to solve local model inaccuracies and data saturation problems in a computationally efficient way.

Original languageEnglish
Pages (from-to)2071-2076
Number of pages6
JournalEnergy Procedia
Volume105
DOIs
Publication statusPublished - May 2017
Externally publishedYes
Event8th International Conference on Applied Energy, ICAE 2016 - Beijing, China
Duration: 8 Oct 201611 Oct 2016

Bibliographical note

Publisher Copyright:
© 2017 The Authors.

Keywords

  • Battery model
  • Electric vehicles
  • Geometry classifier
  • LiFePO battery
  • Multiple gain observer
  • State-of-charge

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