DocumentCode :
60565
Title :
Prediction of L70 Life and Assessment of Color Shift for Solid-State Lighting Using Kalman Filter and Extended Kalman Filter-Based Models
Author :
Lall, Pradeep ; Junchao Wei
Author_Institution :
Dept. of Mech. Eng., Auburn Univ., Auburn, AL, USA
Volume :
15
Issue :
1
fYear :
2015
fDate :
Mar-15
Firstpage :
54
Lastpage :
68
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 nonclimate 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 the 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. Currently, 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. The 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% 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. The measured state variable has been related to the underlying damage using physics-b- sed models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF- and EKF-based models have been compared with the TM-21 model predictions and experimental data.
Keywords :
Kalman filters; LED lamps; failure analysis; filament lamps; lighting; Bayesian framework; EKF; KF; Kalman filter; L70 lamp life prediction; LED; LM-80 test data; SSL luminaire; TM-21 model; color shift assessment; control matrix; control vector; desert environments; extended Kalman filter-based model; light emitting diode failure mechanism; light sources; lumen maintenance life prediction model; measured vector; measurement matrix; measurement noise; nonclimate controlled warehouses; outdoor applications; preceding time step; process noise; solid-state lighting; system dynamics matrix; Color; Computational modeling; Degradation; Image color analysis; Kalman filters; Light emitting diodes; Maintenance engineering; Kalman filters; L70; LED lamps; Lighting; color shift; life prediction; light emitting diodes; luminuous flux degradation; reliability;
fLanguage :
English
Journal_Title :
Device and Materials Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
1530-4388
Type :
jour
DOI :
10.1109/TDMR.2014.2369859
Filename :
6967847
Link To Document :
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