A multi-color LED light mixing optimization calculation method

Abstract

The application discloses a multi-color LED light mixing optimization calculation method, and relates to the technical field of illumination. The application firstly tests and obtains the spectral power distribution of each color light source under the rated working state, then calculates the chromaticity coordinates of each color light source in the CIE1931-RGB system standard colorimetric observer spectral tristimulus value, subsequently calculates the CIE1931-XYZ tristimulus value, CIE1931-XYZ color quality coordinates and CIE1960-UCS color quality coordinates of each color light source, then takes the representative 30 color temperature points in the color temperature 1000K-10000K interval as the light mixing result target points based on the seven-order blackbody locus function, calculates the duty cycle required by the light mixing target points, finds the points with better Ra, Rg and Rf in each color temperature point and the related color temperature, saves the data, and finally optimizes through the genetic algorithm. The application can greatly reduce the calculation time compared with the traversal method under the same calculation accuracy by starting from the light mixing principle, using the chromaticity coordinates to calculate the duty cycle and using the genetic algorithm for optimization.

Description

Technical Field

[0001] This invention belongs to the field of lighting technology, and in particular relates to a method for calculating optimal solutions for multi-color LED mixing. Background Technology

[0002] Multicolor LED mixing is a commonly used model in some professional lighting applications, with common models including RGBW (red, green, blue, and white light) and RGBCW (red, green, blue, cool white, and warm white light). The mixing result achievable with multicolor LEDs is represented in the CIE 1931 color space as the largest area enclosed by the coordinates of each LED.

[0003] In the field of lighting, color temperature and correlated color temperature are commonly used to describe the color of white light. When a light source and a blackbody at a certain temperature have the same color, the color of the light source is described by the temperature of the blackbody, i.e., color temperature. The chromaticity coordinates of a blackbody at various temperatures in CIE 1931 are represented by a curve, called the blackbody locus. For light sources whose coordinates do not fall on the blackbody locus, their color temperature is described by the color temperature of the point on the nearest blackbody locus, i.e., correlated color temperature. The ability of a light source to reproduce the colors of objects is called the color rendering index (CRI). The CRI is usually divided into general color rendering index (Ra) and special color rendering index (R1-R15), with a maximum value of 100. TM-30 uses two indicators, fidelity (Rf) and saturation (Rg), to jointly evaluate color quality; the closer the value is to 100, the higher the color quality of the light source is considered.

[0004] In practical applications, when the control light mixing coordinates fall on the blackbody trajectory, the optimal performance of Ra, Rf, and Rg is usually not obtained. It is necessary to find a correlated color temperature that performs better at that color temperature. Existing light mixing techniques typically use pulse width modulation (PWM) technology to control LEDs, achieving different light mixing effects by changing the duty cycle of each LED. The calculation of the duty cycle is mostly ergonomic, that is, changing the duty cycle of each LED with a fixed step size and selecting the combination of duty cycles that performs better.

[0005] However, most existing technologies determine the duty cycle for light mixing by completely traversing all LEDs with a fixed step size. In pursuit of better color performance, the number of LED colors involved in light mixing is increasing, from the initial warm and cool white light to the current RGBW and RGBCW light mixing. As the number of different colored LEDs involved in light mixing increases, the time required for the fixed step size traversal method increases exponentially. The calculation of a set of four-color LED beads can take tens or even hundreds of hours. Based on this, we propose a method for calculating the optimal solution of multi-color LED light mixing. Summary of the Invention

[0006] The purpose of this invention is to provide a method for calculating the optimal solution of multicolor LED mixing, so as to solve the problems mentioned in the background art.

[0007] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0008] This invention relates to a method for calculating optimal solutions for multi-color LED mixing, including a coordinate calculation method. This coordinate calculation method is based on two colorimetric systems, CIE1931 and CIE1960, and uses points on the blackbody locus and their associated color temperatures within the range of 1000K-10000K as target points. It calculates the proportion required for a given light source to reach the target point. The coordinate calculation method includes the following steps:

[0009] S1. The spectral power distribution of each color light source under rated operating conditions is obtained by testing;

[0010] S2. Calculate the chromaticity coordinates of each light source in the standard chromaticity observer spectral tristimulus values ​​of the CIE1931-RGB system;

[0011] S3. Calculate the CIE1931-XYZ tristimulus values ​​for each color light source;

[0012] S4. Calculate the CIE1931-XYZ chromaticity coordinates of each light source;

[0013] S5. Calculate the CIE1960-UCS chromaticity coordinates of each color light source;

[0014] S6. Based on the seventh-order blackbody locus function, select 30 representative color temperature points in the color temperature range of 1000K-10000K, and calculate the perpendicular function of each selected color temperature point on the blackbody locus in the CIE1960-UCS colorimetric system.

[0015] S7. On the vertical line of each selected color temperature point of the blackbody trajectory calculated in S6 in the CIE1960-UCS color system, select 20 related color temperature points near each point at a fixed interval, record their coordinates (u, v), and convert the coordinates to CIE1931-XYZ color system coordinates (x, y).

[0016] S8. Mix LEDs of different colors with similar chromaticity coordinates in a fixed step size to obtain a set of mixed LED data. The number of mixed LEDs depends on the number of different colors of LEDs. The mixed data is regarded as LEDs of one color. A mixed LED can be obtained by mixing a maximum of three initial LEDs. The final number of LEDs involved in the calculation is three. And calculate the chromaticity coordinates (x, y) of the three LEDs in CIE1931-XYZ.

[0017] S9. Using the three types of LEDs obtained in S8, calculate the required duty cycle for the target point selected on the blackbody trajectory by mixing the light;

[0018] S10. Find the points with good Ra, Rg, and Rf performance in each color temperature point and its related color temperatures, and save the data.

[0019] Furthermore, in S2, the calculation formula is as follows:

[0020]

[0021] In the formula, Let be the spectral distribution function of the light to be measured, and k be the maximum spectral luminous efficacy. These are the standard spectral tristimulus values ​​for the CIE1931-RGB system's colorimetric observer.

[0022] Furthermore, in S3, the calculation formula is as follows:

[0023]

[0024] Furthermore, in S4, the calculation formula is as follows:

[0025]

[0026] Furthermore, in S5, the calculation formula is as follows:

[0027]

[0028] Furthermore, the seventh-order blackbody trajectory function described in S6 is:

[0029] v=-14.336088+319.35498u-2990.9729u 2 +15551.2u 3 -48288.335u 4 +89346.075u 5 -91102.316u 6 +39467.868u 7 .

[0030] Furthermore, in S9, the calculation formula is as follows:

[0031]

[0032] Where K r K g K b Let x be the duty cycle of the three types of LEDs. t y t Let x be the chromaticity coordinates of the target point. ry r x g y g x b y b Here are the chromaticity coordinates of the three types of LEDs.

[0033] Furthermore, it also includes a genetic algorithm, which is based on the results obtained by the coordinate calculation method. Using the results obtained in S10 as initial data, it optimizes each target color temperature point and saves data near the target color temperature point. The genetic algorithm includes the following steps:

[0034] I. The duty cycles of each LED obtained from the coordinate calculation method are binary encoded. Each duty cycle corresponds to 10 bits of binary code, and the total code length is 10n, where n is the number of LED colors;

[0035] II. Calculate the code to obtain the corresponding duty cycle mixing result. The mixing result includes CCT, Ra, Rf and Rg. This set of data is the parent population.

[0036] III. Select 30 color temperature points within the 1000K-10000K color temperature range in the coordinate calculation method, and use them one by one as the target color temperature TargetCCT for the genetic algorithm calculation;

[0037] IV. Based on the light mixing results, perform non-dominated sorting on each group of data. The sorting reference values ​​are |TargetCCT-CCT|, (100-Ra), (100-Rf) and |100-Rg|, and calculate the crowding degree.

[0038] V. Use tournament selection to select two sets of data from the parent population, cross these two sets of data, and store the crossover result in the offspring population;

[0039] VI. Randomly select a parent population to undergo mutation, calculate the corresponding light mixing result for the mutated duty cycle, and store the result in the offspring population;

[0040] VII. Perform a non-dominated sort on the results in the offspring population and eliminate offspring with lower sort rankings;

[0041] VIII. Repeat IV-VII.

[0042] The present invention has the following beneficial effects:

[0043] This invention, based on the principle of light mixing, uses chromaticity coordinates to calculate the duty cycle and optimizes it with a genetic algorithm, thereby significantly reducing the computation time while maintaining the same computational accuracy. Attached Figure Description

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a schematic diagram of the CIE1931 chromaticity coordinates and blackbody trajectory of the present invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figure 1 As shown, this invention is a method for calculating the optimal solution of multi-color LED mixing, including a coordinate calculation method and a genetic algorithm. The coordinate calculation method is based on two colorimetric systems, CIE1931 and CIE1960, and takes points on the blackbody trajectory and their associated color temperatures in the range of 1000K-10000K as target points to solve for the proportion required for a given light source to reach the target point. This coordinate calculation method specifically includes the following steps:

[0048] S1. The spectral power distribution of each color light source under rated operating conditions is obtained by testing;

[0049] S2. Calculate the chromaticity coordinates of each color light source in the CIE1931-RGB system standard chromaticity observer spectral tristimulus values, where the specific calculation formula is as follows:

[0050]

[0051] In the formula, Let be the spectral distribution function of the light to be measured, and k be the maximum spectral luminous efficacy. These are the standard chromaticity observer spectral tristimulus values ​​for the CIE1931-RGB system;

[0052] S3. Calculate the CIE1931-XYZ tristimulus values ​​for each color light source. The specific calculation formula is as follows:

[0053]

[0054] S4. Calculate the CIE1931-XYZ chromaticity coordinates of each color light source. The specific calculation formula is as follows:

[0055]

[0056] S5. Calculate the CIE1960-UCS chromaticity coordinates of each color light source. The calculation formula is as follows:

[0057]

[0058] S6. Based on the seventh-order blackbody locus function, select 30 representative color temperature points within the color temperature range of 1000K-10000K, and calculate the perpendicular function of each selected color temperature point on the blackbody locus in the CIE1960-UCS colorimetric system. The seventh-order blackbody locus function is:

[0059] v=-14.336088+319.35498u-2990.9729u 2 +15551.2u 3 -48288.335u 4 +89346.075u 5 -91102.316u 6 +39467.868u 7 ;

[0060] S7. On the vertical line of each selected color temperature point of the blackbody trajectory calculated in S6 in the CIE1960-UCS color system, select 20 related color temperature points near each point at a fixed interval, record their coordinates (u, v), and convert the coordinates to CIE1931-XYZ color system coordinates (x, y).

[0061] S8. Mix LEDs of different colors with similar chromaticity coordinates in a fixed step size to obtain a set of mixed LED data. The number of mixed LEDs depends on the number of different colors of LEDs. The mixed data is regarded as LEDs of one color. A mixed LED can be obtained by mixing a maximum of three initial LEDs. The final number of LEDs involved in the calculation is three. And calculate the chromaticity coordinates (x, y) of the three LEDs in CIE1931-XYZ.

[0062] S9. Using the three types of LEDs obtained in S8, calculate the required duty cycle for the selected target point on the blackbody trajectory using light mixing. In this embodiment, the calculation formula is as follows:

[0063]

[0064] Where K r K g K b Let x be the duty cycle of the three types of LEDs. t y t Let x be the chromaticity coordinates of the target point.r y r x g y g x b y b Here are the chromaticity coordinates of the three LEDs;

[0065] S10. Find the points with good Ra, Rg, and Rf performance in each color temperature point and its related color temperatures, and save the data.

[0066] The genetic algorithm, based on the coordinate calculation method, uses the results obtained in S10 as initial data to optimize each target color temperature point and saves the data near the target color temperature point. In this embodiment, the genetic algorithm specifically includes the following steps:

[0067] I. The duty cycles of each LED obtained from the coordinate calculation method are binary encoded. Each duty cycle corresponds to 10 bits of binary code, and the total code length is 10n, where n is the number of LED colors;

[0068] II. Calculate the code to obtain the corresponding duty cycle mixing result. The mixing result includes CCT, Ra, Rf and Rg. This set of data is the parent population.

[0069] III. Select 30 color temperature points within the 1000K-10000K color temperature range in the coordinate calculation method, and use them one by one as the target color temperature TargetCCT for the genetic algorithm calculation;

[0070] IV. Based on the light mixing results, perform non-dominated sorting on each group of data. The sorting reference values ​​are |TargetCCT-CCT|, (100-Ra), (100-Rf) and |100-Rg|, and calculate the crowding degree.

[0071] V. Use tournament selection to select two sets of data from the parent population, cross these two sets of data, and store the crossover result in the offspring population;

[0072] VI. Randomly select a parent population to undergo mutation, calculate the corresponding light mixing result for the mutated duty cycle, and store the result in the offspring population;

[0073] VII. Perform a non-dominated sort on the results in the offspring population and eliminate offspring with lower sort rankings;

[0074] Among them, tournament selection is an existing mature method. Its core idea is to randomly select a certain number of individuals from the parent generation in each evolution process, and select the individual with the highest fitness from these individuals for genetic manipulation. This process is repeated until the size of the offspring population is the same as that of the parent population. It will not be elaborated here.

[0075] VIII. Repeat IV-VII.

[0076] In the traversal calculation method, the calculation time increases exponentially with the number of different colored LEDs participating in the light mixing. The more different colored LEDs participating in the light mixing, the shorter the calculation time of the method of the present invention compared to the traversal method. For example, in the case of five-color light mixing and a duty cycle accuracy of 0.001, the calculation time of the traversal method is about 200 hours, while the calculation time of the method of the present invention is about 6 hours.

[0077] Moreover, the coordinate calculation method only needs to perform the calculation with a lower precision, and then improve the calculation precision when using the genetic algorithm later, which can better improve the calculation efficiency.

[0078] In summary, it can be seen that this invention, by starting from the principle of light mixing, using chromaticity coordinates to calculate the duty cycle and optimizing it with a genetic algorithm, can significantly reduce the calculation time required while maintaining the same calculation accuracy compared to existing methods, making it more suitable for widespread application.

[0079] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for calculating the optimal solution of multi-color LED mixing, characterized in that, This includes a coordinate calculation method, which comprises the following steps: S1. The spectral power distribution of each color light source under rated operating conditions is obtained by testing; S2. Calculate the chromaticity coordinates of each light source in the standard chromaticity observer spectral tristimulus values ​​of the CIE1931-RGB system; S3. Calculate the CIE1931-XYZ tristimulus values ​​for each color light source; S4. Calculate the CIE1931-XYZ chromaticity coordinates of each light source; S5. Calculate the CIE1960-UCS chromaticity coordinates of each color light source; S6. Based on the seventh-order blackbody locus function, select 30 representative color temperature points in the color temperature range of 1000K-10000K, and calculate the perpendicular function of each selected color temperature point on the blackbody locus in the CIE1960-UCS colorimetric system. S7. On the vertical line of each selected color temperature point of the blackbody trajectory calculated in S6 in the CIE1960-UCS color system, select 20 related color temperature points near each point at a fixed interval, record their coordinates (u, v), and convert the coordinates to CIE1931-XYZ color system coordinates (x, y). S8. Mix LEDs of different colors with similar chromaticity coordinates in a fixed step size to obtain a set of mixed LED data. The number of mixed LEDs depends on the number of different colors of LEDs. The mixed data is regarded as LEDs of one color. A mixed LED can be obtained by mixing a maximum of three initial LEDs. The final number of LEDs involved in the calculation is three. And calculate the chromaticity coordinates (x, y) of the three LEDs in CIE1931-XYZ. S9. Using the three types of LEDs obtained in S8, calculate the required duty cycle for the target point selected on the blackbody trajectory by mixing the light; S10. Find the points with good Ra, Rg, and Rf performance in each color temperature point and its related color temperatures, and save the data.

2. The method for calculating the optimal solution of multi-color LED mixing according to claim 1, characterized in that, In S2, the calculation formula is as follows: In the formula, Let be the spectral distribution function of the light to be measured, and k be the maximum spectral luminous efficacy. These are the standard spectral tristimulus values ​​for the CIE1931-RGB system's colorimetric observer.

3. The method for calculating the optimal solution of multicolor LED mixing according to claim 2, characterized in that, In S3, the calculation formula is as follows:

4. The method for calculating the optimal solution of multicolor LED mixing according to claim 3, characterized in that, In S4, the calculation formula is as follows:

5. The method for calculating the optimal solution of multicolor LED mixing according to claim 4, characterized in that, In S5, the calculation formula is as follows:

6. The method for calculating the optimal solution of multicolor LED mixing according to claim 5, characterized in that, The seventh-order blackbody trajectory function described in S6 is: v=-14.336088+319.35498u-2990.9729u 2 +15551.2u 3 -48288.335u 4 +89346.075u 5 -91102.316u 6 +39467.868u 7 。 7. The method for calculating the optimal solution of multicolor LED mixing according to claim 6, characterized in that, In S9, the calculation formula is as follows: Where K r K g K b Let x be the duty cycle of the three types of LEDs. t y t Let x be the chromaticity coordinates of the target point. r y r x g y g x b y b Here are the chromaticity coordinates of the three types of LEDs.

8. The method for calculating the optimal solution of multi-color LED mixing according to claim 7, characterized in that, It also includes a genetic algorithm, which comprises the following steps: I. The duty cycles of each LED obtained from the coordinate calculation method are binary encoded. Each duty cycle corresponds to 10 bits of binary code, and the total code length is 10n, where n is the number of LED colors; II. Calculate the code to obtain the corresponding duty cycle light mixing result. The light mixing result includes CCT, Ra, Rf and Rg. This set of data is the parent population. III. Take the 30 color temperature points selected in the 1000K-10000K color temperature range in the coordinate calculation method as the target color temperature TargetCCT calculated by the genetic algorithm. IV. Based on the light mixing results, perform non-dominated sorting on each group of data. The sorting reference values ​​are |TargetCCT-CCT|, (100-Ra), (100-Rf) and |100-Rg|, and calculate the crowding degree. V. Use tournament selection to select two sets of data from the parent population, cross these two sets of data, and store the crossover result in the offspring population; VI. Randomly select a parent population to undergo mutation, calculate the corresponding light mixing result for the mutated duty cycle, and store the result in the offspring population; VII. Perform a non-dominated sort on the results in the offspring population and eliminate offspring with lower sort rankings; VIII. Repeat IV-VII.

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