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  • 标题:Estimation of Best Linear Approximation from Varying Operating Conditions for the Identification of a Li-ion Battery Model * * The corresponding author can be contacted at the (rishi.relan@vub.ac.be)
  • 本地全文:下载
  • 作者:Rishi Relan ; Koen Tiels ; Jean-Marc Timmermans
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2017
  • 卷号:50
  • 期号:1
  • 页码:4739-4744
  • DOI:10.1016/j.ifacol.2017.08.867
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe short term dynamic response of the battery varies with varying operating conditions. Hence, even before proceeding towards the modelling step, it is important to fully characterise and understand the dynamic behaviour of the battery at varying operating conditions. In this paper, a data-driven methodology for characterising the battery’s short term electrical response at varying operating conditions e.g. at different levels of SoC and different temperature levels is discussed. Furthermore, a novel way to estimate the best linear approximation from the data acquired at these operating conditions with varying levels of noise and nonlinear distortions is proposed.
  • 关键词:KeywordsSystem identificationMultiple experimentsNonlinear modelsLi-ion batteryBest linear approximation
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