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A computationally efficient model for performance prediction of lithium-ion batteries
Sustainable Energy Technologies and Assessments ( IF 7.1 ) Pub Date : 2020-12-16 , DOI: 10.1016/j.seta.2020.100938
Mahshid Nejati Amiri , Farschad Torabi

The pseudo-two dimensional electrochemical model is capable of accurately predicting the transient behavior of the batteries. However, since the numerical complexity of this model prohibits its application in real-time simulations, many efforts have been made toward reducing the model order to develop fast and reliable battery modeling methods. In this paper, a computationally efficient electrochemical-based model is proposed to predict the temporal and spatial distributed processes inside the battery. By considering some reasonable assumptions, complex partial differential equations (PDEs) are simplified so they can be analytically solved. Applying Green’s function method, the electrolyte concentration distribution is obtained, and solid concentration is approximated using a simplified expression. Verifying the results with the previous full order model shows high precision in low C-rates; even in high applied currents (4C), the model can deliver reasonable accuracy. Compared to the CFD method, this model is highly efficient and significantly reduces computing time because of utilizing linear algebraic equations.



中文翻译:

计算效率高的锂离子电池性能预测模型

伪二维电化学模型能够准确预测电池的瞬态行为。但是,由于该模型的数值复杂性阻止了其在实时仿真中的应用,因此人们为降低模型顺序做出了许多努力,以开发快速而可靠的电池建模方法。在本文中,提出了一种基于计算的高效电化学模型来预测电池内部的时间和空间分布过程。通过考虑一些合理的假设,可以简化复杂的偏微分方程(PDE),以便可以对其进行解析求解。应用格林函数法,可以获得电解质浓度分布,并使用简化表达式近似估算固体浓度。用先前的全订单模型验证结果表明,在低C速率下精度很高。即使在高施加电流(4C)下,该模型也可以提供合理的精度。与CFD方法相比,该模型非常高效,并且由于利用了线性代数方程,因此大大减少了计算时间。

更新日期:2020-12-16
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