Understanding the thermal stability of lithium-ion (Li-ion) cells is critical to ensuring optimal safety and reliability for various applications such as portable electronics and electric vehicles. In this work, we demonstrate a combined modeling and experimental framework to interrogate and quantify the role of different degradation modes on the thermal stability and safety of Li-ion cells. A physics-based Li-ion cell aging model is developed to describe the underpinning role of degradation mechanisms such as Li plating, solid electrolyte interphase growth, and the loss of electrode active material on the resulting capacity fade during cycling. By incorporating mechanistic degradation descriptors from the aging model, we develop a degradation-aware cell-level thermal stability framework that captures key safety characteristics such as thermal runaway (TR) onset temperature, self-heating rate, and peak TR temperature for different cycling conditions. Additionally, we perform electrochemical and accelerating rate calorimetry (ARC) experiments to evaluate the thermo-kinetic parameters associated with the various exothermic reactions during TR of pristine and aged Li-ion cells. Through a synergistic integration of thermo-electrochemical characteristics from the ARC experiments and degradation insights from the cell aging model, the proposed aging-coupled safety framework provides a baseline to quantify the thermal stability of Li-ion cells subject to a wide range of operating conditions and degradation scenarios.

中文翻译：

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量化退化模式对锂离子电池热不稳定性和安全性的影响


了解锂离子 （Li-ion） 电池的热稳定性对于确保各种应用（如便携式电子产品和电动汽车）的最佳安全性和可靠性至关重要。在这项工作中，我们展示了一个结合的建模和实验框架，以询问和量化不同降解模式对锂离子电池热稳定性和安全性的作用。开发了一种基于物理的锂离子电池老化模型，以描述降解机制的基础作用，例如镀锂、固体电解质界面生长和电极活性材料的损失对循环过程中产生的容量衰减的影响。通过结合老化模型中的机械降解描述符，我们开发了一个抗降解感知的电池级热稳定性框架，该框架捕获了关键安全特性，例如不同循环条件下的热失控 （TR） 起始温度、自热速率和峰值 TR 温度。此外，我们还进行了电化学和加速速率量热法 （ARC） 实验，以评估与原始和老化锂离子电池 TR 期间各种放热反应相关的热动力学参数。通过将 ARC 实验中的热电化学特性与电池老化模型中的降解见解协同整合，所提出的老化耦合安全框架为量化锂离子电池在各种工作条件和降解情景下的热稳定性提供了基线。