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Direct numerical simulation of transport and electrochemical reaction in battery and fuel cell electrodes.

机译:电池和燃料电池电极中迁移和电化学反应的直接数值模拟。

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Batteries and fuel cells are widely used to generate electrical energy, especially in recent applications to electric and hybrid vehicles. To simulate a porous electrode for batteries and fuel cells, macro-homogeneous models are often employed in which the actual morphology of the electrode is ignored, thereby making computations much easier. However, such models are based on the volume-averaging technique, which smears the microscopically complex interfacial structures and has to invoke empirical correlations for describing the effective transport properties in a multiphase system.; In this work, a methodology is developed to achieve the description on the pore level based on direct numerical simulation (DNS) method. The DNS solves the accurate point-wise conservation equations on a real micro-structure of the porous electrode and hence utilizes the intrinsic transport properties for each phase. To demonstrate the DNS method, an idealized morphology and further a random microstructure are constructed to represent all the phases composing the porous electrode. A single set of conservation equations of charge and species valid in all phases are developed and numerically solved using a finite volume technique.; The present DNS model is first applied to simulate the behavior of an intercalative carbon electrode in the widely used lithium-ion cell. The concentration and potential distributions in both solid and electrolyte phases at the pore level are obtained across the electrode during the discharge. The species and charge transport processes, as well as the electrochemical reactions, are computationally visualized when discharging the electrode. In addition, empirical correlations in porous electrode theory, which describe the dependency of effective properties (diffusion coefficient, conductivity, etc.) on the porosity, are corroborated using the fundamental DNS data. Then the discharge processes of a full lithium ion cell at various rates are simulated with DNS approach and verified by the experimental data.; In the application to the cathode catalyst layer of PEM fuel cells, DNS is employed to identify three characteristic voltage losses: kinetics losses, ohmic losses and O2 transport losses. On a constructed random microstructure, DNS is also utilized to optimize the inlet air humidity and the composition design and hence achieve the minimum voltage loss during operation. In summary, the newly developed DNS method has provided an effective method to simulate behavior of thin porous electrodes with microscopically complicated geometries and the fundamentals insight into structure-performance relationships of porous electrodes for the first time.
机译:电池和燃料电池被广泛用于产生电能,尤其是在最近应用于电动和混合动力车辆的应用中。为了模拟用于电池和燃料电池的多孔电极,通常采用宏观均匀模型,其中忽略了电极的实际形态,从而使计算变得更加容易。但是,这些模型是基于体积平均技术的,该技术涂抹了微观上复杂的界面结构,并且必须调用经验相关性来描述多相系统中的有效输运性质。在这项工作中,基于直接数值模拟(DNS)方法,开发了一种方法来实现对孔隙水平的描述。 DNS可以在多孔电极的实际微观结构上求解精确的逐点守恒方程,因此可以利用每个相的固有传输性质。为了证明DNS方法,构建了理想的形态,并进一步构建了随机的微观结构,以代表组成多孔电极的所有相。开发了一套在所有阶段均有效的电荷和物种守恒方程,并使用有限体积技术对其进行了数值求解。首先将本DNS模型应用于模拟广泛使用的锂离子电池中插层碳电极的行为。在放电过程中,在整个电极上获得了孔隙水平的固相和电解质相的浓度和电势分布。放电电极时,可以直观地看到种类和电荷传输过程以及电化学反应。此外,使用基本的DNS数据可以证实多孔电极理论中的经验相关性,该经验相关性描述了有效属性(扩散系数,电导率等)对孔隙率的依赖性。然后用DNS方法模拟了一个完整的锂离子电池在不同速率下的放电过程,并通过实验数据进行了验证。在应用于PEM燃料电池的阴极催化剂层时,DNS用于识别三个特征电压损耗:动力学损耗,欧姆损耗和O 2 传输损耗。在构造的随机微结构上,DNS还用于优化进气湿度和成分设计,从而在运行期间实现最小的电压损失。综上所述,新开发的DNS方法首次提供了一种有效的方法来模拟具有微观复杂几何形状的薄多孔电极的行为,并且首次了解了多孔电极的结构性能关系。

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