A method for controlling the lateral emission angle of LEDs based on an arc-shaped reflector wall

Abstract

The application provides an LED side light angle control method based on an arc-shaped or polygonal reflecting wall and relates to the technical field of LED light emission control. The application establishes a variable parameter model in three-dimensional simulation by acquiring indexes such as illumination uniformity and module spacing, and obtains optimal reflecting wall preparation parameters by applying a multi-objective optimization algorithm. The final reflecting wall is formed through injection molding processing, effective control of the LED side light angle and uniformity is realized, the display screen uniformity is improved, the module spacing is expanded, the material and energy consumption are reduced, the multi-scene application is met, and the application is suitable for efficient, energy-saving and high-reliability display systems.

Description

Technical Field

[0001] This invention relates to the field of LED light emission control technology, and in particular to a method for controlling the lateral light emission angle of LEDs based on an arc-shaped reflector wall. Background Technology

[0002] LED display technology, due to its advantages such as high brightness and low energy consumption, is widely used in the optical module matrix of large display screens. Traditional LED chips mainly emit light from the front, but due to limitations in light pattern distribution, it is difficult to meet the uniformity requirements of matrix arrangement. To address this, the industry has gradually developed "five-sided emitting chips," which enhance lateral emission capabilities by introducing an L-shaped reflector wall structure to expand the effective light-emitting area and reduce the number of LEDs used. However, the linear radiation characteristic of light leads to uneven light energy distribution, especially forming weak light areas at the four corners of the matrix optical module, which seriously affects the uniformity of the display.

[0003] With the market's urgent demand for thinner, lighter, and more energy-efficient display devices, LED bracket design is evolving further towards modularity and high integration. Matrix light modular design has become mainstream due to its economy and arrangement flexibility, but its core challenge lies in how to avoid the generation of dark areas at the four corners while increasing the spacing between modules. Existing technologies attempt to improve light distribution by optimizing the shape of the reflective wall (such as a planar L-shaped structure), but still cannot effectively solve the contradiction between light diffusion and concentration.

[0004] While current L-shaped reflective walls can improve lateral light emission efficiency, their planar structure limits their ability to control light. As the matrix spacing increases, the linear radiation characteristics of light cause significant light intensity attenuation at the four corners, forcing a reduction in module spacing, resulting in material waste and increased costs. Furthermore, existing designs struggle to achieve a dynamic balance between light distribution area and light intensity concentration, limiting further improvements in display uniformity and energy efficiency. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide an LED lateral emission angle control method based on an arc-shaped reflector wall. Through the arc / polygonal reflector wall structure and adaptive optimization design, the uniformity of LED matrix light distribution is significantly improved, the module spacing is increased, and material and energy consumption are reduced. While meeting the needs of multiple scenarios, this invention achieves a high-efficiency, energy-saving and highly reliable display solution.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for controlling the lateral emission angle of LEDs based on an arc-shaped reflector wall, comprising:

[0008] Obtain the target illuminance uniformity U0, module spacing, allowable deviation ε, and target lateral energy percentage K of the optical module matrix;

[0009] Based on the module spacing, a variable model of a pre-defined reflective wall with parameters such as radius of curvature R, wrap angle θ, and wall reflectivity ρ is established in three-dimensional optical simulation software; the pre-defined structure is arc-shaped or polygonal.

[0010] Based on the target illumination uniformity U0, allowable deviation ε, and lateral energy ratio target K, the radius of curvature R, wrap angle θ, and wall reflectivity ρ are optimized using a multi-objective optimization algorithm to obtain the optimal preparation parameters;

[0011] Based on the optimal preparation parameters, the final reflective wall with the preset structure is prepared by injection molding.

[0012] The final reflective wall is used to control the lateral light emission angle of the LED.

[0013] Preferably, the radius of curvature R ranges from 0.5mm to 3mm; the wrap angle θ ranges from 30° to 150°.

[0014] Preferably, the wall reflectivity ρ ranges from 0.85 to 0.99. When ρ is less than 0.92, the surface of the reflective wall is a high-reflectivity mirror layer to increase the value of ρ.

[0015] Preferably, based on the target illuminance uniformity U0, the allowable deviation ε, and the target lateral energy ratio K, a multi-objective optimization algorithm is used to optimize the radius of curvature R, the wrap angle θ, and the wall reflectivity ρ to obtain the optimal preparation parameters, including:

[0016] a. Randomly generate several parameter sets (R) within a preset range of the radius of curvature R, the wrap angle θ, and the wall reflectivity ρ. i ,θ i ,ρ i ); where R i θ i and ρ i These are the i-th radius of curvature, the angle of containment, and the wall reflectivity in the parameter set, respectively.

[0017] b. Perform Monte Carlo ray tracing on each of the parameter groups to obtain the illuminance uniformity U. i And the proportion of lateral energy K i ;

[0018] c. Calculate the overall deviation Δ i =w1|U i –U0|+w2|K i –K|;w1 and w2 are the weights for illuminance uniformity error and lateral energy proportion error, respectively;

[0019] d. Employ a genetic algorithm or gradient descent algorithm, simultaneously adjusting R, θ, and ρ to minimize Δ. i ;

[0020] e. When Δ i If the value is less than or equal to ε or the number of iterations is greater than or equal to N, output the optimal parameters (R*, θ*, ρ*); otherwise, return to step b. Here, N is the maximum number of iterations, and R*, θ*, and ρ* are the radius of curvature, wrap angle, and wall reflectivity of the optimal preparation parameters, respectively.

[0021] Preferably, when using a genetic algorithm, the crossover probability is 0.7–0.9, the mutation probability is 0.01–0.1, and the best 10% of individuals are retained at the end of each generation for elite retention.

[0022] Preferably, when using the gradient descent algorithm, the learning rate η used in the k-th iteration is... k According to formula η k =η0÷(1+k / K) decreasing, where η0 is the preset initial learning rate and K is the decay constant.

[0023] Preferably, it also includes

[0024] An array of light intensity sensors is deployed on the LED modules of the final reflective wall to measure the measured uniformity U. real ;

[0025] Judgment Formula | U real If -U0|>ε is true, then set U real Feedback is sent to step b for re-optimization until the uniformity requirement is met.

[0026] Preferably, the light intensity sensor array is a 4×4 grid.

[0027] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0028] This invention provides a method for controlling the lateral emission angle of LEDs based on an arc-shaped reflective wall, comprising: obtaining the target illuminance uniformity U0, module spacing, allowable deviation ε, and target lateral energy ratio K of the light module matrix; based on the module spacing, establishing a variable model of a preset structure reflective wall with parameters of radius of curvature R, enclosed angle θ, and wall reflectivity ρ in three-dimensional optical simulation software; the preset structure is arc-shaped or polygonal; based on the target illuminance uniformity U0, allowable deviation ε, and target lateral energy ratio K, optimizing the radius of curvature R, enclosed angle θ, and wall reflectivity ρ using a multi-objective optimization algorithm to obtain optimal fabrication parameters; based on the optimal fabrication parameters, fabricating the final reflective wall of the preset structure by injection molding; and using the final reflective wall to control the lateral emission angle of the LEDs. This invention, through the arc / polygonal reflective wall structure and adaptive optimization design, significantly improves the uniformity of light distribution in the LED matrix, expands the module spacing, and reduces material and energy consumption, achieving a highly efficient, energy-saving, and highly reliable display solution while meeting the needs of multiple scenarios. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in 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.

[0030] Figure 1 A flowchart of the method provided in an embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of the technical route provided in the embodiments of the present invention;

[0032] Figure 3 A flowchart for uniformity determination provided in an embodiment of the present invention. Detailed Implementation

[0033] 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.

[0034] The purpose of this invention is to provide an LED lateral emission angle control method based on an arc-shaped reflector wall. Through the arc / polygonal reflector wall structure and adaptive optimization design, the uniformity of LED matrix light distribution is significantly improved, the module spacing is increased, and material and energy consumption are reduced. While meeting the needs of multiple scenarios, it achieves a high-efficiency, energy-saving and highly reliable display solution.

[0035] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] like Figure 1 and Figure 2 As shown, this invention provides a method for controlling the lateral emission angle of an LED based on an arc-shaped reflector wall, comprising:

[0037] Step 100: Obtain the target illuminance uniformity U0, module spacing, allowable deviation ε, and target lateral energy percentage K of the optical module matrix;

[0038] Step 200: Based on the module spacing, establish a variable model of the preset structure reflective wall in the 3D optical simulation software with the radius of curvature R, the wrap angle θ and the wall reflectivity ρ as parameters; the preset structure is arc-shaped or polygonal;

[0039] Step 300: Based on the target illumination uniformity U0, allowable deviation ε, and lateral energy ratio target K, the radius of curvature R, wrap angle θ, and wall reflectivity ρ are optimized using a multi-objective optimization algorithm to obtain the optimal preparation parameters;

[0040] Step 400: Based on the optimal preparation parameters, prepare the final reflective wall with the preset structure by injection molding;

[0041] Step 500: Use the final reflective wall to control the lateral light emission angle of the LED.

[0042] Preferably, the radius of curvature R ranges from 0.5mm to 3mm; the wrap angle θ ranges from 30° to 150°.

[0043] Preferably, the wall reflectivity ρ ranges from 0.85 to 0.99. When ρ is less than 0.92, the surface of the reflective wall is a high-reflectivity mirror layer to increase the value of ρ.

[0044] Specifically, in step 100 of this embodiment, the actual requirements for brightness uniformity are evaluated based on the display screen resolution, expected viewing distance, and application scenario. A suitable target illuminance uniformity value is determined by referencing industry standards, simulation data, and user experience feedback. This target value should reflect the consistency of brightness distribution across the entire display area under normal operating conditions, ensuring that the final product has good display performance.

[0045] Subsequently, this embodiment rationally determines the spacing between modules. This parameter is affected not only by the overall size of the display screen and the pixel arrangement, but also by practical conditions such as structural strength, heat dissipation space, and assembly process. The technical team usually analyzes the optical performance and mechanical feasibility of different spacing schemes in prototype testing or layout simulation, and finally selects the module spacing that can meet the requirements of uniform illumination and has excellent physical compatibility. The above spacing selection also needs to take into account production costs and subsequent maintenance convenience.

[0046] In addition, this embodiment sets allowable deviations for optical design and targets for lateral energy ratio. Allowable deviations are primarily determined by comprehensively considering manufacturing process precision and performance acceptance requirements, setting corresponding values ​​based on actual mass production levels and quality assurance standards, serving as a basis for judgment during subsequent optimization and inspection processes. The lateral energy ratio target is based on the luminous efficacy distribution requirements of the application scenario. Through analysis of luminous characteristics under typical operating conditions, statistics and summaries are conducted to ensure that the final optical module not only emits light uniformly from the front but also possesses excellent lateral illumination effects, meeting the usage requirements of diverse applications such as large-screen splicing and advertising displays.

[0047] Optionally, in step 200 of this embodiment, after obtaining the actual spacing parameters of the optical modules, a spatial skeleton model of the matrix optical modules is first established in 3D optical simulation software to ensure that the placement and spacing of each module consistently reflect the actual assembly. Based on this space, the available installation area around each module is determined, reserving sufficient modeling space for subsequent reflective wall structure design. This process takes into account both the physical separation requirements between modules and optical overlap control, providing a geometric basis for accurate modeling.

[0048] Subsequently, based on the pre-defined structural types, adjustable curved or polygonal reflective wall foundation models were constructed. For curved structures, the shape of the reflective wall was continuously adjusted by setting different radii of curvature and wrap angles; for polygonal structures, wall combinations with different reflective properties were generated by adjusting the lengths and included angles of each side. In the parametric model, the control parameters of the radius of curvature, wrap angle, or polygon were set as input variables for subsequent optimization and iteration. Each structure was based on tolerance analysis and manufacturing capabilities to ensure that the three-dimensional geometric shape could be automatically generated according to parameter changes.

[0049] Finally, considering the different properties of the reflective wall materials, different wall reflectivity attributes are assigned to each reflective wall surface in the simulation model. By assigning different reflectivities, the influence of using high-reflectivity metals, coatings, or matte materials in reality on the light effect distribution is simulated. The above model supports parametric input and batch automatic modeling, which can lay the technical foundation for subsequent multi-round optical path tracing and optimization analysis, and realize the complete modeling needs of structural variability and material diversity.

[0050] Preferably, based on the target illuminance uniformity U0, the allowable deviation ε, and the target lateral energy ratio K, a multi-objective optimization algorithm is used to optimize the radius of curvature R, the wrap angle θ, and the wall reflectivity ρ to obtain the optimal preparation parameters, including:

[0051] a. Randomly generate several parameter sets (R) within a preset range of the radius of curvature R, the wrap angle θ, and the wall reflectivity ρ. i ,θ i ,ρ i ); where R i θ i and ρ i These are the i-th radius of curvature, the angle of containment, and the wall reflectivity in the parameter set, respectively.

[0052] b. Perform Monte Carlo ray tracing on each of the parameter groups to obtain the illuminance uniformity U. i And the proportion of lateral energy K i ;

[0053] c. Calculate the overall deviation Δ i =w1|U i –U0|+w2|K i –K|;w i w1 and w2 are the error weights for illuminance uniformity and lateral energy proportion, respectively;

[0054] d. Employ a genetic algorithm or gradient descent algorithm, simultaneously adjusting R, θ, and ρ to minimize Δ. i ;

[0055] e. When Δ i If the value is less than or equal to ε or the number of iterations is greater than or equal to N, output the optimal parameters (R*, θ*, ρ*); otherwise, return to step b. Here, N is the maximum number of iterations, and R*, θ*, and ρ* are the radius of curvature, wrap angle, and wall reflectivity of the optimal preparation parameters, respectively.

[0056] In a preferred embodiment of the invention, during the multi-objective optimization stage, the ranges for the radius of curvature, wrap angle, and wall reflectivity are first set according to design requirements, and a large number of parameter combinations are randomly generated within these ranges. Each set of parameters represents a feasible geometry and material configuration for the reflective wall. By sampling this initial parameter set in a uniform distribution, the potential structural solution space can be more comprehensively covered, providing diverse starting points for subsequent optimization.

[0057] For each parameter configuration, Monte Carlo ray tracing simulation is performed using 3D optical simulation software. The software automatically calculates the illuminance uniformity and lateral energy ratio under the current configuration. This process can realistically reflect the influence of different radii of curvature, wrap angles, and material reflection characteristics on the final light field distribution. The system scores the simulation output results for each parameter set, determining the comprehensive deviation of the distance-to-target uniformity and energy ratio under that parameter set, to measure its quality.

[0058] Finally, by introducing multi-objective intelligent optimization algorithms such as genetic algorithms or gradient descent, the parameter combination is automatically adjusted to minimize the target deviation. After multiple iterations of the model, if the overall deviation is below the preset allowable range or the set maximum number of iterations is reached, the system outputs the optimal set of parameters for radius of curvature, wrap angle, and wall reflectivity. The optimization process is fully automated, which can significantly improve design efficiency and ensure that the optical performance of the final product meets actual requirements.

[0059] Preferably, when using a genetic algorithm, the crossover probability is 0.7–0.9, the mutation probability is 0.01–0.1, and the best 10% of individuals are retained at the end of each generation for elite retention.

[0060] Specifically, when using a genetic algorithm for multi-parameter optimization, the initially generated parameter combinations are first encoded and sorted according to a preset comprehensive deviation score. During each generation of evolution, selection, crossover, and mutation operations are performed, prioritizing the retention of individuals with lower comprehensive deviations. The crossover operation probability is preferably 70% to 90% to increase the diversity of parameter recombination; the mutation operation probability is preferably 1% to 10% to explore small changes near the global optimum. At the end of each generation, elite retention is performed on the parameter set, directly passing the top 10% of performers to the next generation to prevent excellent solutions from being destroyed by random operations, thus ensuring the convergence and stability of the optimization results.

[0061] Preferably, when using the gradient descent algorithm, the learning rate ηk used in the k-th iteration decreases according to the formula ηk=η0÷(1+k / K), where η0 is the preset initial learning rate and K is the decay constant.

[0062] Optionally, when using the gradient descent algorithm, the learning rate is adjusted according to a decreasing step size principle for each parameter update. That is, the learning rate used in the k-th iteration gradually decreases as the number of iterations increases. This method presets an initial learning rate and a decay constant, and automatically calculates the applicable learning rate after each iteration. This results in a wider search range in the early stages and a smaller step size during convergence, avoiding getting stuck in local oscillations. This decreasing learning rate strategy helps improve the accuracy of parameter optimization and the overall convergence speed, ensuring that the optimal parameter configuration with balanced performance and excellent results is obtained.

[0063] Preferably, such as Figure 3 As shown, it also includes:

[0064] An array of light intensity sensors is deployed on the LED modules of the final reflective wall to measure the measured uniformity U. real ;

[0065] Judgment Formula | U real If -U0|>ε is true, then set U real Feedback is sent to step b for re-optimization until the uniformity requirement is met.

[0066] Specifically, after the final reflective wall structure is installed and assembled with the LED modules, a light intensity sensor array is uniformly deployed throughout the entire display area. Through real-time data acquisition, the actual light intensity distribution at each detection point is obtained, and the global measured illuminance uniformity is then statistically calculated. This sensor array arrangement comprehensively covers key areas, ensuring the representativeness and accuracy of the measured data, and providing reliable practical feedback for subsequent optimization processes.

[0067] After obtaining the measured uniformity, this embodiment automatically compares and analyzes it with the design target uniformity. If the actual uniformity is lower than the allowable range required by the design, that is, the prepared structure fails to achieve the expected performance, the collected measured data will be used as new feedback input and returned to the data processing stage of the parameter optimization step to revise the optimization process from scratch. Through multiple rounds of experiments and feedback loops, the structural parameters of the reflector are continuously adjusted until the measured uniformity reaches the target standard, achieving integrated quality assurance of process and design.

[0068] Preferably, the light intensity sensor array is a 4×4 grid.

[0069] Furthermore, after completing the optimal parameter design and assembling the final reflective wall structure, the lateral emission angle is effectively controlled by rationally matching the position and shape of the LED light-emitting chips with the reflective wall. The final reflective wall adopts a curvature and wrap angle design optimized by multiple objectives, which can effectively guide the light emitted by the LEDs to the required spatial area, making the lateral illumination range more uniform and controllable, thereby significantly improving the edge light field distribution of the display module and meeting the consistency requirements of a wide viewing angle.

[0070] Furthermore, to verify the effectiveness of light angle and uniformity control, a four-by-four light intensity sensor array was deployed on the surface of the LED matrix module, forming a detection grid covering the entire area. Each sensing point can record the light intensity value at its corresponding location in real time. Through statistical analysis of the array data, the guiding effect of the reflector wall on the lateral emission of LEDs can be accurately evaluated. If deviations in local light intensity or emission angle are found, relevant parameters can be further adjusted based on the information reflected by the array, continuously optimizing the module's emission performance and ensuring that the expected lateral lighting effect is achieved in practical applications.

[0071] The beneficial effects of this invention are as follows:

[0072] (1) This invention replaces the traditional planar L-shaped reflective wall with a precisely designed arc-shaped or polygonal reflective wall, and by optimizing the radius of curvature and corner angles, it achieves fine control over the lateral light emission direction of the LEDs, effectively compensating for the weak light areas at the four corners of the matrix. Through simulation or actual measurement, the uniformity of light intensity of the matrix pixels can be greatly improved, effectively avoiding visual defects caused by dark areas on the display screen.

[0073] (2) Since the arc (or polygon) reflective wall enhances the control of light, the LED light modules can achieve a larger spacing without producing dark areas in the four corners, reducing the overall number of LEDs and bracket materials required, effectively saving production costs and improving the economic efficiency of display devices.

[0074] (3) According to different light distribution targets, the present invention can improve the outer diffusion range by selecting a convex arc-shaped reflector wall or enhance the light intensity concentration by selecting a concave arc-shaped reflector wall, and supports multi-target parameter optimization to meet the multiple requirements for light pattern, uniformity and brightness in different occasions.

[0075] (4) This invention improves LED light extraction efficiency and reduces lateral energy loss through precise light path guidance, which can further reduce power consumption and help improve the overall energy efficiency of display devices and support the application requirements of thinner and lighter, more energy-efficient devices. At the same time, structural optimization simplifies the installation and adjustment process and improves the overall system reliability and consistency.

[0076] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0077] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for controlling the side-emitting angle of an LED based on an arc-shaped reflecting wall, characterized in that, The method comprises: acquiring a target illuminance uniformity U0, a module spacing, an allowable deviation ε, and a lateral energy proportion target K of a light module matrix; based on the module spacing, establishing a variable model of a preset structure reflecting wall with a curvature radius R, an included angle θ, and a wall reflectivity ρ as parameters in a three-dimensional optical simulation software; the preset structure is arc-shaped; based on the target illuminance uniformity U0, the allowable deviation ε, and the lateral energy proportion target K, using a multi-objective optimization algorithm to optimize the curvature radius R, the included angle θ, and the wall reflectivity ρ, to obtain optimal preparation parameters; based on the optimal preparation parameters, preparing a final reflecting wall of the preset structure through injection molding processing; using the final reflecting wall to control an LED lateral light emitting angle; based on the target illuminance uniformity U0, the allowable deviation ε, and the lateral energy proportion target K, using a multi-objective optimization algorithm to optimize the curvature radius R, the included angle θ, and the wall reflectivity ρ, to obtain optimal preparation parameters, comprising: a. Randomly generate several parameter sets (R) within a preset range of the radius of curvature R, the wrap angle θ, and the wall reflectivity ρ. i ,θ i ,ρi); where R i θ i ρi and ρi are the i-th radius of curvature, the angle of containment, and the wall reflectivity in the parameter set, respectively; b. performing Monte Carlo ray tracing for each of the parameter sets to obtain an illumination uniformity U i and a lateral energy fraction K i ; c. Calculate the comprehensive deviation Δ i = w1 |U i – U0 | + w2 |K i – K |; w1 and w2 are the illumination uniformity error weight and the lateral energy proportion error weight, respectively; d. Use genetic algorithm or gradient descent algorithm to adjust R, Q, p simultaneously to minimize A i ; e. When Δ i ≤ε or the iteration number ≥N, output the optimal parameters (R*, θ*, ρ*), otherwise return to step b; wherein, N is the maximum iteration number, R*, θ* and ρ* are the curvature radius, wrap angle and wall reflectivity of the optimal preparation parameters, respectively.

2. The arc-shaped reflecting wall based LED side-emitting angle control method according to claim 1, wherein, the value range of the curvature radius R is 0.5 mm-3 mm; the value range of the included angle θ is 30°-150°.

3. The arc-shaped reflecting wall based LED side-emitting angle control method according to claim 1, wherein, The value range of the wall reflectivity ρ is 0.85-0.

99.

4. The arc-shaped reflecting wall based LED side-emitting angle control method according to claim 1, wherein, When a genetic algorithm is used, the crossover probability is 0.7-0.9, the mutation probability is 0.01-0.1, and the best 10% individuals are reserved for elite reservation at the end of each generation.

5. The arc-shaped reflecting wall based LED side-emitting angle control method according to claim 1, wherein, Further comprising An array of light intensity sensors is arranged on the LED modules of which the final reflecting wall is assembled to measure the measured uniformity U real ; |U real whether U0|>ε is true, if so, U real feedback to step b to re-optimize until the uniformity requirement is met.

6. The arcuate reflector wall based LED side-emitting angular control method according to claim 5, wherein, the light intensity sensor array is a 4×4 grid of points.

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