Energy and computational efficient estimation of battery intrinsic parameters

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationECCE 2016 - IEEE Energy Conversion Congress and Exposition, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781509007370
Publication statusPublished - 13 Feb 2017

Conference

Title2016 IEEE Energy Conversion Congress and Exposition, ECCE 2016
PlaceUnited States
CityMilwaukee
Period18 - 22 September 2016

Abstract

This paper presents an efficient battery parameter extraction technique with energy recycling feature. Based on transferring the testing energy to and from a supercapacitor (storage device) through a bidirectional DC-DC converter, the charging and discharging current profile of a battery can be obtained for analyzing the battery characteristics and parameters extraction. With the testing energy stored in a supercapacitor, the concern of thermal management is eliminated. By applying a newly modified efficient particle swarm optimization algorithm, the voltage and current data are used to estimate the intrinsic parameters of a high-order electrical battery model. A prototype has been implemented for extracting the intrinsic parameters of four different types of 12V lead-acid battery, and with evaluation current evaluated up to 150A. The estimated parameters have been verified against the theoretical predictions as well as the test results obtained from the NHR battery testing system.

Research Area(s)

  • battery, battery parameters, energy efficient, particle swarm optimization

Citation Format(s)

Energy and computational efficient estimation of battery intrinsic parameters. / Cheng, Chun Sing; Lau, Ricky Wing Hong; Chung, Henry Shu Hung; Rathi, N. K.

ECCE 2016 - IEEE Energy Conversion Congress and Exposition, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. 7855079.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review