电子器件2024，Vol.47Issue(2)：496-501,6.DOI:10.3969/j.issn.1005-9490.2024.02.031
基于光效和BP神经网络的LED结温预测研究
Research on LED Junction Temperature Prediction Based on Luminous Efficiency and BP Neural Network
摘要
Abstract
A prediction method of junction temperature of high-power LED based on luminous efficiency and BP neural network is pro-posed.It is found that the luminous efficiency of LED will drop sharply when the junction temperature rises to about 80℃,and the functional relationship between luminous efficiency and junction temperature will change,which will affect the measurement accuracy.To solve this problem,based on the functional relationship between luminous efficiency and junction temperature,an experimental plat-form is constructed to obtain the data of luminous efficiency and corresponding junction temperature,and then the LED junction temper-ature prediction model is established through BP neural network.The maximum error between the data obtained from the model and the forward voltage method is 2.1℃,which verifies the feasibility of the proposed method.At the same time,the internal structure of LED does not need to be considered,and the junction temperature of high-power LED can be easily and accurately predicted.关键词
大功率LED/发光效率/BP神经网络/结温Key words
high power LED/luminous efficiency/BP neural network/junction temperature分类
信息技术与安全科学引用本文复制引用
王宸,张军朝,许并社,张婕,付强..基于光效和BP神经网络的LED结温预测研究[J].电子器件,2024,47(2):496-501,6.基金项目
山西省"1331工程"基于大数据的智慧城市照明数据共享与公共服务平台工程技术研究中心专项建设项目(SC19100026) （SC19100026）
山西省电气传动及物联网工程研究中心建设项目(RD1900000333) （RD1900000333）
山西省研究生教改项目(2017JG25) （2017JG25）
