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Multiscale modeling and numerical simulations of Lithium ion battery electrodes using real microstructures

使用真实微观结构的锂离子电池电极的多尺度建模和数值模拟

基本信息

批准号：
252382019
负责人：
Professor Dr. Thomas Carraro
金额：
--
依托单位：
Institut für Angewandte Materialien - Elektrochemische Technologien (IAM-ET)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/252382019?language=en
关键词：
Multiscale modeling numerical simulations Lithium

项目摘要

The long-term objective of this project is to establish an interdisciplinary method that allows the model-driven optimization of porous electrodes. As a special case we consider electrodes for Lithium-ion batteries (LIB), which are of increasing technological interest for existing renewable energy strategies. A state of the art Lithium-ion cell consists of two porous electrodes (anode and cathode) performing the tasks of storing the Lithium within the crystal structure and of providing it to the liquid electrolyte which fills the porosity and serves as an ionic connection between the two electrodes. The electronic connection is provided by the electrodes and the metallic current collectors, which serve as the terminals to an external circuit. Combining precise 3D reconstructions and detailed modeling of the electrodes, the rate limiting processes can be identified and improved microstructure can be obtained.To reach this goal one essential prerequisite is the quantitative characterization of the electrode microstructure and the determination of its influence on the electrochemical mechanisms. The precise quantification of microstructural parameters is required to perform model based simulations that can be used for electrodes optimization. In particular, the characterization with respect to the following processes and related parameters is essential: (a1) electrochemical reaction (reduction and oxidation) and (a2) surface to volume ratio and volume fractions; (b1) transport in percolating systems for ionic and electronic species and (b2) effective transport parameters (tortuosity); (c1) storing the lithium in the crystal structure of the active material and (c2) distribution and dimension of the active particles.The main limits of the state-of-the-art methods affect all these aspects, since they use simplified models, do not reach the needed resolution of all material phases, and do not use numerical methods that allow the needed multi-scale accuracy. In particular, a more precise quantitative method is needed: (a3) to obtain the required approximation of the active surface, (b3) to define whether effective parameters can be used and with which precision they need to be determined, (c3) to achieve the necessary approximation at the microscopic level. In this project we will perform the derivation, implementation and verification of a multi-scale transient model for LIB electrodes, which will be based on a method of partial model reduction that needs the contribution of the Intitut für Werkstoffe der Elektrotechnik (IWE) and Institut für Angewandte Mathematik (IAM). IWE will focus on reliable and original methods for the electrode reconstruction, the modeling and quantification of model and microstructure parameters. IAM will focus on mathematical methods for the model reduction and numerical solution using high performance computing techniques and novel error estimation approaches.

该项目的长期目标是建立一种跨学科的方法，允许多孔电极的模型驱动优化。作为一个特例，我们考虑了锂离子电池（LIB）的电极，这是现有可再生能源战略中日益增加的技术兴趣。最先进的锂离子电池由两个多孔电极（阳极和阴极）组成，它们的任务是将锂储存在晶体结构中，并将其提供给液体电解质，液体电解质填充孔隙并充当两个电极之间的离子连接。电子连接由电极和金属集流器提供，它们作为外部电路的终端。结合精确的三维重建和电极的详细建模，可以识别出限速过程，并获得改进的微观结构。要实现这一目标，一个必不可少的先决条件是电极微观结构的定量表征及其对电化学机制的影响的确定。微观结构参数的精确量化需要进行基于模型的模拟，可以用于电极优化。特别是，以下过程和相关参数的表征是必不可少的：（a1）电化学反应（还原和氧化）和（a2）表面体积比和体积分数；（b1）离子和电子物质在渗透系统中的输运，（b2）有效输运参数（扭曲度）；（c1）活性物质晶体结构中锂的存储；（c2）活性粒子的分布和尺寸。最先进的方法的主要局限性影响了所有这些方面，因为它们使用简化的模型，不能达到所有材料阶段所需的分辨率，并且不能使用允许所需的多尺度精度的数值方法。特别是，需要一种更精确的定量方法：（a3）获得所需的活性表面近似值，（b3）确定是否可以使用有效参数以及需要以何种精度确定有效参数，（c3）在微观水平上实现必要的近似值。在这个项目中，我们将对LIB电极的多尺度瞬态模型进行推导、实现和验证，该模型将基于部分模型缩减的方法，这需要<s:1>电力技术研究所（IWE）和<s:2>安吉wandte数学研究所（IAM）的贡献。IWE将专注于可靠和原创的电极重建方法，模型和微观结构参数的建模和量化。IAM将专注于使用高性能计算技术和新的误差估计方法进行模型简化和数值解决的数学方法。