期刊
IEEE TRANSACTIONS ON ENERGY CONVERSION
卷 34, 期 1, 页码 109-119出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEC.2018.2861994
关键词
Battery energy storage systems (BESS); capacity estimation; Coulomb Counting; equivalent circuit model (ECM); model-based methods; parameter identification; state estimation algorithms; state-of-charge (SOC) estimation
Modeling of battery energy storage systems used for applications, such as electric vehicles and smart grids, emerged as a necessity over the last decade and depends heavily on the accurate estimation of battery states and parameters. Depending on the battery-cell type and operation, a combination of algorithms is used to identify battery parameters and define battery states. This paper deals with robust Li-ion batteries modeling with a specific focus on a hybrid approach for a more accurate state-of-charge (SOC) estimation. The analysis presents a detailed description of the state-of-the-art stand-alone SOC estimation methods and focuses on a hybrid SOC estimation technique to improve accuracy under varying conditions. Emphasis is given on performance improvements of the proposed hybrid approach compared to the conventional methods, whereas a thorough experimental validation is presented to evaluate the accuracy of the proposed method.
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