Uncertainty Quantification for Junction Temperature of Automotive LED With Die-Attach Layer Microstructure

Abstract

Junction temperature is a critical metric for reliability evaluation of light-emitting diodes (LEDs) as light sources for automotive lamps. While numerous researchers have quantified the junction temperature accurately, uncertainty factors including electrical–thermal–mechanical boundary conditions and the die-attach layer (DAL) microstructure in automotive LEDs have not been addressed; the propagation of these variables degrades the precision of the junction temperature quantification. In this paper, a junction temperature uncertainty quantification framework involving finite element modeling, the evolution separation spectrum, and Monte Carlo simulation is introduced to build 3-D stochastic finite element models for automotive LEDs with stochastic DAL microstructures. Evolution of the statistical junction temperature probability for three types of automotive LEDs subjected to electrical–thermal–mechanical loadings is discussed and the failure risk is predicted. The results show that the temperature-mechanical displacement coupling of the DAL plays a major role in the junction temperature with regard to automotive boundary loadings, and the thermal power load is more likely to cause junction temperature deterioration of LED with DALs having voids. The automotive LED failure rate is dependent upon the boundary conditions, the DAL microstructures, and the LED numbers. The failure rate for LED modules with DALs having voids is higher than that for modules with uniform DALs; the failure rate is higher in aged LED modules; the failure risk at the given junction temperature threshold increases with increasing LED numbers in the module; and when operating at lower junction temperatures, the voids in LED DALs may not increase the module failure risk.