A novel technique for modelling the state of charge of lithium ion batteries using artificial neural networks

SS Grewal, DA Grant

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

This paper present a novel design for a lithium ion battery pack state of charge estimator for cellular phones using artificial neural networks (ANNs). The state of charge of a battery is a nonlinear function of the load current, battery temperature, battery chemistry and battery history and hence cannot easily be determined. Different methods have been previously been proposed in the literature for calculating the state of charge for different battery types. However, these methods are not ideally suited for mobile communication applications since the current loads they require are pulsed and hence exhibit a different behaviour on the battery. The new method investigates the effects of pulse currents loads and uses a three-layer feedforward artificial neural network which will be trained using the back propagation algorithm. Experimental and computer results are presented to highlight the advantages of the new technique and to confirm the theoretical developments.
Translated title of the contributionA novel technique for modelling the state of charge of lithium ion batteries using artificial neural networks
Original languageEnglish
Title of host publication23rd Telecommunications Energy Conference, INTELEC 2001, Edinburgh, 14-18 October
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages174 - 179
Number of pages6
VolumeIEE No.484
ISBN (Print)0852967446
Publication statusPublished - 2001

Bibliographical note

Conference Organiser: IEEE

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