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Physics-of-Failure Approach to PrognosticsAs 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.
Document ID
20170011538
Document Type
Presentation
Authors
Kulkarni, Chetan S. (SGT, Inc. Moffett Field, CA, United States)
Date Acquired
December 6, 2017
Publication Date
September 11, 2017
Subject Category
Electronics and Electrical Engineering
Report/Patent Number
ARC-E-DAA-TN46588
Meeting Information
Center for Advanced Life Cycle Engineering (CALCE)(College Park, MD)
Funding Number(s)
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Public Use Permitted.

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