U.S. patent application number 17/238137 was filed with the patent office on 2021-08-05 for system and method for light optimization.
This patent application is currently assigned to SHENZHEN UNIVERSITY. The applicant listed for this patent is SHENZHEN UNIVERSITY. Invention is credited to Qi YAO.
Application Number | 20210239522 17/238137 |
Document ID | / |
Family ID | 1000005534913 |
Filed Date | 2021-08-05 |
United States Patent
Application |
20210239522 |
Kind Code |
A1 |
YAO; Qi |
August 5, 2021 |
SYSTEM AND METHOD FOR LIGHT OPTIMIZATION
Abstract
The present disclosure relates to a method and related system
for spectrum optimization of an illumination light source. Spectrum
optimization according to the present disclosure can be based on
various optimization parameters, including but not limited to
luminous efficacy, color rendering effect, luminous efficacy of
radiation, mesopic efficacy of radiation, cirtopic efficacy of
radiation, etc. The present method and system are capable of
optimizing illumination performance of a light source in various
aspects in an individual or integrated manner. Further, the present
method and system are capable of accommodating different
illumination purposes and conditions by combining and prioritizing
different optimization parameters.
Inventors: |
YAO; Qi; (Shenzhen,
CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SHENZHEN UNIVERSITY |
Shenzhen |
|
CN |
|
|
Assignee: |
SHENZHEN UNIVERSITY
Shenzhen
CN
|
Family ID: |
1000005534913 |
Appl. No.: |
17/238137 |
Filed: |
April 22, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16695040 |
Nov 25, 2019 |
10989598 |
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17238137 |
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16417798 |
May 21, 2019 |
10488257 |
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16695040 |
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15573510 |
Nov 13, 2017 |
10302493 |
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PCT/CN2016/080365 |
Apr 27, 2016 |
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16417798 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H05B 47/10 20200101;
G01M 11/02 20130101; H05B 45/22 20200101; H05B 45/20 20200101; G01J
1/4228 20130101; G01J 3/40 20130101 |
International
Class: |
G01J 1/42 20060101
G01J001/42; H05B 45/20 20060101 H05B045/20; H05B 45/22 20060101
H05B045/22; G01J 3/40 20060101 G01J003/40 |
Foreign Application Data
Date |
Code |
Application Number |
May 13, 2015 |
CN |
201510241210.4 |
Aug 12, 2015 |
CN |
201510493084.1 |
Claims
1. A method implemented on a computing device having at least one
processor and at least one computer-readable storage medium for
providing artificial lighting under a working condition, the method
comprising: determining a destined chromaticity of a destined
light; determining a proportion for each component light of one or
more component lights, wherein the one or more proportions of the
one or more component lights have a first functional correlation
with respect to each other; and combining the one or more component
lights according to the one or more proportions of the one or more
component lights, thereby synthesizing the destined light.
2. The method of claim 28, wherein the second functional
correlation is a linear function, an inverse function, an
exponential function, a logarithmic function, a power function or a
regular non-linear function.
3. (canceled)
4. The method of claim 1, wherein the first functional correlation
is a linear function or a multivariate function.
5. The method of claim 1, wherein before the determining a destined
chromaticity of a destined light, the method further comprises
acquiring information of the working condition.
6. The method of claim 5, wherein the information is one or more
selected from a group consisting of a reflectance spectrum of a
target object, color appearance of a target object under the
artificial lighting, a condition of an ambient environment, and a
purpose of the artificial lighting,
7. The method of claim 6, wherein the reflectance spectrum of the
target object depends on a spectrum power distribution of the
destined light and a spectral reflectance curve of the target
object.
8. The method of claim 5, wherein the acquiring information of the
working condition is performed by receiving the information via a
user input or detecting the information via a sensor.
9. The method of claim 1, wherein before the determining a
proportion for each component light, the method further comprises
selecting at least one optimization parameter.
10. The method of claim 9, wherein the at least one optimization
parameter is selected from the group consisting of luminous
efficacy, luminous efficacy of radiation, color rendering index,
color temperature, circadian efficacy of radiation, mesopic
efficacy of radiation, luminous efficacy in scotopic vision,
spectral reflectance luminous efficacy of radiation, photosynthetic
photon flux, and chromaticity of light reflected by a target
object.
11. (canceled)
12. The method of claim 1, wherein the determining a destined
chromaticity of a destined light is based on a chromaticity of
light reflected by a target object under artificial
illumination.
13. The method of claim 1, wherein the one or more component lights
include four component lights.
14. The method of claim 1, wherein at least one of the one or more
component lights is monochromatic or polychromatic.
15. A system for providing an artificial lighting under a working
condition, the system comprising: a plurality of light sources,
each light source capable of emitting a component light having a
component chromaticity; a computer-readable storage medium storing
executable instructions, and at least one processor in
communication with the computer-readable storage medium, when
executing the executable instructions, causing the system to
implement operations comprising: determining a destined
chromaticity of a destined light; selecting one or more component
lights, each component light having a component chromaticity;
determining a proportion of each selected component light, wherein
the one or more proportions of the one or more component lights
have a first functional correlation with respect to each other; and
combining the one or more component lights according to the one or
more proportions of the one or more component lights, thereby
synthesizing the destined light.
16. (canceled)
17. The system of claim 15, wherein the operations comprise
acquiring working condition information.
18. The system of claim 17, wherein the working condition
information comprises a reflectance spectrum of a target object,
detected by one or more sensors.
19- 22 (canceled)
23. The system of claim 29, wherein the first functional
correlation and the second functional correlation are defined
according to working condition information.
24-25 (canceled)
26. The system of claim 15, wherein at least one of the plurality
of light sources is a LED, a polychromatic LED, a multi-packaged
LED, a phosphor-converted LED, a high pressure sodium lamp,. or a
fluorescent lamp.
27. The system of claim 15, wherein the operations further comprise
controlling a magnitude of current or voltage delivered to each
light source, thereby individually controlling an amount of
component light emitted by the corresponding light source.
28. The method of claim 1, wherein the determining a proportion for
each component light comprises: determining the proportion for each
component light based on a function, wherein the function includes
a parameter having a second functional correlation with the
proportion of at least one component light.
29. The system of claim 15, wherein determining a proportion for
each component light comprises: determining the proportion for each
component light based on a function, wherein the function includes
a parameter having a second functional correlation with the
proportion of at least one component light.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. application Ser.
No. 16/695,040, filed on Nov. 25, 2019, which is a continuation of
U.S. application Ser. No. 16/417,798, filed on May 21, 2019, now
U.S. Pat. No. 10,488,257, which is a continuation of U.S.
application Ser. No. 15/573,510, filed on Nov. 13, 2017, now U.S.
Pat. No. 10,302,493, which is U.S. national stage entry under 35
U.S.C. .sctn. 371 of International Application No.
PCT/CN2016/080365, filed on Apr. 27, 2016, claims priority to
Chinese patent application No. 201510241210.4, filed on May 13,
2015, and Chinese patent application No. 201510493084.1, filed on
Aug. 12, 2015, the contents of each of which are hereby
incorporated by reference.
FIELD OF THE INVENTION
[0002] The present disclosure relates to the field of lighting
technology and particularly relates to a method and related system
for spectrum optimization of an illumination light source.
BACKGROUND OF THE INVENTION
[0003] Artificial lighting is an essential element of modern life.
How to achieve ideal effects of artificial lighting has been a hot
research topic. Many factors are to be considered for optimizing
artificial lighting, such as efficiency of energy saving of the
lighting solution, safety of an environment under lighting,
aesthetics of illuminated objects or scenes, and animal's
physiological or psychological reactions to artificial lighting,
etc. For example, some studies show that long-term exposure under
inappropriate illumination spectra could incur human health
problems, such as the seasonal affective disorder. Research on
human mesopic vision also suggests that in mesopic vision, spectral
responses of human eyes bias towards shorter wavelengths. Thus, a
satisfying luminous efficacy under photopic vision conditions may
not be sufficient or as satisfactory under mesopic vision
conditions.
[0004] Traditional evaluation on artificial light sources typically
focuses on parameters such as luminous efficacy, color rendering
and color temperature. However, as artificial lighting needs in
modern life diversify and with advancement in research fields such
as mesopic vision and non-visual biological effect, the traditional
parameters quickly become insufficient to account for efficiency,
comfort, safety, health concerns and various other considerations
of artificial lighting. Thus, there exists a need in the field for
a new artificial lighting solution capable of solving the above
problems.
[0005] SUMMARY
[0006] This application relates generally to spectrum optimization
of an illumination light source. A method and related system
disclosed herein can provide a destined light under a working
condition based on a merit function.
[0007] In one example, a method for providing artificial lighting
under a working condition is provided. The method includes
determining a destined chromaticity of a destined light; selecting
one or more component lights, each component light having a
suitable component chromaticity; calculating proportion for each
component light based on a merit function, wherein the merit
function includes at least one optimization parameter having a
first functional correlation with the proportion of at least one
component light; and combining the one or more component lights
according to the calculated proportion, thereby synthesizing the
destined light. In some embodiments, the first functional
correlation may be a linear function, an inverse function, an
exponential function, a power function or a regular non-linear
function. The number of the one or more component lights may be
four and the component lights may be monochromatic or
polychromatic.
[0008] In another example, the proportion of the component lights
may assume a second functional correlation with respect to each
other. The second functional correlation may be a linear function
or a multivariate function. The type of the second correlation
function and the first correlation function may be the same, or
different.
[0009] In a further example, the method includes acquiring
information of the working condition. The information may be one or
more selected from the group consisting of a reflectance spectrum
of a target object, color appearance of a target object under the
artificial lighting, a condition of an ambient environment, and a
purpose of the artificial lighting. The reflectance spectrum of the
target object depends on a spectrum power distribution of the
destined light and a spectral reflectance curve of the target
object.
[0010] In still a further example, the method includes choosing the
at least one optimization parameter. The at least one parameter may
be selected from the group consisting of luminous efficacy,
luminous efficacy of radiation, color rendering index, color
temperature, circadian efficacy of radiation, mesopic efficacy of
radiation, luminous efficacy in scotopic vision, spectral
reflectance luminous efficacy of radiation, photosynthetic photon
flux and chromaticity of light reflected by a target subject under
the artificial illumination.
[0011] In still a further example, a system for providing an
artificial lighting under a working condition is provided. The
system includes a plurality of light sources, each of which is
capable of emitting a component light having a component
chromaticity. The system also includes a chromaticity coordinate
unit configured to determine a destined chromaticity of a destined
light and select one or more component lights of suitable component
chromaticity, a calculating unit configured to calculate proportion
of each selected component light based on a merit function. The
merit function includes at least on optimization parameter having a
first functional correlation with the proportion of at least one
component light. The system further includes a light source driver
configured to combine the one or more component lights according to
the calculated proportion, thereby synthesizing the destined light.
The calculation unit may be configured to define a second
functional correlation between the proportions of the component
lights. The system may further include an ambient information
obtaining module configured for acquiring working condition
information. The working condition information may include a
reflectance spectrum of a target object, and the ambient
information obtaining module includes one or more sensors
configured for detection the reflectance spectrum or a user
interface configured for receiving a user input of the working
condition information. The working condition information includes
luminance, color, temperature, weather, climate or time of an
ambient environment. The calculating unit may be configured to
define the first functional correlation and the second functional
correlation according to the working condition. The chromaticity
coordinate unit may be configured to determine the destined
chromaticity based on chromaticity of light reflected by a target
object under the artificial illumination. At least one of the
plurality of light sources may be a LED, a polychromatic LED, a
multi-packaged LED, a phosphor-converted LED, a high pressure
sodium lamp or a fluorescent lamp. The light source driver may be
capable of control a magnitude of current or voltage delivered to
each light source, thereby individually controlling an amount of
component light emitted by the corresponding light source.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The present invention will be more readily understood from
the detailed description of exemplary embodiments presented below
considered in conjunction with the attached drawings, of which:
[0013] FIG. 1 illustrates an exemplary lighting system capable of
spectrum optimization according to some embodiments of the present
disclosure.
[0014] FIG. 2 depicts an exemplary working condition of the
lighting system according to some embodiments of the present
disclosure.
[0015] FIG. 3 is a block diagram illustrating an exemplary spectrum
optimization system according to some embodiments of the present
disclosure.
[0016] FIG. 4A shows the spectral power distributions (SPD) of the
component lights according to some embodiments of the present
disclosure.
[0017] FIG. 4B shows the chromaticity coordinates of the
corresponding colors according to some embodiments of the
disclosure.
[0018] FIG. 5 illustrates a block diagram of a lighting system
according to some embodiments of the present disclosure.
[0019] FIG. 6 is a flowchart illustrating a process for spectrum
optimization according to some embodiments of the present
disclosure.
[0020] FIG. 7 is a flowchart illustrating the process for
determining optimization parameters and optimizing illumination
spectrum according to some embodiments of the present
disclosure.
[0021] FIG. 8 is a flowchart illustrating an exemplary spectrum
optimization process that takes into consideration the reflectance
spectrum of the target object according to some embodiments of the
present disclosure.
[0022] FIG. 9 illustrates the result of the proportion of each
light source based on a determined chromaticity coordinate of the
light mixture according to some embodiments of the present
disclosure.
[0023] FIG. 10 illustrates the simulated spectrum of incandescent
lamp and four-packages LEDs using 11 channels LED cube with fit
goodness.
[0024] FIG. 11 illustrates the linear fit of SRLER and t of
theoretical and simulated four-package LEDs.
[0025] FIG. 12 illustrates the relationship between LE, CRI and the
proportion of a light source in a four-package LED system according
to some embodiments of the present disclosure.
[0026] FIGS. 13A-13C illustrate the mesopic efficacy at different
luminances according to some embodiments of the present
disclosure.
[0027] FIG. 14A and FIG. 14B illustrate the optimization process
considering LER, C/P and S/P ratio according to some embodiments of
the present disclosure.
[0028] FIG. 15 illustrates an exemplary embodiment of an artificial
lighting solution for indoor plantations.
[0029] FIG. 16 is an embodiment of color mixing of four-package LED
at different color temperature.
[0030] FIG. 17 shows the proportion of each LED as a function of t
for color mixing of four CCTs according to some embodiments of the
present disclosure.
[0031] FIG. 18 shows CRI color samples with their chromaticity
coordinates according to some embodiments of the present
disclosure.
[0032] FIG. 19 shows chromaticity coordinates on eight general
color samples according to some embodiments of the present
disclosure.
[0033] FIG. 20 shows color effect changing under different CCTs
light sources according to some embodiments of the present
disclosure.
[0034] FIG. 21 shows SRLER as function oft for color mixing of
four-package at 3000K, 4000K, 5000K and 6000K according to some
embodiments of the present disclosure.
[0035] FIG. 22 shows SRLER as function of t for color mixing of
four-package at 4000K on a color sample according to some
embodiments of the present disclosure.
[0036] FIG. 23A shows incandescent lamp as light source and light
greyish red as color sample according to some embodiments of the
present disclosure.
[0037] FIG. 23B shows the spectrum power distribution of four LEDs
and spectrum reflected from color sample light greyish red
according to some embodiments of the present disclosure.
[0038] FIG. 24 shows the chromaticity coordinates of incandescent
lamp, light greyish red and illuminated color according to some
embodiments of the present disclosure.
[0039] FIG. 25 shows the proportion of each LED as a function oft
for color mixing of destined target chromaticity according to some
embodiments of the present disclosure.
[0040] FIG. 26 shows the chromaticity coordinates of four-package
LEDs following linear function according to some embodiments of the
present disclosure.
[0041] FIG. 27 shows SRLER of spectrum of four-package LEDs as
inverse proportion function oft according to some embodiments of
the present disclosure.
DETAILED DESCRIPTION OF THE INVENTION
[0042] Provided herein are methods and systems for spectrum
optimization of artificial illumination (lighting). Particularly,
in some embodiments, the methods and systems disclosed herein are
capable of adjusting optical characteristics of the illumination
light to accommodate particular needs and/or purposes of the
artificial lighting. In some embodiments, the present method and
system is capable of automatically recognizing features of an
object or environment under illumination. The object is hereinafter
referred to as the "target object" or "illuminated object"; and the
environment is hereinafter referred to as the "target environment"
or "illuminated environment." In some embodiments, when discussing
an environment surrounding an illuminated object, the surrounding
environment is also referred to as the "ambient environment." In
various embodiments, an ambient environment may be illuminated or
not illuminated by the artificial lighting.
[0043] In some embodiments, the present method and system is
configured to optimize the illumination spectrum based on one or
more optimization parameters. In various embodiments, the
optimization parameters may include but are not limited to
luminance, luminous efficacy (LE), luminous efficacy of radiation
(LER), spectral reflectance luminous efficacy of radiation (SRLER),
reflectance spectrum of illuminated object, color rendering index
(CRI), color temperature, chromaticity, mesopic efficacy of
radiation, luminous efficacy in scotopic vision, and circadian
efficacy of radiation, photosynthetic photon flux (PPF), etc. The
reflectance spectrum denotes the reflection of an object under the
illumination of a certain light. The certain light may include but
not limit to reference light. The reflectance spectrum may be
expressed as P(.lamda.)p(.lamda.), wherein P(.lamda.) is the
spectral power distributions (SPD) of the illumination light, and
p(.lamda.) is the spectral reflectance curve of the illuminated
object, p(.lamda.) is the spectral reflectance curve of the
illuminated object, which equals to the ratio between the reflected
visible energy and the energy of the illumination light source.
Further, various optimization parameters may be selected and
determined based on various considerations, including but not
limited to energy efficiency, luminous efficacy, color effect,
biological or physiological, psychological compatibility, health,
purpose and environment of the lighting.
[0044] Particularly, energy efficiency is an important parameter
for evaluating and providing a lighting solution. As used herein,
the term "lighting solution" refers to a method and/or system that
provide illumination. Energy efficiency may be mathematically
expressed as the luminous efficacy (LE) and luminous efficacy of
radiation (LER) of the lighting solution. As used herein, LE is a
measurement of how efficient a lighting solution converts a source
energy into visible light energy. Thus, the higher value of LE, the
more energy efficient the lighting solution is. In some
embodiments, the source energy may be in the form of electrical
power, chemical energy, biological energy or other suitable forms.
Particularly, in some embodiments, LE is defined as the efficiency
of energy conversion by an illumination light source, such as the
present lighting system disclosed herein.
[0045] Due to the spectral sensitivity of human eyes, not all
wavelengths of light are equally visible to human, or equally
effective at stimulating human vision. For example, radiation in
the infrared and ultraviolet parts of the spectrum is useless for
illumination, because they cannot be seen by human. As used herein,
LER is a measurement of the fraction of electromagnetic radiation
that is useful for lighting. In some embodiments, LER may be
obtained by dividing the luminous flux by the radiant flux. In some
embodiments, light of a wavelength ranging from 380 nm to 780 nm is
visible and useful for lighting. Thus, like LE, LER is also
parameter for measuring efficiency of a lighting solution.
[0046] Spectrum of an illumination light (illumination spectrum)
and the spectrum of the light reflected by target objects
(reflectance spectrum) are important considerations for evaluating
and providing a lighting solution. Particularly, the illumination
spectrum of the light and the reflectance spectrum of the target
object may together determine the atmosphere created by the
illumination. For example, in some embodiments, illumination
spectrum and reflectance spectrum may together decide luminance of
the lighting solution. Particularly, as used herein, luminance
refers to a photometric measure of the density of luminous
intensity in a given direction, measured in candela per square
meter (cd/m.sup.2). Thus, luminance measures how a light source
works on an illuminated object. In some embodiments, luminance is
mathematically expressed by luminous reflectance Y, which is the
product of object's reflectance, the spectral power of a light
source, and the luminosity function of the CIE standard observer.
Thus, luminance is a measurement relying upon characteristics of
both illumination and reflectance. Particularly, if the reflectance
spectrum under a lighting system matches the reflectance spectrum
of this object under equal-energy white, the lighting solution is
likely to produce higher luminance as compared to when the two
spectra mismatch. The reflectance spectrum of an object under
equal-energy white can be defined as reference reflectance
spectrum.
[0047] As described above, luminance relates to both the
illumination source and the target object's reflectance. While LER
may be used to describe efficiency of an illumination light source,
it does not directly relate to reflectance property of the object.
Thus, LER is not a precise measurement for reflected luminance.
That is, from LER alone, one cannot evaluate the illumination
efficacy refer to reflectance spectrum, thereby unable to determine
whether a satisfactory LER value would lead to also satisfactory
luminance of the lighting solution. Accordingly, in some
embodiments, another parameter that is similar to LER but also
considers target object's reflectance is used for spectrum
optimization. As used herein, spectral reflectance luminous
efficacy of radiation (SRLER) refers to the ratio between energy
reflected by an illuminated object that is visible to human eyes
and energy radiated by an illumination source. Thus, the higher
SRLER is, the more visible light is reflected by the target object,
and thus the higher luminance of the target object. Particularly,
in some embodiments, SRLER may be mathematically expressed as:
SRLER = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times.
P .function. ( .lamda. ) .times. y .function. ( .lamda. ) .times.
.rho. .function. ( .lamda. ) .times. d .times. .lamda. .intg. 3
.times. 8 .times. 0 7 .times. 8 .times. 0 .times. P .function. (
.lamda. ) .times. d .times. .lamda. = 3 .times. 8 .times. 0 7
.times. 8 .times. 0 .times. P .function. ( .lamda. ) .times. V
.function. ( .lamda. ) .times. .rho. .function. ( .lamda. ) .times.
.DELTA. .times. .lamda. / 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. P .function. ( .lamda. ) .times. .DELTA. .times. .lamda.
( 1 ) ##EQU00001##
[0048] where P(.lamda.) is the SPD of the illumination light,
V(.lamda.) is the standard luminosity function, p(.lamda.) is the
spectral reflectance curve of the illuminated object, which equals
to the ratio between the reflected visible energy and the energy of
the illumination light source. The spectral reflectance curve
herein denotes the reflection curve of an object under the
illumination of reference light.
[0049] In some embodiments, illumination spectrum and reflectance
spectrum may together decide also the color appearance of the
illuminated object. Particularly, color appearance of an
illuminated object or environment to an observer may be
mathematically expressed as the chromaticity of the reflected
light. In some embodiments, color effect of an illumination
solution may be also expressed as the color temperature or color
rendering index (CRI). Color temperature is conventionally
expressed in Kelvin, using the symbol K, a unit of measure for
temperature based on the Kelvin scale. Typically, color
temperatures over 5,000K are referred to as cool colors (bluish
white), while lower color temperatures (2,700 to 3,000 K) are
referred to as warm colors (yellowish white through red).
Chromaticity is an objective specification of the quality of a
color regardless of its luminance. In some embodiments,
chromaticity of a light corresponds to a chromaticity coordinate
(x, y) on a standard chromaticity diagram, such as the 1931 CIE
chromaticity diagram. As used herein, CRI is a quantitative
measurement of the ability of an illumination light source to
reveal colors of an illuminated object faithfully in comparison
with an ideal or natural light source.
[0050] Additionally, human psychological, biological or
physiological reactions to artificial lights are also important
considerations in providing a lighting solution. For example,
spectral sensitivity of human visual perception changes with
ambient luminance under a mesopic vision condition. Particularly,
photopic efficacy refers to the average spectral sensitivity of
human visual perception of brightness. In some embodiments,
photopic efficacy may be expressed as a ratio of luminous flux for
photopic vision to the total luminous flux radiated by an
illumination light source. However, spectral sensitivity of human
eyes is different from photopic vision in a dark environment.
Spectral sensitivity of human eyes may be more precisely measured
as mesopic efficacy in a mesopic vision environment, which may
occur when luminance ranges approximately from 0.005 to 5
cd/m.sup.2, and as scotopic efficacy in a scotopic vision
environment, which may occur when ambient luminance is below 0.005
cd/m.sup.2. Thus, under mesopic or scotopic vision conditions,
illumination effects may be perceived differently from those
calculated under standard (photopic) conditions. Accordingly, in
some embodiments illumination spectrum may be optimized to account
for the mesopic vision effect. For example, in mesopic vision,
spectral responses of human eyes bias towards shorter wavelengths,
thus in an mesopic environment, such as a highway tunnel,
illumination using short wavelength lights may be more efficient in
stimulating drivers' vision response and thus keeping them
alert.
[0051] Additionally, spectral response of human visual perception
also changes with non-visual physiology of a human body, herein
referred to as non-visual biological effect. For example, in some
embodiments, spectral response of human visual perception may
change with the circadian rhythms of a human body. In other
embodiments, human visual perception may in turn affect the
circadian rhythms. For example, blue light may suppress production
of the hormone melatonin, leading to increases in alertness at
night and reduction in sleep time and quality. In some embodiments,
the parameter circadian efficacy of radiation (CER) may be used to
measure cirtopic effect of illumination.
[0052] Further, purpose and environment of illumination are
important considerations in providing a lighting solution. For
example, illumination light matching the illuminated environment
improves aesthetic effect of the lighting. For another example,
landscape lighting has its own characteristics. Some landscape,
like architecture and sculptures, are color saturated and some are
not. While landscape such as a dense vegetation area is likely
color saturated, typically landscape has fewer color types. Thus,
for landscape lighting, luminance or color of the light source is
less important than luminance or color reflected by the illuminated
environment. For another example, smart lighting, such as mood
lighting, provides adjustable lighting atmosphere according to
human's behavior or mood change. For another example, in functional
lighting, such as for a reading lamp, sufficient luminance and
color contrast tend to make reading comfortable and healthy to
human eyes. For yet another example, in agricultural lighting,
photosynthetic photon flux (PPF) of a light source may be
considered. As used herein, the term "photosynthetic photon flux"
or "PPF" refers to the ratio of flux for photosynthesis to the
number of absorbed photon, thus reflects the efficiency of the
artificial light solution in stimulating plant growth.
[0053] According to the present disclosure, spectrum optimization
may be based on one or more optimization parameters. Further,
multiple parameters may be optimized individually or concurrently.
In some embodiment, values of the one or more optimization
parameters may be pre-determined. In other embodiments, values of
the one or more optimization parameters may be determined during
the spectrum optimization process.
[0054] In some embodiments, the present methods and systems
optimize the spectrum of an illumination light source by mixing
multiple component lights having desirable characteristics, thereby
outputting a destined light with a spectrum optimized according to
one or more optimization parameters. As used herein, the term
"component light" refers to one or more of the lights that are to
be mixed together, and the term "destined light" refers to the
light output that has the optimized spectrum. According to the
present disclosure, the component light may be monochromatic or
polychromatic. In some embodiment, a component light may be
produced by a LED, such as but not limited to a polychromatic LED,
multi-chip LED, PC LED, a high pressure sodium lamp (HPS),
fluorescent lamp (FL), or other optical devices capable of emitting
a single wavelength light or light having a narrow range of
spectral power distribution (SPD), such as a peak width at half
height of smaller than 30 nm.
[0055] The present systems and methods may find their applications
in various fields, including but not limited to multi-packaged
LEDs, a phosphor- converted LED (PC LED), high pressure sodium lamp
(HPS), fluorescent lamp (FL), or the like, or a combination
thereof.
[0056] The following paragraphs will describe the present method
and system more fully hereinafter with reference to the
accompanying drawings in order to provide a thorough understanding
of the relevant disclosure, in which preferred embodiments of the
invention are shown. Various modifications to the disclosed
embodiments will be readily apparent to those skilled in the art,
and the general principles defined herein may be applied to other
embodiments and applications without departing from the spirit and
scope of the present disclosure. Thus, the invention may be
embodied in many different forms and should not be construed as
limited to the embodiments set forth herein; but to be accorded the
widest scope consistent with the claims.
[0057] In one aspect of the present disclosure, provided herein is
a system for spectrum optimization. As used herein, the term
"system," "device", "module", and/or "unit" are one method to
distinguish different components, elements, parts, section or
assembly of different level in descending order. However, the terms
may be displaced by other expression if they may achieve the same
purpose.
[0058] FIG. 1 illustrates an exemplary lighting system capable of
spectrum optimization according to some embodiments of the present
disclosure. As shown in the figure, the lighting system 100 may
include a light emitting device 110, a driver 120, a controller 130
and a receiver 140. The light emitting device 110 may include a
single light source, or a set of multiple light sources. Light
emitted by the emitting device may be monochromatic having a single
wavelength or a narrow SPD with a single peak, or may be
polychromatic having a mixture of different wavelengths. In some
embodiments, the light sources produce component lights that are to
be mixed to produce a destined light having an optimized
spectrum.
[0059] The driver 120 may be configured to drive the component
light sources in the light emitting device 110. In some
embodiments, the driver 120 may change the composition of the
destined light by adjusting the proportion of a component
light.
[0060] The controller 130 may control the function of the driver
120. In some embodiments, the controller 130 may include a
processor that is configured to execute instructions for spectrum
optimization in the system 100. In some embodiments, the
instructions may depend on information acquired by the receiver
140. The receiver 140 may be configured to acquire different types
of information to determine light emission of the system 100.
Exemplary types of information may include optical characteristics
of a target object and/or conditions of an ambient environment
acquired by a detector (not shown in FIG. 1), data transmitted from
a local storage device or a remote server, or a manual input by a
user, or the like, or a combination thereof. In some embodiments,
the ambient condition may relate to a target object, brightness of
surrounding environment, temperate of environment, a user's
preference, or the like, or a combination thereof. The data
transmitted from local storage device or a remote server may
include a schedule relating to the working condition of the light
emitting device 110, an instruction relating to the operation of
the light emitting device 110, or the like, or a combination
thereof. Manual input by a user may be performed through a user
input interface, such as a wireless or wire-connected keyboard, a
touchscreen with virtual buttons for communicating commands and
other input information to the lighting system 100.
[0061] FIG. 2 depicts an exemplary working condition of the
lighting system according to some embodiments of the present
disclosure. The working condition 200 relates to adjusting the
illumination spectrum for a user's reading of a book, such that the
user's eyesight is protected. In this example, the lighting system
includes multiple component light sources for providing
illumination on a target object (e.g., a book in this example). In
some embodiments, the illumination light is monochromatic. In other
embodiments, the illumination light may be polychromatic having
RGBA colors or multi-colors of other kinds. In some embodiments,
the illumination light is produced by mixing multiple component
lights together.
[0062] Additionally, the lighting system may include a detector 240
configured to sense conditions of a target object, such as its
color, shape and/or reflectance spectrum. In various embodiments,
the detector 240 may be arranged as a unit separated from the light
sources. A controller (not shown in FIG. 2) may be configured to
optimize illumination spectrum of the lighting system to comfort
human eyes, based on the information acquired by the detector, such
as the book's reflectance spectrum. Specifically, in the spectrum
optimization process, one or more parameters of the illumination
light may be optimized, such as chromaticity, color rendering
effect, luminous efficacy, reflected efficiency, circadian effect,
etc. The optimization parameters may be determined during the
optimization process, based on information acquired by the
detector, or pre-determined or input by a user. Further details
regarding the optimization parameters will be discussed below.
[0063] FIG. 3 is a block diagram illustrating an exemplary spectrum
optimization system 300 according to some embodiments of the
present disclosure. For better illustration, the spectrum
optimization system is described with the example of a lighting
system having an adjustable illumination spectrum. As shown in FIG.
3, the lighting system 300 may include a light emitting device 310,
a light source driver 320, a light sources calculating module 330,
and an input 340. In some embodiments, the light emitting device
310 may include multiple light sources that may be monochromatic or
polychromatic. In some embodiments, a component light source may
produce a monochromatic light having a single wavelength or a
narrow SPD with a single peak. In other embodiments, a component
light source may produce a polychromatic light having multiple
different peaks in its SPD. In some embodiments, a component light
source may be any type of light source capable of emitting single
wavelength light or light with a narrow SPD with a single peak,
such as a LED, high pressure sodium lamp (HPS), fluorescent lamp
(FL), or the like, or any combination thereof. Of different kinds
of light sources, multi-package LEDs are flexible in spectral
composition, and spectrum proportions of each LED are easy to
control. For example, in some embodiments, by choosing different
chips, a variety of LEDs with different spectra could be
obtained.
[0064] In some embodiments, chromaticity of each light source
corresponds to a specific chromaticity coordinate on a chromaticity
diagram, which in turn corresponds to a specific color presented on
the chromaticity diagram. Further details of chromaticity
coordinates will be discussed in relation to FIG. 4B.
[0065] For example, in some embodiments, the light emitting device
310 comprises four component light sources (e.g., four LEDs). As
described above, each component light source may emit light having
a specific color. For example, in some embodiments, the four colors
may be red, amber, green and blue. In various embodiments, any
colors presented on the chromaticity diagram may be used. A
polychromatic destined light having desirable optical
characteristics may be produced by mixing the component lights
according to certain proportions. In some embodiments, proportions
of the component lights may correlate with each other.
Particularly, in some embodiments, proportion of one component
light may assume a linear relationship with proportion of another
component light. It shall be noted that the above description of
the light emitting device is provided for illustration purpose, and
is not intended to limit the scope of the present disclosure. For
persons having ordinary skills in the art, various variations and
modifications may be conducted under the teaching of the present
disclosure. For example, the light emitting device 310 may have any
number of component light sources, each light source may produce a
component light of any color, and a component light may be a
monochromatic or polychromatic light.
[0066] The light source driver 320 may drive the light sources by
delivering to them voltage or current at calculated levels. The
light source driver 320 may receive a command from the light source
calculating module 330, and adjust driving voltage or current for
individual light sources accordingly. The light source calculating
module 330 may be configured to select and determine parameters for
spectrum optimization based on information received from the input
340. For example, the light source calculating module 330 may
calculate respective proportions of multiple component lights to be
combined to generate a destined light having a desirable
synthesized chromaticity. In some embodiments, the input 340 may
provide the light source calculating module 330 information
regarding a working condition of the lighting emitting device 310.
As used herein, the term "working condition" broadly relates to any
condition or circumstance under which a lighting solution operates,
which includes but are not limited to the purpose or goal of the
lighting, the target object or environment to be illuminated, the
requirement or input by a system default or a user, etc. In some
embodiments, information regarding the working condition relates to
conditions of an ambient environment of a target object and may be
acquired by a detector, transmitted from a local storage device or
a remote server, or manually input by a user, or the like, or a
combination thereof.
[0067] In some embodiments, the light source calculating module 330
calculates respective proportions of component lights based on the
component chromaticity and the destined chromaticity. As used
herein, the term "component chromaticity" refers to the
chromaticity of a component light, and the term "destined
chromaticity" or "synthesized chromaticity" refers to the
chromaticity of the destined light. In some embodiments, the input
340 decides the component and destined chromaticity and transmits
the values to the light source calculating module 330.
[0068] Below is an example to illustrate the calculating process.
Four LEDs are selected to produce component lights of red, amber,
green and blue colors, respectively. FIG. 4A shows the spectral
power distributions (SPD) of the component lights. Particularly,
FIG. 4A shows the normalized SPD of the four LEDs with red, amber,
green and blue for color mixture and spectrum optimization. The
abscissa represents the wavelength, and the ordinate P(.lamda.)
represents the SPD. As shown in the figure, each LED has a narrow
range of spectral power distribution and a central maximum. For
example, the LED generating blue light may have a spectrum
centralized at 450 nm.
[0069] As described above, each color corresponds to a chromaticity
coordinate (x, y) on the 1931 CIE chromaticity diagram. Thus, FIG.
4B shows the chromaticity coordinates of the corresponding colors
according to some embodiments of the disclosure. As shown in FIG.
4B, points R, A, G and B correspond to the chromaticity coordinates
of colors in red, amber, green and blue, respectively. Point X is
the intersection point of points R, A, G and B.
[0070] In this example, the destined light is set to have a
chromaticity corresponding to point D on the chromaticity diagram.
The destined light is also set to have a desirable color
temperature of 4000K. See the figure showing point D sitting on the
Planckian curve representing blackbody radiation of 4000K. If point
D falls within an area surrounded by the selected component
chromaticity coordinates, the destined light can be synthesized by
mixing some or all of the selected component lights.
[0071] Particularly in this example, the destined chromaticity D
locates within triangle XGB. Accordingly, the destined light may be
generated by combining the three of green, amber and blue lights,
or by combining the three of green, red and blue lights, or by
combining the four of green, amber, red and blue lights.
Alternatively, the destined light may be generated by combining all
four of green, red, blue and amber lights. Thus, component light
sources may be selected. In various embodiments, the number of
component lights can be any number, including 1, 2, 3, 4 or greater
than 4 component lights.
[0072] After deciding the component lights, their respective
proportions for generating the destined light can be calculated by
the color mixture function as writing in equation (2) below.
Further details regarding spectrum optimization using the color
mixture function will be discussed in relation to FIGS. 6 through
8.
[0073] In some embodiments, connection between different modules or
units may be in a wired or wireless fashion. The wired connection
may include using a metal cable, an optical cable, a hybrid cable,
an interface, or the like, or any combination thereof. The wireless
connection may include using a Local Area Network (LAN), a Wide
Area Network (WAN), a Bluetooth, a ZigBee, a Near Field
Communication (NFC), or the like, or any combination thereof.
[0074] It should be noted that the above description about the
lighting system is merely an example, and should not be understood
as the only embodiment. Obviously, to those skilled in the art,
after understanding the basic principles of the connection between
different modules or units, the modules or units and connection
thereof may be modified or varied without departing from the
principles. The modifications and variations are still within the
scope of the current disclosure. In some embodiments, these modules
or units may be independent. In some embodiments, part of the
modules or units may be integrated into a single module or unit to
work together.
[0075] FIG. 5 illustrates a block diagram of a lighting system 500
according to some embodiments of the present disclosure. The
lighting system 500 may include a light emitting device 510, a
light source driver 520, a light source calculating module 530 and
an ambient information obtaining module 550. The light source
calculating module 530 may include a chromaticity unit 531, an
optimization parameter unit 532, a weight factor unit 533 and a
calculating unit 534. The ambient information obtaining module 550
may include a reflectance spectrum sensing unit 551 and an ambient
environment sensing unit 552. Under the control of the light source
driver 520, the light emitting device 510 generates illumination
light to illuminate on a target object 560. In some embodiments,
the illumination light may be a monochromatic light. In some
embodiments, the illumination light may be a polychromatic
light.
[0076] In some embodiments, the ambient information obtaining
module 550 may be configured to acquire and analyze the reflectance
spectrum of the target object under illumination. In some
embodiments, the reflectance spectrum sensing unit 551 may analyze
SPD of the reflected light. Reflectance spectrum of the target
object may reflect certain optical characteristics of the object.
For example, a valley in the SPD at a particular wavelength may
indicate strong absorption of that wavelength by the object.
Similarly, a peak in the SPD at a particular wavelength may
indicate strong reflection of that wavelength by the object. Also,
the reflectance spectrum affects color appearance of the target
object under illumination. Thus, acquired reflectance information
may be used to set or optimize illumination spectrum of the light
emitting device 510.
[0077] For example, illumination condition may affect plant growth.
Illumination spectrum matching a plant's absorbing spectrum is more
efficient to stimulate plant growth and illumination spectrum
matching a plant's reflectance spectrum may be used to prevent
overgrowth of the plant. Thus, according to different needs, the
lighting system may choose to combine component lights having a
desirable wavelength to synthetize the destined light. As another
example, spectrum of landscape lighting may be designed or
optimized to match reflectance spectrum of the landscape in a
natural environment (e.g., under sunlight). Particularly, providing
illumination spectrum matching the landscape's natural reflectance
spectrum may make the artificially illuminated landscape appear
real and vivid. Specifically, for a vegetation area that strongly
reflects green light under the sun, increasing green light
component in an artificial illumination spectrum may help to
achieve a desirable lighting effect.
[0078] Besides the target object's optical characteristics, the
ambient information obtaining module 550 may be further configured
to acquire and analyze conditions of the target object's ambient
environment. In some embodiments, the ambient environment sensing
unit 552 may collect environmental information, such as
temperature, time, humidity, weather, or the like, or a combination
thereof.
[0079] In some embodiments, during a spectrum optimization process,
the destined chromaticity coordinate unit 531 of the system may
determine the destined chromaticity of the destined light according
to the ambient environment. For example, chromaticity for daytime
illumination may correspond to a higher color temperature, and
chromaticity for night time illumination may correspond to a lower
color temperature. In some embodiments, the destined chromaticity
coordinate unit 531 of the system may determine an acceptable range
of the destined chromaticity.
[0080] In some embodiments, the chromaticity unit 531 may further
select one or more component light sources for synthesizing the
destined chromaticity, the component light sources each produce
light of a particular chromaticity. In some embodiments, the
component light sources are monochromatic, each producing a
component light having a single wavelength or a narrow SPD with a
single peak. In other embodiments, the component light sources are
polychromatic, each producing a component light having multiple
peaks in the SPD. In yet other embodiments, some component light
sources are monochromatic while other component light sources are
polychromatic.
[0081] The optimization parameter unit 532 may determine one or
more parameters for optimizing the illumination spectrum of the
light emitting device 510. Exemplary parameters may include
luminous efficacy (LE), color rendering index (CRI) and luminous
efficacy of radiation (LER), photopic efficacy, mesopic efficacy,
circadian efficacy of radiation (CER) for non-visual biological
effects, the spectral reflectance luminous efficacy of radiation
(SRLER), photosynthetic photon flux (PPF) or a combination
thereof.
[0082] The weight factor unit 533 may be configured to operate in
connection with the optimization parameter unit 532. Particularly,
different weight factors may be given to different optimization
parameters. In some embodiments, optimization parameters and their
respective weight factors may be determined based on the working
condition under which the lighting system is used. Merely by way of
example, luminous efficacy may be considered for lighting in an
environment where brightness and visibility are important, such as
roads, highway tunnels, manufacturing plants, offices, classrooms,
etc. Circadian efficacy may be considered for lighting in a
human-populated environment, such as bedrooms, hospital wards,
offices, and classrooms, etc. Spectral reflectance luminous
efficacy of radiation may be considered for lighting in an
environment where colored objects need to be illuminated, such as
retail lighting, museum lighting, landscape lighting, etc. Color
rending may be considered for lighting in an environment where
discerning colorful representations is important, such as a
painting room, a museum, a shopping mall etc. Mesopic efficacy may
be considered for lighting in an environment of which the luminance
condition may trigger mesopic vision of the human eye, such as
highway tunnels and certain outdoor environment. Furthermore,
multiple parameters chosen for the optimization may be given
different weight factors before composition of the destined light
is calculated. Also, Table 1 below provides several examples for
how multiple optimization parameters may be considered under
different working condition.
TABLE-US-00001 TABLE 1 Exemplary requirements of optimization
parameters for different circumstances Parameter Mesopic Circadian
Circumstance LE CRI efficacy efficacy SRLER Requirement Classroom
high high very low fair very low Office high high very low fair
very low Bedroom fair high very low high very low Shopping mall
fair very very low very low very high high Museum fair very very
low very low very high high Manufacturing high fair very low high
very low plant Highway very low high high very low tunnel/Road high
Landscape fair fair very low very low very high General outdoor
high fair high fair very low
[0083] The calculating unit 534 may be configured to calculate
respective proportions of component lights to be combined according
to the optimization parameters and weight factors. Further details
regarding the calculation are provided below in relation to FIGS. 6
to 8. The light source driver 520 may provide driving current
and/or voltage to the respective component light sources according
to the calculation result, such that the light emitting device 510
produces the destined illumination light having optimized
spectrum.
[0084] FIG. 6 is a flowchart illustrating a process 600 for
spectrum optimization according to some embodiments of the present
disclosure.
[0085] In step 610, information of the working condition may be
acquired. For example, in some embodiments, information regarding
one or more target objects and the ambient environment may be
acquired. As described elsewhere in the disclosure, information
regarding the target object may include optical characteristics of
the object, such as its color appearance, shape or reflectance
spectrum. Information regarding the ambient environment may include
features such as brightness, dominant color, size, temperature, and
weather of the environment, or the like, or a combination thereof.
In some embodiments, information regarding the working condition
may be acquired by the lighting system 500 through a sensor. In
some embodiments, the sensor may be integrated in the ambient
information obtaining module 550 as shown in FIG. 5. In various
embodiments, information regarding the working condition may be
input into the lighting system 500 by a user or pre-stored in and
retrieved from a memory of the lighting system 500. For example, in
some embodiments, a user may set the lighting system 500 to work
for a particular working condition. In some embodiments, the
lighting system 500 may have various pre-set modes suitable for
working under particular conditions. For example, in some
embodiments, the lighting system 500 may have a sleep mode, a
daytime mode, an energy efficient mode, and a bright mode, etc. In
some embodiments, the lighting system 500 may optimize the
illumination spectrum to accommodate circadian effects of the human
body. In some embodiments, the lighting system 500 may optimize the
illumination spectrum according to user's customized request. For
example, if the user sets the lighting system 500 to the energy
efficient mode, the lighting system 500 may change the optimization
parameters to achieve the highest power efficiency. Specifically,
the optimization parameter unit 532 may increase the LE setting to
achieve the energy-saving goal. As another example, if the user
sets the lighting system 500 to the bright mode, the lighting
system 500 may change the optimization parameters to achieve the
best luminous efficacy.
[0086] In step 620, chromaticity of the illumination light may be
determined. In some embodiments, the chromaticity may be determined
by the chromaticity unit 531 as described in relation to FIG. 5. In
some embodiments, the chromaticity may be determined according to
the working condition information as received in step 610.
Alternatively, in other embodiments, the chromaticity may be input
by a user or pre-stored in the lighting system. For example, a
commonly predetermined chromaticity of illumination light is
white.
[0087] For illustrative purpose, an example of combining four
component lights of particular chromaticity coordinates to generate
destined illumination light of desirable chromaticity is provided
below. According to the color mixture function, the relationship
between the chromaticity coordinates of the component lights and
that of the produced polychromatic light can be expressed as:
{ ( a 1 .times. l 1 + a 2 .times. l 2 + a 3 .times. l 3 + a 4
.times. l 4 ) .times. x = a 1 .times. l 1 .times. x 1 + a 2 .times.
l 2 .times. x 2 + a 3 .times. l 3 .times. x 3 + a 4 .times. l 4
.times. x 4 ( a 1 .times. l 1 + a 2 .times. l 2 + a 3 .times. l 3 +
a 4 .times. l 4 ) .times. y = a 1 .times. l 1 .times. y 1 + a 2
.times. l 2 .times. y 2 + a 3 .times. l 3 .times. y 3 + a 4 .times.
l 4 .times. y 4 a 1 + a 2 + a 3 + a 4 = 1 ( 2 ) ##EQU00002##
[0088] where, x.sub.1, y.sub.1; x.sub.2, y.sub.2; x.sub.3, y.sub.3;
x.sub.4, y.sub.4 are the chromaticity coordinates of the component
lights; x, y is the chromaticity coordinate of the destined light;
a.sub.1, a.sub.2, a.sub.3, a.sub.4 are the proportions of the
component lights; l.sub.1, l.sub.2, l.sub.3, l.sub.4 are the sum of
tri-stimulus values of the component lights. As used herein, the
tri-stimulus value refers to the amount of the three primary colors
in a tri-chromatic additive color model, such as in the 1931 CIE
XYZ color space. Equation (2) is to be solved for unknown factors
a.sub.1, a.sub.2, a.sub.3 and a.sub.4.
[0089] According to the present disclosure, component lights having
any chromaticity coordinates may be used in connection with the
present method or system. In some embodiments, proportions of the
component lights may correlate with each other. For illustration
purpose, suppose a.sub.1=t, according to equation (3), a.sub.i may
linearly relate to t.
a.sub.i=k.sub.it+b.sub.i (3)
where k.sub.i denotes the slope of proportion corresponding to the
i.sup.th component light with respect to t, b.sub.i is a constant
corresponding to the i.sup.th component light. Since the
chromaticity coordinates of component lights and destined light may
be predetermined, k.sub.i and b.sub.i may be calculated in equation
(2). Also, the range oft is limited since a.sub.i ranges from 0 to
1.
[0090] As shown, in the case where four component lights are used,
equation (2) is an underdetermined equation and may have indefinite
number of solutions for a.sub.1, a.sub.2, a.sub.3 and a.sub.4.
Thus, to reach a definite solution, one or more optimization
parameter may be taken into consideration.
[0091] In step 630, one or more optimization parameters may be
determined by, for example, the optimization parameter unit 532 as
shown in FIG. 5. Since the lighting solution is provided for
particular working conditions, the parameter(s) may be optimized
accordingly.
[0092] As described elsewhere in the disclosure, the optimization
parameters may include but are not limited to color rendering index
(CRI), luminous efficacy (LE), luminous efficacy of radiation
(LER), mesopic efficacy, efficacy for circadian effects and
spectral reflectance luminous efficacy of radiation. The
optimization parameters may represent different qualities of the
lighting solution. In some embodiments, the optimization parameters
may correspond to the proportion of a component light (e.g., "t" in
equation (3)). Light optimization may be based on one or more
parameters. For example, luminous efficacy may be considered for
lighting in an environment where brightness and visibility are
important, such as roads, highway tunnels, manufacturing plants,
offices, classrooms, etc. Circadian efficacy may be considered for
lighting in a human-populated environment, such as bedrooms,
hospital wards, offices, and classrooms, etc. Spectral reflectance
luminous efficacy may be considered for lighting in an environment
where colored objects need to be illuminated, such as retail
lighting, museum lighting, landscape lighting, etc. Color rendering
effect may be considered for lighting in an environment where
discerning colorful representations is important, such as a
painting room, a museum, a shopping mall etc. Mesopic efficacy may
be considered for lighting in an environment of which the luminance
condition may trigger mesopic vision of the human eye, such as
highway tunnels and certain outdoor environment. Furthermore,
multiple parameters chosen for the optimization may be given
different weight factors before composition of the destined light
is calculated. See also Table 1 above.
[0093] In step 640, proportions of component lights may be
calculated. In some embodiments, the proportions may be calculated
by the calculating unit 534 as shown in FIG. 5. After determining
the optimization parameters in step 630, the optimization process
may be performed according to the selected optimization parameters
and weight factors.
[0094] In step 650, the driver unit 520 may drive the component
light sources according to the proportions determined in step
640.
[0095] It shall be noticed that many alternatives, modifications,
and variations will be apparent to those skilled in the art. The
features, structures, methods, and other characteristics of the
exemplary embodiments described herein may be combined in various
ways to obtain additional and/or alternative exemplary embodiments.
In one example, the sequential order of steps in the flowchart may
be adjusted, such that the determination of the weight factors of
the optimization parameters may be conducted before acquiring
information regarding the working condition or determining the
chromaticity of the destined light. In another example, the step
for acquiring of the working condition information may be not
necessary, as the chromaticity and wavelength composition of the
destined light may be predetermined by a system default, or input
by a user.
[0096] FIG. 7 is a flowchart illustrating an exemplary process for
optimizing illumination spectrum based various parameters according
to some embodiments of the present disclosure. In step 720, a
destined chromaticity and one or more optimization parameters may
be selected, such as by the optimization parameter unit 532 as
shown in FIG. 5. In some embodiments, one or more of the
optimization parameters may relate to the proportion of a component
light (t). Particularly, the one or more optimization parameters
may have a certain functional relationship with t, such as a linear
function, an inverse function, an exponential function, a
logarithmic function, a power function and other regular non-linear
function relationship.
[0097] In step 731, the illumination spectrum destined light may be
optimized according to the parameter of luminous efficacy (LE). In
some embodiments, LE of the lighting solution may relate to t.
Merely by way of example, in some embodiments, LE may be expressed
as a monotonic increasing/decreasing function of t.
.eta.=.SIGMA..sub.i=1.sup.4(k.sub.it+b.sub.i).eta..sub.i (4)
where represents the i.sup.th component light's LE that relates to
the SPD of i.sup.th component light and the photopic spectral
sensitivity curve, k.sub.i, b.sub.i are constants corresponding to
the proportion of i.sup.th component light (e.g., t).
[0098] In step 732, the illumination spectrum destined light may be
optimized according to the parameter of color rendering index
(CRI). In some embodiments, CRI of the lighting solution may relate
to t. For example, in some embodiments, the CRI may be expressed as
a reverse function of t.
[0099] In step 733, the illumination spectrum destined light may be
optimized according to the parameter of luminous efficacy of
radiation (LER). LER may also be an inverse function expressed by
the proportion of a light source (e.g., t). For example, in human
visible range, LER may be expressed as:
LER = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. P
.function. ( .lamda. ) .times. V .function. ( .lamda. ) .times. d
.times. .lamda. / .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. P .function. ( .lamda. ) .times. d.lamda. = t .times.
.intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. ( k 1
.times. P 1 + k 2 .times. P 2 + k 3 .times. P 3 + k 4 .times. P 4 )
.times. V .function. ( .lamda. ) .times. d .times. .lamda. + .intg.
3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. ( b 1 .times. P
1 + b 2 .times. P 2 + b 3 .times. P 3 + b 4 .times. P 4 ) .times. V
.function. ( .lamda. ) .times. d.lamda. t .times. .intg. 3 .times.
8 .times. 0 7 .times. 8 .times. 0 .times. ( k 1 .times. P 1 + k 2
.times. P 2 + k 3 .times. P 3 + k 4 .times. P 4 ) .times. d .times.
.lamda. + .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0
.times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3 .times. P 3 + b 4
.times. P 4 ) .times. d.lamda. ( 5 ) ##EQU00003##
where P(.lamda.) is the SPD of the destined light, P.sub.1,
P.sub.2, P.sub.3, P.sub.4 are the corresponding SPD of the
component light. V(.lamda.) is the photopic spectral sensitivity
curve, .lamda. is the wavelength, k.sub.i, b.sub.i are constants
corresponding to the proportion of i.sup.th component light source
(e.g., t).
[0100] In step 734, the illumination spectrum destined light may be
optimized according to the parameter of mesopic efficacy. In some
embodiments, S/P ratio or M/P ratio may be used to evaluate whether
a light source has a high mesopic efficacy. Particularly, as used
herein, the S/P ratio represents the ratio between scotopic
luminous flux and photopic luminous flux, and may be used to
describe how a light source works under mesopic conditions. The
calculation of the S/P may be expressed as:
S/P = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. P
.function. ( .lamda. ) .times. V ' .times. ( .lamda. ) .times. d
.times. .lamda. / .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. P .function. ( .lamda. ) .times. V .function. ( .lamda. )
.times. d.lamda. = t .times. .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3
.times. P 3 + k 4 .times. P 4 ) .times. V ' .function. ( .lamda. )
.times. d .times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3
.times. P 3 + b 4 .times. P 4 ) .times. V ' .function. ( .lamda. )
.times. d.lamda. t .times. .intg. 3 .times. 8 .times. 0 7 .times. 8
.times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3 .times.
P 3 + k 4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d
.times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3 .times. P 3 + b
4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d.lamda. (
6 ) ##EQU00004##
where P(.lamda.) is the SPD of the destined light, V'(.lamda.) is
the scotopic spectral sensitivity curve, is the wavelength,
k.sub.i, b.sub.i are constants corresponding to the proportion of
i.sup.th component light source. As shown, the S/P may be an
inverse function expressed by the proportion of a component light
(e.g., t).
[0101] The M/P ratio, which may represent LER under mesopic vision,
is the ratio of mesopic luminous flux to photopic luminous flux,
and may be deemed to represent the mesopic efficacy. Calculation of
M/P may be expressed as:
M/P = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. P
.function. ( .lamda. ) .times. V m .function. ( .lamda. ) .times. d
.times. .lamda. / .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. P .function. ( .lamda. ) .times. V .function. ( .lamda. )
.times. d.lamda. = t .times. .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3
.times. P 3 + k 4 .times. P 4 ) .times. V m .function. ( .lamda. )
.times. d .times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3
.times. P 3 + b 4 .times. P 4 ) .times. V m .function. ( .lamda. )
.times. d.lamda. t .times. .intg. 3 .times. 8 .times. 0 7 .times. 8
.times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3 .times.
P 3 + k 4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d
.times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3 .times. P 3 + b
4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d.lamda. (
7 ) ##EQU00005##
where P(.lamda.) is the SPD of the destined light, V.sub.m(.lamda.)
is a combination of V(.lamda.)and V'(.lamda.), as shown in equation
(8). As shown, the M/P may be an inverse function of the spectrum
proportion of a component light (e.g., t).
V.sub.m(.lamda.)=mV(.lamda.)+(1-m)V'(.lamda.) (8)
where m is a coefficient ranging from 0 to 1.
[0102] In step 735, the illumination spectrum of the destined light
may be optimized according to the parameter of cirtopic efficiency.
As described elsewhere in the disclosure, the cirtopic effect may
relate to the non-visual biological reaction of a human. In some
embodiments, the cirtopic effect may be taken into account in
functional lighting. For a lighting device in a bedroom, the "sleep
mode" may be set to adjust the light to optimize cirtopic effect.
In another example, for traffic lighting, the cirtopic effect may
be optimized to keep a driver alert. The C/P ratio, which
represents the efficiency for circadian effect, is the ratio
between circadian flux and radiant flux as shown in equation (7),
where C(.lamda.) is the circadian action function.
C/P = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times. P
.function. ( .lamda. ) .times. C .function. ( .lamda. ) .times. d
.times. .lamda. / .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. P .function. ( .lamda. ) .times. V .function. ( .lamda. )
.times. d.lamda. = t .times. .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3
.times. P 3 + k 4 .times. P 4 ) .times. C .function. ( .lamda. )
.times. d .times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times.
8 .times. 0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3
.times. P 3 + b 4 .times. P 4 ) .times. C .function. ( .lamda. )
.times. d.lamda. t .times. .intg. 3 .times. 8 .times. 0 7 .times. 8
.times. 0 .times. ( k 1 .times. P 1 + k 2 .times. P 2 + k 3 .times.
P 3 + k 4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d
.times. .lamda. + .intg. 3 .times. 8 .times. 0 7 .times. 8 .times.
0 .times. ( b 1 .times. P 1 + b 2 .times. P 2 + b 3 .times. P 3 + b
4 .times. P 4 ) .times. V .function. ( .lamda. ) .times. d.lamda. (
9 ) ##EQU00006##
where P(.lamda.) is the SPD of the destined light, C(.lamda.) is
the circadian action function, V(.lamda.) is the photopic spectral
sensitivity curve.
[0103] As shown, the C/P may be an inverse function of the spectrum
proportion of a component light (e.g., t).
[0104] In step 736, the illumination spectrum of the destined light
may be optimized according to the parameter of spectral reflectance
luminous efficacy (SRLER). As defined in equation (1), SRLER can be
expressed as:
SRLER = .intg. 3 .times. 8 .times. 0 7 .times. 8 .times. 0 .times.
P .function. ( .lamda. ) .times. V .function. ( .lamda. ) .times.
.rho. .function. ( .lamda. ) .times. d .times. .lamda. .intg. 3
.times. 8 .times. 0 7 .times. 8 .times. 0 .times. P .function. (
.lamda. ) .times. d .times. .lamda. ##EQU00007##
where P(.lamda.) is the SPD of the destined light, V(.lamda.) is
the photopic spectral sensitivity curve, p(.lamda.) is the spectral
reflectance curve of the illuminated object.
[0105] In step 737, the illumination spectrum of the destined light
may be optimized for photosynthetic photon flux (PPF). Particular,
PPF can be expressed by equation (10):
P .times. P .times. F = .intg. 4 .times. 0 .times. 0 7 .times. 0
.times. 0 .times. P .function. ( .lamda. ) .times. .lamda. .times.
d .times. .lamda. n A .times. h .times. c = 4 .times. 0 .times. 0 7
.times. 0 .times. 0 .times. P .function. ( .lamda. ) .times.
.lamda..DELTA..lamda. / n A .times. hc = 4 .times. 0 .times. 0 7
.times. 0 .times. 0 .times. [ ( k 1 .times. t + b 1 ) .times. P 1 +
... + ( k 4 .times. t + b 4 ) .times. P 4 ] .times.
.lamda..DELTA..lamda. / n A .times. hc = 4 .times. 0 .times. 0 7
.times. 0 .times. 0 .times. ( k 1 .times. P 1 + ... + k 4 .times. P
4 ) .times. .lamda..DELTA..lamda. .times. t / n A .times. h .times.
c + 4 .times. 0 .times. 0 7 .times. 0 .times. 0 .times. ( b 1
.times. P 1 + ... + b 4 .times. P 4 ) .times. .lamda..DELTA..lamda.
/ n A .times. hc ( 10 ) ##EQU00008##
where P(.lamda.) is the SPD of the destined light produced by the
lighting solution, n.sub.A is the Avogadro constant
(.lamda.mol.sup.-1), h is the Planck constant, c is speed of light.
Another property named photosynthetic radiation flux can be
expressed as P.sub.p=.intg.P(.lamda.)Q(.lamda.)d.lamda., where
Q(.lamda.) is the sensitive curve for photosynthesis of plant which
is corresponding to the V(.lamda.) for human. It should be noted
that different kinds of plants may have different Q(.lamda.), even
one plant may have different through different growing stages.
[0106] As shown, the PPF may be a linear function of the spectrum
proportion of a component light (e.g., t).
[0107] In step 738, the illumination spectrum of the destined light
may be optimized for the chromaticity light reflected by a target
object. Particularly, in some embodiments, chromaticity coordinates
of reflected light (x.sub.p, y.sub.p) may be an inverse function of
the spectrum proportion of a component light (e.g., t).
[0108] In some embodiments, chromaticity of reflected light
(x.sub.p, y.sub.p) may be derived from equation (11)-(17).
X .rho. = .intg. P .function. ( .lamda. ) .times. .rho. .function.
( .lamda. ) .times. x .function. ( .lamda. ) .times. d.lamda. =
.intg. [ ( k 1 .times. t + b 1 ) .times. P 1 .function. ( .lamda. )
+ ... + ( k 4 .times. t + b 4 ) .times. P 4 .function. ( .lamda. )
] .times. .rho. .function. ( .lamda. ) .times. x .function. (
.lamda. ) .times. d.lamda. = ( k 1 .times. t + b 1 ) .times. .intg.
P 1 .function. ( .lamda. ) .times. .rho. .function. ( .lamda. )
.times. x .function. ( .lamda. ) .times. d .times. .lamda. + ... +
( k 4 .times. t + b 4 ) .times. .intg. P 4 .function. ( .lamda. )
.times. .rho. .function. ( .lamda. ) .times. x .function. ( .lamda.
) .times. d.lamda. = ( k 1 .times. t + b 1 ) .times. X .rho.
.times. 1 + ... + ( k 4 .times. t + b 4 ) .times. X .rho. .times. 4
( 11 ) Y .rho. = .intg. P .function. ( .lamda. ) .times. .rho.
.function. ( .lamda. ) .times. y .function. ( .lamda. ) .times.
d.lamda. = ( k 1 .times. t + b 1 ) .times. Y .rho. .times. 1 + ...
+ ( k 4 .times. t + b 4 ) .times. Y .rho. .times. 4 ( 12 ) Z .rho.
= .intg. P .function. ( .lamda. ) .times. .rho. .function. (
.lamda. ) .times. z .function. ( .lamda. ) .times. d.lamda. = ( k 1
.times. t + b 1 ) .times. Z .rho. .times. 1 + ... + ( k 4 .times. t
+ b 4 ) .times. Z .rho. .times. 4 ( 13 ) x .rho. = X .rho. X .rho.
+ Y .rho. + Z .rho. = ( k 1 .times. t + b 1 ) .times. X .rho.
.times. 1 + + ( k 4 .times. t + b 4 ) .times. X .rho. .times. 4 ( k
1 .times. t + b 1 ) .times. ( X .rho. .times. 1 + Y .rho. .times. 1
+ Z .rho. .times. 1 ) + + ( k 4 .times. t + b 4 ) .times. ( X .rho.
.times. 4 + Y .rho. .times. 4 + Z .rho. .times. 4 ) = ( i = 1 4
.times. k i .times. X .rho.i ) t + i = 1 4 .times. b i .times. X
.rho.i ( i = 1 4 .times. k i .function. ( X .rho.i + Y .rho.i + Z
.rho.i ) ) t + i = 1 4 .times. b i .function. ( X .rho.i + Y .rho.i
+ Z .rho.i ) ( 14 ) y .rho. = ( i = 1 4 .times. k i .times. y .rho.
.times. i ) t + i = 1 4 .times. b i .times. Y .rho. .times. i ( i =
1 4 .times. k i .function. ( X .rho. .times. i + Y .rho. .times. i
+ Z .rho. .times. i ) ) t + i = 1 4 .times. b i .function. ( X
.rho. .times. i + Y .rho. .times. i + Z .rho. .times. i ) ( 15 ) {
x .rho. = a x .times. t + c x b .times. t + d = a x b + ( b .times.
c x - a x .times. d ) / b 2 t + d / b y .rho. = a y .times. t + c y
b .times. t + d = a y b + ( b .times. c y - a y .times. d ) / b 2 t
+ d / b ( 16 ) y .rho. = = b .times. c y - a y .times. d b .times.
c x - a x .times. d x .rho. + a y b - a x b b .times. c y - a y
.times. d b .times. c x - a x .times. d ( 17 ) ##EQU00009##
where X.sub.p, Y.sub.p, Z.sub.p are the tri-stimulus values of the
color appearance reflected by the object, X.sub.pi, Y.sub.pi,
Z.sub.pi are the tri-stimulus values of the each component light,
x(.lamda.), y(.lamda.), z(.lamda.) are the color matching functions
(CMF) of the destined light, P(.lamda.) is the SPD of the destined
light produced by the lighting solution, P.sub.1(.lamda.),
P.sub.2(.lamda.), P.sub.3(.lamda.), and P.sub.4(.lamda.) are
spectral power distribution (SPD) of respective four LEDs in a
package, p(.lamda.) is the spectrum reflectance curve of the target
object, k.sub.i, b.sub.i are constants corresponding to the
proportion of i.sup.th component light source, a.sub.i, c.sub.i, b,
d are constants. x.sub.p and y.sub.p are chromaticity coordinates
of reflected light, a desired chromaticity coordinate of reflected
color appearance (x.sub.p, y.sub.p) may be acquired by choosing a
proper t, so that (x.sub.p, y.sub.p) may be a property under
optimization and can be optimized by giving a weight factor to the
functions oft in equation (19).
[0109] As described above, equation (2) may be solved together with
an additional equation based on a selected optimization parameter,
such that proportions of the component lights (a.sub.1, a.sub.2,
a.sub.3 and a.sub.4) may be obtained. In some embodiments, multiple
optimization parameters may be considered individually. In other
embodiments, multiple optimization parameters may be considered
concurrently. Particularly, in some embodiments, multiple
optimizations may be given different weight factors when considered
together.
[0110] Accordingly, in step 730, multiple optimization parameters
may be optimized concurrently by giving each parameter a weight
factor or weight coefficient. Particularly, in some embodiments, a
merit function can be used for considering multiple optimization
parameters concurrently. In some embodiments, the merit function
may be written as:
Merit Function=f(p.sub.1, p.sub.2. . . p.sub.n) (18)
where n.gtoreq.1 and p.sub.1,p.sub.2. . . p.sub.n represent the one
or more selected optimization parameters as described above. The
merit function can represent the integrated impact on the destined
light by various parameters. In some embodiments, one or more of
the optimization parameters may have no effect on the calculation.
In some embodiments, some optimization parameters may have greater
effect on the calculation than other parameters.
[0111] More particularly, in some embodiments, a weight factor
function can be used for considering multiple optimization
parameters concurrently. For example, in some embodiments, three
parameters LER, C/P and M/P are considered for spectrum
optimization, and the weight factor function may be written as:
f(LER, C/P, M/P)=w.sub.1f
(t).sub.LER+w.sub.2f(t).sub.C/P+w.sub.3f(t).sub.M/P (19)
where w.sub.1, w.sub.2, w.sub.3 are weight factors corresponding to
LER, C/P and M/P, respectively. In various embodiments, weight
factors for different parameters may be the same or different,
according to particular needs under particular working
conditions.
[0112] It shall be noticed that many alternatives, modifications,
and variations will be apparent to those skilled in the art. The
features, structures, methods, and other characteristics of the
exemplary embodiments described herein may be combined in various
ways to obtain additional and/or alternative exemplary embodiments.
In some embodiments, the sequential order in which various
optimization parameters are considered may be changed. In some
embodiments, some parameters may be left out from the spectrum
optimization process. In some embodiments, the selection of
parameters to be optimized may be based on conditions of the target
object and/or its ambient environment.
[0113] FIG. 8 is a flowchart illustrating an exemplary spectrum
optimization process that takes into consideration the reflectance
spectrum of the target object according to some embodiments of the
present disclosure.
[0114] In step 810, information regarding the working condition may
be acquired. For example, in some embodiments, the working
condition information includes the reflectance spectrum of the
target object.
[0115] In step 811 the desired color appearance of a target object
under illumination of the destined light may be determined. For
example, for landscaping lighting, sometimes reproducing lighting
is preferred, while other times reshaping lighting is preferred.
Particularly, in some embodiments, illumination spectrum is
designed or optimized such that appearance of illuminated objects
or environment (e.g., landscape) is similar to that under a natural
condition (e.g., under sunlight in daytime). In these embodiments,
illumination spectrum of the destined light may be optimized to
mimic the spectrum of sunlight or white light. In other
embodiments, illumination spectrum is designed or optimized such
that appearance of illuminated objects or environment (e.g.,
landscape) unlike its natural appearance (e.g., simulate an unusual
night effect). In these embodiments, illumination spectrum of the
destined light may be optimized to achieve color enhanced effect
for objects.
[0116] In step 820 the chromaticity of the destined light may be
determined based on the desired chromaticity coordinates of light
reflected by the illuminated object or environment. For example, if
the color appearance of a target object under illumination is
determined, the color mixing process for combining four component
lights is similar to the previous example. The difference is that
spectrum reflectance curve of the target object p(.lamda.) is also
considered in the mixing process, and P(.lamda.) is replaced with
P(.lamda.)p(.lamda.). Thus, parameters P.sub.1(.lamda.)p(.lamda.),
P.sub.2(.lamda.)p(.lamda.), P.sub.3(.lamda.)p(.lamda.), and
P.sub.4(.lamda.)p(.lamda.) replace the original parameters
P.sub.1(.lamda.), P.sub.2(.lamda.), P.sub.3(.lamda.), and
P.sub.4(.lamda.), respectively, of the four component lights.
Although p(.lamda.) is considered, it is deemed as a modification
of the spectral power, and the intensity proportions of the four
component lights a.sub.1, a.sub.2, a.sub.3 , and a.sub.4 can still
be expressed as a.sub.i=k.sub.it.sub.i+b.sub.i. Consequently, the
deduction of the SRLER is similar to that in equation (3), and the
SRLER remains an inverse proportion function of t.
[0117] The destined chromaticity (x, y) of the destined light can
subsequently be quantified with the use of a process similar to the
one described above. The tristimulus value X of the destined light
can be determined via equation (20) and the chromaticity coordinate
x via equation (21), where X.sub.i, Y.sub.i, and Z.sub.i represent
the tristimulus values of the i.sup.th component light, with i
ranging from 1 to 4. Similarly, the chromaticity coordinate x is an
inverse proportion function of t, as is y , and y is a linear
function of x.
X = .intg. P .function. ( .lamda. ) .times. x .function. ( .lamda.
) .times. d.lamda. = .intg. [ ( k 1 .times. t + b 1 ) .times. P 1
.function. ( .lamda. ) + ... .times. ( k 4 .times. t + b 4 )
.times. P 4 .function. ( .lamda. ) ] .times. x _ .function. (
.lamda. ) .times. d.lamda. = ( k 1 .times. t + b 1 ) .times. .intg.
P 1 .function. ( .lamda. ) .times. x .function. ( .lamda. ) .times.
d .times. .lamda. + ... + ( k 4 .times. t + b 4 ) .times. .intg. P
4 .function. ( .lamda. ) .times. x .function. ( .lamda. ) .times.
d.lamda. = ( k 1 .times. t + b 1 ) .times. X 1 + + ( k 4 .times. t
+ b 4 ) .times. X 4 ( 20 ) x = X X + Y + Z = ( k 1 .times. t + b 1
) .times. X 1 + + ( k 4 .times. t + b 4 ) .times. X 4 ( k 1 .times.
t + b 1 ) .times. ( X 1 + Y 1 + Z 1 ) + + ( k 4 .times. t + b 4 )
.times. ( X 4 + Y 4 + Z 4 ) = ( i = 1 4 .times. k i .times. X i ) t
+ i = 1 4 .times. b i .times. X i ( i = 1 4 .times. k i .function.
( X i + Y i + Z i ) ) t + i = 1 4 .times. b i .function. ( X i + Y
i + Z i ) ( 21 ) ##EQU00010##
[0118] After determining chromaticity of the destined light, one or
more optimization parameters may be determined. In some
embodiments, multiple optimization parameters may be considered
concurrently by giving each parameter a weight factor
(coefficient), and the proportions of component lights may be
determined in step 840.
[0119] In step 850, the driver unit 220 may control the component
light sources according to the proportion determined in step
840.
[0120] Similarly to the process described in relation to FIGS. 6
through 8, the present method can be used for combining more than
four component lights. For example, for combining n number of
component lights, Equation (2) becomes:
{ ( a 1 .times. l 1 + a 2 .times. l 2 + + a i .times. l i + .times.
.times. a n .times. l n ) .times. x = a 1 .times. l 1 .times. x 1 +
a 2 .times. l 2 .times. x 2 + + a i .times. l i .times. x i + + a n
.times. l n .times. x n ( a 1 .times. l 1 + a 2 .times. l 2 + + a i
.times. l i + .times. .times. a n .times. l n ) .times. y = a 1
.times. l 1 .times. y 1 + a 2 .times. l 2 .times. y 2 + + a i
.times. l i .times. y i + a n .times. l n .times. y n a 1 + a 2 + +
a i + .times. .times. a n = 1 ( 2 ) ' ##EQU00011##
where, x.sub.i, y.sub.i is the chromaticity coordinate of the
i.sup.th component light; x, y is the chromaticity coordinate of
the destined light; a.sub.i is the proportion of the i.sup.th
component lights; l.sub.i, is the sum of tri-stimulus value of the
i.sup.th component lights. As used herein, the tri-stimulus value
refers to the amount of the three primary colors in a tri-chromatic
additive color model, such as in the 1931 CIE XYZ color space.
[0121] Equation (2)' is to be solved for unknown factors a.sub.i.
Under this scenario, to optimize the solution of equation (2)', for
different working conditions, the proportions of the different
component lights may be defined to correlate with one another in
various forms. In some embodiments, the particular correlation
between proportions of different component lights may be defined
according to practical needs and/or goals under a particular
working condition. In some embodiments, the particular correlations
may be defined according to one or more optimization parameters,
such as but not limited to luminous efficacy (LE), color rendering
index (CRI) and luminous efficacy of radiation (LER), photopic
efficacy, mesopic efficacy, circadian efficacy of radiation (CER)
for non-visual biological effects, the spectral reflectance
luminous efficacy of radiation (SRLER), photosynthetic photon flux
(PPF) or a combination thereof. In some embodiments, the particular
correlations may affect one or more optimization parameters with
respect to one or more proportions of the component lights.
[0122] For example, in some embodiments, proportions of component
lights may correlate with a multivariate function. Particularly, in
some embodiments, the number of variances in the multivariate
function varies with the number of component lights. For example,
in some embodiments that combine 5 component lights, the
multivariate function may be written as:
a.sub.i=k.sub.i1t.sub.1+k.sub.i2t.sub.2+c.sub.i (3)'
where k.sub.i1 denotes the proportion corresponding to the i.sup.th
component light with respect to t.sub.1, k.sub.i2 denotes the
proportion corresponding to the i.sup.th component light with
respect to t.sub.2, and c.sub.i is a constant corresponding to the
i.sup.th component light.
[0123] In other embodiments, proportions of some component lights
may correlate in one particular form, while proportions of other
component lights may correlate in a different form. Such as,
{ a 1 + a 2 = 0.5 a 3 + a 4 + a 5 = 0.5 ( 3 ) '' ##EQU00012##
where a.sub.1, a.sub.2, a.sub.3, a.sub.4, and a.sub.5 are
proportions of five different component lights respectively.
[0124] It should be noted that the above description about the
functional correlations between proportions of different component
lights is merely exemplary and for illustrative purposes, and
should not be understood as the only embodiments. Various
modifications to the disclosed embodiments will be readily apparent
to those skilled in the art, and the general principles defined
herein may be applied to other embodiments and applications without
departing from the spirit and scope of the present disclosure.
EXAMPLES
[0125] The following examples are for illustrative proposes only
and should not be interpreted as limitations of the claimed
invention. There are a variety of alternative techniques and
procedures available to those of ordinary skill in the art which
would similarly permit one to successfully perform the intended
invention.
Example 1
Relationship Between the Proportions of the LED Sources in
Application of Four-Package LED for High Performance
[0126] FIG. 9 illustrates the result of the proportion of each
light source based on a determined chromaticity coordinate of the
light mixture according to some embodiments of the present
disclosure.
[0127] Four different LEDs may be used as light sources. The color
of the LEDs may be red, amber, green and blue. Their chromaticity
coordinates may be R (0.6849, 0.3151), A (0.6046, 0.3953), G
(0.1221, 0.5706) and B (0.1496, 0.0421). The color-mixing point
used herein may have a color temperature of 4000K with chromaticity
coordinates (0.3805, 0.3768). Suppose the proportion of the amber
LED to be coefficient t, the other LED proportions may be solved
from equation (3). The results is shown as equation (22).
{ f .function. ( t ) R = - 1 . 0 .times. 8 .times. 4 .times. 8
.times. t + 0 . 5 .times. 7 .times. 1 .times. 5 .times. 6 .times. 3
f .function. ( t ) A = t f .function. ( t ) G = - 0 . 0 .times. 4
.times. 1 .times. 5 .times. t + 0 . 3 .times. 3 .times. 5 .times. 7
.times. 9 f .function. ( t ) B = 0 . 1 .times. 2 .times. 6 .times.
3 .times. 0 .times. 2 .times. t + 0 . 0 .times. 9 .times. 2 .times.
6 .times. 4 .times. 6 ( 22 ) ##EQU00013##
where f (t).sub.R, f (t).sub.A, f (t).sub.G, f (t).sub.B may be the
proportions of red, amber, green and blue LED as a function oft.
The slopes of the four linear functions are different. As shown,
the proportion of green LED or blue LED changes slowly with respect
to t, and the proportion of red LED changes fast with respect to
t.
[0128] Incandescent lamp and 7 kinds of four-package LEDs with
different t values derived from equation (20) are used in the
experiment. Simulated spectrums are shown in FIG. 10 but limited to
the LED cube. Corresponding inverse proportion function of
four-package LEDs on red and blue samples are
y=(-0.177t+0.620)/(-0.177t+7.82) and y=(0.183t+0.430)/(-0.
177t+7.817) respectively. However, in a small range, they are very
approximate to linear function as shown in FIG. 11.
Example 2
Relationship Between the Optimization Parameters and the Proportion
of a Light Source in a Four-Package LED System
[0129] FIG. 12 illustrates the relationship between LE, CRI and the
proportion of a light source in a four-package LED system
comprising red, amber, green and blue LEDs. The proportion of the
amber LED may be supposed to be t. The chromaticity coordinates of
the four LEDs may be R (0.6849, 0.3151), A (0.6046, 0.3953), G
(0.1221, 0.5706) and B (0.1496, 0.0421). The color-mixing point
used here may have a color temperature of 4000K with chromaticity
coordinates (0.3805, 0.3768).
[0130] The target of the optimization may be to achieve high LE and
good color rendering. As shown, the LE may be a linearly
monotonically increasing/decreasing function of proportion for all
the combinations of four-package LEDs. As for LE, relative value
would be of concern in the embodiment, and may be normalized to its
maximum value of 100 lm/W. The CRI may range from 0 to 100 in terms
of the general CRI (Ra). After calculate the LE and the CRI (Ra) as
a function of t, the results may be seen in FIG. 10. For LE, the
result may be a linear function; while for CRI, the result may be a
single peak function of proportion.
[0131] For different applications, requirements may be different
for optimizations. Merely by way of example, for outdoor lighting,
a CRI of over 50 may be good enough, and the higher the effective
LE the better. So the coefficient t may be around 0.5. For indoor
lighting, high color rendering may be needed. Considering the
requirement of LE, the coefficient t may be set to 0.3.
[0132] FIG. 13A, FIG. 13B and FIG. 13C illustrate the mesopic
efficacy at different luminances.
[0133] In some embodiments, the light sources of the lighting
system 500 are R (0.6849, 0.3151), A (0.6046, 0.3953), G (0.1221,
0.5706) and B (0.1496, 0.0421). The proportion of the amber LED may
be supposed to be t.
[0134] Under mesopic vision, the mesopic spectral sensitivity curve
may be a combination of photopic and scotopic spectral sensitivity
curves as shown in equation (8). The coefficient m equals 0 for
L.sub.mes.ltoreq.0.005 cd/m.sup.2; m=0.767+0.3334 log(L.sub.mes)
for 0.005 cd/m.sup.2<L.sub.mes<5 cd/m.sup.2; m=1 for
L.sub.mes.gtoreq.0.005 cd/m.sup.2.
[0135] The S/P ratio may be calculated in equation (7) to be
f(t).sub.S/P=(0.4702t+3.3820)/(2.2525t+3.1176). The M/P ratio may
be modified by f(t).sub.S/P=(1-m) f(t).sub.S/P+m. For different
combinations of LEDs, there may be one combination where
f(t).sub.S/P=1, and f(t).sub.M/P=1 at any luminance, which is
denoted as the concentrated point in FIG. 13A and FIG. 13B.
Although f(t).sub.M/P may show inverse proportion functions, they
would converge to the point where the M/P ratio equals 1. The
converged point may appear in meaningful regions or not. In
engineering applications, the inverse proportion functions may have
has two types. One is monotonic increasing and the other is
monotonic decreasing. When both independent variable and dependent
variable are positive, each type may be divided into three zones as
shown in FIG. 13A and FIG. 13B.
[0136] At different luminances, different formulas may be deduced.
For example, f(t).sub.M/P=f(t).sub.S/P at 0.005 cd/m.sup.2,
f(t).sub.M/P=0.8411f(t).sub.S/P+0.1589 at 0.015 cd/m.sup.2,
f(t).sub.M/P=0.6668f(t).sub.S/P+0.3332 at 0.05 cd/m.sup.2 ,
f(t).sub.M/P=0.5077f(t).sub.S/P+0.4923 at 0.15 cd/m.sup.2 ,
f(t).sub.M/P=0.3334f(t).sub.S/P+0.6666 at 0.5 cd/m.sup.2,
f(t).sub.M/P=0.1743f(t).sub.S/P+0.8257 at 1.5 cd/m.sup.2, and
f(t).sub.M/P=1 at 5 cd/m.sup.2, respectively.
[0137] The M/P ratios of different combinations of four-package
LEDs at 4000K at different luminances are shown in FIG. 13C.
Compared to the M/P ratio of FIG. 13A and FIG. 13B, these may
belong to zone 2, type 1. At different luminance, the M/P ratio may
change over a large range, from about 0.85 to 1.1. Such great
differences may mean that spectrum optimization would be very
important for energy saving. In this embodiment, it is obvious that
a high M/P ratio with a maximum reaching to about 1.1 leads to high
mesopic efficacy, and may be the optimization result ignoring other
factors.
[0138] FIG. 14A-14B illustrate the optimization process considering
LER, C/P and S/P ratio.
[0139] In some embodiments, the light sources of the lighting
system 500 are R (0.6849, 0.3151), A (0.6046, 0.3953), G (0.1221,
0.5706) and B (0.1496, 0.0421). The proportion of the amber LED may
be supposed to be t.
[0140] LER, C/P ratio and S/P ratio may be expressed by the
proportion the LEDs (e.g. t).
f(t).sub.LER=(2.2525t+3.1176)/(-1.766t+7.8167), (23)
f(t).sub.C/P=(0.5565t+2.4175)/(2.2525t+3.1176), (24)
f(t).sub.S/P=(0.4702t+3.3820)/(2.2525t+3.1176). (25)
where f(t).sub.LER, f(t).sub.C/P, f(t).sub.S/P denotes the LER, C/P
ratio and S/P ratio as functions of t.
[0141] LER, C/P and S/P as functions of coefficient t of different
combinations of LEDs are shown in FIG. 14A. In some embodiments,
different properties may be of different importance, and it may be
necessary to weight each property. After all properties have been
weighted, equation (26) may be used to optimize the spectrum.
f(LER, C/P, M/P)=w.sub.1f
(t).sub.LER+w.sub.2f(t).sub.C/P+w.sub.3f(t).sub.M/P (26)
where w.sub.1, w.sub.2, w.sub.3 are weight factors corresponding to
respective optimization parameters. The sum of all the weights may
be equal to 1 to make different optimizations comparable. Suppose
that the four-package LED lighting system 500 is to be used for
road lighting, where LER may of most importance although the S/P
ratio may also important to ensure a high mesopic efficacy. While
for C/P, the desired value might depend on population density of
the area in which the lamps are to be deployed. If it is designed
to avoid disruption of human sleep patterns, the C/P ratio may be
small and have a minus weight. If it is designed to help keep
drivers' alertness high during nighttime, the C/P ratio may be high
and have a positive weight. In this application, the system may be
designed to keep the drivers alert, so the C/P ratio may be chosen
to be small. The weight coefficients may be set to be
w.sub.1:w.sub.2:w.sub.3=0.7: -0.1: 0.4. The curve of the function
f(LER, C/P, M/P) based on the chosen weight coefficients is shown
in FIG. 14B. It should be noticed that the weights given to
different properties not only differ for different embodiments but
also differ for different design purpose.
Example 3
Selection of Spectrum Optimization Parameters According to a Target
Object's Ambient Environment
[0142] FIG. 15 illustrates an exemplary embodiment of an artificial
lighting solution for indoor plantations. Particularly, at initial
stages of planting, the main purpose is to promote vigorous plant
growth. Thus, the illumination spectrum of the lighting solution is
set to have a dominant proportion of wavelengths that plants absorb
for photosynthesis. Particularly, photosynthetic pigments contained
in plants have strong light absorption and characteristic
absorption spectra. For example, chlorophyll absorbs strongly in
two regions: 660 to 640 nm (red light) and 430 to 450 nm (blue
violet light). Absorption of orange, yellow and especially green
light is very little. Carotene and lutein are different from
chlorophyll, they only absorbing visible light in the blue violet
region.
[0143] Particularly, in some embodiments involving agricultural
lighting, the parameter of photosynthetic photon flux (PPF) may be
considered. As used herein, the term "photosynthetic photon flux"
or "PPF" refers to the ratio of flux for photosynthesis to the
number of absorbed photon, which can be expressed by equation
(10).
[0144] At later stages, plant growth slows down, and the main
purpose of the plantation becomes indoor ornamenting. Thus, the
illumination spectrum of the lighting solution is adjusted to
accommodate different needs. For example, the amount of
photosynthesis-stimulating lights may be reduced to control plant
growth. On the other hand, reflected efficiency, color rendering,
and non-visual biological effect and other aesthetic factors of the
lighting solution may become more important considerations at this
stage. Color of illumination light and that reflected from
illuminated objects together decide the atmosphere created by the
lighting solution. For example, illumination light matching the
environment helps to create a sense of space and improve the
lighting effect. Thus, various ambient conditions, such as time,
weather, season, background (ambient) color, may affect the choices
of an illumination spectrum. Particularly, affording weights to the
various considerations, such as color rendering, reflected
efficiency, non-visual biological effect, and other esthetic
factors, a synthesized chromaticity coordinate may be decided for
the destined light, component lights having desirable properties
(e.g. color and wavelength composition) may be chosen, and their
mixing proportions may be calculated according to the methods
described above. In this way the lighting system 1300 gives a
quantitative solution for spectrum optimization of indoor
plantation lighting.
Example 4
Spectrum Optimization to Reach Destined Color Temperature
[0145] FIG. 16 is an embodiment of color mixing of four-package LED
at different color temperature. Four different LEDs, red, amber,
green and blue LED are used in the study with their chromaticity
coordinates R (0.1496, 0.0421), A (0.1221, 0.5706), G (0.6047,
0.3953), and B (0.6849, 0.3151) as shown in FIG. 17. Synthesized
correlated color temperature (CCTs) of component light sources are
3000K, 4000K, 5000K, and 6000K, respectively. Linear functions
corresponding to the four CCTs are shown in equation (25) to (28),
and proportion of each LED as a function oft for color mixing of
the four CCTs are shown in FIG. 17.
[0146] CRI color samples with their chromaticity coordinates shown
in FIG. 18 are taken as illuminated objects in this example.
Chromaticity coordinates as a function oft for color mixing of
four-package LED at 3000K, 4000K, 5000K and 6000K on eight general
color samples are shown in FIG. 19, which conform to linear
function at each different color temperature. Low color temperature
light sources make illuminated object more biased to warm color,
while high color temperature light sources make illuminated object
more biased to cold color. Take color effect on color sample 9 in
FIG. 20 for example, and see that how color effect change under
different CCTs of light sources. With the change of CCT of light
sources, color effect form a color strip, following a same trend
with CCTs. Calculating chromatic aberration in CIE 1976 uv uniform
color space by transforming chromaticity coordinates from xy
chromatic diagram to uv chromatic diagram. Maximum color
aberrations .DELTA.C= {square root over
((u.sub.2-u.sub.1).sup.2+(v.sub.2-v.sub.1).sup.2)} of color samples
under four-package LEDs with different CCTs are shown in Table 2.
Color aberrations vary in a relative large range, and purity does
not directly influence them. In FIG. 20, maximum chromatic
aberration at 3000K, 4000K, 5000K, and 6000K are 0.1352, 0.1409,
0.1441, and 0.1459 respectively.
TABLE-US-00002 TABLE 2 Maximum color aberration of color samples
under four-package LEDs with different CCTs Maximum color CCT (K)
Purity(%) of aberration 3000 4000 5000 6000 color sample Color
sample 1 0.0482 0.0423 0.0384 0.0358 22.2 Color sample 2 0.0276
0.0231 0.0205 0.0189 43.7 Color sample 3 0.0024 0.0035 0.0041
0.0045 59.3 Color sample 4 0.0298 0.0244 0.0215 0.0196 20.7 Color
sample 5 0.0246 0.0197 0.0170 0.0153 18.5 Color sample 6 0.0093
0.0076 0.0070 0.0066 31.1 Color sample 7 0.0376 0.0332 0.0299
0.0275 21.8 Color sample 8 0.0690 0.0631 0.0582 0.0546 22.3
[0147] As deduced above, SRLER is inverse proportion function of t,
and SRLER as a function oft for color mixing of four-package LED at
3000K, 4000K, 5000K and 6000K are shown in FIG. 21. In the range
shown in FIG. 21, SRLER is very likely to be linear function of t.
Take color sample 9 for example, SRLER at 4000K on color sample 9
as inverse proportion function oft is shown in FIG. 22, when t is
in a large range, it conforms to inverse proportion function.
However, for parameter tin a small meaningful range, make linear
fit of SRLER oft in FIG. 22 with adj. R.sup.2 0.999, it is a
perfect linear function. So SRLER and t can be taken as linear
relationship, and maybe more convenient in some applications. At
different CCTs, SRLERs of four-package LED vary a little. CCT of
light source is not the main factor influence SRLER. It is spectrum
reflectance characteristic that influence SRLER much. Color sample
9 is more saturated than other eight general color samples, and
SRLERs of color sample 9 under light sources vary greatly. SRLERs
for eight general color samples vary from about 10% to 50%, while
variance of sample 9 reaches to about 100% or more.
{ f .function. ( t ) R = - 1.0 .times. 3 .times. 0 .times. 4
.times. 3 * t + 0 . 6 .times. 6 .times. 0 .times. 6 .times. 2
.times. 2 f .function. ( t ) A = t f .function. ( t ) G = - 0.0
.times. 5 .times. 5 .times. 6 .times. 7 * t + 0 . 3 .times. 1
.times. 2 .times. 5 .times. 8 .times. 7 f .function. ( t ) B = 0 .
0 .times. 8 .times. 6 .times. 0 .times. 9 .times. 2 * t + 0 . 0
.times. 2 .times. 6 .times. 7 .times. 9 .times. 1 ( 27 ) { f
.function. ( t ) R = - 1.084 .times. 8 * .times. t + 0 . 5 .times.
7 .times. 1 .times. 5 .times. 6 .times. 3 f .function. ( t ) A = t
f .function. ( t ) G = - 0 . 0 .times. 4 .times. 1 .times. 5 *
.times. t + 0 . 3 .times. 3 .times. 5 .times. 7 .times. 9 f
.function. ( t ) B = 0 . 1 .times. 2 .times. 6 .times. 3 .times. 0
.times. 2 * .times. t + 0 . 0 .times. 9 .times. 2 .times. 6 .times.
4 .times. 6 ( 28 ) { f .function. ( t ) R = - 1 . 1 .times. 2
.times. 2 .times. 1 .times. 8 * t + 0.510 .times. 3 .times. 4
.times. 3 f .function. ( t ) A = t f .function. ( t ) G = - 0 . 0
.times. 3 .times. 8 .times. 7 .times. 8 * t + 0.340 .times. 2
.times. 3 .times. 9 f .function. ( t ) B = 0 . 1 .times. 6 .times.
0 .times. 9 .times. 6 .times. 5 * t + 0.149 .times. 4 .times. 1
.times. 7 ( 29 ) { f .function. ( t ) R = - 1 . 1 .times. 4 .times.
8 .times. 2 .times. 6 * t + 0.467 .times. 6 .times. 3 .times. 5 f
.function. ( t ) A = t f .function. ( t ) G = - 0 . 0 .times. 4
.times. 0 .times. 0 .times. 6 * t + 0.338 .times. 1 .times. 4
.times. 7 f .function. ( t ) B = 0 . 1 .times. 8 .times. 8 .times.
3 .times. 1 .times. 7 * t + 0.194 .times. 2 .times. 1 .times. 8 (
30 ) ##EQU00014##
where f (t) .sub.i denotes the proportion of i.sup.th monochromatic
light source as function of t.
Example 5
Spectrum Optimization to Reach Destined Chromaticity
[0148] In some applications, people are more concerned about color
effect of objects, and it requires illuminated object to reach
destined chromaticity. In this part, color mixing of four-package
LED to reach destined target chromaticity has been shown.
Incandescent lamp as light source and light greyish red as color
sample have been taken as reference in FIG. 23A. To simulate color
effect of light greyish red under incandescent lamp, use the four
LEDs mentioned in Example 4 above with spectrum power P(.lamda.),
and obtain P(.lamda.)p(.lamda.), denoted as P'(.lamda.).
Chromaticity coordinates of P'(.lamda.) of four LEDs are R'
(0.67887, 0.32113), A' (0.58663, 0.41336), G' (0.13769, 0.61965),
and B' (0.14858, 0.04404), and chromaticity coordinates of
incandescent lamp (0.45437, 0.40658), light greyish red (0.3983,
0.34233), illuminated object color (0.51381, 0.39339) are all shown
in FIG. 24. Color mixing of R', A', G', and B' for illuminated
object color, and obtain proportion of each LED as a function oft
in FIG. 25 with linear function shown in equation (31).
Chromaticity coordinates of all the four-package LEDs are linear
function relationship as shown in FIG. 26 located around
incandescent lamp. Maximum chromatic aberration AC reaches to
0.0477. SRLER of spectrum of four-package LEDs are inverse
proportion function oft shown in FIG. 27 ranging from 0.13 to 0.22,
and relative difference reaches to about 70%.
{ f .function. ( t ) R = t f .function. ( t ) A = - 1 . 1 .times. 8
.times. 7 .times. 8 .times. 3 * t + 0 . 7 .times. 6 .times. 1
.times. 9 .times. 2 .times. 6 f .function. ( t ) G = 0 . 3 .times.
2 .times. 6 .times. 1 .times. 1 .times. 2 * t + 0 . 1 .times. 1
.times. 9 .times. 5 .times. 5 .times. 9 f .function. ( t ) B = - 1
. 1 .times. 3 .times. 8 .times. 2 .times. 8 * t + 0 . 1 .times. 1
.times. 8 .times. 5 .times. 1 .times. 6 ( 31 ) ##EQU00015##
[0149] The examples set forth above are provided to give those of
ordinary skill in the art a complete disclosure and description of
how to make and use the embodiments of the arrangements, devices,
compositions, systems and methods of the disclosure, and are not
intended to limit the scope of what the inventors regard as their
disclosure. All patents and publications mentioned in the
specification are indicative of the levels of skill of those
skilled in the art to which the disclosure pertains.
[0150] The entire disclosure of each document cited (including
patents, patent applications, journal articles, abstracts,
laboratory manuals, books, or other disclosures) in the Background,
Summary, Detailed Description, and Examples is hereby incorporated
herein by reference. All references cited in this disclosure are
incorporated by reference to the same extent as if each reference
had been incorporated by reference in its entirety individually.
However, if any inconsistency arises between a cited reference and
the present disclosure, the present disclosure takes
precedence.
[0151] The terms and expressions which have been employed herein
are used as terms of description and not of limitation, and there
is no intention in the use of such terms and expressions of
excluding any equivalents of the features shown and described or
portions thereof, but it is recognized that various modifications
are possible within the scope of the disclosure claimed Thus, it
should be understood that although the disclosure has been
specifically disclosed by preferred embodiments, exemplary
embodiments and optional features, modification and variation of
the concepts herein disclosed can be resorted to by those skilled
in the art, and that such modifications and variations are
considered to be within the scope of this disclosure as defined by
the appended claims.
[0152] It is also to be understood that the terminology used herein
is for the purpose of describing particular embodiments only, and
is not intended to be limiting. As used in this specification and
the appended claims, the singular forms "a," "an," and "the"
include plural referents unless the content clearly dictates
otherwise. The term "plurality" includes two or more referents
unless the content clearly dictates otherwise. Unless defined
otherwise, all technical and scientific terms used herein have the
same meaning as commonly understood by one of ordinary skill in the
art to which the disclosure pertains.
[0153] When a Markush group or other grouping is used herein, all
individual members of the group and all combinations and possible
subcombinations of the group are intended to be individually
included in the disclosure. Every combination of components or
materials described or exemplified herein can be used to practice
the disclosure, unless otherwise stated. One of ordinary skill in
the art will appreciate that methods, device elements, and
materials other than those specifically exemplified can be employed
in the practice of the disclosure without resort to undue
experimentation. All art-known functional equivalents, of any such
methods, device elements, and materials are intended to be included
in this disclosure. Whenever a range is given in the specification,
for example, a temperature range, a frequency range, a time range,
or a composition range, all intermediate ranges and all subranges,
as well as, all individual values included in the ranges given are
intended to be included in the disclosure. Any one or more
individual members of a range or group disclosed herein can be
excluded from a claim of this disclosure. The disclosure
illustratively described herein suitably can be practiced in the
absence of any element or elements, limitation or limitations that
is not specifically disclosed herein.
[0154] A number of embodiments of the disclosure have been
described. The specific embodiments provided herein are examples of
useful embodiments of the disclosure and it will be apparent to one
skilled in the art that the disclosure can be carried out using a
large number of variations of the devices, device components,
methods steps set forth in the present description. As will be
obvious to one of skill in the art, methods and devices useful for
the present methods can include a large number of optional
composition and processing elements and steps. In particular, it
will be understood that various modifications may be made without
departing from the spirit and scope of the present disclosure.
Accordingly, other embodiments are within the scope of the
following claims.
[0155] It should be also appreciated that the above described
method embodiments may take the form of computer or controller
implemented processes and apparatuses for practicing those
processes. The disclosure can also be embodied in the form of
computer program code containing instructions embodied in tangible
media, such as floppy diskettes, CD-ROMs, hard drives, or any other
computer-readable storage medium, wherein, when the computer
program code is loaded into and executed by a computer or
controller, the computer becomes an apparatus for practicing the
invention. The disclosure may also be embodied in the form of
computer program code or signal, for example, whether stored in a
storage medium, loaded into and/or executed by a computer or
controller, or transmitted over some transmission medium, such as
over electrical wiring or cabling, through fiber optics, or via
electromagnetic radiation, wherein, when the computer program code
is loaded into and executed by a computer, the computer becomes an
apparatus for practicing the invention. When implemented on a
general-purpose microprocessor, the computer program code segments
configure the microprocessor to create specific logic circuits.
[0156] While the invention has been described with reference to a
preferred embodiment, it will be understood by those skilled in the
art that various changes may be made and equivalents may be
substituted for elements thereof without departing from the scope
of the invention. In addition, many modifications may be made to
adapt a particular situation or material to the teachings of the
invention without departing from the essential scope thereof.
Therefore, it is intended that the invention not be limited to the
particular embodiment disclosed as the best mode contemplated for
carrying out this invention, but that the invention will include
all embodiments falling within the scope of the appended
claims.
* * * * *