Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency

Aging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the battery sta...

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Main Authors: Jeong Lee, Jun-Mo Kim, Junsin Yi, Chung-Yuen Won
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/10/15/1859
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spelling doaj-477ff2d3d6cd44f888f67d3db3859fb02021-08-06T15:21:22ZengMDPI AGElectronics2079-92922021-08-01101859185910.3390/electronics10151859Battery Management System Algorithm for Energy Storage Systems Considering Battery EfficiencyJeong Lee0Jun-Mo Kim1Junsin Yi2Chung-Yuen Won3Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaInterdisciplinary Program in Photovoltaic System Engineering, Sungkyunkwan University, Suwon 16419, KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaDepartment of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, KoreaAging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the battery state. The proposed battery efficiency calculation formula uses the charging time, charging current, and battery capacity. An algorithm that can accurately determine the battery state is proposed by applying the proposed state of charge (SoC) and state of health (SoH) calculations. To reduce the initial error of the Coulomb counting method (CCM), the SoC can be calculated accurately by applying the battery efficiency to the open circuit voltage (OCV). During the charging and discharging process, the internal resistance of a battery increase and the constant current (CC) charging time decrease. The SoH can be predicted from the CC charging time of the battery and the battery efficiency, as proposed in this paper. Furthermore, a safe system is implemented during charging and discharging by applying a fault diagnosis algorithm to reduce the battery efficiency. The validity of the proposed BMS algorithm is demonstrated by applying it in a 3-kW ESS.https://www.mdpi.com/2079-9292/10/15/1859energy storage system (ESS)battery management system (BMS)battery efficiencystate of charge (SoC)state of health (SoH)
collection DOAJ
language English
format Article
sources DOAJ
author Jeong Lee
Jun-Mo Kim
Junsin Yi
Chung-Yuen Won
spellingShingle Jeong Lee
Jun-Mo Kim
Junsin Yi
Chung-Yuen Won
Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
Electronics
energy storage system (ESS)
battery management system (BMS)
battery efficiency
state of charge (SoC)
state of health (SoH)
author_facet Jeong Lee
Jun-Mo Kim
Junsin Yi
Chung-Yuen Won
author_sort Jeong Lee
title Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
title_short Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
title_full Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
title_fullStr Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
title_full_unstemmed Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
title_sort battery management system algorithm for energy storage systems considering battery efficiency
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2021-08-01
description Aging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the battery state. The proposed battery efficiency calculation formula uses the charging time, charging current, and battery capacity. An algorithm that can accurately determine the battery state is proposed by applying the proposed state of charge (SoC) and state of health (SoH) calculations. To reduce the initial error of the Coulomb counting method (CCM), the SoC can be calculated accurately by applying the battery efficiency to the open circuit voltage (OCV). During the charging and discharging process, the internal resistance of a battery increase and the constant current (CC) charging time decrease. The SoH can be predicted from the CC charging time of the battery and the battery efficiency, as proposed in this paper. Furthermore, a safe system is implemented during charging and discharging by applying a fault diagnosis algorithm to reduce the battery efficiency. The validity of the proposed BMS algorithm is demonstrated by applying it in a 3-kW ESS.
topic energy storage system (ESS)
battery management system (BMS)
battery efficiency
state of charge (SoC)
state of health (SoH)
url https://www.mdpi.com/2079-9292/10/15/1859
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AT junmokim batterymanagementsystemalgorithmforenergystoragesystemsconsideringbatteryefficiency
AT junsinyi batterymanagementsystemalgorithmforenergystoragesystemsconsideringbatteryefficiency
AT chungyuenwon batterymanagementsystemalgorithmforenergystoragesystemsconsideringbatteryefficiency
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