Energy efficiency and color quality limits in artificial light sources emulating natural illumination

Wim Hertog; Aleix Llenas; Jesús M. Quintero; Charles E. Hunt; Josep Carreras

doi:10.1364/OE.22.0A1659

Optics Express
Vol. 22,
Issue S7,
pp. A1659-A1668
(2014)
•https://doi.org/10.1364/OE.22.0A1659

Energy efficiency and color quality limits in artificial light sources emulating natural illumination

Wim Hertog, Aleix Llenas, Jesús M. Quintero, Charles E. Hunt, and Josep Carreras

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Wim Hertog, Aleix Llenas, Jesús M. Quintero, Charles E. Hunt, and Josep Carreras, "Energy efficiency and color quality limits in artificial light sources emulating natural illumination," Opt. Express 22, A1659-A1668 (2014)

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- Illumination Design
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About this Article
History
- Original Manuscript: June 25, 2014
- Revised Manuscript: August 25, 2014
- Manuscript Accepted: October 6, 2014
- Published: October 23, 2014
Virtual Issues
Virtual Journal for Biomedical Optics Vol. 10, Iss. 1

Abstract

We present in this work a calculation of the theoretical limits attainable for natural light emulation with regard to the joint optimization of the Luminous Efficacy of Radiation and color fidelity by using multiple reflectance spectra datasets, along with an implementation of a physical device that approaches these limits. A reduced visible spectrum of blackbody radiators is introduced and demonstrated which allows lamps designed to emulate natural light to operate with excellent color fidelity and higher efficiency as compared to full visible spectrum sources. It is shown that even though 3,000K and 5,500K blackbody sources have maximum efficacies of 21 lm/W and 89 lm/W, respectively, reduced-spectrum artificial light sources can exceed those values up to 363 lm/W and 313 lm/W, respectively, while retaining excellent color fidelity. Experimental demonstration approaching these values is accomplished through the design and implementation of a 12-channel light engine which emits arbitrarily-tunable spectra. The color fidelity of the designed spectra is assessed through Color Rendering Maps, showing that color fidelity is preserved uniformly over a large spectral reflectance dataset, unlike other approaches to generate white light.

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Fig. 1 Spectral limits for natural-light emulation. Trade-offs between R_a (left column) and efficacy (central column) in Reduced Visible blackbody spectrum light sources with 3,000K and 5,500K CCTs. The right column gives the score, S, obtained using Equation (1) when a spectrum satisfies the (user-defined) criteria of R_a >90, Efficacy>200 lm/W and Δ_uv <0.0054

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Fig. 2 Limits to photometric properties of natural light. Theoretical maximum achievable efficacy and color-rendering limits for two different scenarios: (a) optimized for highest efficacy and (b) optimized for best color quality, emulating natural light. (Solid and dashed lines are spline interpolations of data, and should be understood as a simple guide to the eye)

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Fig. 3 Color Rendering Maps (CRM) represented in the CIE 1976 (a^*, b^*) color space for the best rated (HS) reduced visible spectra with a CCT of 3,000K and 5,500K, an RGB LED based light source with a CCT of 3,000K and finally a triphosphor fluorescent light source with a CCT of 5,500K. Row (a) shows the color fidelity of the light sources tested using 1,269 reflectance spectra of the Munsell Book of Colors. Row (b) uses the Agfa IT8.7 standard while rows (c) and (d) show the color rendering properties evaluated over a large number of reflectance spectra of natural materials such as different woods and leaves (c) and flower leaves (d). CRM (e) uses a comprehensive dataset using thousands of artificially generated smooth reflectance spectra, including reflectance data not occurring in existing man-made or natural materials

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Fig. 4 Measured light engine spectral power distribution (solid line) compared with ideal reduced- spectrum input (dotted line) for 3,000K and 5,500K

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Tables (2)

Table 1 Spectral parameters of best natural–light emulation. Detailed information of Highest Efficacy (HE), Highest R_a (HR_a) and Highest Score (HS) spectra

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Table 2 Efficacy and color quality assessment of the real light engine spectra shown in Figure 4 as compared to the best-rated spectra obtained from the calculated theoretical limits

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Equations (1)

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S = \frac{1}{\sqrt{2}} \sqrt{{(\frac{R_{a}}{R_{a}^{*}})}^{2} + {(\frac{Eff}{{Eff}^{*}})}^{2}}

Highest Efficacy (HE)	Highest Ra (HRa)	Highest Score (HS)

Emulation at 3,000K. Target Efficacy = 364.41 lm/W

Eff = 363 lm/W Ra = 90.0 S = 0.950 Δ_uv = 0.0053 Δλ = [421, 648] CCT = 3, 280K R_9–12 = 75.0	Eff = 250 lm/W Ra = 99.7 S = 0.856 Δ_uv = 0.0002 Δλ = [403, 703] CCT = 3, 010K R_9–12 = 99.2	Eff = 363 lm/W Ra = 90.5 S = 0.951 Δ_uv = 0.0054 Δλ = [424, 649] CCT = 3, 260K R_9–12 = 76.0

Emulation at 5,500K. Target Efficacy = 314.92 lm/W

Eff = 315 lm/W Ra = 94.4 S = 0.972 Δ_uv = 0.0054 Δλ = [421, 653] CCT = 5, 620K R_9–12 = 85.7	Eff = 262 lm/W Ra = 99.2 S = 0.916 Δ_uv = 0.0021 Δλ = [421, 709] CCT = 5, 370K R_9–12 = 98.4	Eff = 313 lm/W Ra = 95.4 S = 0.975 Δ_uv = 0.0053 Δλ = [424, 658] CCT = 5, 490K R_9–12 = 88.6

Parameter assessment	3,000K	5,500K
LER (theoretical, lm/W)	363	313
LER (engine, lm/W)	329	295
R_a (theoretical)	90.5	95.4
R_a (engine)	94	92.1
Δ_uv (theoretical)	0.0054	0.0053
Δ_uv (engine)	0.0054	0.0053
CCT (theoretical, K)	3,260	5,490
CCT (engine, K)	3,256	5,494
R₉ (theoretical)	39.1	66.3
R₉ (engine)	62.5	88.2
R_9–12 (theoretical)	76.0	88.6
R_9–12 (engine)	85.2	87.1

Highest Efficacy (HE)	Highest Ra (HRa)	Highest Score (HS)

Emulation at 3,000K. Target Efficacy = 364.41 lm/W

Eff = 363 lm/W Ra = 90.0 S = 0.950 Δ_uv = 0.0053 Δλ = [421, 648] CCT = 3, 280K R_9–12 = 75.0	Eff = 250 lm/W Ra = 99.7 S = 0.856 Δ_uv = 0.0002 Δλ = [403, 703] CCT = 3, 010K R_9–12 = 99.2	Eff = 363 lm/W Ra = 90.5 S = 0.951 Δ_uv = 0.0054 Δλ = [424, 649] CCT = 3, 260K R_9–12 = 76.0

Emulation at 5,500K. Target Efficacy = 314.92 lm/W

Eff = 315 lm/W Ra = 94.4 S = 0.972 Δ_uv = 0.0054 Δλ = [421, 653] CCT = 5, 620K R_9–12 = 85.7	Eff = 262 lm/W Ra = 99.2 S = 0.916 Δ_uv = 0.0021 Δλ = [421, 709] CCT = 5, 370K R_9–12 = 98.4	Eff = 313 lm/W Ra = 95.4 S = 0.975 Δ_uv = 0.0053 Δλ = [424, 658] CCT = 5, 490K R_9–12 = 88.6

Parameter assessment	3,000K	5,500K
LER (theoretical, lm/W)	363	313
LER (engine, lm/W)	329	295
R_a (theoretical)	90.5	95.4
R_a (engine)	94	92.1
Δ_uv (theoretical)	0.0054	0.0053
Δ_uv (engine)	0.0054	0.0053
CCT (theoretical, K)	3,260	5,490
CCT (engine, K)	3,256	5,494
R₉ (theoretical)	39.1	66.3
R₉ (engine)	62.5	88.2
R_9–12 (theoretical)	76.0	88.6
R_9–12 (engine)	85.2	87.1

Abstract

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Figures (4)

Tables (2)

Equations (1)

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