A stochastic process based reliability prediction method for LED driver. (October 2018)

• Record Type: Journal Article
• Authors: Sun, Bo; Fan, Xuejun; van Driel, Willem; Cui, Chengqiang; Zhang, Guoqi
• Is Part Of: Reliability engineering & system safety. Volume 178(2018)
• Page Start: 140
• Page End: 146
• Publication Date: 2018-10
• Subjects: LED driver -- LED lamp -- Lumen depreciation -- Stochastic process -- Reliability prediction; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2018.06.001
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: More general issues have been discussed in the conclusion section. The reason of selecting the exponential Wiener process has been added. Definition of scenarios have been updated in the case study section. Abstract: In this study, we present a general methodology that combines the reliability theory with physics of failure for reliability prediction of an LED driver. More specifically, an integrated LED lamp, which includes an LED light source with statistical distribution of luminous flux, and a driver with a few critical components, is considered. The Wiener process is introduced to describe the randomness of lumen depreciation. The driver's survival probability is described using a general Markov Chain method. The system compact thermal model (physics of failure model) is developed to couple with the reliability methods used. Two scenarios are studied: Scenario S1 considers constant driver's operation temperature, while Scenario S2 considers driver's temperature rise due to lumen depreciation. It has been found that the wide life distribution of LEDs will lead to a large range of the driver's survival probability. The proposed analysis provides a general approach for an electronic system to integrate the reliability method with physics models.