TY - GEN
T1 - Battery asset management with remaining cycle life prognostics
AU - Liu, Xinyang
AU - Wang, Pingfeng
N1 - Funding Information:
This research is partially supported by the National Science Foundation through the Faculty Early Career Development (CAREER) award (CMMI-1813111), and the NSF award (CMMI-1802489).
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Asset management
KW - Battery
KW - Energy storage system
KW - Mixed-integer programming
KW - Prognostics
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M3 - Conference contribution
AN - SCOPUS:85095412983
T3 - IISE Annual Conference and Expo 2019
BT - IISE Annual Conference and Expo 2019
PB - Institute of Industrial and Systems Engineers, IISE
T2 - 2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019
Y2 - 18 May 2019 through 21 May 2019
ER -