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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Imane Chaoufi
TMB University
Computer Science & IT Engineering

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State of charge estimation of lithium-ion batteries using adaptive neuro fuzzy inference system Imane Chaoufi; Othmane Abdelkhalek; Brahim Gasbaoui
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp473-484

Abstract

A battery’s state of charge (SOC) is used to assess its residual capacity. It is a very important parameter for the control of the electric vehicle (EV). The objective of this paper is to estimate the SOC of a lithium-ion battery (LIB) using an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) because SOC of a battery must be estimated from measurable battery parameters such as current, voltage or temperature. Two intelligent SOC estimation methods are compared according to their suitability and accuracy. ANN estimation is more precise and perfectly represents the experimental data.
Co-Authors Brahim Gasbaoui Othmane Abdelkhalek