An improved accelerated degradation model for LED reliability assessment with self-heating impacts

Abstract

Light-emitting diodes (LEDs) are a solid-state light source being used in numerous applications, including display, communications, medical services, etc. However, the reliability assessment of LED components is still challenging due to the growing up of the LED complexity and/or the miniaturization of assembly technologies. To face this challenge, this paper proposes a novel accelerated degradation testing (ADT) model considering the self-heating impact in the degradation process of a LED component. So, the self-heating impact is first analyzed and modeled. In fact, the junction temperature of a LED component depends not only on the heat generation (e.g., drive current, dispersing heat) but also on the current state (degradation level) of the component. Then, a modified stochastic difference equation is developed for modelling the degradation process by considering the self-heating impact. The LED reliability formulation is finally derived. In addition, an estimation method based on the maximum likelihood is developed to estimate the proposed model's parameters from experimental data. To validate our models, a case study for LED light sources is implemented. The obtained results show that, compared to the TM-21 standard and the conventional ADT methods, our proposed approach achieves better results in the LED reliability assessment.