Adaptive neuro-fuzzy modeling of battery residual capacity for electric vehicles

W. X. Shen, C. C. Chan, Wai Chau Edward Lo, K. T. Chau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

101 Citations (Scopus)

Abstract

This paper proposes and implements a new method for the estimation of the battery residual capacity (BRC) for electric vehicles (EVs). The key of the proposed method is to model the EV battery by using the adaptive neuro-fuzzy inference system. Different operating profiles of the EV battery are investigated, including the constant current discharge and the random current discharge as well as the standard EV driving cycles in Europe, the U.S., and Japan. The estimated BRCs are directly compared with the actual BRCs, verifying the accuracy and effectiveness of the proposed modeling method. Moreover, this method can be easily implemented by a low-cost microcontroller and can readily be extended to the estimation of the BRC for other types of EV batteries.
Original languageEnglish
Pages (from-to)677-684
Number of pages8
JournalIEEE Transactions on Industrial Electronics
Volume49
Issue number3
DOIs
Publication statusPublished - 1 Jun 2002
Externally publishedYes

Keywords

  • Adaptive neuro-fuzzy inference system
  • Battery modeling
  • Battery residual capacity
  • Electric vehicles

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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