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

该资助将专注于开发一个集成的计算建模和实验框架，用于在机械滥用条件下模拟锂离子电池（LIB），例如冲击载荷。LIB是电动汽车最常用的电源，这导致对提高LIB安全性的需求不断增加，以便它们可以在机械滥用条件下使用。为了提高先进的长寿命和高能量LIB的安全设计和最终可靠性，最近的趋势是使用数值模拟作为替代昂贵和耗时的真实世界测试，用于在机械滥用条件下预测LIB响应。然而，由于LIB的多尺度性质和LIB部件的非线性响应，通过考虑不同LIB部件的复杂微结构和非线性响应来直接对LIB进行建模在计算上是昂贵的。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，这将有助于模型开发并最终验证计算框架。这项研究还将通过建立一个响应和灵活的教育和推广计划，基于课程开发和暑期研究计划，为本科和高中学生提供工程重点，以及K-12和代表性不足的少数民族外展通过STEM教育中心在两个参与机构。该项目的目标是开发一个综合的多尺度减少-通过将基于物理模型的LIB组件本构模型与多尺度降阶建模技术相结合，建立了机械滥用条件下LIB的降阶建模和实验框架。为了实现这一目标，本研究包括以下三个目标和计划：1）确定电池组件的本构模型，并完全覆盖低、中、高应变率：2）通过改进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，预测锂离子电池的响应; 3）对电池组电池进行动态测试，以验证所开发的多尺度模型，并将经验证的模型用于LIB设计和安全评估。多尺度建模框架将在设计最佳LIB系统方面实现重新定位，这将扩展LIB性能的传统边界。该项目将使PI能够推进其当前的计算建模和实验测试专业知识，用于LIB建模和设计，这可能会加速最先进电池技术的发现，创新和认证。建立自己的长期该奖项反映了NSF的法定使命，并被认为是值得支持的，使用基金会的知识价值和更广泛的影响审查标准进行评估。

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.