GOALI: Model-Based System Fault Diagnosis and Prognosis - Passive Robustness and Aging Prediction - Application to automotive electrical systems

GOALI：基于模型的系统故障诊断和预测 - 被动鲁棒性和老化预测 - 在汽车电气系统中的应用

• 批准号: 0825655
• 负责人: Giorgio Rizzoni
• 金额: $ 24.99万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0825655&HistoricalAwards=false
• 关键词: GOALI; Model; Based; System; Fault

The research objective of this award is to develop methods for improving the diagnosis and prognosis of complex engineered systems. Real world systems are inherently subject to faults, and information on abnormal behavior of components and processes can be obtained through measured signals. The aim of this research is to exploit the information provided by sensor signals together with deep knowledge of the physical behavior of a complex system to create a unified framework for the systematic design of diagnostic and prognostic algorithms and for the prediction of system aging. Today, there are few, if any, general results concerning system prognosis and aging; the research, if successful, will result in methods that are general enough to be applied to engineered systems in different domains, for example automotive, aerospace, chemical processes and manufacturing. Deliverables for this project include software for the design and analysis of diagnostic algorithms, experimental data, mathematical models, and educational materials for engineering students.This GOALI project is conducted in close collaboration with a major automotive manufacturer, General Motors, and aims to apply the new methodology to the diagnosis of automotive electrical systems and to the prognosis and life prediction of automotive batteries. If successful, the research will result in significantly greater reliability of future automotive electrical and energy storage systems. This may eventually result in reduced warranty costs and increased customer satisfaction, with the potential of touching millions of automobile owners around the world. The research may also have a positive impact on accelerating the introduction of advanced electrical and energy storage systems in future electric and hybrid automobiles by increasing their reliability and serviceability. Further, the educational outcomes of the project will affect undergraduate and graduate engineering students at two major universities as well as practicing engineers in the automotive industry through distance education programs.

该奖项的研究目标是开发改进复杂工程系统的诊断和预测的方法。现实世界的系统固有地受到故障的影响，并且可以通过测量信号获得有关组件和过程异常行为的信息。本研究的目的是利用传感器信号提供的信息，结合对复杂系统物理行为的深入了解，为诊断和预测算法的系统设计以及系统老化的预测创建一个统一的框架。今天，关于系统预后和老化的一般结果很少，如果有的话；这项研究如果成功，将产生足够通用的方法，应用于不同领域的工程系统，例如汽车、航空航天、化学过程和制造业。该项目的可交付成果包括用于设计和分析诊断算法的软件、实验数据、数学模型和工程专业学生的教材。该GOALI项目是与主要汽车制造商通用汽车公司密切合作进行的，旨在将新方法应用于汽车电气系统的诊断以及汽车电池的预后和寿命预测。如果成功，这项研究将显著提高未来汽车电气和储能系统的可靠性。这可能最终会降低保修成本，提高客户满意度，并有可能触及全球数百万车主。该研究还可能通过提高可靠性和可维护性，对加速在未来电动和混合动力汽车中引入先进的电力和能量存储系统产生积极影响。此外，该项目的教育成果将通过远程教育计划影响两所主要大学的本科和研究生工程专业学生以及汽车行业的实践工程师。