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Prognostics and Health Monitoring: Application to Electric VehiclesAs more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. 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.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. determine state-of-charge in batteries. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.
Document ID
20170011585
Acquisition Source
Ames Research Center
Document Type
Presentation
Authors
Kulkarni, Chetan S.
(SGT, Inc. Moffett Field, CA, United States)
Date Acquired
December 7, 2017
Publication Date
August 23, 2017
Subject Category
Electronics And Electrical Engineering
Report/Patent Number
ARC-E-DAA-TN46259
Meeting Information
Meeting: Palto Alto Research Center
Location: Palto Alto, CA
Country: United States
Start Date: August 23, 2017
Sponsors: Palto Alto Research Ctr.
Funding Number(s)
CONTRACT_GRANT: NNA14AA60C
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Prognostics
Electric Vehicles
Health Monitoring
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