电池(电)
介电谱
锂(药物)
计算机科学
电阻抗
锂离子电池
透视图(图形)
材料科学
电化学
电气工程
工程类
化学
电极
功率(物理)
物理
人工智能
医学
内分泌学
物理化学
量子力学
作者
Tushar Telmasre,Neha Goswami,Anthony César Concepción,Suryanarayana Kolluri,Manan Pathak,Gerald L. Morrison,Venkat R. Subramanian
标识
DOI:10.1016/j.coelec.2022.101140
摘要
The battery is an electrochemical system that may be considered a black box with no practical way of observing processes occurring within in a nondestructive manner at an affordable cost. Fortunately, most physical and chemical processes in electrochemical systems can be distinguished by their distinct characteristic time constants. Electrochemical impedance spectroscopy (EIS) is a powerful technique to distinguish internal processes within batteries based on their frequency response. EIS has been successful at identifying relevant electrochemical mechanisms and battery parameters and therefore can be integrated with model-based battery management systems (BMS) which are critical for improving the battery life and performance. In this article, we provide our perspective on different simulation strategies for modeling the impedance response of lithium-ion batteries, implementation of EIS models in BMS, and some challenges associated with achieving a computationally efficient approach.
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