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

协作研究：机械滥用条件下锂离子电池的集成多尺度降阶建模和实验框架

• 批准号: 2114822
• 负责人: Xiang Zhang
• 金额: $ 27.18万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2114822&HistoricalAwards=false
• 关键词: Collaborative; Research; Integrated; Multiscale; Reduced

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.

该赠款将着重于在机械滥用条件下（例如撞击负载）下开发一个集成的计算建模和实验框架，以模拟锂离子电池（LIB）。 LIB是电动汽车最常用的电源，这导致了提高LIB的安全性的不断增加的需求，因此可以在机械滥用条件下使用它们。为了改善先进的长寿和高能液生物的安全设计和最终的可靠性，最近的趋势是使用数值模拟作为在机械滥用条件下进行LIB响应预测的昂贵且耗时的现实世界测试的替代方案。但是，由于LIB的多尺度和LIB组件的非线性响应，通过考虑复杂的微结构和不同LIB组件的非线性响应来直接建模LIB在计算上是昂贵的。为了解决这个问题，PIS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。还计划了在不同的加载条件下LIB组件的表征和测试，这将支持模型开发并最终验证计算框架。这项研究还将通过建立基于课程开发和夏季研究计划的响应迅速，灵活的教育和宣传计划，为本科和高中生的学生提供工程重点，以及K-12的少数群体以及代表性不足的少数群体通过STEM教育中心进行的，这两个项目都可以通过参与该项目进行整体效果模型，以实验的范围。具有多尺度降低订单建模技术的LIB组件的基于物理的本构模型。为了实现这一目标，研究涵盖了以下三个目标和计划：1）确定电池组件的组成型模型，并全面覆盖低，中间和高应变速率； 2）开发一个多尺度降低的计算模型，以通过推进基于特征性的降低订单均化模型（EHM）来预测LIB细胞的响应； 3）对电池电池进行动态测试，以验证已开发的多尺寸模型，并锻炼经过验证的LIB设计和安全评估模型。多尺度建模框架将在设计最佳的LIB系统时实现ReakThrough，这将扩大LIB性能的传统界限。该项目将允许PI推进其当前的LIB建模和设计实验测试专家，这可能会加速最先进的电池技术的发现，创新和认证，并确定其在复杂材料系统的建模和测试方面的长期职业，并通过评估NSF的智力统计范围来进行建立，以表达NSF的合法统计范围。 标准。

项目成果

Multiscale Modeling of Composite Materials under Volumetric and Interfacial Damage: Achieving Adaptive Model Order Reduction

体积和界面损伤下复合材料的多尺度建模：实现自适应模型降阶

• DOI: 10.2514/6.2023-0138
• 发表时间: 2023
• 期刊: AIAA SCITECH 2023 Forum
• 作者: Lin, Min;Brandyberry, David;Zhang, Xiang
• 通讯作者: Zhang, Xiang

Multiscale design of nonlinear materials using reduced-order modeling

• DOI: 10.1016/j.cma.2022.115388
• 发表时间: 2022-09
• 期刊: Computer Methods in Applied Mechanics and Engineering
• 影响因子: 7.2
• 作者: David R. Brandyberry;Xiang Zhang;P. Geubelle