可用的
电池(电)
等效电路
计算模型
计算机科学
电压
锂离子电池
电子线路
锂(药物)
模拟
电气工程
工程类
功率(物理)
医学
物理
量子力学
内分泌学
万维网
作者
Nikhil Biju,Huazhen Fang
出处
期刊:Applied Energy
[Elsevier]
日期:2023-06-01
卷期号:339: 120905-120905
被引量:15
标识
DOI:10.1016/j.apenergy.2023.120905
摘要
Advanced battery management is as important for lithium-ion battery systems as the brain is for the human body. Its performance is based on the use of fast and accurate battery models. However, the mainstream equivalent circuit models and electrochemical models have yet to meet this need well, due to their struggle with either predictive accuracy or computational complexity. This problem has acquired urgency as some emerging battery applications running across broad current ranges, e.g., electric vertical take-off and landing aircraft, can hardly find usable models from the literature. Motivated to address this problem, we develop an innovative model in this study. Called BattX, the model is an equivalent circuit model that draws comparisons to a single particle model with electrolyte and thermal dynamics, thus combining their respective merits to be computationally efficient, accurate, and physically interpretable. The model design pivots on leveraging multiple circuits to approximate major electrochemical and physical processes in charging/discharging. Given the model, we develop a multipronged approach to design experiments and identify its parameters in groups from experimental data. Experimental validation proves that the BattX model is capable of accurate voltage prediction for charging/discharging across low to high C-rates.
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