Untangling the relationship between reactions, mass transfer, and temperature within lithium-ion batteries enables control approaches that mitigate thermal hot spots and slow degradation. Here, we develop an efficient physics-based pouch-cell model to simulate lock-in thermography experiments, which synchronously record the applied current, cell voltage, and surface-temperature distribution. Prior modelling efforts have been confounded by experimental temperature profiles whose characteristics suggest anisotropic heat conduction. Accounting for a multiscale coupling between heat flow and solid-state diffusion rationalizes this surface-temperature nonuniformity. We extend an earlier streamlined model based on the popular Doyle--Fuller--Newman theory, augmented by a local heat balance. The reduced-order model is exploited to parametrize and simulate commercial 20 Ah lithium iron phosphate (LFP) cells at currents up to 80 A. This work highlights how microscopic intercalation processes produce distinctive macroscopic heat signatures in large-format cells, as well as how heat signatures can be exploited to fingerprint material properties.
翻译:在锂离子电池内解开反应、大规模转移和温度之间的关系,可以采取减少热热点和缓慢降解的控制方法。在这里,我们开发了一个高效的基于物理的邮袋细胞模型,以模拟锁定热量实验,同步记录应用的电流、电池电压和表面温度分布。先前的建模工作被实验性温度剖面图所混淆,其特征表明有厌异热导。计算热流和固态扩散之间的多尺度交错使这种表面温度不统一的情况合理化。我们根据流行的多伊尔-富勒-纽曼理论,推广了早期的简化模型,并辅之以当地的热平衡。减序模型被用于模拟和模拟20个商用阿利硫磷酸铁电池,目前可达80 A.A. 这项工作突出了微分层间化过程如何在大型细胞中产生独特的宏观热信号,以及如何将热信号用于指纹材料特性。