A Novel Battery Diagnostic Method for Smart Electric Vehicle Charger

Sachio Nagamitsu, Ryo Gondo, Naoto Nagaoka, Ahmed A. Abdullah Al-Karakchi, Ghanim Putrus, Yue Wang

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

2 Citations (Scopus)

Abstract

Indications of mileage, charging-time and residual lifetime of the battery of EV are indispensable to any smart EV. These values have strong relation with the capacity (SoH) and impedance of the battery. Traditional off-board measurement approaches require the battery to be removed from the vehicle and the associated lengthy processing time would cause interruption to the normal operation of the battery driving equipment. A program that is capable of predicting the battery impedance and the internal voltage during its operation is developed in this work for a one-chip microcomputer that is embedded into a smart EV charger. In addition, pulse current is also employed to prolong the battery life. The prediction is performed by a numerical convolution and fitting techniques. This method has an advantage in low memory requirement, because the sampled voltage waveform of a single pulse is used. A comparison to the measurement result by AC superposition method proofed that the accuracy of the proposed method is satisfactory. The average error is less than 6 %.

Original languageEnglish
Title of host publicationProceedings - 2018 53rd International Universities Power Engineering Conference, UPEC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538629109
ISBN (Print)9781538629116
DOIs
Publication statusPublished - 13 Dec 2018
Event53rd International Universities Power Engineering Conference, UPEC 2018 - Glasgow, United Kingdom
Duration: 4 Sep 20187 Sep 2018

Conference

Conference53rd International Universities Power Engineering Conference, UPEC 2018
CountryUnited Kingdom
CityGlasgow
Period4/09/187/09/18

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