Application of Particle Filter to On-Board Life Estimation of LED Lights

Light-emitting diode (LED) based lights used in safety critical applications need continuous monitoring of their light output since lumen degradation is one of many failure modes. Airport ground lighting is one such application where LED lights are replacing traditional halogen lamp-based lights in the approach, runways, and taxiways. The question that still remains to be addressed is the prediction of the remaining useful life (RUL) of LED light any time during the service life cycle of the light. Life prediction methods based on reliability analysis and filtering algorithms proposed in the past were predominantly based on accelerated life tests and cannot be readily implemented for on-board diagnosis. Here, we present a model-based prognostic approach that uses particle filtering (PF) to predict the RUL for high power white LEDs that can be readily implemented on-board the lighting system. Lumen maintenance data at different test conditions are used in the PF method to calculate the
$L_{70}$
, i.e., time at which lumen output reaches 70% of the initial value. A junction temperature model is developed by mapping the lumen degradation data to the junction temperature.
$L_{70}$
calculated from PF is compared with a standard method recommended by the Illumination Engineering Society (IES). Finally, the RUL obtained using both the methods were analyzed.