电池单元的几何缩放及其对关键性能指标的影响
Geometric Scaling of Battery Cells and Its Effect on Key Performance Indicators
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中文总结 AI 辅助
该研究针对圆柱形锂离子电池单元提出计算轻量级缩放模型，用于早期设计空间探索，映射设计变量到性能指标，经数据验证后用于探索与分析，确定了主要变量、参数方向及关键权衡，为高级别优化框架提供基础。
中文摘要 AI 辅助
本文提出了一种用于圆柱形锂离子电池单元的计算轻量级缩放模型，用于早期电池设计空间探索。该模型将选定的几何和电极级设计变量，包括电池高度、电池直径、阴极活性负载和阴极孔隙率，映射到电池级性能指标，如容量、直流内阻、质量、体积和绕组长度。通过比较预测的容量、内阻和绕组长度，针对可用的圆柱形电池数据验证了缩放模型。随后，将经过验证的模型用于单电池设计空间探索和全局敏感性分析，以评估容量、内阻、重量能量密度和体积能量密度。结果确定了主要设计变量、有利的参数方向以及电池几何形状、电极负载、电阻和能量密度之间的关键权衡。所提出的模型为未来集成到更高级别的电池系统和车辆优化框架提供了基础。
英文摘要
This paper presents a computationally lightweight scaling model for cylindrical lithium-ion battery cells, intended for early-stage battery design-space exploration. The model maps selected geometric and electrode-level design variables, including cell height, cell diameter, cathode active loading, and cathode porosity, to cell-level performance indicators such as capacity, DC internal resistance, mass, volume, and winding length. The scaling model is validated against available cylindrical cell data by comparing predicted capacity, internal resistance, and winding length. The validated model is subsequently used in a single-cell design-space exploration and global sensitivity analysis to evaluate capacity, internal resistance, gravimetric energy density, and volumetric energy density. The results identify the dominant design variables, favourable parameter directions, and key trade-offs between cell geometry, electrode loading, resistance, and energy density. The proposed model provides a basis for future integration into higher-level battery system and vehicle optimization frameworks.
