GOALI: Aging Propagation and Model-Based Prognosis for Interconnected Systems

这项学术联络与工业（GOALI）奖的研究目标是开发一种方法来理解由许多互连子系统和组件组成的工程系统中的老化传播，并通过开发工具和方法来预测寿命和了解插电式混合动力汽车中电池组系统的健康状态。研究的第一个目标是了解单个组件（例如：电池）的老化行为如何转化为整个系统的老化。第二个目标是根据对系统各组成部分健康状况的了解，制定一种评估系统健康状况的系统方法。然后，与通用汽车公司合作，使用插电式混合动力汽车电池组作为案例研究来演示所得方法。交付成果包括：电池组老化传播的数学模型和计算机模拟；与通用汽车公司合作，对寿命预测方法进行实验验证；研究生课程教材；以及为工业观众设计的短期课程。这项工作的结果将对工程系统故障预测的理论、方法和应用产生广泛的影响，超出了本项目所考虑的具体应用。通用汽车公司在这个项目中的参与是至关重要的，因为它提供了一个在现实环境中验证和实现方法的机会，这些方法提出了许多重要的挑战，例如成本限制，对大量系统（可能有数百万辆汽车）的应用，以及实现与当今消费者对保修的期望一致的稳健性程度的需求。如果这项关于互联系统老化传播和预测的研究取得成功，将极大地有助于做出明智和及时的生命周期管理决策，降低保修和维护成本，同时提高可维护性、可用性和安全性。

The research objectives of this Grant Opportunity for Academic Liaison with Industry (GOALI) award are to develop a methodology to understand the propagation of aging in engineered system consisting of many interconnects subsystem and components, and to demonstrate it by developing tools and methods to predict life and understand the state of health of battery pack systems in plug-in hybrid electric vehicles. The first goal of the research is to understand how knowledge of the aging behavior of individual components (e.g.: battery cells) translates into overall system aging. The second goal is to develop a systematic approach to assess the state of health of the system based on knowledge of its components states of health. The resulting approaches are then demonstrated using a plug-in hybrid electric vehicle battery pack as a case study, in collaboration with General Motors. Deliverables include: mathematical models and computer simulations of aging propagation in a battery pack; the experimental validation of the life prediction methods, in collaboration with General Motors; graduate course materials; and a short course designed for industrial audiences. The outcome of this work will have a broad impact on the theory, methodology and application of failure prognosis to engineered systems, beyond the specific application considered in this project. The participation of General Motors in this project is critical in that it provides an opportunity to validate and implement the methodology in a real-world setting that presents many important challenges such as cost constraints, the application to a large number of systems (potentially millions of vehicles), and the need to achieve a degree of robustness that is consistent with today's consumer expectations of warranty. If this research on aging propagation and prognosis for interconnected systems is successful, it will greatly help in making informed and timely life cycle management decisions, reducing warranty and maintenance costs while improving serviceability, availability and safety.