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Online identification of internal impedance of Li-ion battery using ternary-sequence injection

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationThe 10th Annual IEEE Energy Conversion Congress and Exposition (ECCE 2018)
Subtitle of host publicationSeptember 23 – 27, 2018, Portland, Oregon, USA
PublisherIEEE
Pages2705-2711
Number of pages7
ISBN (Electronic)978-1-4799-7312-5
DOIs
Publication statusPublished - 6 Dec 2018
Publication typeA4 Article in a conference publication
EventIEEE Energy Conversion Congress and Exposition - Portland, United States
Duration: 23 Sep 201827 Sep 2018

Publication series

Name
ISSN (Electronic)2329-3748

Conference

ConferenceIEEE Energy Conversion Congress and Exposition
CountryUnited States
CityPortland
Period23/09/1827/09/18

Abstract

The internal impedance of a battery has been shown to change as a function of state-of-charge (SOC) and state-of-health (SOH). Therefore, online impedance measurements can provide useful information for SOC- and SOH-estimation algorithms. Broadband injections techniques such as pseudo-random-binary-sequence (PRBS) are attractive alternative for replacing conventional electrochemical-impedance-spectroscopy (EIS) which is very slow for online battery impedance measurements. However, non-linearities of batteries have a negative impact on the measurement results obtained by the PRBS for which the identified system is assumed to be linear. This paper demonstrates the use of ternary-sequence excitation signal for battery impedance measurements. Appropriately designed ternary-sequence can efficiently capture the linear component of the impedance by canceling out the distortion caused by the non-linear parts. The presented method can be used for rapid impedance measurements and thus, as a valuable tool in online SOC- and SOH-estimation algorithms. Experimental measurements are shown from a Lithium-Iron-Phosphate (LiFePO4) battery cell.

Publication forum classification

Field of science, Statistics Finland