CAREER: Identifiability Optimization in Electrochemical Battery Systems

该学院早期职业发展(CALEAR)计划奖旨在检查电化学电池模型参数的可识别性，定义为能够从实验数据快速、唯一和准确地确定这些参数的程度。该研究将建立在PI在电池参数识别中的前人研究基础上。第一个目标是探索量化可识别性的不同指标。该研究还将开发用于从实验数据估计锂离子电池的内部状态变量(例如，给定电池充满或耗尽的程度)和参数(例如，电池健康或不健康的程度)的算法。这两个贡献加在一起将成为可识别性优化的基础。在可识别性优化中需要获得的关键信息包括：要安装在锂离子电池上以提高其健康退化的检测速度和准确性的传感器的类型，以及能够以最少的时间和成本产生关于电池模型参数的最大量信息的实验室循环实验的类型。这项研究将对多个社会利益相关者产生更广泛的影响。整个社会将受益于电池参数可识别性的提高带来的在线电池诊断的改善。电池实验者将能够从更短、更便宜的实验室测试中获得更准确的参数。科学界将从弥合电化学、在线评估和最优控制文献之间当前差距的努力中受益。最后，这项工作将侧重于外联和教育活动，其中包括：(I)通过宾夕法尼亚州立大学的Schreyer荣誉学院吸引本科生，特别是妇女和代表性不足的少数群体的参与；(Ii)在电池系统动力学和控制领域创建基于网络的课程；(Iii)通过ARPA-E等机构资助的补充性研究努力吸引行业合作伙伴的参与；以及(Iv)为K-12 STEM外联创建以电池为重点的教材。

This Faculty Early Career Development (CAREER) Program award is to examine the identifiability of electrochemical battery model parameters, defined as the degree to which one can quickly, uniquely, and accurately determine these parameters from experimental data. The research will build on previous research by the PI in battery parameter identification. The first goal is to explore different metrics for quantifying identifiability. The research will also develop algorithms for estimating both the internal state variables (e.g., degree to which a given battery is full or empty) and parameters (e.g., degree to which a battery is healthy or unhealthy) of lithium-ion batteries from experimental data. Together, these two contributions will serve as foundations for identifiability optimization. Critical information to be acquired in identifiability optimization include: the type of of sensors to be install on a lithium-ion battery to improve the detection speed and accuracy of its health degradation and the type of laboratory cycling experiments that can yield the greatest amount of information about battery model parameters with minimal time and cost.The research will have broader impact on multiple societal stakeholders. Society at large will benefit from improvements in online battery diagnostics enabled by improvements in battery parameter identifiability. Battery experimentalists will be able to obtain more accurate parameters from shorter, less expensive laboratory tests. The scientific community will benefit from the efforts to bridge current gaps among electrochemistry, online estimation, and optimal control literature. Finally, the effort will focus on outreach and education activities including: (i) the engagement of undergraduate students, especially women and underrepresented minorities through Penn State University's Schreyer Honors College; (ii) the creation of web-based courses in the areas of battery system dynamics and control; (iii) the engagement of industrial partners through complementary research efforts funded by agencies such as ARPA-E; and (iv) the creation of battery-focused educational materials for K-12 STEM outreach.