The full-spectrum white light-emitting diode (LED) emits light with a broad wavelength range by mixing all lights from multiple LED chips and phosphors. Thus, it has great potentials to be used in healthy lighting, high resolution displays, plant lighting with higher color rendering index close to sunlight and higher color fidelity index. The spectral power distribution (SPD) of light source, representing its light quality, is always dynamically controlled by complex electrical and thermal loadings when the light source operates under usage conditions. Therefore, a dynamic prediction of SPD for the full-spectrum white LED has become a hot but challenging research topic in the high quality lighting design and application. This paper proposes a dynamic SPD prediction method for the full-spectrum white LED by integrating the SPD decomposition approach with the artificial neural network (ANN) based machine learning method. Firstly, the continuous SPDs of a full-spectrum white LED driven by an electrical-thermal loading matrix are discretized by the multi-peak fitting with Gaussian model as the relevant spectral characteristic parameters. Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. Finally, the dynamically predicted spectral characteristic parameters are used to reconstruct the SPDs. The results show that: (1) The spectral characteristic parameters obtained by fitting with the Gaussian model can be used to represent the emission lights from multiple chips and phosphors in a full-spectrum white LED; (2) The prediction errors of both BP NN and GA-BP NN can be controlled at low level, that is to say, our proposed method can achieve a highly accurate SPD dynamic prediction for the full-spectrum white LED when it operates under different operation mission profiles.

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As an increasing attention towards sustainable development of energy and environment, the power electronics (PEs) are gaining more and more attraction on various energy systems. The insulated gate bipolar transistor (IGBT), as one of the PEs with numerous advantages and potentials for development of higher voltage and current ratings, has been used in a board range of applications. However, the continuing miniaturization and rapid increasing power ratings of IGBTs have remarkable high heat flux, which requires complex thermal management. In this paper, studies of the thermal management on IGBTs are generally reviewed including analyzing, comparing, and classifying the results originating from these researches. The thermal models to accurately calculate the dynamic heat dissipation are divided into analytical models, numerical models, and thermal network models, respectively. The thermal resistances of current IGBT modules are also studied. According to the current products on a number of IGBTs, we observe that the junction-to-case thermal resistance generally decreases inversely in terms of the total thermal power. In addition, the cooling solutions of IGBTs are reviewed and the performance of the various solutions are studied and compared. At last, we have proposed a quick and efficient evaluation judgment for the thermal management of the IGBTs depended on the requirements on the junction-to-case thermal resistance and equivalent heat transfer coefficient of the test samples.@en

Mid-power LED packages are now widely used in many indoor illumination applications due to several advantages. Temperature stress, humidity stress and current stress were experimentally designed and performed to accelerate the color shift of mid-power LED packages and color shift mechanisms have been discussed based on the color shift results obtained from measurements. Conclusions could be drawn:

Linear function fitting demonstrates a good linear relationship between color shift (Δu′ Δv′) and aging time almost for all the aging conditions. We can extrapolate the color shift Δu′ and Δv′ based on the fitted regression equations and then make the prediction for the total color shift Δu′v′.

Current stress can induce a different failure mode. Peak intensity reduction analysis reveals that the current stress accelerates the degradation of LED die.

Humidity test induced a substantial color shift both in u′ and v′. The u′ has an increased degradation rate after aging of 3000 h at 85%RH & 85 °C, there should be different degradation mechanisms during the whole humidity test. The molecular structure decomposition of silicone plates and then follows the silicone carbonization due to the long-term (3000 h) accumulated high localized temperature aging.@en

During the encapsulation of electronic components stresses are generated due to curing effects and the difference in thermal shrinkage between molding compound and die.@en

During the encapsulation of electronic components stresses are generated due to curing effects and the difference in thermal shrinkage between molding compound and die. These residual stresses add up to the stresses generated during thermal cycling and mechanical loading and may eventually lead to product failure. In this paper we focus on three commercial molding compounds and analyze in detail the increase in elastic modulus and the change in viscoelastic behaviour during cure. This was done with a special shear tool which allows to measure mechanical properties with sufficient accuracy in the liquid as well as in the solid state. The cure dependent viscoelastic material behaviour was modeled using a cure dependent shift factor and rubber modulus. The visoelastic behaviour of the molding compounds is also shown not to be stable. During postcure the materials slowly continue to crosslink thereby systematically changing their viscoelastic behaviour. The material models presented here therefore only account for the initial curing stage and do not include postcure.@en