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Prognostics and Health Monitoring: Application to Electric Vehicles
NTRS Full-Text: Click to View  [PDF Size: 3.6 MB]
Author and Affiliation:
Kulkarni, Chetan S.(SGT, Inc., Moffett Field, CA, United States)
Abstract: As 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.
Publication Date: Aug 23, 2017
Document ID:
20170011585
(Acquired Dec 13, 2017)
Subject Category: ELECTRONICS AND ELECTRICAL ENGINEERING
Report/Patent Number: ARC-E-DAA-TN46259
Document Type: Oral/Visual Presentation
Meeting Information: Palto Alto Research Center; 23 Aug. 2017; Palto Alto, CA; United States
Meeting Sponsor: Palto Alto Research Ctr.; Palto Alto, CA, 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: 61p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: SYSTEMS HEALTH MONITORING; DECISION MAKING; ELECTRIC MOTOR VEHICLES; AUTONOMY; MATHEMATICAL MODELS; ALGORITHMS; TRANSISTORS; FAILURE MODES; DEGRADATION; CAPACITORS; CIRCUITS; LITHIUM BATTERIES
Other Descriptors: PROGNOSTICS; ELECTRIC VEHICLES; HEALTH MONITORING
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