The Application and Study of LED Tunable Spectrum Technology Based on Improved Particle Swarm Optimization Algorithm
CHEN Yayong
Abstract：This study is based on particle swarm optimization combined with a BP neural network algorithm to construct a multi-channel LED spectral control model simulating sunlight,achieving matching between LED lighting spectra and solar spectra at different times.The photoelectric performance of 4-channel white LED and RGB monochromatic SMD LED integrated packages was experimentally verified.The input power ratio of each channel was optimized to regulate spectral output,using spectral goodness fit coefficient e(GFC),luminous efficacy,and CRI as optimization evaluation values under different target color temperatures.Results show that the deviation of e(GFC)between simulation and measurement was controlled within±0.5%.This optimization algorithm and testing were further validated on high-power 4-channel RGBW COB integrated LED packaging devices.The research is applicable to multi-color integrated LED packaging devices,providing exploration and practical significance for setting the light power ratio and driving parameters of channels emitting spectra close to sunlight,promoting the industrial development of full-spectrum healthy white LED lighting.
Keywords：LED tunable spectrumLED integrated packaging deviceparticle swarm optimization algorithmspectral goodness fit coefficientLED full spectrum white lighting
Publication Date：2025-04-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 104-110 )