Lithium iron phosphate intelligent SOC prediction for efficient electric vehicle

Siti Fauziah Toha, Nor Hazima Faeza, Nor Aziah Mohd Azubair, Nizam Hanisa, Mohd Khair Hassan, Babul Salam K Ibrahim

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

This paper presents modelling techniques for Lithium Iron Phosphate (LiFePO4) battery in an electric vehicle. Artificial intelligence techniques namely multi-layered perceptron neural network (MLPNN) and Elman recurrent neural network are devised to estimate the energy remained in the battery bank which referred to state of charge (SOC). The New European Driving Cycle (NEDC) test data is used to excite the cells in driving cycle-based conditions under varied temperature range [0-55]0C. Accurate SOC prediction is a key function for satisfactory implementation of Battery Supervisory System (BSS). It is demonstrated that artificial intelligence methods can be effectively used with highly accurate results. The accuracy of the modeling results is demonstrated through validation and correlation tests.

Original languageEnglish
Title of host publicationMaterial Research and Applications
PublisherTrans Tech Publications
Pages1613-1619
Number of pages7
ISBN (Print)9783037859933
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2012 International Conference on Advanced Material and Manufacturing Science, ICAMMS 2012 - Beijing, China
Duration: 20 Dec 201221 Dec 2012

Publication series

NameAdvanced Materials Research
Volume875-877
ISSN (Print)1022-6680
ISSN (Electronic)1662-8985

Conference

Conference2012 International Conference on Advanced Material and Manufacturing Science, ICAMMS 2012
CountryChina
CityBeijing
Period20/12/1221/12/12

Keywords

  • Elman recurrent neural network and battery supervisory system (BSS)
  • Lithium iron phosphate
  • Multi-layered perceptron neural network (MLPNN)
  • State of charge (SOC)

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Toha, S. F., Faeza, N. H., Azubair, N. A. M., Hanisa, N., Hassan, M. K., & Ibrahim, B. S. K. (2014). Lithium iron phosphate intelligent SOC prediction for efficient electric vehicle. In Material Research and Applications (pp. 1613-1619). (Advanced Materials Research; Vol. 875-877). Trans Tech Publications. https://doi.org/10.4028/www.scientific.net/AMR.875-877.1613