Solar spectrum matching using monochromatic LEDs

Xu, G-Q; Jing-hui, 张竞辉 Zhang; Cao, G-Y; Xing, M-S; DS(李东生), Li; Yu, J.J.

doi:10.1177/1477153516628330

Cited by 20 publications

(7 citation statements)

References 21 publications

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“…It does not use any reflector or optics to achieve the AAA Class in contrast with [19] or [21], while ranges a wider wavelength interval than the 400-750 nm in [23]. It improves other low-cost attempts using off-the-shelf components and Arduino microcontroller, reaching AAA Class in contrast with [25] or [28], and using a lower number of LEDs than [27], reaching the theoretical value obtained in [26].…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…Wang et al [26] use a numerical algorithm by MATLAB to obtain a theoretical estimation of the number of LEDs needed for achieving the solar spectrum using 14 wavelengths. Xu et al [27] sweep the market to explore 103 kinds of LEDs, obtaining a theoretical 380-780-nm sun simulator by fitting the emissions of 34 of them to a spectrum that approximates to 88.7% of the sun one, and seeking how this fitting reduces when decreasing the number of LED types. In the lower limit of the low cost, Nakajima et al [28] used even a single LED with a cover of a custom phosphor powder to achieve a broadband sun simulator.…”

Section: Introductionmentioning

confidence: 99%

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A Low-Cost LED-Based Solar Simulator

López-Fraguas

Sánchez‐Pena

Vergaz

2019

IEEE Trans. Instrum. Meas.

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Solar simulators are a fundamental instrument to characterize solar cells parameters, as they can reproduce the operating conditions under which the solar cells are going to work. However, these systems are frequently big, heavy, and expensive, and a small solar simulator could be a good contribution to test small prototyping devices manufactured in research labs, especially if it could manage the irradiation at any wavelength interval in a custom way. We have designed, developed, and calibrated a small solar simulator made entirely with LEDs, no optics inside, and electronically controlled through a PC using an Arduino microcontroller. The whole structure is 3-D printed in black PLA plastic. The electrical current through the LEDs, and thus the spectral irradiance of the simulator, is controlled with a very intuitive LabVIEW interface. As our calibration proves, we have built an easily reproducible and lowcost Class AAA solar simulator in a central illumination area of 1 cm 2 , according to the IEC60904-9 standard. This means that the homogeneity in that area is under a 2% deviation in spatial terms, below 0.5% in temporal terms, and is a factor of a 3% close to the AM1.5G sun reference spectrum. The system can be built and used in any research lab to get quick tests of new small solar cells of any material.

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Section: Discussion Of Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Low-Cost LED-Based Solar Simulator

López-Fraguas

Sánchez‐Pena

Vergaz

2019

IEEE Trans. Instrum. Meas.

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“…It is difficult to fill the "green gap" between 520 nm -600 nm and 675 nm-690 nm. The reason for this gap has been described in Ref [30], [26], [27], [7]. The green gap can be covered with phosphorcoated LEDs.…”

Section: Led Modellingmentioning

confidence: 91%

“…This method determines the power per LED PowerLEDi, where i= 1, 2, …, the number of LEDs that needs to be applied to achieve the target spectrum. Let SPDLEDi(𝝺) define the SPD of the modelled LEDs [24], [26], [27]. The implementation of the LM algorithm given in Figure 2 is described below [21], [22. Step 1 : Select the initial value for each PowerLEDi Step 2…”

Section: Lm Algorithm For Horticulturementioning

confidence: 99%

Metabolic Variations in Grass C. dactylon and Selection of Optimal LEDs for the Horticulture Luminaire Using LM Algorithm

et al. 2021

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Healing of various ailments using herbal medicines is gaining much interest. Plants classified as grasses, specifically Cynodon dactylon, are an appreciated group of monocots used in many herbal remedies. In this work, C. dactylon, is grown naturally and also under market available LED Luminaires with different lighting conditions. Until 2010, most of the plants were grown under conventional lamps that are not spectrally tunable. Cynodon dactylon, the grass, was grown under two different light spectrum, two light levels and three photoperiods (9hours, 12 hours, 15 hours) to extend our experiential knowledge. The biomass accumulation was highest when grown under a lower RB ratio-12-hour-163μmol/s, and phenolic content was highest at 92.8 mg/g wt Gallic Acid Equivalents under combined light source at 15-hour photoperiod. A spectrally tunable LED light source with an optimal quantity of LEDs saves cost, space and energy. Considering the light parameters from the light sources used for growing C. dactylon , Levenberg-Marquardt (LM) algorithm is implemented to select an optimal LED quantity that composes the light source. The algorithm simulates the given target spectrum with minimum fitness error. The method applied to model LEDs, its validation against the practical LED spectrum, spectrum matching and computation of Luminous flux, Photosynthetic Photon Flux and efficacy is also presented. Many spectrums were simulated to validate the performance of the algorithm. A solution of optimal LEDs for three Photosynthetic Photon Flux (PPF) levels with LEDs derived, and it is observed that the number of LEDs increased with PPF.

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“…Peak wavelengths and Full-Width-at-Half-Maximum (FWHM) varied respectively from 400 nm to 700 nm and from 20 nm to 300 nm (Ohno Yoshi 2005;Xie B. et al 2016). In practice, optimal projector spectra can be fabricated by a combination of monochromatic LEDs, quantum dots, and phosphors (Xie Bin et al 2017;Xu et al 2017).…”

Section: Theoretical Systemsmentioning

confidence: 99%

Improved and Robust Spectral Reflectance Estimation

Zhang

Meuret

Xiang-guo

et al. 2020

LEUKOS

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Accurately estimating spectral reflectance functions from color camera images is a hot research subject that demonstrates tremendous potential for illuminating engineering and computer vision applications. However, the impact of the illumination spectrum and camera responsivity (system functions) to the estimation accuracy has not been systematically studied so far, nor the impact of 'training' spectral reflectance set. In this study, a dual imaging reflectance optimization system is used based on a neural network and optimal system functions that are resp. trained and optimized using several sample sets. Simulations showed that such optimal systems, trained and optimized with the IES TM30 spectral reflectance set, can have a substantially higher estimation accuracy compared to 'real' systems composed of commercially available projector spectra and camera responsivities and that they are sufficiently robust under small changes in system function peak wavelength and spectral width due to changes in working temperature or with passing time. An analysis of the impact of the specific sample set database adopted for neural net training on estimation accuracy showed that training with the IES set results in good and stable performance, even for other sample sets and different illumination spectra. Training with the spectrally uniform IES spectral reflectance set is therefore advised for general purpose, high-accuracy reflectance estimation systems. A comparison with a state-ofthe-art method shows that the proposed method has a higher color prediction accuracy and a significantly shorter running time for realistic images with high resolution.

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Solar spectrum matching using monochromatic LEDs

Cited by 20 publications

References 21 publications

A Low-Cost LED-Based Solar Simulator

A Low-Cost LED-Based Solar Simulator

Metabolic Variations in Grass C. dactylon and Selection of Optimal LEDs for the Horticulture Luminaire Using LM Algorithm

Improved and Robust Spectral Reflectance Estimation

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