Battery asset management with remaining cycle life prognostics

Xinyang Liu, Pingfeng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Battery Asset Management problem determines the minimum cost replacement schedules for each individual asset in a group of battery assets that operate in parallel. Battery cycle life varies under different operating conditions including temperature, depth of discharge, discharge rate, etc. and battery deteriorates due to usage, which cannot be handled by current asset management models. This paper presents battery cycle life prognosis and its integration with parallel asset management to reduce lifecycle cost of battery energy storage systems. Battery cycle life is predicted as a function of temperature, depth of discharge and discharge rate based on experimental data. Aging index of the battery is then determined and incorporated in parallel asset management model. Experiment results verify the effectiveness of this new framework and suggest that the increase in battery lifetime leads to decrease in lifecycle cost.

Original languageEnglish (US)
Title of host publicationIISE Annual Conference and Expo 2019
PublisherInstitute of Industrial and Systems Engineers, IISE
ISBN (Electronic)9781713814092
StatePublished - 2019
Event2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019 - Orlando, United States
Duration: May 18 2019May 21 2019

Publication series

NameIISE Annual Conference and Expo 2019

Conference

Conference2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019
CountryUnited States
CityOrlando
Period5/18/195/21/19

Keywords

  • Asset management
  • Battery
  • Energy storage system
  • Mixed-integer programming
  • Prognostics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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