4.6 Article

Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency

期刊

ELECTRONICS
卷 10, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/electronics10151859

关键词

energy storage system (ESS); battery management system (BMS); battery efficiency; state of charge (SoC); state of health (SoH)

资金

  1. Korea Institute of Energy Technology Evaluation and Planning (KETEP)
  2. Ministry of Trade, Industry, and Energy (MOTIE) of the Republic of Korea [2019381010001B]
  3. Korea Evaluation Institute of Industrial Technology (KEIT) [2019381010001B] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

This paper proposes a battery efficiency calculation formula to manage the battery state, and also introduces an algorithm that can accurately determine the battery state through the application of SoC and SoH calculations.
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.

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