A new battery available capacity indicator for electric vehicles using neural network

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

Research output: Journal article publicationJournal articleAcademic researchpeer-review

106 Citations (Scopus)

Abstract

The ability to calculate the battery available capacity (BAC) for electric vehicles (EVs) is very important. Knowing the BAC and, thus, the driving range cannot only prevent EVs from being stranding on the road but also optimize the utilization of the battery energy storage in EVs. In order to determine the BAC, this paper presents a new neural network (NN) model of the lead-acid battery, based on the battery discharge current and temperature. Comparisons between the calculated BAC from the NN model and the measured BAC from experiments show good agreement. Furthermore, this new approach can readily be extended to the calculation of the BAC for other types of batteries.
Original languageEnglish
Pages (from-to)817-826
Number of pages10
JournalEnergy Conversion and Management
Volume43
Issue number6
DOIs
Publication statusPublished - 1 Apr 2002
Externally publishedYes

Keywords

  • Battery available capacity
  • Electric vehicles
  • Neural network model

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Nuclear Energy and Engineering
  • Fuel Technology
  • Energy Engineering and Power Technology

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