Ultra-low power consumption micro-LED visible light intensity adaptive regulation method and system

Abstract

The application relates to the technical field of intelligent control, and discloses a kind of ultra-low power consumption micro-LED visible light intensity self-adaptive regulation and control method and system, the method includes obtaining analog light intensity signal and obtaining ambient light intensity value by smoothing processing;Calculate the light intensity change rate, if it exceeds dynamic threshold, mark the environment state and output the light intensity difference value;According to state matching control parameter, with difference value quantization mapping generates preliminary adjustment instruction, combines basic brightness to calculate target light intensity;Calculate the actual and target deviation after executing the instruction, and obtain the light intensity control signal by iterative correction;If power consumption is over limit, then optimize signal amplitude;Input drive circuit analyzes and synthesizes pulse current, excites pixel to emit light and converges to obtain adjustment data;Calculate visual contrast, if it is lower than threshold, then re-adjust the change rate to realize closed loop refining, improve light intensity regulation accuracy.This method can improve the real-time sensing ability of ambient light.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a method and system for adaptive control of visible light intensity of ultra-low power micro LEDs. Background Technology

[0002] Currently, with the rapid development of new lighting technologies, micro light-emitting diodes (LEDs), as highly efficient and energy-saving light sources, are showing broad application potential in smart displays, wearable devices, and the Internet of Things (IoT). Their light intensity saving performance directly affects the device's battery life and user experience. Especially in dynamic lighting environments, such as when a user moves from indoors to outdoors and the light intensity suddenly increases from hundreds of lux to thousands of lux within seconds, existing technologies struggle to achieve a fast and accurate response, resulting in lag in screen brightness adjustment. This not only causes visual discomfort but also leads to unnecessary energy waste. This challenge highlights the urgent need to balance energy efficiency and visual comfort in complex lighting environments.

[0003] In a current technology, ultra-low power micro-LED visible light intensity control typically relies on fixed-frequency sampling by an ambient light sensor, combined with basic filtering algorithms (such as moving average filtering) to remove noise, and a static threshold comparison to trigger light intensity adjustment. For example, when the ambient light intensity exceeds a preset threshold, such as 500 lux, the system linearly increases the LED drive current to improve brightness. However, this method has significant shortcomings: because it does not incorporate dynamic calculation of the rate of light change and real-time feedback loops, in scenarios with drastic fluctuations in ambient light, such as a rapid increase in light intensity from 300 lux to 8000 lux within 3 seconds, the system cannot promptly identify the sudden change. Calculations show that the overall delay from data acquisition to drive adjustment can reach over 200 milliseconds, far exceeding the instantaneous requirements of light change, resulting in slow adjustment response, a disconnect between light intensity output and the actual environment, and decreased screen readability or excessive power consumption.

[0004] In summary, existing technologies suffer from insufficient real-time ambient light sensing capabilities, making it impossible to achieve precise control within milliseconds and thus failing to meet energy efficiency and stability requirements in dynamic environments. Summary of the Invention

[0005] This invention provides an adaptive control method and system for visible light intensity of ultra-low power micro LEDs to solve the problem of insufficient real-time ambient light sensing capability in existing technologies.

[0006] In a first aspect, to solve the above-mentioned technical problems, the present invention provides a method for adaptive control of visible light intensity of ultra-low power micro LEDs, comprising:

[0007] The simulated light signal is acquired and preprocessed to obtain the ambient light intensity value;

[0008] Based on the ambient light intensity value, calculate the light intensity change rate. If the light intensity change rate exceeds a preset dynamic environmental change threshold, mark the environmental state and output the ambient light intensity difference.

[0009] Based on the environmental state, preset control and adjustment parameters are matched, and the difference in ambient light intensity is quantified and mapped according to the control and adjustment parameters to generate a preliminary light intensity adjustment command and calculate the target light intensity level in combination with the pre-determined basic brightness of the equipment.

[0010] Execute the initial light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain a light intensity control signal;

[0011] If the power consumption corresponding to the light intensity control signal exceeds the preset low power consumption range, the signal amplitude is reduced to obtain an optimized control signal;

[0012] The optimized control signal is input into the driving circuit, and after analysis and synthesis, a pulse driving current is generated to excite the pixel array to generate instantaneous luminous flux. The instantaneous luminous flux is then collected to generate adjusted light intensity data.

[0013] Based on the adjusted light intensity data, the visual contrast value is calculated. If the visual contrast value is lower than the preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy.

[0014] Secondly, the present invention provides an ultra-low power micro-LED visible light intensity adaptive control system, comprising:

[0015] The data acquisition module is used to acquire and preprocess analog light signals to obtain ambient light intensity values;

[0016] The difference calculation module is used to calculate the rate of change of light intensity based on the ambient light intensity value. If the rate of change of light intensity exceeds a preset dynamic environmental change threshold, the environmental state is marked and the ambient light intensity difference is output.

[0017] The instruction generation module is used to match preset control and adjustment parameters according to the environmental state, quantize and map the difference in ambient light intensity according to the control and adjustment parameters, generate a preliminary light intensity adjustment instruction, and calculate the target light intensity level in combination with the predetermined basic brightness of the device.

[0018] The deviation correction module is used to execute the preliminary light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain the light intensity control signal;

[0019] The control optimization module is used to reduce the signal amplitude and obtain an optimized control signal if the power consumption corresponding to the light intensity control signal exceeds a preset low power consumption range.

[0020] The circuit adjustment module is used to input the optimized control signal into the driving circuit, generate a pulse driving current after analysis and synthesis, excite the pixel array to generate instantaneous luminous flux, and gather the instantaneous luminous flux to generate adjusted light intensity data.

[0021] The feedback optimization module is used to calculate the visual contrast value based on the adjusted light intensity data. If the visual contrast value is lower than the preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy.

[0022] Thirdly, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the ultra-low power micro-LED visible light intensity adaptive control method described in any one of the above.

[0023] Fourthly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the ultra-low power micro-LED visible light intensity adaptive control method described in any one of the above.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] (1) The present invention obtains the ambient light intensity value by acquiring the simulated light signal and smoothing it, and then calculates the light intensity change rate and compares it with the preset threshold to quickly identify light change events and output the light intensity difference. This process effectively filters out sensor noise, improves the accuracy and response speed of ambient light perception, provides reliable input for subsequent control, fundamentally enhances the system's real-time perception capability of dynamic illumination, and solves the problem of lagging environmental perception in the prior art.

[0026] (2) Based on the difference between the environmental state and the light intensity, the present invention dynamically matches and adjusts the proportional, integral, and derivative control parameters to generate a preliminary adjustment command and a target light intensity. By iteratively correcting the deviation between the actual and target light intensity, the final light intensity control signal is obtained. This closed-loop control mechanism realizes the adaptive optimization of control parameters and the fine adjustment of output, which significantly improves the adaptability and adjustment stability and convergence speed of the system under different lighting scenarios, and solves the shortcomings of the existing technology of fixed parameters and slow response.

[0027] (3) When the light intensity control signal exceeds the low power consumption range, the present invention compresses and optimizes its amplitude to ensure that the drive signal is always in the high efficiency and energy saving range. This method avoids hardware overload and energy waste while maintaining effective light intensity output, and significantly improves the system's sustainable operation capability under resource-constrained conditions.

[0028] (4) The present invention inputs the optimized control signal into the driving circuit, analyzes and synthesizes it into a driving voltage, and precisely excites the light-emitting unit and gathers the flux by adjusting the pulse current to obtain the adjusted light intensity data; this driving method realizes the rapid and dynamic matching of light intensity with environmental changes, and improves the coordination between light efficiency utilization and overall system response.

[0029] (5) The present invention calculates the visual contrast based on the adjusted light intensity data, and when it is lower than the perception threshold, recalculates the light intensity change rate and adjusts the control signal; this closed-loop refining mechanism based on visual effect can continuously optimize the adjustment accuracy, ensure that the output light intensity always meets the visual comfort requirements, and improve the long-term stability and adaptability of the system in complex environments. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of a method for adaptive control of visible light intensity of ultra-low power micro LEDs according to the first embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of an ultra-low power micro-LED visible light intensity adaptive control system provided in the second embodiment of the present invention. Detailed Implementation

[0032] 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.

[0033] Reference Figure 1 The first embodiment of the present invention provides a method for adaptive control of visible light intensity of ultra-low power micro LEDs, comprising the following steps:

[0034] S11, acquire the simulated light signal and perform preprocessing to obtain the ambient light intensity value;

[0035] S12, calculate the light intensity change rate based on the ambient light intensity value; if the light intensity change rate exceeds the preset dynamic environment change threshold, mark the environment state and output the ambient light intensity difference.

[0036] S13, Match the preset control adjustment parameters according to the environmental state, quantify and map the difference in ambient light intensity according to the control adjustment parameters, generate a preliminary light intensity adjustment command, and calculate the target light intensity level in combination with the predetermined basic brightness of the device.

[0037] S14, execute the preliminary light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain the light intensity control signal;

[0038] S15, if the power consumption corresponding to the light intensity control signal exceeds the preset low power consumption range, reduce the signal amplitude to obtain an optimized control signal;

[0039] S16, the optimized control signal is input into the driving circuit, and after analysis and synthesis, a pulse driving current is generated to excite the pixel array to generate instantaneous luminous flux. The instantaneous luminous flux is then gathered to generate adjusted light intensity data.

[0040] S17. Based on the adjusted light intensity data, calculate the visual contrast value. If the visual contrast value is lower than the preset visual perception threshold, recalculate the light intensity change rate and adjust the control signal to achieve closed-loop refinement of the light intensity adjustment accuracy.

[0041] In step S11, it is necessary to acquire and preprocess the simulated light signal to obtain the ambient light intensity value, including:

[0042] A simulated optical signal is acquired, and the simulated optical signal is discretized to obtain the original discrete optical intensity sequence;

[0043] The original discrete light intensity sequence is subjected to Kalman filtering to obtain a smoothed ambient light intensity value.

[0044] It's important to note that in ambient light sensor applications, acquiring and discretizing analog light signals is a fundamental step in achieving accurate light intensity sensing. The ambient light sensor converts the continuous light intensity signal into an analog electrical signal using a photoelectric conversion device, and then performs discretization sampling at a preset sampling frequency. The set sampling frequency must adhere to the Nyquist sampling theorem, meaning it must be greater than twice the highest frequency component of the light signal to ensure distortion-free signal recovery. Subsequently, an analog-to-digital converter quantizes the analog voltage signal into a digital sequence at this frequency, thus obtaining the original discrete light intensity sequence. The sequence length is determined by the sampling duration, and each sampling point contains a timestamp and a light intensity value.

[0045] Then, when performing Kalman filtering on the original discrete light intensity sequence, a linear state-space model is first established to describe the dynamic law of light intensity change. The prediction step estimates the current prior value based on the state at the previous time step, and the update step calculates the Kalman gain in combination with the actual observation value. The prior value is then weighted and corrected to obtain the posterior state estimate. After iterative execution, a smooth ambient light intensity value sequence is generated. This value serves as the optimal estimate after removing noise interference and is used for subsequent calculation of the light change rate and identification of abrupt ambient light events.

[0046] In step S12, the rate of change of light intensity needs to be calculated based on the ambient light intensity value. If the rate of change of light intensity exceeds a preset dynamic environmental change threshold, the environmental state is marked and the ambient light intensity difference is output, including:

[0047] Based on the ambient light intensity value, calculate the light change rate at the current moment. If the light change rate is greater than the preset dynamic environment change threshold, mark the current environment as a light change state; otherwise, mark it as a light no-change state.

[0048] The difference in light intensity between the start time of the mutation and the current time is calculated to obtain the ambient light intensity difference. The start time of the mutation is the sampling point when the light intensity first exceeds the threshold.

[0049] It should be noted that when calculating the rate of change of light at the current moment based on the smoothed ambient light intensity value, the central difference method is used to process the continuous sampling point data. Specifically, the difference between the smoothed light intensity value at the current moment and the smoothed light intensity value at the previous moment is calculated and then divided by the sampling time interval determined by the system sampling frequency (for example, when the sampling frequency is set to 100Hz, the corresponding sampling time interval is 0.01 seconds). The setting of this time interval is essentially the reciprocal of the sampling frequency. By configuring the sampling frequency, the system response speed and data stability are balanced to obtain the value of the rate of change of light. The calculated absolute value of the rate is compared with a preset dynamic environmental change threshold. This threshold is set based on a combination of measured data statistics, human eye perception characteristics, and system response requirements. In typical indoor-outdoor transition and sudden light switching scenarios, more than 1,000 sets of light intensity change curves were collected and analyzed. The statistics show that the light intensity change rate is mainly concentrated in the range of 2,000 lux per second to 5,000 lux per second. Further, combined with the human eye's perceptible threshold for brightness changes (approximately 2,500-3,000 lux per second) and the response margin required for the system to achieve stable tracking, the threshold was finally calibrated to 3,000 lux per second. This value can cover approximately 85% of actual sudden change scenarios, while effectively filtering out false triggers caused by small fluctuations.

[0050] If the absolute value of the rate exceeds the threshold, the current environment is marked as a sudden change in light by the state machine logic. The state flag is stored using Boolean variables, where "1" indicates a sudden change and "0" indicates no sudden change. A lag mechanism is introduced to the state judgment to avoid misjudgment due to instantaneous fluctuations. The state transition is confirmed only after three consecutive sampling points exceed the threshold.

[0051] When the system determines that there is a sudden change in light intensity, it first records the light intensity value corresponding to the start of the change. This moment is defined as the sampling point where the rate of change in light intensity first exceeds the threshold. Then, it calculates the absolute difference between the current light intensity value and the light intensity value at the start of the change, and takes the absolute value of the difference to obtain the ambient light intensity difference. The difference calculation uses a sliding window optimization method, and the window size is dynamically adjusted according to the sampling frequency. For example, under the condition of 100 samples per second, the window length is set to 5 consecutive sampling points. This can capture the maximum change amplitude while effectively suppressing random noise interference.

[0052] In step S13, preset control adjustment parameters need to be matched according to the environmental state. The ambient light intensity difference is quantized and mapped according to the control adjustment parameters to generate a preliminary light intensity adjustment command. The target light intensity level is then calculated by combining the pre-determined basic brightness of the device. This includes:

[0053] Based on the environmental state, the corresponding proportional gain coefficient, integral time constant and differential gain coefficient are matched, and calculated with the difference in ambient light intensity to generate control variable values;

[0054] The values ​​of the control variables are quantized and mapped to generate preliminary light intensity adjustment instructions;

[0055] Based on the preliminary light intensity adjustment command, the current brightness of the device is calculated to obtain the target light intensity level.

[0056] It should be noted that when matching the corresponding proportional gain coefficient, integral time constant, and derivative gain coefficient according to the environmental state, the system achieves dynamic parameter configuration through a state machine model. The environmental state is divided into two modes: abrupt change and steady state. The abrupt change environmental state corresponds to the light change state, which corresponds to the high response speed parameter set. The proportional gain coefficient is set to 2.5 to quickly amplify the instantaneous deviation, the integral time constant is set to 0.2 seconds to reduce the accumulation of historical errors, and the derivative gain coefficient is set to 0.8 to enhance the system's ability to predict changing trends. The steady state corresponds to the non-abrupt light change state, which corresponds to the high stability parameter set. The derivative gain coefficient is set to 0.8 to avoid overshoot, the integral time constant is set to 1.0 seconds to achieve smooth adjustment, and the proportional gain coefficient is set to 0.3 to suppress noise interference. The specific values ​​of these core control parameters are derived from the system identification experiments and closed-loop tuning.

[0057] The specific determination process is as follows: First, a standard step excitation is applied to the system under open-loop conditions, and its response curve (such as rise time and overshoot) is measured. The critical proportional gain and critical oscillation period are calculated using engineering tuning methods such as Ziegler-Nichols, and used as the initial design values ​​for the proportional and integral parameters. Second, closed-loop tests are conducted under typical illumination jump and steady-state scenarios. Based on the actual output response speed, stability accuracy, and anti-interference capability of the system, the initial parameters are iteratively optimized. For example, the proportional gain is moderately attenuated to suppress overshoot while ensuring speed. The integral time constant is set according to the time constant of the main inertial elements of the system to avoid integral saturation. The differential gain is selected by analyzing the phase lag in the open-loop frequency response, achieving a balance between providing sufficient phase lead (enhancing damping) and not excessively amplifying the high-frequency noise of the sensor.

[0058] All parameters were finally solidified into the parameter mapping table after extensive testing and verification of their robustness in both simulated and real-world environments. The parameter mapping table uses a hash index structure to achieve millisecond-level matching, directly locating parameter groups by using status flags as keys. When performing PID calculations on the ambient light intensity difference and the matched parameters, the proportional term output is obtained by multiplying the ambient light intensity difference by the proportional gain coefficient, directly reflecting the magnitude of the current deviation. The integral term is calculated by accumulating historical light intensity differences and multiplying by the integral gain coefficient, which is determined by both the proportional gain coefficient and the integral time constant, and is used to eliminate the system's steady-state error. The derivative term is obtained by calculating the rate of change of the ambient light intensity difference between the current and previous moments and multiplying by the derivative gain coefficient, and is used to predict future trends. The sampling time interval in the above calculations is 0.01 seconds to ensure real-time control. Finally, the outputs of the proportional, integral, and derivative terms are directly added to generate a comprehensive control variable value that reflects the system's requirement for light intensity deviation correction.

[0059] For example, when the device is moved from indoors to outdoors, the system detects a sudden change in light intensity and immediately switches to the sudden change state parameter group, so that the screen brightness can be quickly increased to a suitable level within 0.5 seconds; when the ambient light stabilizes, the system automatically switches to the stable state parameter group to ensure that the brightness remains stable and flicker-free.

[0060] Subsequently, when quantizing and mapping the control variable value U, a piecewise linear interpolation algorithm is used to map continuous U values ​​to a discrete adjustment instruction set. The mapping standard is determined based on historical control data statistics and experimental verification of system response characteristics. The setting principles for the interval boundaries [0,10], [10,30], and the threshold 30 are as follows: when U<10, the system is in the fine-tuning stage, with an adjustment range of 0-5%; when 10≤U≤30, it is in the medium-tuning stage, with an adjustment range of 5-15%; when U>30, it enters the large-scale adjustment stage, with an adjustment range of 15-40% and an upper limit of 40%. Within each interval, a uniform linear mapping is employed: In the fine-tuning interval [0,10], the U value linearly increases from 0% to 5% as it rises from 0 to 10, with a fixed slope of 0.5% per unit increase in U; ​​in the medium-tuning interval [10,30], the U value linearly increases from 5% to 15% as it rises from 10 to 30, maintaining the slope of 0.5% per unit increase in U; ​​in the large-scale adjustment interval (U>30), to maintain consistency, the mapping continues with the same slope, i.e., starting from 30, the adjustment increases by 0.5% for every unit increase in U, linearly increasing from 15% until the maximum adjustment reaches 40% (corresponding to U=80), after which the adjustment remains constant at 40% as the U value continues to increase. The entire mapping process is hardware-accelerated through a pre-compiled lookup table to ensure nanosecond-level response speed, while least-squares fitting optimizes the interval range to ensure sensitivity and avoid instruction jumps.

[0061] When calculating the target light intensity according to the adjustment instruction, the system first performs structured parsing of the preliminary light intensity adjustment instruction. The instruction syntax analyzer identifies the operation type (e.g., "increase" or "decrease") and the adjustment percentage. A pattern matching algorithm extracts key parameters from the instruction string. This identification process is based on a predefined keyword mapping table: the analyzer first segments the instruction string, extracts core verb phrases, and then performs precise matching with built-in "increase" keywords (e.g., "increase", "raise", "up") and "decrease" keywords (e.g., "decrease", "reduce", "down"). When a match is successful, the operation type is determined. Subsequently, the percentage parameter is converted to a fixed-point number format, and a scalar multiplication operation is performed with the device's base brightness value using a hardware multiplication unit. Specifically, the adjustment percentage is converted to an equivalent decimal coefficient, which is then multiplied by the device's base brightness value to obtain the adjusted brightness value. The calculation process integrates a dynamic range checking mechanism to verify in real time whether the target value is within the hardware-supported brightness range (e.g., 0 to 1000 lux). If an out-of-range error is detected, a limiter is automatically activated for clamping. Finally, a verified target light intensity level variable is generated, providing an accurate benchmark for subsequent light intensity adjustment. Specifically, the system reads the device's base brightness value. If the instruction is to increase brightness by 40%, the base brightness value is increased by the corresponding 40% increment. Fixed-point arithmetic is used in the calculation process to avoid floating-point errors.

[0062] In step S14, the preliminary light intensity adjustment command needs to be executed, the deviation between the adjusted actual light intensity and the target light intensity level needs to be calculated, the light intensity correction increment needs to be calculated based on the deviation, and the light intensity needs to be corrected to obtain a light intensity control signal, including:

[0063] Execute the initial light intensity adjustment command, obtain the adjusted actual light intensity, and calculate the deviation between the adjusted actual light intensity and the target light intensity level; the deviation includes the light intensity deviation amplitude and the deviation direction sign;

[0064] The brightness deviation amplitude is iterated and the correction step size and feedback gain coefficient are updated. The light intensity correction increment is calculated by combining the deviation direction sign and the correction step size.

[0065] If the light intensity correction increment is greater than the preset minimum convergence threshold, the correction step size and feedback gain coefficient are updated to gradually reduce the light intensity correction increment; if the light intensity correction increment is less than or equal to the preset minimum convergence threshold, the control variable value is locked and the drive protocol is formatted and encapsulated to obtain the light intensity control signal.

[0066] It should be noted that after executing the initial light intensity adjustment command, the system first parses the command into a target duty cycle or drive current value, and sends it to the constant current drive circuit of the micro LED via I2C or SPI communication protocol. The drive circuit adjusts its output according to the command, changing the brightness of the light source. Subsequently, the system triggers the integrated ambient light sensor to measure after a stabilization time (usually 2-3 sampling cycles) following command execution to obtain stabilized illumination data. The sensor converts the analog light signal into a digital reading via an on-chip ADC, and processes instantaneous noise through a moving average filter to finally obtain the adjusted actual light intensity value. The system collects this actual light intensity value in real time at a preset sampling frequency and calculates the deviation between it and the target light intensity level: first, it calculates the absolute value of the difference between the actual value and the target value to obtain the magnitude of the light intensity deviation; simultaneously, it determines whether the actual value is too low or too high relative to the target value. If the actual value is too low, the deviation direction is marked as positive, indicating that the light intensity needs to be increased; if the actual value is too high, the deviation direction is marked as negative, indicating that the light intensity needs to be reduced. The entire calculation process uses fixed-point arithmetic to avoid floating-point errors and ensure real-time processing.

[0067] Subsequently, the system performs precise classification and parameter matching based on the magnitude of the current absolute deviation: when the absolute deviation exceeds 200 lux, it is determined to be a "large deviation," and the abrupt parameter group is automatically called, using a larger correction step size (e.g., 0.8 lux) and a higher feedback gain coefficient (e.g., 1.2) to quickly reduce the deviation; when the absolute deviation is between 50 lux and 200 lux, it is determined to be a "medium deviation," and the transition parameter group is used, with the step size and gain coefficient taking the middle value (e.g., step size 0.5 lux, gain coefficient 1.0); when the absolute deviation is less than or equal to 50 lux, it is determined to be a "small deviation," and the system switches to the steady-state parameter group, using a smaller step size (e.g., 0.2 lux) and a lower gain coefficient (e.g., 0.8) to achieve fine-tuning. The iterative process is executed cyclically at a fixed frequency (e.g., 10 Hz). At the beginning of each iteration, the actual light intensity is re-acquired and the latest deviation value is calculated. Then, the gradient descent method is applied to optimize the step size: by comparing the difference between the current deviation and the previous deviation, if the deviation continues to decrease, the current step size is maintained; if the deviation does not improve, the step size is shrunk by a preset ratio (e.g., 0.9) to suppress oscillation. Finally, the matching feedback gain coefficient, the absolute value of the current deviation, the sign representing the adjustment direction (positive indicates increasing light intensity, negative indicates decreasing light intensity), and the optimized step size are multiplied to obtain the light intensity correction increment.

[0068] Finally, if the absolute value of the calculated light intensity correction increment exceeds the preset minimum convergence threshold, the system will enter a closed-loop iterative correction process. This minimum convergence threshold is set during the calibration process in the system initialization phase. Its specific value is obtained by statistically analyzing the background noise of the ambient light sensor in a standard darkroom environment, and is typically taken as 2 to 3 times the noise standard deviation (e.g., 0.03 lux). This setting ensures that the iteration stops in time when the correction amount enters the noise-dominated range, avoiding over-adjustment of the system to meaningless small fluctuations. In this process, if the increment still exceeds the limit, the system will multiply the current correction step size by a decay factor less than 1 according to the gradient descent principle, thereby obtaining a smaller new step size and recalculating the increment. Through multiple such iterations, the increment value is gradually reduced to suppress oscillations. The initial value of the decay factor is usually set to 0.9, which is based on the following: Under the gradient descent framework, by gradually reducing the search step size exponentially, oscillations or overshoot caused by excessively large step sizes can be effectively suppressed when approaching the optimal solution, thereby ensuring the smoothness of the convergence process. The system will also intelligently monitor the convergence trend. If the rate of decrease of the correction amount is too slow in several consecutive iterations, the decay factor will be automatically increased to accelerate convergence. The feedback gain coefficient will also be dynamically fine-tuned according to the rate of change of the deviation. If the deviation changes too drastically, the gain value will be appropriately reduced to prevent the system from overshooting and ensure the smoothness of the adjustment process. When the absolute value of the light intensity correction increment is less than or equal to the minimum convergence threshold, the system determines that a stable state has been reached. It then locks the final control variable value and converts it into a fixed-point number in a specific format. Next, the system encapsulates the value with the frame start bit, device address, command code, data field, and check code according to the I2C or SPI communication protocol specification, generating the final light intensity control signal. This digitally encoded command frame can directly drive the micro LED circuit to adjust the light intensity, achieving dynamic matching with the ambient light, and can automatically reduce the signal update frequency to enter a low-power mode when the ambient light is stable.

[0069] In step S15, if the power consumption corresponding to the light intensity control signal exceeds a preset low power consumption range, the signal amplitude needs to be reduced to obtain an optimized control signal, including:

[0070] The original driving voltage amplitude is extracted from the light intensity control signal. If the original driving voltage amplitude is greater than the preset low power consumption voltage threshold, a linear interpolation correction function is constructed.

[0071] Based on the linear interpolation correction function, the original driving voltage amplitude is compressed and mapped to obtain a compliant driving amplitude within the low power consumption range;

[0072] Based on the compliant drive amplitude, reconstruct the instruction frame and output an optimized control signal;

[0073] When extracting the original driving voltage amplitude from the light intensity control signal, the system first parses the frame structure of the control signal. Specifically, it uses bit operations to strip away the start bit, address byte, and command code from the I2C or SPI protocol, locating the data field carrying the voltage data. This data field typically consists of two bytes, encoding an integer from 0 to 65535 in big-endian order. The system divides this integer by a preset scaling factor to convert it into a floating-point number in volts. This scaling factor is determined during the system hardware design phase and its value is equal to the ratio of the analog-to-digital converter's reference voltage to the digital range. During the calibration phase, the system applies a standard voltage signal with known accuracy, and fine-tunes the scaling factor by comparing the measured digital reading with the theoretical value to ensure voltage conversion accuracy. This yields the original driving voltage amplitude. The parsing process is accompanied by CRC verification to ensure data integrity. If the voltage value exceeds a preset power threshold (e.g., 4.5 volts), a linear interpolation correction function is constructed. This function is implemented by setting the absolute maximum safe voltage allowed by the system hardware. (e.g., 5.5V), the preset upper limit of the low-power operating range is (Usually equal to or slightly below the upper limit of the power threshold) (e.g., 4.5V). For any voltage greater than... The original voltage Its corresponding compliant output voltage It is uniquely determined by the following relationship: The linear compression coefficient This function ensures that within the input range... Within this range, the output voltage is linearly and seamlessly mapped to the low-power output range. This function linearly and monotonically compresses the original voltage value exceeding the limit to a low-power operating range. The power threshold, theoretically, is calculated based on the continuous power supply capability of the power management unit (PMIC), the thermal resistance and junction temperature limit of the micro LED driver chip, and the power consumption formula combined with the thermal derating curve to determine the maximum allowable voltage that ensures the long-term reliable operation of the chip. During the self-calibration phase of system startup, the control chip actively measures the actual current and voltage characteristics of the drive circuit under the current ambient temperature and monitors the estimated changes in the chip junction temperature in real time, dynamically fine-tuning the theoretical threshold to an optimal value that simultaneously meets performance requirements, thermal safety boundaries, and overall power consumption budget.

[0074] Finally, the system converts the calculated compliant drive amplitude into a format suitable for digital transmission. Specifically, it quantizes it into a 16-bit fixed-point number, a format that can simultaneously represent the integer and fractional parts of the value to maintain precision. Next, following a predetermined communication protocol (such as I2C or SPI), the system assembles this quantized value with other necessary control information into a complete instruction frame. This instruction frame includes a start bit indicating the start of communication, the address of the target device, the specific operation command, the data field carrying the voltage value, a cyclic redundancy check (CRC) code for verifying data integrity, and a stop bit indicating the end of communication. The optimized control signal obtained after this series of encapsulation steps is the final instruction with low-power processing. It can be directly sent to the driver circuit of the micro-LED to precisely adjust the luminous intensity, optimizing energy efficiency while maintaining performance. This signal also has intelligent management capabilities; when the system detects that the ambient light is stabilizing, it automatically reduces the instruction transmission frequency to further save power.

[0075] In step S16, the optimized control signal needs to be input into the driving circuit, and after analysis and synthesis, a pulse driving current is generated to excite the pixel array to generate instantaneous luminous flux. The instantaneous luminous flux is then collected to generate adjusted light intensity data, including:

[0076] Voltage amplitude data and time-domain duty cycle data are separated from the optimized control signal, and the voltage amplitude data and the time-domain duty cycle data are combined to obtain a composite drive control voltage;

[0077] Based on the composite drive control voltage, the parameters of the drive transistor are adjusted to obtain the pulse drive current;

[0078] The pulsed driving current is injected into the micro LED pixel array to excite the instantaneous luminous flux. The instantaneous luminous flux is then collected to obtain the adjusted light intensity data. The adjusted light intensity data includes the theoretically output brightness data and chromaticity data.

[0079] It should be noted that when separating voltage amplitude data and time-domain duty cycle data from the optimized control signal, the system first parses the instruction frame, determines the frame start position by identifying a predefined synchronization word, and then decapsulates it field by field according to the communication protocol format. The data domain of this optimized control signal simultaneously encodes two key pieces of information: voltage amplitude and time duty cycle. The data representing the voltage magnitude is located at a specific position in the data domain. The system extracts the integer value represented by this data through shifting and masking operations, and then converts it into the actual voltage value according to a preset conversion relationship. The data representing the time duty cycle is obtained from another specific offset address in the data domain according to the protocol definition, and its value can be easily converted into a percentage form of the duty cycle. These parsed data are discrete in time. The system then uses a linear interpolation algorithm to calculate and insert intermediate values ​​between adjacent discrete data points, thereby generating a continuous and smooth control signal. When synthesizing the composite drive control voltage, the system uses the obtained continuous voltage amplitude as a reference level. Simultaneously, it uses a continuous duty cycle signal to control a pulse width modulation module, which generates a square wave signal with a fixed period but a high-level time proportional to the duty cycle. Finally, the system multiplies the reference level voltage with this square wave signal using a hardware multiplier or equivalent digital logic to obtain a composite drive control voltage waveform with an amplitude equal to the reference voltage and a pulse width determined by the duty cycle. This synthesis process is completed in real-time by a digital signal processor, ensuring accurate waveform generation and rapid system response.

[0080] Then, when adjusting the parameters of the drive transistor according to the composite drive control voltage, the system inputs this voltage waveform to the gate drive circuit. This circuit typically consists of a high-speed operational amplifier and a push-pull output stage, capable of quickly responding to and amplifying the input signal, and precisely controlling the turn-on and turn-off speed of the transistor by adjusting the gate drive resistor. Based on the real-time waveform of the input voltage and combined with the inherent voltage-to-current conversion characteristic curve of the transistor, the system dynamically adjusts the control voltage applied between the gate and source, so that the transistor operates in a suitable region (such as the saturation region or the linear region), thereby outputting a current waveform that matches the target light intensity adjustment requirements.

[0081] Finally, a pulsed driving current is injected into the micro-LED pixel array. This injection process is completed by a constant current driving circuit, which precisely controls the amplitude and time distribution of the current based on the pulse width modulation signal to ensure that each pixel unit receives uniform excitation. Under current excitation, each pixel emits instantaneous light based on the electroluminescence effect of the semiconductor PN junction. The magnitude of its luminous flux is proportional to the intensity of the injected current, and the proportionality coefficient is determined by the photoelectric conversion efficiency of the LED material, which is obtained through material characteristic calibration. Subsequently, the luminous flux generated by multiple pixels is converged by an optical microlens array. The microlens array adopts a specific curved surface design, which collimates and guides the diverging light rays of each pixel to the light-emitting surface through the principle of refraction. Combined with an optical path optimization algorithm, it ensures that the emitted light field is uniform and avoids dark areas with uneven brightness. The uniform light field formed on the light-emitting surface is collected by a high-precision photoelectric sensor. The brightness detection unit integrated in the sensor converts the light intensity into an electrical signal, while the chromaticity detection unit separates the spectral components through an RGB filter array and converts them into digital values, thereby obtaining adjusted light intensity data containing brightness values ​​and chromaticity coordinates. The luminance value is calculated by integrating the luminous flux over time and combining it with a calibration coefficient. The chromaticity coordinates are obtained by mapping the collected RGB values ​​to the standard CIE chromaticity coordinate system through a pre-calibrated transformation matrix. This adjusted light intensity data is transmitted to the main processor via the I2C interface in a fixed format with a frame header and checksum, serving as feedback for closed-loop control. If the deviation from the target value exceeds the allowable range, the system is triggered to re-execute the adjustment process, thereby ensuring that the output light intensity always accurately matches environmental changes.

[0082] In step S17, the visual contrast value needs to be calculated based on the adjusted light intensity data. If the visual contrast value is lower than a preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy, including:

[0083] The actual brightness data and chromaticity deviation data of the micro LED array are collected, and the real-time visual contrast value is calculated by combining the adjusted light intensity data.

[0084] If the visual contrast value is lower than a preset visual perception threshold, calculate the difference between the visual contrast value and the visual perception threshold to obtain the error feedback amount.

[0085] Based on the error feedback, a precise drive compensation value is derived, and a refined drive signal is generated using the precise drive compensation value to achieve closed-loop refinement of the light intensity adjustment accuracy.

[0086] It should be noted that when collecting the actual brightness and chromaticity deviation data of the micro LED array, the system monitors the luminous intensity of each pixel unit in real time through a high-precision photoelectric sensor array. The brightness data is collected directly in lux, while the chromaticity deviation data is separated into the three primary color components through an RGB filter and then converted to the CIE xy chromaticity space to calculate the color coordinate offset. In practice, the sensor array is spatially staggered and closely attached to the light-emitting surface of the LED array. It synchronously samples the brightness and RGB spectral energy of each pixel at a period of 10 milliseconds. Then, it maps the RGB values ​​to the standard CIE 1931 chromaticity coordinates through a pre-stored chromaticity conversion matrix and calculates the Euclidean distance between the sensor array and the target white point (such as a D65 standard light source) as the chromaticity deviation. Combining the target brightness value and target chromaticity value calculated in real time according to the ambient light condition, the system performs timestamp alignment to ensure data consistency. The calculation of the real-time visual contrast ratio integrates the differences in brightness and chromaticity: the brightness contrast ratio is calculated by dividing the absolute value of the difference between the actual brightness and the target brightness by the sum of the two to simulate the non-linear perception of relative brightness by the human eye; the chromaticity contrast ratio is quantified by calculating the straight-line distance between the actual chromaticity coordinates and the target chromaticity coordinates. The fusion of these two parts relies on a pre-calibrated weighting coefficient, which is determined as follows: Under standard D65 illumination, the minimum visual difference data of 20 subjects are collected using the stepwise method by adjusting the luminance and chromaticity of the test pattern. The weighting coefficient is then fitted using the least squares method, with typical values ​​of 0.7 for luminance and 0.3 for chromaticity (i.e., chromaticity weighting coefficient k=0.3). In actual calculations, the system multiplies the calculated luminance contrast and chromaticity contrast by their respective weights, then sums them to output a dimensionless scalar value that comprehensively represents visual differences.

[0087] If the real-time visual contrast value is lower than the preset visual perception threshold, the system first verifies and dynamically adjusts it through the threshold management module. The baseline value (0.8) of this visual perception threshold originates from the psychophysical experiment on the minimum visual difference of the human eye under standard observation conditions. This experiment determines the threshold by presenting a series of contrast patterns with varying gradients and statistically analyzing the critical point at which subjects can reliably perceive the difference. To achieve environmental adaptability, the system dynamically adjusts the threshold based on the readings of the ambient light sensor: in strong light environments, to counteract the "washing" effect of ambient light on screen content and maintain readability, the system raises the threshold to a higher level (e.g., 1.2) based on the light intensity-contrast sensitivity model; in low light environments, the threshold is appropriately lowered to match the higher contrast sensitivity of the human eye. Meanwhile, to filter out random fluctuations, the system employs a sliding window algorithm to perform median filtering on the contrast values ​​of multiple consecutive sampling points to eliminate instantaneous fluctuations. Subsequently, the error feedback is calculated, a process comprising three steps: a difference calculation stage directly performs arithmetic subtraction; a sign determination stage identifies the positive or negative nature of the error to determine the adjustment direction; and an amplitude normalization stage specifically uses the Sigmoid function to smoothly compress the original error value and map it to a finite interval of [-1, 1], effectively suppressing drastic jumps in control output caused by excessively large original errors, while maintaining high sensitivity within a small error range. When the difference is positive, it indicates insufficient visual experience requiring increased light intensity. The system also records the duration of the error; when the error persists beyond a set time limit and its direction remains constant, the compensation intensity coefficient is automatically increased, forming a time-cumulative enhancement mechanism.

[0088] Finally, when deriving the precise drive compensation value based on the error feedback, the system employs a proportional-integral-derivative (PID) control algorithm. The algorithm's output consists of three parts: the proportional term output is obtained by multiplying the current error feedback by the proportional gain coefficient, primarily used for rapid response to the current deviation; the integral term output is obtained by accumulating historical error feedback over a period of time and then multiplying by the integral gain coefficient, aiming to eliminate persistent small deviations; and the derivative term output is obtained by calculating the difference between the current error feedback and the previous time step, dividing by the sampling interval, and multiplying by the derivative gain coefficient, used to predict the deviation change trend.

[0089] The proportional, integral, and derivative gain coefficients are determined using the Ziegler-Nichols engineering tuning method: First, the integral and derivative gains are set to zero. The proportional gain is gradually increased until the system exhibits constant-amplitude oscillations. The critical gain and oscillation period at this point are recorded. Then, the final parameter values ​​are calculated using formulas, achieving a balance between response speed and stability. For example, when ambient light suddenly increases from 300 lux to 1000 lux, the system detects a brightness deviation of 700 lux. The proportional term immediately outputs a large correction for rapid response; the integral term continuously accumulates historical deviations to ensure the eventual elimination of steady-state error; and the derivative term suppresses potential overshoot based on the light intensity change trend. After parameter tuning, the system stabilizes the screen brightness to the target value within 1.2 seconds, with overshoot controlled within 5%. When generating refined drive signals using precise drive compensation values, the system maps the compensation values ​​to specific PWM duty cycle adjustment instructions using a lookup table. For example, a positive compensation value increases the duty cycle, while a negative value decreases it, thus achieving precise control of light intensity. This closed-loop control mechanism effectively improves the adaptability and stability of the new lighting system in dynamic environments.

[0090] Reference Figure 2 The second embodiment of the present invention provides an ultra-low power micro LED visible light intensity adaptive control system, comprising:

[0091] The data acquisition module is used to acquire and preprocess analog light signals to obtain ambient light intensity values;

[0092] The difference calculation module is used to calculate the rate of change of light intensity based on the ambient light intensity value. If the rate of change of light intensity exceeds a preset dynamic environmental change threshold, the environmental state is marked and the ambient light intensity difference is output.

[0093] The instruction generation module is used to match preset control and adjustment parameters according to the environmental state, quantize and map the difference in ambient light intensity according to the control and adjustment parameters, generate a preliminary light intensity adjustment instruction, and calculate the target light intensity level in combination with the predetermined basic brightness of the device.

[0094] The deviation correction module is used to execute the preliminary light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain the light intensity control signal;

[0095] The control optimization module is used to reduce the signal amplitude and obtain an optimized control signal if the power consumption corresponding to the light intensity control signal exceeds a preset low power consumption range.

[0096] The circuit adjustment module is used to input the optimized control signal into the driving circuit, generate a pulse driving current after analysis and synthesis, excite the pixel array to generate instantaneous luminous flux, and gather the instantaneous luminous flux to generate adjusted light intensity data.

[0097] The feedback optimization module is used to calculate the visual contrast value based on the adjusted light intensity data. If the visual contrast value is lower than the preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy.

[0098] It should be noted that the ultra-low power micro LED visible light intensity adaptive control system provided in this embodiment of the invention is used to execute all the process steps of the ultra-low power micro LED visible light intensity adaptive control method in the above embodiment. The working principle and beneficial effects of the two are one-to-one, so they will not be described again.

[0099] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0100] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for adaptive control of visible light intensity of ultra-low power micro LEDs, characterized in that, include: The simulated light signal is acquired and preprocessed to obtain the ambient light intensity value; Based on the ambient light intensity value, calculate the light intensity change rate. If the light intensity change rate exceeds a preset dynamic environmental change threshold, mark the environmental state and output the ambient light intensity difference. Based on the environmental state, preset control and adjustment parameters are matched, and the difference in ambient light intensity is quantified and mapped according to the control and adjustment parameters to generate a preliminary light intensity adjustment command and calculate the target light intensity level in combination with the pre-determined basic brightness of the equipment. Execute the initial light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain a light intensity control signal; If the power consumption corresponding to the light intensity control signal exceeds the preset low power consumption range, the signal amplitude is reduced to obtain an optimized control signal; The optimized control signal is input into the driving circuit, and after analysis and synthesis, a pulse driving current is generated to excite the pixel array to generate instantaneous luminous flux. The instantaneous luminous flux is then collected to generate adjusted light intensity data. Based on the adjusted light intensity data, the visual contrast value is calculated. If the visual contrast value is lower than the preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy. The step of matching preset control adjustment parameters according to the environmental state, quantizing and mapping the ambient light intensity difference according to the control adjustment parameters, generating a preliminary light intensity adjustment command, and calculating the target light intensity level in conjunction with a pre-determined device baseline brightness includes: Based on the environmental state, the corresponding proportional gain coefficient, integral time constant and differential gain coefficient are matched, and calculated with the difference in ambient light intensity to generate control variable values; The values ​​of the control variables are quantized and mapped to generate preliminary light intensity adjustment instructions; Based on the preliminary light intensity adjustment command, the current brightness of the device is calculated to obtain the target light intensity level; Specifically, the process involves executing the initial light intensity adjustment command, calculating the deviation between the adjusted actual light intensity and the target light intensity level, calculating the light intensity correction increment based on the deviation, and correcting the light intensity to obtain a light intensity control signal. Execute the initial light intensity adjustment command, obtain the adjusted actual light intensity, and calculate the deviation between the adjusted actual light intensity and the target light intensity level; the deviation includes the light intensity deviation amplitude and the deviation direction sign; The light intensity deviation amplitude is fed back iteratively to update the correction step size and feedback gain coefficient, and the light intensity correction increment is calculated by combining the deviation direction sign and the correction step size. If the light intensity correction increment is greater than the preset minimum convergence threshold, the correction step size and feedback gain coefficient are updated to gradually reduce the light intensity correction increment. If the light intensity correction increment is less than or equal to the preset minimum convergence threshold, the value of the control variable is locked and the drive protocol is formatted and encapsulated to obtain the light intensity control signal.

2. The method for adaptive control of visible light intensity of ultra-low power micro-LEDs according to claim 1, characterized in that, The process of acquiring and preprocessing the simulated light signal to obtain the ambient light intensity value includes: A simulated optical signal is acquired, and the simulated optical signal is discretized to obtain the original discrete optical intensity sequence; The original discrete light intensity sequence is subjected to Kalman filtering to obtain a smoothed ambient light intensity value.

3. The method for adaptive control of visible light intensity of ultra-low power micro-LEDs according to claim 1, characterized in that, The step of calculating the rate of change of light intensity based on the ambient light intensity value, and if the rate of change of light intensity exceeds a preset dynamic environmental change threshold, marking the environmental state and outputting the ambient light intensity difference, includes: Based on the ambient light intensity value, calculate the light change rate at the current moment. If the light change rate is greater than the preset dynamic environment change threshold, mark the current environment as a light change state; otherwise, mark it as a light no-change state. The difference in light intensity between the start time of the mutation and the current time is calculated to obtain the ambient light intensity difference. The start time of the mutation is the sampling point when the light intensity first exceeds the threshold.

4. The method for adaptive control of visible light intensity of ultra-low power micro-LEDs according to claim 1, characterized in that, If the power consumption corresponding to the light intensity control signal exceeds a preset low power consumption range, the signal amplitude is reduced to obtain an optimized control signal, including: The original driving voltage amplitude is extracted from the light intensity control signal. If the original driving voltage amplitude is greater than the preset low power consumption voltage threshold, a linear interpolation correction function is constructed. Based on the linear interpolation correction function, the original driving voltage amplitude is compressed and mapped to obtain a compliant driving amplitude within the low power consumption range; Based on the compliance drive amplitude, reconstruct the instruction frame and output the optimized control signal.

5. The method for adaptive control of visible light intensity of ultra-low power micro-LEDs according to claim 1, characterized in that, The process of inputting the optimized control signal into the driving circuit, generating a pulse driving current after analysis and synthesis, exciting the pixel array to produce instantaneous luminous flux, and converging the instantaneous luminous flux to generate adjusted light intensity data includes: Voltage amplitude data and time-domain duty cycle data are separated from the optimized control signal, and the voltage amplitude data and the time-domain duty cycle data are combined to obtain a composite drive control voltage; Based on the composite drive control voltage, the parameters of the drive transistor are adjusted to obtain the pulse drive current; The pulsed driving current is injected into the micro LED pixel array to excite the instantaneous luminous flux. The instantaneous luminous flux is then collected to obtain the adjusted light intensity data. The adjusted light intensity data includes the theoretically output brightness data and chromaticity data.

6. The method for adaptive control of visible light intensity of ultra-low power micro-LEDs according to claim 1, characterized in that, The step of calculating a visual contrast value based on the adjusted light intensity data, and if the visual contrast value is lower than a preset visual perception threshold, recalculating the light intensity change rate and adjusting the control signal to achieve closed-loop refinement of light intensity adjustment accuracy includes: The actual brightness and chromaticity deviation data of the micro LED array are collected, and combined with the adjusted light intensity data, the real-time visual contrast value is calculated. If the visual contrast value is lower than a preset visual perception threshold, calculate the difference between the visual contrast value and the visual perception threshold to obtain the error feedback amount. Based on the error feedback, a precise drive compensation value is derived, and a refined drive signal is generated using the precise drive compensation value to achieve closed-loop refinement of the light intensity adjustment accuracy.

7. A system for adaptive control of visible light intensity of ultra-low power micro LEDs, characterized in that, For implementing the method as described in any one of claims 1-6, comprising: The data acquisition module is used to acquire and preprocess analog light signals to obtain ambient light intensity values; The difference calculation module is used to calculate the rate of change of light intensity based on the ambient light intensity value. If the rate of change of light intensity exceeds a preset dynamic environmental change threshold, the environmental state is marked and the ambient light intensity difference is output. The instruction generation module is used to match preset control and adjustment parameters according to the environmental state, quantize and map the difference in ambient light intensity according to the control and adjustment parameters, generate a preliminary light intensity adjustment instruction, and calculate the target light intensity level in combination with the predetermined basic brightness of the device. The deviation correction module is used to execute the preliminary light intensity adjustment command, calculate the deviation between the adjusted actual light intensity and the target light intensity level, calculate the light intensity correction increment based on the deviation and correct the light intensity to obtain the light intensity control signal; The control optimization module is used to reduce the signal amplitude and obtain an optimized control signal if the power consumption corresponding to the light intensity control signal exceeds a preset low power consumption range. The circuit adjustment module is used to input the optimized control signal into the driving circuit, generate a pulse driving current after analysis and synthesis, excite the pixel array to generate instantaneous luminous flux, and gather the instantaneous luminous flux to generate adjusted light intensity data. The feedback optimization module is used to calculate the visual contrast value based on the adjusted light intensity data. If the visual contrast value is lower than the preset visual perception threshold, the light intensity change rate is recalculated and the control signal is adjusted to achieve closed-loop refinement of the light intensity adjustment accuracy.

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