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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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 |
work_keys_str_mv |
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