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Physics-of-Failure Approach to Prognostics
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Author and Affiliation:
Kulkarni, Chetan S.(SGT, Inc., Moffett Field, CA, United States)
Abstract: As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.
Publication Date: Sep 11, 2017
Document ID:
20170011538
(Acquired Dec 11, 2017)
Subject Category: ELECTRONICS AND ELECTRICAL ENGINEERING
Report/Patent Number: ARC-E-DAA-TN46588
Document Type: Oral/Visual Presentation
Meeting Information: Center for Advanced Life Cycle Engineering (CALCE) ; 11 Sep. 2017; College Park, MD; United States
Meeting Sponsor: Maryland Univ.; College Park, MD, United States
Contract/Grant/Task Num: NNA14AA60C
Financial Sponsor: NASA Ames Research Center; Moffett Field, CA, United States
Organization Source: NASA Ames Research Center; Moffett Field, CA, United States
Description: 72p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: PILOTLESS AIRCRAFT; FLIGHT INSTRUMENTS; MANUFACTURING; FAILURE; SAFETY; SYSTEMS HEALTH MONITORING; INDICATORS; LIFE (DURABILITY); CAPACITORS; TRANSISTORS; DEGRADATION; PREDICTIONS; ALGORITHMS; DECISION MAKING
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Last Modified: December 11, 2017
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