DocumentCode
3365300
Title
Prediction of lumen output and chromaticity shift in LEDs using Kalman Filter and Extended Kalman Filter based models
Author
Lall, P. ; Junchao Wei ; Davis, Lisa
Author_Institution
NSF-CAVE3 Electron. Res. Center, Auburn Univ., Auburn, AL, USA
fYear
2013
fDate
24-27 June 2013
Firstpage
1
Lastpage
14
Abstract
Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based mo- els have been compared with the TM-21 model predictions and experimental data.
Keywords
Kalman filters; LED lamps; matrix algebra; remaining life assessment; Bayesian framework; EKF; L70 life; LED; LM-80 test; SSL luminaires; TM-21 model predictions; chromaticity shift prediction; control matrix; control vector; extended Kalman filter; light emitting diodes; lumen depreciation; lumen maintenance life prediction model; lumen output prediction; measured vector; measurement matrix; measurement noise; process noise; second order Kalman Filter model; solid-state lighting luminaires; system dynamics matrix; Color; Computational modeling; Degradation; Image color analysis; Kalman filters; Light emitting diodes; Maintenance engineering; Extended Kalman Filter; Kalman Filter; LEDs; Life Prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Prognostics and Health Management (PHM), 2013 IEEE Conference on
Conference_Location
Gaithersburg, MD
Print_ISBN
978-1-4673-5722-7
Type
conf
DOI
10.1109/ICPHM.2013.6621457
Filename
6621457
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