Collaborative Research: An Integrated Multiscale Reduced-Order Modeling and Experimental Framework for Lithium-ion Batteries under Mechanical Abuse Conditions

这笔赠款将专注于开发一个集成的计算建模和实验框架，用于模拟在机械滥用条件下的锂离子电池(LIB)，例如冲击加载。LIBS是电动汽车最常用的动力源，因此对LIBS的安全性提出了越来越高的要求，使其能够在机械滥用的条件下使用。为了改善先进的长寿命和高能LIB的安全性设计和最终的可靠性，最近的趋势是使用数值模拟来替代昂贵和耗时的真实世界测试来预测在机械滥用条件下的LIB响应。然而，由于LiBS的多尺度特性和LiB组分的非线性响应，通过考虑不同LiB组分的复杂微观结构和非线性响应来直接建模LIBS的计算代价很高。为了解决这个问题，PI计划开发一个多尺度建模框架，以更好地平衡LIB建模的准确性和效率。还计划在不同加载条件下对LiB组件进行表征和测试，这将促进模型的开发并最终验证计算框架。这项研究还将通过建立响应和灵活的教育和推广计划来补充，该计划基于课程开发和暑期研究计划，面向以工程为重点的本科生和高中生，以及通过两所参与机构的STEM教育中心的K-12和未被充分代表的少数族裔的推广。该项目的目标是通过将基于物理的LIB组件的本构模型与多尺度降阶建模技术相结合，为机械滥用条件下的LIB开发一个集成的多尺度降阶建模和实验框架。为了实现这一目标，研究包括以下三个目标和计划：1)确定完全覆盖低、中、高应变率的电池部件的本构模型；2)通过提出基于特征变形的降阶均匀化模型(EHM)，建立多尺度降阶计算模型来预测锂离子电池的响应；3)对电池单元进行动态测试，以验证所开发的多尺度模型的有效性，并将验证后的模型用于锂离子电池的设计和安全评估。多尺度建模框架将在设计最优LIB系统方面实现突破，这将扩展LIB性能的传统边界。该项目将允许PIS提升他们目前在LIB建模和设计方面的计算建模和实验测试专业知识，这可能会加速最先进电池技术的发现、创新和认证，并建立他们在复杂材料系统和结构的建模和测试方面的长期职业生涯。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will focus on developing an integrated computational modeling and experimental framework for simulating lithium-ion batteries (LIBs) under mechanical abuse conditions, such as impact loading. LIBs are the most used power source for electric vehicles, which leads to an ever-increasing need to improve the safety of LIBs so that they can be used in mechanical abuse conditions. To improve the safety design and ultimately reliability of advanced long life and high energy LIBs, a recent trend is to use numerical simulations as an alternative to expensive and time-consuming real-world testing for LIB response prediction under mechanical abuse conditions. However, due to the multiscale nature of LIBs and the nonlinear response of LIB components, it is computationally expensive to directly model the LIBs by accounting for the complex microstructures and nonlinear responses of different LIB components. To address this issue, the PIs plan to develop a multiscale modeling framework that better balances accuracy and efficiency for LIB modeling. The characterization and testing of LIB components at different loading conditions are also planned, which will facilitate the model development and eventually validate the computational framework. The research will also be complemented by establishing a responsive and flexible educational and outreach program based on curriculum development and summer research programs for undergraduate and high-school students with an engineering focus, as well as K-12 and underrepresented minority outreach through STEM education centers at both participating institutes.The objective of this project is to develop an integrated multiscale reduced-order modeling and experimental framework for LIBs under mechanical abuse conditions by integrating physics­-based constitutive models for LIB components with a multiscale reduced order modeling technique. To achieve this goal, the research encompasses the following three aims and plans: 1) Determine the constitutive models of battery components with full coverage of low, intermediate, and high strain rates; 2) Develop a multiscale reduced-order computational model to predict the response of LIB cells by advancing the eigendeformation-based reduced ­order homogenization model (EHM); 3) Conduct dynamic testing of battery cells to validate the developed multiscale models and exercise the validated model for LIB design and safety evaluation. The multiscale modeling framework will achieve reakthroughs in designing optimal LIB systems, which will expand the conventional boundaries of LIB performance. This project will allow the PIs to advance their current computational modeling and experimental testing expertise for LIB modeling and design, which could potentially accelerate the discovery, innovation, and certification of state-of-the-art battery technologies, and establish their long-term career in modeling and testing of complex material systems and structures.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.