电池(电)
计算机科学
锂离子电池
功率(物理)
线性化
数学优化
数学
物理
非线性系统
量子力学
作者
Yuxuan Gu,Yuanbo Chen,Jianxiao Wang,Wei Xiao,Qixin Chen
标识
DOI:10.1109/tii.2022.3195731
摘要
Sizeable lithium-ion battery (LIB) sources in the transportation and power sectors provide a promising approach to alleviate the increasing volatility in energy systems. To dispatch LIBs durably and safely, operators need to estimate the battery power characteristics, which are commonly derived from external states of the battery obtained by empirical models. However, the internal states that play a decisive role are rarely considered. In this work, the power characterization is based on an interpretable and analytical electrochemical model. In addition to external states, internal states, including Li-ion concentrations, side reaction rates, and the energy conversion efficiency, are considered in the characterization. Since the dispatch time interval is usually longer than the time resolution of the battery model, an optimization-based approach taking the idea of model predictive control is designed for efficient calculation. A linearization scheme is proposed to embed power characteristics into the optimization-based dispatch of an integrated energy-transportation system with low complexity. Case studies on LiNCM and LiFePO $_{4}$ batteries in different temperatures are conducted. The calculation of power characteristics takes about two minutes. By considering power characteristics, the energy conversion efficiency of the dispatched battery can be increased by 5%–15%. At the same time, the degradation stress and heat generation can be reduced to around one-fourth of the naïve case.
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