A sun tracking method and device for a distributed light-avoiding photosensitive sensor

Abstract

This invention relates to a solar tracking method and apparatus using distributed light-shielding photosensitive sensors. The solar tracking method includes: dividing a device plate into multiple regions corresponding to the sun's azimuth; arranging photosensitive sensors on each region on the side of the device plate facing away from the sun, with the photosensitive surfaces of each photosensitive sensor being coplanar and equally spaced; monitoring the light intensity values ​​detected by each photosensitive sensor in real time, and determining the maximum and minimum values ​​among the light intensity values; setting a strong light threshold; when the minimum light intensity value is not less than the strong light threshold, determining the sun's azimuth based on the region where the photosensitive sensor corresponding to the maximum value is located; when the minimum light intensity value is less than the strong light threshold, performing light intensity gradient surface fitting based on the positions of each photosensitive sensor and the detected light intensity values, and determining the sun's azimuth based on the light intensity gradient surface; achieving precise solar tracking with coarse-to-fine hierarchical classification, time-division collaborative operation, and lightweight algorithm.

Description

Technical Field

[0001] This invention relates to the field of solar energy acquisition direction control technology, and particularly to a solar tracking method and apparatus using a distributed light-avoiding photosensitive sensor. Background Technology

[0002] Solar energy, as a clean and renewable energy source, is widely used in fields such as photovoltaic power generation and solar thermal utilization. The photovoltaic light-collecting module, based on this biomimetic principle, moves in real time to follow the sun's position like a sunflower and keeps the light perpendicular to the ground. This is the core means to improve the efficiency of solar energy reception and conversion, and has important engineering value for improving the efficiency of new energy utilization.

[0003] Existing technologies offer several methods for coarse-to-precision differential tracking of the sun. One method uses the sun's trajectory for coarse tracking and a four-quadrant photodetector to measure the solar spot for fine tracking. Another method uses a large field-of-view fisheye imaging system to acquire fisheye images and calculate the sun's azimuth angle; fine tracking is then performed based on the solar spot obtained from the image using an imaging tube. Yet another method calculates the solar altitude and azimuth angles of the photovoltaic array and sets different calculation intervals for both coarse and fine tracking.

[0004] Existing technologies generally have complex structural designs, requiring the integration of light tubes, cross-shaped light-shielding plates, and internal and external dual-set photosensitive components, making assembly and calibration difficult. Their coarse and fine tracking logic is simplistic, relying solely on the dual-set components to determine orientation, lacking a unified algorithm for modeling light intensity gradient surfaces and solving extreme values, resulting in insufficient ability to correct minor deviations. Tracking range is limited, with tracking accuracy strongly correlated with light tube length; longer light tubes improve accuracy but reduce the tracking range, while shorter light tubes expand the range but reduce accuracy. Component and manufacturing costs are high, hindering the large-scale application of small- to medium-sized, low-cost photovoltaic tracking systems. Other technologies require the acquisition of multi-point discrete data from the light spot edge, performing complex ellipse fitting and quadratic form calculations. These algorithms are cumbersome and computationally intensive, placing high demands on the controller's computing power and storage, making real-time operation difficult with ordinary microcontrollers. The hardware structure is complex, requiring containers with light-transmitting holes and color-changing convex lenses, making assembly and calibration difficult. The high cost also hinders large-scale adoption in low-cost scenarios.

[0005] Existing technologies using conventional photosensitive devices lack natural light-shielding and anti-interference characteristics and are mostly installed on the light-receiving surface, making them susceptible to interference from ambient diffuse reflection stray light, leading to distortion in light intensity acquisition. Therefore, it is necessary to forcibly shield stray light through physical light-shielding structures. At the same time, dual sets of components are used to perform coarse positioning and fine calibration functions respectively. Thus, redundant physical light-shielding structures such as light tubes and cross light-shielding plates must be set up. Moreover, dual sets of photosensitive components, both internal and external, are commonly used to complete the coarse and fine-level adjustments. The core reason is that this not only directly increases the number of photosensitive components used, driving up hardware costs, but also increases the complexity of algorithm design due to the signal comparison and coordinated control of dual sets of components. Furthermore, the size of the physical light-shielding structure also limits the tracking range, creating a problem of mutual constraint between tracking accuracy and range. Summary of the Invention

[0006] This invention addresses the technical problems existing in the prior art by providing a solar tracking method and apparatus using a distributed light-shielding photosensitive sensor, achieving precise solar tracking with coarse-to-fine classification, time-division coordination, and lightweight algorithms. According to a first aspect of the present invention, a solar tracking method using a distributed light-avoiding photosensor is provided, comprising: Step 1: Divide the device plate into multiple regions corresponding to the sun's orientation. Arrange photosensitive sensors on each region on the side of the device plate facing away from the sun. The photosensitive surfaces of each photosensitive sensor are coplanar and equally spaced. Step 2: Monitor the light intensity values ​​detected by each of the photosensitive sensors in real time, and determine the maximum and minimum values ​​among the various light intensity values; Step 3: Set a strong light threshold; when the minimum light intensity value is not less than the strong light threshold, determine the sun's azimuth based on the area of ​​the photosensitive sensor corresponding to the maximum value; when the minimum light intensity value is less than the strong light threshold, perform light intensity gradient surface fitting based on the position of each photosensitive sensor and the detected light intensity value, and determine the sun's azimuth based on the light intensity gradient surface. Based on the above technical solution, the present invention can also be improved as follows.

[0007] Optionally, the process of constructing the light intensity gradient surface equation in step 3 includes: With the center of the back of the device plate as the origin, a coordinate system with a horizontal X-axis and a vertical Y-axis is established, and the corresponding fixed coordinates of each photosensitive sensor in the coordinate system are determined. Using the fixed coordinates of the photosensitive sensor as the independent variable and the effective light intensity value as the dependent variable, the two-dimensional quadratic equation of the light intensity gradient surface is constructed as follows: ; in, Represents the fixed coordinates of each of the aforementioned photosensitive sensors; The coefficients to be solved are denoted as .

[0008] Optionally, the process of calculating the equation of the light intensity gradient surface in step 3 is as follows: Step 301: Determine the fixed coordinates of each photosensitive sensor and the effective light intensity value collected: ,in, Let represent the fixed coordinates of any i-th photosensitive sensor. This represents the effective light intensity value collected by any i-th photosensitive sensor; Step 302, each Substituting the equation of the light intensity gradient surface into the equation of the overdetermined linear equation system MA=B, we can obtain matrix A by solving the equation system. Where, matrix M is composed of Composed of 1; Matrix A represents the coefficients to be fitted. ; Matrix B is N is the number of photosensitive sensors.

[0009] Optionally, after determining the coefficients of the light intensity gradient surface equation, the method further includes: Step 303: Calculate the partial derivatives of the fitted light intensity gradient surface, set the partial derivatives to 0, and solve for the coordinates of the extreme points. for: Step 304: Determine whether an acquisition anomaly has occurred based on whether the coordinates of the extreme point are within the area enclosed by each sensor. If so, re-execute steps 301-302.

[0010] Optionally, after obtaining the coordinates of the extreme point, the solution further includes: Step 305: If no acquisition anomaly has occurred, perform an angle transformation on the coordinates of the extreme point to obtain the horizontal rotation angle. and vertical pitch angle : , ;in, The vertical distance from the sensor to the center of rotation of the device board; Step 306, based on the horizontal rotation angle and vertical pitch angle The position of the device plate is adjusted.

[0011] According to a second aspect of the present invention, a solar tracking device with a distributed light-shielding photosensitive sensor is provided, comprising: a device board, a photosensitive sensor, a photovoltaic panel, a drive motor, a rotating connecting platform, and a support column; The photovoltaic panel is installed on the sun-facing side of the device plate, and the middle of the side of the device plate facing away from the sun is connected to the drive motor via a rotating connecting platform. The drive motor is installed on the support column.

[0012] Optionally, the solar tracking device further includes: a microcontroller; The drive motors include a horizontal drive motor and a pitch drive motor, which operate based on control commands from the microcontroller.

[0013] Optionally, the device panel is circular, and the number of photosensitive sensors is 6. The device panel is divided into 6 60° sector areas corresponding to the sun's azimuth, and the 6 photosensitive sensors are symmetrically arranged on the back of the photovoltaic panel with adjacent angles of 60° and equal distances from the center of the device panel.

[0014] Optionally, the device plate is annular, and the number of photosensitive sensors is four. A coordinate system with the geometric center of the device plate as the origin is established, comprising a horizontal X-axis and a vertical Y-axis. The four photosensitive sensors are respectively installed on the device plate at positions equidistant from the origin in the positive X-axis direction, negative X-axis direction, positive Y-axis direction, and negative Y-axis direction of the coordinate system. This invention provides a solar tracking method and apparatus using a distributed light-shielding photosensitive sensor. The light-shielding photosensitive sensor is installed on the back of a photovoltaic panel, eliminating the need for redundant light-shielding structures such as light tubes or light shields. It utilizes a single hardware unit composed of low-cost, general-purpose GL5516 photoresistors, combined with a pure algorithm logic for coarse and fine calibration. This single hardware unit can perform both coarse tracking and fine calibration functions, fundamentally reducing the number of photosensitive components and lowering hardware costs. Furthermore, the algorithm does not require adaptation to the complex logic of two sets of devices; it can complete calculations using only the light intensity data from the single hardware unit, significantly simplifying algorithm design. It also overcomes the limitations of physical light-shielding structures on the tracking range, effectively solving the technical problems of existing solar tracking technologies, such as complex structures, insufficient coarse tracking accuracy, cumbersome fine calibration algorithms, mutual constraints between tracking range and accuracy, and high hardware costs. This significantly improves anti-interference capabilities and tracking accuracy, thereby avoiding problems such as large solar tracking deviations, inaccurate calibration, and insufficient utilization of sunlight caused by light interference, algorithm complexity, and structural limitations. Attached Figure Description

[0015] Figure 1 A flowchart of a distributed light-avoiding photosensitive sensor for solar tracking is provided by the present invention; Figure 2 This is a schematic diagram of the overall structure of an embodiment of a solar tracking device using a distributed light-avoiding photosensitive sensor provided by the present invention; Figure 3 A side view of one embodiment of a solar tracking device using a distributed light-avoiding photosensitive sensor provided by this invention; Figure 4 This is a schematic diagram of the overall structure of another embodiment of a solar tracking device using a distributed light-avoiding photosensitive sensor provided by the present invention. Figure 5 This is a side view of another embodiment of a solar tracking device for a distributed light-avoiding photosensitive sensor provided by an embodiment of the present invention.

[0016] In the diagram, 1-ring device plate; 2-eastward photosensitive sensor; 3-northeastward photosensitive sensor; 4-northwestward photosensitive sensor; 5-westward photosensitive sensor; 6-southwestward photosensitive sensor; 7-southeastward photosensitive sensor; 8-microcontroller; 9-horizontal drive motor; 10-pitch drive motor; 11-photovoltaic panel; 12-rotating connecting platform; 13-support column; 14-eastward photosensitive sensor; 15-southward photosensitive sensor; 16-westward photosensitive sensor; 17-northward photosensitive sensor; 18-motor drive control module. Detailed Implementation

[0017] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0018] Figure 1 A flowchart of a solar tracking method using a distributed light-shielding photosensitive sensor provided by this invention is shown below. Figure 1 As shown, the method includes: Step 1: Divide the device panel into multiple regions corresponding to the sun's orientation. On each region of the side of the device panel facing away from the sun, a photosensitive sensor is arranged. The photosensitive surfaces of each photosensitive sensor are coplanar and equally spaced.

[0019] Step 2: Monitor the light intensity values ​​detected by each photosensitive sensor in real time, and determine the maximum and minimum values ​​among the various light intensity values.

[0020] Step 3: Set a strong light threshold. When the minimum light intensity value is not less than the strong light threshold, determine the sun's azimuth based on the area where the photosensitive sensor corresponding to the maximum value is located. When the minimum light intensity value is less than the strong light threshold, perform light intensity gradient surface fitting based on the position of each photosensitive sensor and the detected light intensity value, and determine the sun's azimuth based on the light intensity gradient surface.

[0021] This invention provides a solar tracking method for a distributed, light-shielding photosensitive sensor. Using a strong light threshold as the graded trigger boundary, it achieves seamless integration of coarse and fine tracking, with no conflict during the entire time-sharing process. When the light intensity value is greater than or equal to the strong light threshold: only coarse tracking is performed, locking onto the sensor with the highest light intensity value, directly determining that the sun is located in the azimuth region corresponding to that sensor. When the light intensity values ​​of all sensors are less than the strong light threshold: coarse tracking is completed, all sensors are removed from direct sunlight and enter a low-light state, coarse tracking ends and fine tracking is automatically triggered, completing a large-scale rapid repositioning, and automatically switching to fine tracking for micro-calibration. After fine tracking is completed, the system returns to real-time monitoring of coarse tracking, forming a closed-loop tracking logic. Example 1

[0022] Embodiment 1 provided by this invention is an embodiment of a solar tracking method using a distributed light-avoiding photosensor provided by this invention, combined with... Figure 1It can be seen that embodiments of this solar tracking method include: Step 1: Divide the device panel into multiple regions corresponding to the sun's orientation. On each region of the side of the device panel facing away from the sun, a photosensitive sensor is arranged. The photosensitive surfaces of each photosensitive sensor are coplanar and equally spaced.

[0023] Step 2: Monitor the light intensity values ​​detected by each photosensitive sensor in real time, and determine the maximum and minimum values ​​among the various light intensity values.

[0024] Step 3: Set a strong light threshold. When the minimum light intensity value is not less than the strong light threshold, determine the sun's azimuth based on the area where the photosensitive sensor corresponding to the maximum value is located. When the minimum light intensity value is less than the strong light threshold, perform light intensity gradient surface fitting based on the position of each photosensitive sensor and the detected light intensity value, and determine the sun's azimuth based on the light intensity gradient surface.

[0025] In one possible embodiment, the process of constructing the light intensity gradient surface equation in step 3 includes: With the center of the back of the device board as the origin, establish a coordinate system with a horizontal X-axis and a vertical Y-axis, and determine the corresponding fixed coordinates of each photosensitive sensor in the coordinate system.

[0026] Using the fixed coordinates of the photosensitive sensor as the independent variable and the effective light intensity as the dependent variable, the two-dimensional quadratic light intensity gradient surface equation is constructed as follows: .

[0027] in, Represents the fixed coordinates of each photosensitive sensor; The coefficients to be solved are denoted as .

[0028] In one possible implementation, the surface fitting coefficients are solved using the least squares method, and Gaussian elimination is used for fast computation. The process of calculating the light intensity gradient surface equation in step 3 is as follows: Step 301: Determine the fixed coordinates of each photosensitive sensor and the effective light intensity value collected: ,in, Let represent the fixed coordinates of any i-th photosensitive sensor. Let represent the effective light intensity value collected by any i-th photosensitive sensor.

[0029] Step 302, each Substituting the equation of the light intensity gradient surface, we construct the overdetermined linear equation system MA=B, and solve it to obtain matrix A.

[0030] Where, matrix M is composed of It consists of 1 and 2.

[0031] Matrix A represents the coefficients to be fitted. .

[0032] Matrix B is N is the number of photosensitive sensors.

[0033] In one possible embodiment, after determining the coefficients of the light intensity gradient surface equation, the method further includes: Step 303: Calculate the partial derivatives of the fitted light intensity gradient surface, set the partial derivatives to 0, and solve for the coordinates of the extreme points. for: Step 304: Determine whether an acquisition anomaly has occurred based on whether the coordinates of the extreme point are within the enclosed area of ​​each sensor. If so, re-execute steps 301-302.

[0034] In one possible implementation, after obtaining the coordinates of the extreme points, the method further includes: Step 305: If no acquisition anomaly has occurred, perform an angle transformation on the extreme point coordinates to obtain the horizontal rotation angle. and vertical pitch angle : , ;in, This is the vertical distance from the sensor to the rotation center of the device board.

[0035] Step 306, based on the horizontal rotation angle and vertical pitch angle Adjust the position of the device plate. Example 2

[0036] Embodiment 2 provided by the present invention is an embodiment of a solar tracking device based on a distributed light-avoiding photosensor provided by the present invention. Figure 2 and Figure 3 These are a schematic diagram and a side view of an embodiment of a solar tracking device using a distributed light-shielding photosensitive sensor provided by the present invention, combined with... Figures 1-3 It is known that the embodiment of the solar tracking device includes: a ring-shaped device plate 1, 6 photosensitive sensors, a photovoltaic panel 11, a drive motor, a rotating connecting platform 12, a support column 13, and a microcontroller 8.

[0037] The annular device plate 1 serves as the sensor mounting carrier. With the geometric center as the origin O(0,0), the annular device plate 1 is divided into six 60° sector areas corresponding to the sun's azimuth. These sectors are used to fix six azimuth-shielded photosensitive sensors, ensuring a symmetrical and uniform sensor layout.

[0038] Six photosensitive sensors are symmetrically arranged on the back of the photovoltaic panel with adjacent sensors at 60° angles and equidistant from the center of the annular device plate 1. Coarse tracking is achieved through six-directional strong light discrimination and regional positioning. The core principle is to divide the sun's azimuth into six 60° sector areas, determine the region where the sun is located based on the maximum light intensity, and drive the photovoltaic panel to quickly turn to achieve strong light avoidance coarse positioning.

[0039] Specifically, the six photosensitive sensors include: East-facing photosensitive sensor 2, Northeast-facing photosensitive sensor 3, Northwest-facing photosensitive sensor 4, West-facing photosensitive sensor 5, Southwest-facing photosensitive sensor 6, and Southeast-facing photosensitive sensor 7. These six photosensitive sensors (2-7) are arranged symmetrically in a regular hexagon, with adjacent angles of 60° and all distances from the origin equal to R. The photosensitive surfaces are coplanar with no height difference, completely eliminating hardware installation errors and unifying the light intensity acquisition benchmark.

[0040] The eastward photosensitive sensor 2 is installed on the positive X-axis direction of the circular device plate 1, with coordinates (R, 0). It uses a GL5516 photoresistor to collect the light intensity signal from the east side.

[0041] The northeast-oriented photosensitive sensor 3 is installed on the circular device plate 1 at a 60° offset from the positive Y-axis direction along the positive X-axis, with coordinates (R / 2, (R×1.732) / 2). It uses a GL5516 photoresistor to collect the light intensity signal from the northeast side.

[0042] The northwest-oriented photosensitive sensor 4 is installed on the circular device plate 1 at a 60° angle from the positive Y-axis in the negative X-axis direction, with coordinates (-R / 2, (R×1.732) / 2). It uses a GL5516 photoresistor to collect the light intensity signal from the northwest side.

[0043] The westward photosensitive sensor 5 is installed on the negative X-axis direction of the circular device plate 1, with coordinates (-R, 0). It uses a GL5516 photoresistor to collect the light intensity signal from the west.

[0044] The southwest-facing photosensitive sensor 6 is installed on the circular device plate 1 at a 60° angle to the negative Y-axis direction of the X-axis, with coordinates (-R / 2, -(R×1.732) / 2). It uses a GL5516 photoresistor to collect the light intensity signal from the southwest side.

[0045] The southeast-facing photosensitive sensor 7 is installed on the circular device plate 1 at a 60° offset from the positive X-axis direction and negative Y-axis direction, with coordinates (R / 2, -(R×1.732) / 2). It uses a GL5516 photoresistor to collect the light intensity signal from the southeast side.

[0046] The photovoltaic panel 11 is installed on the sun-facing side of the device panel 1. The middle of the side of the device panel 1 facing away from the sun is connected to the drive motor via a rotating connecting platform 12. The drive motor is installed on the support column 13.

[0047] The photovoltaic panel 11 is located on the front of the circular device plate 1, which is fixed to the center of the back of the photovoltaic panel and rotates synchronously with it to achieve efficient sunlight reception. The rotating connecting platform 12 connects the microcontroller and the dual-axis motor, converting control signals into motor drive signals. The support column 13 supports all components and provides a fixed support function.

[0048] The drive motors include a horizontal drive motor 9 and a pitch drive motor 10. The horizontal drive motor 9 and the pitch drive motor 10 operate according to the control commands of the microcontroller 8 and rotate rapidly toward the direction of strong light until the light intensity of the 6 sensors is lower than the preset strong light threshold.

[0049] Microcontroller 8 is an Arduino UNO / STM32F103 microcontroller with AD conversion, responsible for light intensity acquisition, algorithm calculation, and motor drive control. It connects the microcontroller control to the dual-axis motor, converting the microcontroller control signals into motor drive voltage signals to ensure stable motor operation. The microcontroller and motor drive module are located above the support column 14. The microcontroller 8 control module completely reuses the coarse tracking hardware, adding only a fine calibration algorithm program, resulting in no additional hardware cost, a minimalist structure, and convenient assembly and calibration.

[0050] The horizontal drive motor 9 is electrically connected to the microcontroller 8 control module, driving the photovoltaic panel to rotate horizontally and completing the coarse and fine adjustment of the sun's position.

[0051] The pitch drive motor 10 is electrically connected to the microcontroller 8 control module to drive the photovoltaic panel to pitch vertically, completing the coarse and fine vertical adjustment of the sun's azimuth.

[0052] After coarse tracking is completed, all six sensors are in low light conditions with only minor orientation deviations. This invention achieves fine calibration through a pure algorithm that combines light intensity gradient surface modeling with extreme point solving.

[0053] The fine calibration process is automatically executed by a microcontroller, with each calibration taking ≤0.5s. The steps are as follows: coarse tracking completed → light intensity acquisition and preprocessing → light intensity gradient surface fitting → extreme point solution → angle conversion and motor fine adjustment → calibration completion verification. After calibration, the light intensity is acquired again. If it reaches the fine calibration threshold, the calibration is considered successful. Otherwise, the fine calibration steps are repeated until the photovoltaic panel is completely and accurately aligned with the sun. Then, it returns to the coarse tracking monitoring state, realizing all-weather cyclic closed-loop solar tracking.

[0054] In one possible embodiment, the execution process of one embodiment provided by the present invention includes: Step 1: Coarse tracking for rapid, large-scale repositioning.

[0055] The microcontroller can collect the analog light intensity from 6 sensors in real time and convert it into digital I (unit: 0~1023, corresponding to 0~5V voltage). The light intensity and the digital quantity are positively correlated (the stronger the light intensity, the larger the digital quantity).

[0056] The microcontroller control module 9 collects the digital light intensity data from 6 sensors in real time, compares and locks the sensor with the maximum light intensity, and determines the general area of ​​the sun's location; it drives the horizontal drive motor 10 and the pitch drive motor 11 to turn quickly until the light intensity of all 6 sensors is lower than the strong light threshold (I<200), all sensors enter the weak light state, coarse tracking is completed and fine tracking is automatically triggered.

[0057] It achieves millisecond-level completion of large-scale solar azimuth repositioning, creating working conditions without direct sunlight for precise tracking.

[0058] Step 2: Light intensity acquisition preprocessing.

[0059] The microcontroller collects 5-10 sets of data from each sensor and averages them to eliminate random noise; that is, if the six sensors have inherent sensitivity deviations (such as some sensors having baseline values ​​in the absence of light), these are eliminated in advance through zero-point calibration: in a completely dark environment, the baseline values ​​of the six sensors are collected. The actual effective light intensity value is This ensures the accuracy of the light intensity value.

[0060] Multiple data acquisitions and averaging: The microcontroller acquires 5-10 sets of digital light intensity data from each of the 6 sensors. Take the average value To eliminate random noise from the sensor, which refers to the irregular, minute fluctuations in the output value when the sensor collects the same stable light intensity, such as the influence of sensor characteristics, circuit interference, and minor environmental changes (e.g., the sensor in Dong collected 5 sets of data: 180, 182, 179, 181, and 180, with the average value...). =180.4).

[0061] Eliminate hardware errors to ensure the absolute accuracy of input data for the precision tracking algorithm.

[0062] Step 3: Fitting the light intensity gradient surface A two-dimensional quadratic light intensity gradient surface is constructed using the sensor's fixed coordinates as the independent variable and the effective light intensity value as the dependent variable. The microcontroller solves for the least squares fitting coefficients using Gaussian elimination.

[0063] The discrete light intensity signal is transformed into a continuous light intensity gradient surface, providing a mathematical model for accurate orientation calculation.

[0064] Extreme point solution and coordinate-angle transformation: Take the partial derivative with respect to the surface and set it to 0, then substitute it into the formula to calculate the coordinates of the minimum point. (Precise sun position); Convert coordinates to horizontal rotation angle Vertical pitch angle .

[0065] Two-dimensional quadratic light intensity gradient surface fitting (coefficients solved by least squares method): The microcontroller solves the quadratic surface using the least squares method. The six coefficients a, b, c, d, e, and f are implemented as follows: Determine the known quantities: the fixed hexagonal coordinates of the 6 sensors (e.g., if R=5cm, then East: (5,0), Northeast: (2.5,4.33), Northwest: (-2.5,4.33), West: (-5,0), Southwest: (-2.5,-4.33), Southeast: (2.5,-4.33)), and the obtained effective light intensity values. , , , , and .

[0066] Constructing a system of equations: combining the equations from the 6 sensors Substituting the equations into the quadric surface formula, we obtain six equations, forming an overdetermined linear system of equations MA=B: Matrix M (6 rows, 6 columns): composed of It consists of 1 and 2.

[0067] Matrix A (6 rows, 1 column): Fitting coefficients .

[0068] Matrix B (6 rows, 1 column): .

[0069] Solving for coefficients: The microcontroller solves the least squares solution of the overdetermined system of equations using Gaussian elimination to obtain six fitting coefficients a, b, c, d, e, and f (Gaussian elimination is a commonly used algorithm for microcontrollers, which involves no complex calculations and is easy to implement).

[0070] Step 4: Solve for the minimum points of the light intensity surface (Precise location coordinates).

[0071] Taking the partial derivative of the fitted quadratic light intensity surface and setting it to 0, then solving for the coordinates of the extreme points is crucial for converting light intensity information into azimuth coordinates. The mathematical derivation and microcontroller implementation are both simple. Find the partial derivative and set it to 0: =2aX+cY+d=0 =2bY+cX+e=0 Solve the system of two linear equations in two variables: Solving the two equations simultaneously, we can obtain the coordinates of the extreme point. The formula is: This formula is derived in advance, and the microcontroller can directly substitute the coefficients for calculation without real-time differentiation, thus improving the calculation speed.

[0072] Extreme point validity determination: Due to the small deviation after coarse tracking, the extreme point... It must be within the area enclosed by the regular hexagon of the 6 sensors ( ∈[-R,R], If the range is outside the range of [-(R×1.732) / 2,(R×1.732) / 2], it is determined to be an abnormal data collection, and step two is executed again.

[0073] Coordinate to Angle Conversion: Assuming the sensor placement distance is L=5cm, the calculation is as follows: =1.2cm, =-0.8cm: This indicates that the photovoltaic panel is currently 1.2cm off to the west horizontally (needs to be adjusted eastward) and 0.8cm off to the south vertically (needs to be adjusted northward).

[0074] =0, =0: This indicates that the photovoltaic panel is precisely facing the sun, and the six sensors are in the weakest light state with complete backlighting, requiring no fine-tuning.

[0075] From "coordinate offset" to "angle fine-tuning": and It is a spatial coordinate offset, not a direct angle value, and needs to be converted to the value you mentioned. (Horizontal rotation angle) and (Vertical pitch angle), the conversion logic is very simple: Horizontal rotation angle : (H is the vertical distance from the sensor to the rotation center of the photovoltaic panel, which is calibrated in advance).

[0076] For example, H=10cm, =1.2cm→ =arctan(1.2 / 10)≈6.84° (rotated eastward by about 6.84°).

[0077] Vertical pitch angle : .

[0078] for example =-0.8cm→ =arctan(-0.8 / 10)≈-4.57° (approximately 4.57° northward elevation).

[0079] microcontroller received and After that, simply drive the motor to rotate at the corresponding angle to make the photovoltaic panel precisely aligned with the sun.

[0080] The light intensity information is converted into the motor's fine-tuning angle, enabling precise correction of minute azimuth deviations.

[0081] Step 5: Motor fine-tuning and closed-loop verification.

[0082] The microcontroller drives the dual-axis motor to rotate the corresponding angle and collects the light intensity again; if the light intensity at the extreme point is ≤ the fine calibration threshold (I≤50), the calibration is complete; otherwise, repeat steps 2-5 until the standard is met.

[0083] Closed-loop calibration ensures tracking accuracy, with a tracking angle error ≤0.5°.

[0084] Step Six: 24 / 7 closed-loop tracking.

[0085] After fine calibration is completed, the system returns to coarse tracking monitoring status and performs fine calibration every 3 seconds. When a significant change in the sun's azimuth causes the light intensity to exceed the threshold, coarse tracking + fine tracking is retried. The entire process is automatic and closed-loop, requiring no manual intervention and adapting to the sun's azimuth movement in real time.

[0086] This invention relies on the biomimetic working logic of six light-shielding photosensitive sensors installed on the back of a photovoltaic panel. It eliminates the need for redundant light-shielding structures such as light tubes or light shields. Using only a single hardware unit consisting of six low-cost, general-purpose GL5516 photoresistors, combined with a pure algorithm logic for coarse and fine calibration, it achieves both coarse tracking and fine calibration functions. This fundamentally reduces the number of photosensitive components used and lowers hardware costs. Furthermore, the algorithm does not require adaptation to the complex coordination logic of two sets of devices; it can complete calculations using only the light intensity data from the single hardware unit, significantly simplifying algorithm design. It also overcomes the limitations of physical light-shielding structures on the tracking range, effectively solving the technical problems of existing solar tracking technologies, such as complex structures, insufficient coarse tracking accuracy, cumbersome fine calibration algorithms, mutual constraints between tracking range and accuracy, and high hardware costs. This results in a significant improvement in anti-interference capability and tracking accuracy, thereby avoiding problems such as large solar tracking deviations, inaccurate calibration, and insufficient utilization of sunlight caused by light interference, algorithm complexity, and structural limitations.

[0087] This invention employs an integrated hardware structure of a circular device board and a regular hexagonal symmetrical photoresistor with a low light-sensing range. Using the geometric center of the device board as the origin, six identical photoresistors are symmetrically arranged on the back of the photovoltaic panel in regular hexagonal shapes with adjacent angles of 60° and equal radii R. The orientation is divided into six directions: east, northeast, northwest, west, southwest, and southeast. The photosensitive surfaces of the sensors are coplanar with no height difference, eliminating hardware installation errors. A microcontroller with AD conversion function serves as the control core, reusing the coarse-tracking light intensity acquisition, AD conversion, and motor drive hardware. Only a fine calibration algorithm program is added, requiring no additional hardware cost.

[0088] This invention provides a solar tracking device using a distributed light-avoiding photosensitive sensor. By mimicking the natural biological characteristic of sunflowers where auxin on the back of the solar panel avoids light, six GL5516 photoresistors are designed as light-avoiding photosensitive sensors and symmetrically arranged on the back of the photovoltaic panel. This type of sensor is named "light-avoiding." While the GL5516 photoresistor itself is a general-purpose photoresistor without active light-avoidance hardware, when installed on the back of the photovoltaic panel, it can achieve "light-avoidance and orientation" through a program algorithm. The photoresistor converts light intensity signals into analog electrical signals. A microcontroller can collect the analog light intensity from the six sensors in real time and convert it into a digital quantity (I, unit: 0~1023, corresponding to 0~5V voltage; the stronger the light intensity, the larger the digital quantity). By comparing the six digital light intensity values, the sensor corresponding to the maximum value is locked, accurately determining the general area of ​​the sun's location, and thus driving the front of the photovoltaic panel to face the sun. This orientation ensures that the sensors on the back of the photovoltaic panel are away from direct sunlight and in a low-light state. This logic of "achieving light avoidance on the back side and light attraction on the light-receiving side through light intensity numerical comparison and program control" is the core basis for the "light-avoidance type" name. It also ensures the accuracy of orientation determination without additional external intervention in light intensity acquisition. Based on this, this invention reuses only six low-cost, general-purpose light-avoidance photosensitive sensors arranged symmetrically in a regular hexagon on the back of the photovoltaic panel. Using a microcontroller with AD conversion function as the control core, it adopts a closed-loop execution logic of coarse tracking followed by fine tracking: first, the orientation of direct sunlight is determined by the six light-avoidance photosensitive sensors installed on the back of the panel, completing the rapid and large-scale coarse positioning of the sun's orientation. Then, the sun's orientation is micro-calibrated through a pure algorithm of light intensity gradient surface modeling, least squares fitting, extreme point solving, and coordinate-angle transformation, thereby driving the photovoltaic panel to accurately align with the sun in real time.

[0089] Employing a 6-directional strong light discrimination coarse tracking method, the sun's azimuth is divided into six 60° sector regions. By locking onto the maximum light intensity sensor, the region where the sun is located is quickly determined, and the drive motor rapidly rotates to achieve strong light avoidance coarse positioning. This key design achieves millisecond-level large-area positioning of the sun's azimuth, requiring no complex mathematical calculations and can be executed quickly by a common microcontroller. It solves the problems of slow response and ambiguous positioning range in existing coarse tracking technologies, balancing tracking speed and large-area positioning capability.

[0090] • Using a preset strong light threshold as a boundary, coarse tracking and fine tracking are seamlessly integrated in a time-sharing manner. When the light intensity is greater than or equal to the threshold, only coarse tracking is performed; when the light intensity is less than the threshold, fine tracking is automatically switched to. The entire process operates in a time-sharing manner without conflict or preemption. This key design constructs a hierarchical closed-loop tracking logic, avoiding mutual interference between coarse and fine tracking. It solves the problems of poor integration between coarse and fine positioning and control disorder caused by synchronous operation in existing technologies, making the tracking process more stable and reliable.

[0091] • A two-dimensional quadratic light intensity gradient surface is constructed based on the fixed coordinates of six sensors. The coefficients are fitted using the least squares method, and the minimum points of the surface are solved using a formula, directly determining the precise orientation of the sun at these minimum points. This key design can complete micro-calibration using only data from six sensors, eliminating the need for collecting multi-point data of the light spot, complex ellipse fitting, and quadratic form calculations. The algorithm is lightweight and computationally minimal, solving the problems of cumbersome precision calibration algorithms, high computing power requirements, and the inability to run on a single microcontroller in real time in existing technologies. The calibration time for a single operation is ≤0.5s.

[0092] Multiple sets of averaging noise reduction and zero-point calibration preprocessing are performed on the light intensity data to accurately convert the coordinates of extreme points into horizontal rotation angle Δα and vertical pitch angle Δβ. After calibration, a closed-loop verification of the light intensity is performed. This key design eliminates random noise and inherent sensitivity errors of the sensor, accurately converts coordinate offsets into motor fine-tuning angles, and ensures that the calibration meets the standards through closed-loop verification. It solves the problems of insufficient tracking accuracy caused by the inability to correct small deviations and the lack of calibration verification in existing technologies, achieving a tracking angle error of ≤0.5°.

[0093] The coarse tracking sensor and hardware circuitry are reused throughout the entire process, with only the fine calibration program logic added, without any additional hardware. This key design maximizes hardware reuse, resulting in a minimalist structure and convenient assembly and calibration. It solves the problems of complex structure, numerous parts, high processing and assembly costs, and difficulty in large-scale deployment of existing technologies, making it perfectly compatible with low-cost small and medium-sized photovoltaic tracking systems.

[0094] It is understood that the solar tracking system of the distributed light-shielding photosensitive sensor provided by the present invention corresponds to the solar tracking method of the distributed light-shielding photosensitive sensor provided in the foregoing embodiments. The relevant technical features of the solar tracking system of the distributed light-shielding photosensitive sensor can be referred to the relevant technical features of the solar tracking method of the distributed light-shielding photosensitive sensor, and will not be repeated here. Example 3

[0095] Embodiment 3 provided by the present invention is another embodiment of the solar tracking device of the distributed light-avoiding photosensitive sensor provided by the present invention. Figure 4 and Figure 5 These are schematic diagrams and side views of another embodiment of a solar tracking device using a distributed light-shielding photosensitive sensor provided in this invention, combined with... Figure 1 , Figure 4 and Figure 5 It is known that the embodiment of the solar tracking device includes: a ring-shaped device plate 1, four photosensitive sensors, a photovoltaic panel 11, a drive motor, a rotating connecting platform 12, a support column 13, and a microcontroller 8.

[0096] The ring-shaped device plate 1 serves as the sensor mounting carrier, with its geometric center as the origin O(0,0). It is used to fix the four-directional light-shielding photosensitive sensor, ensuring a uniform orthogonal and symmetrical layout of the sensor without installation deviation.

[0097] The photovoltaic panel 11 is installed on the sun-facing side of the annular device plate 1. The center of the side of the device plate facing away from the sun is connected to the drive motor via a rotating connecting platform. The drive motor is mounted on a support column. Centered on the center of the photovoltaic panel 11, six sensors are symmetrically distributed in a regular hexagon with adjacent angles of 60°. The orientation and coordinates of each sensor are clearly marked, demonstrating a symmetrical layout structure.

[0098] The photosensitive sensors include: east-facing photosensitive sensor 14, south-facing photosensitive sensor 15, west-facing photosensitive sensor 16, and north-facing photosensitive sensor 17.

[0099] The eastward-facing photosensitive sensor 14 is installed on the positive X-axis direction of the annular device plate 1, with coordinates (R, 0). It uses a GL5516 photoresistor to collect the solar intensity signal on the east side.

[0100] The south-facing photosensitive sensor 15 is installed on the negative Y-axis of the annular device plate 1, with coordinates (0, -R). It uses a GL5516 photoresistor to collect the solar intensity signal on the south side.

[0101] A westward-facing photosensitive sensor 16 is installed on the negative X-axis direction of the annular device plate 1, with coordinates (-R, 0). It uses a GL5516 photoresistor to collect the intensity signal of sunlight on the west side.

[0102] The north-facing photosensitive sensor 17 is installed on the positive Y-axis of the annular device plate 1, with coordinates (0,R). It uses a GL5516 photoresistor to collect the solar intensity signal on the north side.

[0103] Microcontroller 18: An Arduino UNO / STM32F103 microcontroller with AD conversion is installed on the platform above the support column 13. It completes the entire process control of light intensity acquisition, algorithm calculation, and motor drive signal output. It is connected to the motor drive control module 18 and the dual-axis motor, converting the microcontroller control signal into the motor drive voltage signal to ensure stable motor operation.

[0104] The drive motors include a horizontal drive motor 7 and a pitch drive motor 8, which operate based on control commands from a microcontroller.

[0105] The horizontal drive motor 7 is electrically connected to the microcontroller control module 6, driving the photovoltaic panel to rotate horizontally in the east-west direction to complete the coarse and fine adjustment of the sun's position.

[0106] The pitch drive motor 8 is electrically connected to the microcontroller control module 6, driving the photovoltaic panel to pitch along the vertical north-south direction to complete the coarse and fine vertical adjustment of the sun's position.

[0107] Photovoltaic panel 11; located on the front of circular device plate 1, the device plate is fixed at the center of the back of the photovoltaic panel and rotates synchronously with the photovoltaic panel to ensure that the sensor and the photovoltaic panel are completely aligned.

[0108] Rotate the connecting platform 12; connect the microcontroller and the dual-axis motor, and convert the control signal into a motor drive signal.

[0109] Support column 13; used to support all components and provide fixed support.

[0110] The device board is ring-shaped and has four photosensitive sensors. A coordinate system with the geometric center of the device board as the origin is established with the horizontal X-axis and the vertical Y-axis as the origin. The four photosensitive sensors are installed on the device board at positions equidistant from the origin in the positive X-axis direction, negative X-axis direction, positive Y-axis direction, and negative Y-axis direction of the coordinate system.

[0111] This invention mimics the natural biological characteristic of sunflowers, where auxin on the back of the solar panel grows in the dark. Four GL5516 photoresistors are designed as light-shielding photosensitive sensors and orthogonally and symmetrically arranged on the back of the photovoltaic panel. These sensors are named "light-shielding" because their core principle stems from the biomimetic working logic of this invention. While the sensors themselves are general-purpose photoresistors without active light-shielding hardware, when installed on the back of the photovoltaic panel, they can achieve a "light-shielding and positive orientation" biomimetic effect through a program algorithm. The photoresistors convert light intensity signals into analog electrical signals. The microcontroller can collect the analog light intensity from the four sensors in real time and convert it into a digital quantity (I, unit: 0~1023, corresponding to 0~5V voltage; the stronger the light intensity, the larger the digital quantity). By comparing the four digital light intensity values, the sensor corresponding to the maximum value is locked, accurately determining the general area of ​​the sun's location, and then driving the front of the photovoltaic panel to face that direction, thus aligning the solar panel with the back of the panel. The sensors on the back of the photovoltaic panel are located away from direct sunlight and in a low-light state. This logic of "achieving light avoidance on the back side and light attraction on the light-receiving side through light intensity numerical comparison and program control" is the core basis for the name "light-avoiding type". It also ensures the accuracy of orientation determination without additional external intervention in light intensity acquisition. Based on this, this invention reuses only four low-cost general-purpose light-avoiding photosensitive sensors of this type, orthogonally and symmetrically arranged on the back of the photovoltaic panel. With a microcontroller with AD conversion function as the control core, it adopts a closed-loop execution logic of coarse tracking followed by fine tracking: first, the orientation of direct sunlight is determined by the four light-avoiding photosensitive sensors installed on the back of the panel, and the orientation of the sun is quickly and coarsely determined over a large range. Then, the orientation of the sun is finely calibrated by a pure algorithm of light intensity gradient surface modeling, least squares fitting, extreme point solution and coordinate-angle transformation, thereby driving the photovoltaic panel to be accurately aligned with the sun in real time.

[0112] This invention relies on the biomimetic working logic of four light-shielding photosensitive sensors installed on the back of a photovoltaic panel. It eliminates the need for redundant light-shielding structures such as light tubes or light shields. Using only a single hardware unit consisting of four low-cost, general-purpose GL5516 photoresistors, combined with a pure algorithm logic for coarse and fine calibration, it achieves both coarse tracking and fine calibration functions. This fundamentally reduces the number of photosensitive components used and significantly lowers hardware costs. Furthermore, the algorithm does not require adaptation to the complex coordination logic of two sets of devices; it can complete calculations using only the light intensity data from the single hardware unit, significantly simplifying algorithm design. It also overcomes the limitations of physical light-shielding structures on the tracking range, effectively solving the technical problems of existing solar tracking technologies, such as complex structures, insufficient coarse tracking accuracy, cumbersome fine calibration algorithms, mutual constraints between tracking range and accuracy, and high hardware costs. This results in a significant improvement in anti-interference capability and tracking accuracy, thereby avoiding problems such as large solar tracking deviations, inaccurate calibration, and insufficient utilization of sunlight caused by light interference, algorithm complexity, and structural limitations.

[0113] This invention employs an integrated, minimalist hardware structure consisting of a ring-shaped device board and four orthogonally symmetrical light-shielding sensors. Using the geometric center of the device board as the origin, four identical light-shielding photosensitive sensors are arranged orthogonally and symmetrically on the back of the photovoltaic panel, with adjacent sensors at 90° angles and equal radii (R). The sensor photosensitive surfaces are coplanar with no height difference, completely eliminating hardware installation errors and unifying the light intensity acquisition benchmark. A microcontroller with AD conversion function serves as the control core, fully reusing the coarse-tracking light intensity acquisition, AD conversion, and motor drive hardware. Only a fine calibration algorithm program is added, requiring no additional hardware cost. The structure is extremely simple and assembly is convenient.

[0114] This invention achieves coarse tracking through four-directional strong light discrimination and zoning. The core principle is to divide the sun's position into four 90° sector regions: east, south, west, and north. The region where the sun is located is determined by the maximum light intensity, driving the photovoltaic panel to quickly turn and achieve strong light avoidance coarse tracking. The specific steps are as follows: Real-time light intensity acquisition: The microcontroller acquires the digital light intensity values ​​from the four sensors in real time, compares the values ​​of each light intensity value synchronously, and eliminates random interference signals.

[0115] Strong light orientation determination: Locate the single sensor with the highest light intensity value and directly determine that the sun is located in the orthogonal orientation region corresponding to that sensor. The determination logic is clear and there is no ambiguous range.

[0116] Rapid motor drive: Drive the horizontal / tilt motor to rotate rapidly and uniformly towards the direction of strong light until the light intensity of all 4 sensors is lower than the preset strong light threshold, thus escaping the direct sunlight state.

[0117] Coarse tracking completion determination: All sensors have entered a low-light stable state, the orientation deviation has been reduced to a very small range, coarse tracking ends and the fine tracking process is automatically triggered to complete a large-scale rapid return to position.

[0118] This invention uses a preset strong light threshold as the boundary for graded triggering, achieving seamless connection between coarse and fine tracking, and conflict-free time-sharing operation throughout the process, thus avoiding control logic disorder. If the light intensity value is greater than or equal to the strong light threshold, the system will only perform coarse tracking to quickly locate the orthogonal position of the sun and complete the large-scale repositioning.

[0119] All sensor light intensity values ​​are below the strong light threshold: coarse tracking meets the standard, automatically switching to fine tracking mode for precise calibration of minor orientation errors.

[0120] After fine tracking is completed, the system returns to the coarse tracking monitoring status in real time, forming an all-weather closed-loop tracking logic that adapts to the dynamic movement of the sun.

[0121] Implement the logic for connecting coarse and fine tracking, with no time-sharing conflicts.

[0122] After coarse tracking is completed, all four sensors are in low light conditions with only minor orientation deviations. This invention combines the characteristics of a local approximate parabolic surface with a four-directional orthogonal symmetric structure to optimize the light intensity gradient surface model, and achieves fine calibration of the minor errors through pure algorithms. The specific steps are as follows: Coordinate system establishment: A two-dimensional orthogonal coordinate system with the center of the back of the photovoltaic panel as the origin and the horizontal X-axis (east-west direction) and vertical Y-axis (north-south direction) is established. The four sensors correspond to fixed coordinates to provide a unified spatial reference benchmark for algorithm operation.

[0123] Light intensity acquisition preprocessing: Collect 5-10 sets of data from each of the 4 sensors, take the average value to eliminate random noise, and subtract the inherent sensitivity error of the sensors through zero-point calibration in a dark environment to obtain accurate and effective light intensity values, ensuring the reliability of the algorithm input data.

[0124] The fine calibration process is automatically executed by a microcontroller, with each calibration taking ≤0.5s. The standard execution steps are: coarse tracking completed → light intensity acquisition and preprocessing → light intensity gradient surface fitting → extreme point solution → angle conversion and motor fine adjustment → calibration completion verification. After calibration, the light intensity of the four sensors is acquired again. If it reaches the fine calibration threshold, the calibration is considered successful. Otherwise, the fine calibration steps are repeated until the photovoltaic panel is completely and accurately aligned with the sun. Then, it returns to the coarse tracking real-time monitoring state to achieve all-weather cyclic closed-loop solar tracking.

[0125] In one possible embodiment, the execution process of one embodiment provided by the present invention includes: Step 1: Coarse tracking for rapid, large-scale repositioning The microcontroller can collect the analog light intensity from four sensors in real time and convert it into digital I (unit: 0~1023, corresponding to 0~5V voltage). The light intensity and the digital quantity are positively correlated (the stronger the light intensity, the larger the digital quantity).

[0126] The microcontroller control module compares the digital values ​​of the four light intensity signals in real time, locks onto the sensor with the highest value, and determines the sun's corresponding azimuth. It then synchronously drives the horizontal and vertical motors to rapidly rotate towards that azimuth until the light intensity of all four sensors falls below a preset strong light threshold (I<200). All sensors then move out of direct sunlight and enter a stable low-light state, completing coarse tracking and automatically transitioning to fine tracking. This step can achieve a large-scale sun repositioning within milliseconds, reducing azimuth deviation to within a few degrees, laying the foundation for fine tracking.

[0127] It achieves millisecond-level completion of large-scale solar azimuth repositioning, creating working conditions without direct sunlight for precise tracking.

[0128] Step 2: Light Intensity Acquisition Preprocessing The microcontroller collects 5-10 sets of data from each sensor and averages them to eliminate random noise; that is, if the four sensors have inherent sensitivity deviations (such as some sensors having baseline values ​​in the absence of light), these are eliminated in advance through zero-point calibration: in a completely dark environment, the baseline values ​​of the four sensors are collected. The actual effective light intensity value is This ensures the accuracy of the light intensity value.

[0129] Multiple data acquisitions and averaging: The microcontroller acquires 5-10 sets of digital light intensity data from each of the four sensors. Take the average value To eliminate random noise from the sensor, which refers to the irregular, minute fluctuations in the output value when the sensor collects the same stable light intensity, such as the influence of sensor characteristics, circuit interference, and minor environmental changes (e.g., the sensor in Dong collected 5 sets of data: 180, 182, 179, 181, and 180, with the average value...). =180.4).

[0130] This eliminates hardware errors and ensures that the input data for the precision tracking algorithm is absolutely accurate.

[0131] Step 3: Light intensity gradient surface fitting (core simplified algorithm) After coarse tracking is completed, the deviation between the sun and the center of the sensor is minimal, and the local light intensity distribution approximates a standard circular parabola. .

[0132] Based on this characteristic, the first layer of optimization is performed: there is no cross-coupling in the X and Y directions, so the cross-term coefficient c=0; combined with the four-directional orthogonal symmetrical layout, the geometry and photosensitive characteristics in the east-west and north-south directions are completely consistent, so the second layer of optimization is performed: the horizontal and vertical light intensity curvatures are equal, so the curvature coefficient a=b. Finally, a simplified two-dimensional quadratic light intensity gradient surface is constructed: .

[0133] The number of unknowns has been reduced from the traditional 6 terms (a, b, c, d, e, f) to 4 terms (a, d, e, f). The microcontroller substitutes the fixed coordinates and effective light intensity values ​​of the 4 sensors into the equations to construct an overdetermined linear system. The 4 fitting coefficients are then quickly solved using Gaussian elimination, significantly reducing the computational load. This process can be completed instantly by a regular microcontroller.

[0134] Step 4: Solve for the minimum points of the light intensity surface (Precise location coordinates) By taking the partial derivative of the simplified light intensity surface and setting the partial derivative to 0, a simplified formula for calculating the extreme point is derived. This eliminates the need for real-time differentiation; the microcontroller can directly substitute the coefficients to solve the problem. Solving the simultaneous equations yields the precise azimuth coordinates of the sun: Extreme point validity determination: Since the deviation is extremely small after coarse tracking, the precise azimuth coordinates must be within the circular area surrounded by the four-position sensors. If they are outside the range, it is determined that the light intensity acquisition is abnormal, and the system will automatically return to step two to reacquire data to avoid false actions.

[0135] The coordinate offset is then converted into motor rotation angles, specifically the horizontal rotation angle. Vertical pitch angle Where H is the vertical distance from the sensor to the rotation center of the photovoltaic panel, which can be calibrated at the factory in advance. The microcontroller drives the dual-axis motor to complete micro-adjustments based on the calculated angle, achieving precise orientation calibration.

[0136] Step 5: Motor fine-tuning and closed-loop verification After the motor completes the fine adjustment, the microcontroller collects the light intensity of the four sensors again. If the light intensity at the extreme point is ≤ the fine calibration threshold (I≤50), the calibration is considered successful and the photovoltaic panel is completely facing the sun. If it does not meet the standard, steps 2-4 are automatically repeated until the calibration is qualified. The closed-loop verification ensures that the tracking accuracy is stable and meets the standard, and the tracking angle error is ≤0.5°.

[0137] Step Six: 24 / 7 closed-loop tracking.

[0138] After fine calibration is completed, the system automatically returns to the coarse tracking real-time monitoring state and performs a light fine calibration every 3 seconds to ensure continuous accuracy of the orientation. If the sun's orientation moves significantly and causes the light intensity of a certain sensor to exceed the threshold, the entire process of coarse tracking + fine tracking is immediately retried to achieve all-weather, unattended automatic tracking, adapting to the sun's rising and setting and the all-day variation of altitude angle.

[0139] Four-directional orthogonal symmetrical sensor layout: It adopts a four-directional layout with adjacent angles of 90° and equal radii, which replaces the traditional multi-directional redundant layout, completely eliminates installation errors, simplifies the hardware structure, and retains the ability to collect light intensity in all directions. It solves the problem of side light collection failure caused by traditional light-blocking structure, and greatly improves the stability of light intensity collection.

[0140] Four-directional strong light discrimination coarse tracking: The sun's position is divided into four 90° orthogonal sector regions. The sun's position is quickly locked by the maximum light intensity. No complex calculations are required. Ordinary microcontrollers can execute the operation in milliseconds. It balances the speed of positioning over a wide range with the accuracy of position determination, solving the problems of slow response and ambiguous judgment in traditional coarse tracking.

[0141] The dual-layer optimization simplifies the light intensity surface model: based on the local approximate parabolic characteristics after coarse tracking, cross terms are eliminated, and the curvature coefficient is unified by the four-directional orthogonal symmetry characteristics. The number of unknowns in the two-dimensional quadratic surface is reduced from 6 to 4, which greatly reduces the algorithm complexity and increases the computing speed by more than 30%. Ordinary low-end microcontrollers can run it in real time, making it suitable for low-cost scenarios.

[0142] Hierarchical closed-loop time-division tracking logic: The strong light threshold is used as the boundary to achieve seamless switching between coarse and fine tracking. There is no conflict or preemption throughout the process. After fine tracking, a closed-loop verification link is added to eliminate sensor error and calculation deviation. The tracking angle error is ≤0.5°, and the micro-position correction capability far exceeds that of existing technologies.

[0143] Low-cost design with full hardware reuse: The coarse and fine tracking process reuses four sensors and core hardware circuits. Only the algorithm program is added, and there is no additional hardware. The assembly and calibration difficulty is extremely low, and the processing and component costs are greatly reduced. It is perfectly adapted to the large-scale popularization of small and medium-sized distributed photovoltaic tracking systems.

[0144] It is understood that the solar tracking system of the distributed light-shielding photosensitive sensor provided by the present invention corresponds to the solar tracking method of the distributed light-shielding photosensitive sensor provided in the foregoing embodiments. The relevant technical features of the solar tracking system of the distributed light-shielding photosensitive sensor can be referred to the relevant technical features of the solar tracking method of the distributed light-shielding photosensitive sensor, and will not be repeated here.

[0145] This invention provides a solar tracking method and apparatus using a distributed light-shielding photosensitive sensor. The light-shielding photosensitive sensor is installed on the back of a photovoltaic panel, eliminating the need for redundant light-shielding structures such as light tubes or light shields. It utilizes only a single set of hardware composed of low-cost, general-purpose GL5516 photoresistors, combined with a pure algorithm logic for coarse and fine calibration. This single set of hardware can perform both coarse tracking and fine calibration functions, fundamentally reducing the number of photosensitive components used and lowering hardware costs. Furthermore, the algorithm does not require adaptation to the complex logic of two sets of devices; it can complete calculations using only the light intensity data from the single set of hardware, significantly simplifying algorithm design. It also overcomes the limitations of physical light-shielding structures on the tracking range, effectively solving the technical problems of existing solar tracking technologies, such as complex structures, insufficient coarse tracking accuracy, cumbersome fine calibration algorithms, mutual constraints between tracking range and accuracy, and high hardware costs. This significantly improves anti-interference capabilities and tracking accuracy, thereby avoiding problems such as large solar tracking deviations, inaccurate calibration, and insufficient utilization of sunlight caused by light interference, algorithm complexity, and structural limitations.

[0146] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0147] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0149] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0150] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0151] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0152] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A solar tracking method using a distributed light-avoiding photosensor, characterized in that, The solar tracking method includes: Step 1: Divide the device plate into multiple regions corresponding to the sun's orientation. Arrange photosensitive sensors on each region on the side of the device plate facing away from the sun. The photosensitive surfaces of each photosensitive sensor are coplanar and equally spaced. Step 2: Monitor the light intensity values ​​detected by each of the photosensitive sensors in real time, and determine the maximum and minimum values ​​among the various light intensity values; Step 3: Set a strong light threshold; when the minimum value of the light intensity is not less than the strong light threshold, determine the sun's azimuth based on the area where the photosensitive sensor corresponding to the maximum value is located; when the minimum value of the light intensity is less than the strong light threshold, perform light intensity gradient surface fitting based on the position of each photosensitive sensor and the detected light intensity value, and determine the sun's azimuth based on the light intensity gradient surface.

2. The solar tracking method according to claim 1, characterized in that, The process of constructing the light intensity gradient surface equation in step 3 includes: With the center of the back of the device plate as the origin, a coordinate system with a horizontal X-axis and a vertical Y-axis is established, and the corresponding fixed coordinates of each photosensitive sensor in the coordinate system are determined. Using the fixed coordinates of the photosensitive sensor as the independent variable and the effective light intensity value as the dependent variable, the two-dimensional quadratic equation of the light intensity gradient surface is constructed as follows: ； in, The coordinates of each of the aforementioned photosensitive sensors are represented, and I represents the light intensity value; The coefficients to be solved are denoted as .

3. The solar tracking method according to claim 2, characterized in that, The process of calculating the equation of the light intensity gradient surface in step 3 is as follows: Step 301: Determine the fixed coordinates of each photosensitive sensor and the effective light intensity value collected: ,in, Let represent the fixed coordinates of any i-th photosensitive sensor. This represents the effective light intensity value collected by any i-th photosensitive sensor; Step 302, each Substituting the equation of the light intensity gradient surface into the equation of the overdetermined linear equation system MA=B, we can obtain matrix A by solving the equation system. Where, matrix M is composed of Composed of 1; Matrix A represents the coefficients to be fitted. ; Matrix B is N is the number of photosensitive sensors.

4. The solar tracking method according to claim 3, characterized in that, After determining the coefficients of the light intensity gradient surface equation, the process further includes: Step 303: Calculate the partial derivatives of the fitted light intensity gradient surface, set the partial derivatives to 0, and solve for the coordinates of the extreme points. for: Step 304: Determine whether an acquisition anomaly has occurred based on whether the coordinates of the extreme point are within the area enclosed by each sensor. If so, re-execute steps 301-302.

5. The solar tracking method according to claim 1, characterized in that, After obtaining the coordinates of the extreme points, the process also includes: Step 305: If no acquisition anomaly has occurred, perform an angle transformation on the coordinates of the extreme point to obtain the horizontal rotation angle. and vertical pitch angle : , ;in, The vertical distance from the sensor to the center of rotation of the device board; Step 306, based on the horizontal rotation angle and vertical pitch angle The position of the device plate is adjusted.

6. A solar tracking device for a solar tracking method using a distributed light-shielding photosensitive sensor as described in any one of claims 1-5, characterized in that, The solar tracking device includes: a device board, a photosensitive sensor, a photovoltaic panel, a drive motor, a rotating connecting platform, and a support column; The photovoltaic panel is installed on the sun-facing side of the device plate, and the middle of the side of the device plate facing away from the sun is connected to the drive motor via a rotating connecting platform. The drive motor is installed on the support column.

7. The solar tracking device according to claim 6, characterized in that, The solar tracking device also includes: a microcontroller; The drive motors include: a horizontal drive motor and a pitch drive motor. The microcontroller collects multiple sets of sensor values ​​from each of the photosensitive sensors, averages them to eliminate random noise, and eliminates the inherent sensitivity error of the sensors through zero-point calibration to obtain accurate and effective light intensity values. The microcontroller calculates the sun's azimuth based on the accurate and effective light intensity value and then controls the horizontal drive motor and the pitch drive motor to operate.

8. The solar tracking device according to claim 6, characterized in that, The photosensitive sensor is a GL5516 photoresistor.

9. The solar tracking device according to claim 6, characterized in that, The device panel is circular, and there are 6 photosensitive sensors. The device panel is divided into 6 60° sector areas corresponding to the sun's position. The 6 photosensitive sensors are symmetrically arranged on the back of the photovoltaic panel with adjacent angles of 60° and equal distances from the center of the device panel.

10. The solar tracking device according to claim 6, characterized in that, The device plate is ring-shaped, and there are four photosensitive sensors. A coordinate system with the geometric center of the device plate as the origin is established with a horizontal X-axis and a vertical Y-axis. The four photosensitive sensors are respectively installed on the device plate at positions equidistant from the origin in the positive X-axis direction, negative X-axis direction, positive Y-axis direction, and negative Y-axis direction of the coordinate system.

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