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Junction temperature and luminous flux prediction for white LED array based on electrical-photo-thermal modeling

Journal Article (2024)
Author(s)

Minne Liu (Fudan University)

Wenyu Li (Fudan University)

Wei Chen (Fudan University)

Mesfin S. Ibrahim (New Territories)

Jingkang Xiong (Changzhou Institute of Technology Research for Solid State Lighting)

Guoqi Zhang (TU Delft - Electronic Components, Technology and Materials)

Jiajie Fan (Fudan University, Chinese Academy of Sciences, Fudan Zhangjiang Institute)

Research Group
Electronic Components, Technology and Materials
DOI related publication
https://doi.org/10.1016/j.csite.2023.103940
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Publication Year
2024
Language
English
Research Group
Electronic Components, Technology and Materials
Volume number
54
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Abstract

During the operation of an LED array, its thermal and optical performances are always not equal to the superposition of the individual LED's characteristics because of a significant thermal coupling effect between the arrays. Based on this, this paper proposes an electrical–photo-thermal model, with considering both junction temperature and luminous flux, to predict the both the thermal and optical performances of LED arrays operated under different currents, case temperatures, and lighting methods. The junction temperature and luminous flux of a single LED operating under different driving currents and case temperature conditions are firstly collected to establish the luminous flux response surface model of a single chip. Then it is used to predict the luminous flux of an array, whose junction temperature is predicted using both thermal coupling matrix (TCM) and numerical models. Experiments verify the luminous flux of the LED array under different operation conditions and show that the proposed electrical–photo-thermal modeling can be used to predict the thermal and optical parameters of LED arrays with 95 % accuracy. Thus, it is effective for the fast prediction of the junction temperature and luminous flux of large LED systems with array structures, i.e. intelligent automotive lightings and displays.