Assessment of Lumen Degradation and Remaining Life of Light-Emitting Diodes Using Physics-Based Indicators and Particle Filter

Author:

Lall Pradeep1,Zhang Hao2

Affiliation:

1. Department of Mechanical Engineering, NSF CAVE3 Electronics Research Center, Auburn University, Auburn, AL 36849 e-mail:

2. Department of Mechanical Engineering, NSF CAVE3 Electronics Research Center, Auburn University, Auburn, AL 36849

Abstract

The development of light-emitting diode (LED) technology has resulted in widespread solid state lighting (SSL) use in consumer and industrial applications. Previous researchers have shown that LEDs from the same manufacturer and operating under same use-condition may have significantly different degradation behavior. Applications of LEDs to safety critical and harsh environment applications necessitate the characterization of failure mechanisms and modes. This paper focuses on a prognostic health management (PHM) method based on the measurement of forward voltage and forward current of bare LED under harsh environment. In this paper, experiments have been done on single LEDs subjected to combined temperature–humidity environment of 85 °C, 85% relative humidity. Pulse width modulation (PWM) control method has been employed to drive the bare LED in order to reduce the heat effect caused by forward current and high frequency (300 Hz). A data acquisition system has been used to measure the peak forward voltage and forward current. Test to failure (luminous flux drops to 70%) data has been measured to study the effects of high temperature and humid environment loadings on the bare LEDs. A solid state cooling method with a Peltier cooler has been used to control the temperature of the LED in the integrating sphere when taking the measurement of luminous flux. The shift of forward voltage forward current curve and lumen degradation has been recorded to help build the failure model and predict the remaining useful life (RUL). Particle filter has been employed to assess the RUL of the bare LED. Model predictions of RUL have been correlated with experimental data. Results show that prediction of RUL of LEDs, made by the particle filter model, works with acceptable error-bounds. The presented method can be employed to predict the failure of LED caused by thermal and humid stresses.

Publisher

ASME International

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanics of Materials,Electronic, Optical and Magnetic Materials

Reference49 articles.

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