An intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes

Abstract

The present application relates to the technical field of light-emitting diodes, and discloses an intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes. The method comprises: measuring the temperature-light efficiency of the light-emitting diode, establishing a junction temperature-light efficiency mapping model and determining an optimal working junction temperature range; hierarchically configuring the heat dissipation unit based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range to obtain a multi-level heat dissipation control system; deploying a temperature sensor array and a light sensor array in the light-emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve; adjusting the parameters of the multi-level heat dissipation control system according to the temperature-light efficiency relationship curve to obtain a heat dissipation control instruction sequence; dynamically compensating the driving current of the light-emitting diode based on the heat dissipation control instruction sequence to obtain the optimal driving parameters, thereby realizing the stable operation of the LED within the optimal working junction temperature range and significantly improving the photoelectric conversion efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of light emitting diodes, and in particular to an intelligent heat dissipation control method for improving the light efficiency of light emitting diodes. Background Art

[0002] With the rapid development of LED lighting technology, high-brightness LEDs have been widely used in various lighting fields, but there is a nonlinear relationship between the luminous efficiency of LEDs and their junction temperature. Traditional LED heat dissipation technology mostly adopts a constant temperature control mode, ignoring the characteristics that different LEDs have their own optimal photoelectric conversion efficiency points at different junction temperatures, resulting in the inability of LEDs to continuously work at the optimal quantum efficiency state, thereby limiting the luminous efficiency and service life. Existing heat dissipation systems mainly rely on passive heat dissipation or simple temperature control, and cannot be intelligently controlled according to the junction temperature-luminous efficiency characteristics of LEDs. Especially in working environments with large junction temperature fluctuations, the luminous efficiency stability and color temperature stability of LEDs are significantly reduced.

[0003] Modern high-brightness LED application scenarios require a high junction temperature-light efficiency dynamic range (TEDR) for the cooling system, but the cooling solutions currently on the market lack the ability to monitor and compensate for the relationship between LED junction temperature and light efficiency in real time. Traditional designs usually separate the cooling system from the drive circuit, making it impossible to achieve coordinated regulation of temperature and drive current, and ignoring the linkage effect between the two. Although advanced cooling technologies such as microchannel liquid cooling and phase change materials have been applied to the field of LED cooling, they lack intelligent control strategies based on quantum efficiency optimization, resulting in low efficiency and high energy consumption of the cooling system. Summary of the invention

[0004] The present application provides an intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes, thereby achieving stable operation of the LED within the optimal operating junction temperature range and significantly improving the photoelectric conversion efficiency.

[0005] In a first aspect, the present application provides an intelligent heat dissipation control method for improving the light efficiency of a light emitting diode, the intelligent heat dissipation control method for improving the light efficiency of a light emitting diode comprising:

[0006] Measure the temperature-light efficiency of light-emitting diodes, establish a junction temperature-light efficiency mapping model, and determine the optimal operating junction temperature range;

[0007] Based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range, the heat dissipation units are configured in a hierarchical manner to obtain a multi-level heat dissipation control system;

[0008] Deploy a temperature sensor array and a light sensor array in the light emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve;

[0009] According to the temperature-light efficiency relationship curve, the parameters of the multi-level heat dissipation control system are adjusted to obtain a heat dissipation control instruction sequence;

[0010] The driving current of the light emitting diode is dynamically compensated based on the heat dissipation control instruction sequence to obtain the optimal driving parameter.

[0011] Optionally, in the first implementation of the present invention, the step of measuring the temperature-light efficiency of the light emitting diode, establishing a junction temperature-light efficiency mapping model and determining an optimal operating junction temperature range includes:

[0012] Obtain parameters of the rated power, chip structure type, emission wavelength, thermal conductivity of substrate material, and thermal resistance of packaging structure of the light-emitting diode to obtain a basic parameter set;

[0013] Based on the basic parameter set, the light emitting diode is installed on a temperature controllable test platform, and photoelectric parameters are recorded within a preset range to obtain temperature-light efficiency raw data;

[0014] Apply infrared thermal imaging and micro-thermocouple array measurement to the light-emitting diode and perform finite element thermal analysis to obtain chip junction temperature distribution data;

[0015] Based on the temperature-light efficiency raw data and the chip junction temperature distribution data, a polynomial fitting model is performed on the relationship between junction temperature and luminous flux to obtain a junction temperature-light efficiency function model;

[0016] An extended analysis is performed on the junction temperature-light efficiency function model, and a correlation analysis is performed between the junction temperature and the quantum efficiency, the electro-optical conversion efficiency, and the spectrum drift parameter to construct a junction temperature-light efficiency mapping model;

[0017] The photoelectric conversion efficiency data in the junction temperature-light efficiency mapping model is analyzed to determine the temperature range with the highest photoelectric conversion efficiency, thereby obtaining the optimal operating junction temperature range.

[0018] Optionally, in a second implementation of the present invention, the heat dissipation units are configured in a hierarchical manner based on the junction temperature-light efficiency mapping model and the optimal operating junction temperature range to obtain a multi-level heat dissipation control system, including:

[0019] Performing surface treatment on the aluminum nitride ceramic substrate according to the heat conduction requirements in the junction temperature-light efficiency mapping model to form a primary heat dissipation unit with a microchannel structure;

[0020] Based on the microchannel structure of the primary heat dissipation unit, epoxy resin material is packaged into a capillary microtube array, and a heat-conducting working liquid is filled into the capillary microtube array to obtain a secondary heat dissipation unit;

[0021] Conducting material analysis on the contact interface of the secondary heat dissipation unit, selecting and configuring a graphene / phase change material composite layer, and obtaining a tertiary heat dissipation unit;

[0022] According to the temperature range of the optimal working junction temperature range, parameter matching and power configuration are performed on the TEC cooling sheet and the high-efficiency centrifugal fan to obtain a four-stage heat dissipation unit;

[0023] Physically connecting and optimizing contact pressure of the primary heat dissipation unit, the secondary heat dissipation unit, the tertiary heat dissipation unit, and the quaternary heat dissipation unit to obtain an integrated heat dissipation assembly;

[0024] The integrated heat dissipation component is connected to a temperature controller, the start threshold and control logic of each level of heat dissipation units are programmed and set, a closed-loop feedback control mechanism based on the optimal working junction temperature range is established, and a multi-level heat dissipation control system is obtained.

[0025] Optionally, in a third implementation of the present invention, a temperature sensor array and a light sensor array are deployed in the light emitting diode to collect real-time data to obtain a temperature-light efficiency relationship curve, including:

[0026] Performing point planning on the peripheral area of ​​the light-emitting diode to obtain a temperature sensor array for measuring the temperature distribution on the chip surface, and arranging silicon photodiode sensors around the light-emitting surface of the light-emitting diode according to the light intensity distribution law to obtain a light sensor array for collecting light flux data;

[0027] Connecting the temperature sensor array and the light sensor array to a data acquisition and processing module;

[0028] Calculating the surface temperature data collected by the temperature sensor array to obtain the chip junction temperature value, and integrating the light intensity data and wavelength data collected by the light sensor array to obtain real-time light effect parameters;

[0029] The chip junction temperature value and the real-time light effect parameter are matched and data fitted to obtain a temperature-light effect relationship curve representing the working state of the light emitting diode.

[0030] Optionally, in a fourth implementation of the present invention, the surface temperature data collected by the temperature sensor array is calculated to obtain a chip junction temperature value, and the light intensity data and wavelength data collected by the light sensor array are integrated to obtain real-time light effect parameters, including:

[0031] Eliminating noise and cleaning abnormal data on the surface temperature data set collected by the temperature sensor array to obtain a calibrated temperature data matrix;

[0032] Substituting the calibrated temperature data matrix into a three-dimensional finite element heat conduction equation based on the structural characteristics of the light-emitting diode package, performing boundary constraint iterative calculations, and obtaining a heat distribution field function;

[0033] Performing spatial integration and averaging processing on the temperature values ​​of the corresponding PN junction area in the heat distribution field function to obtain the chip junction temperature value;

[0034] Applying a spherical integral algorithm and a light intensity correction factor to the light intensity data collected by the light sensor array at different solid angles to calculate the total space light flux, thereby obtaining a total light flux value;

[0035] The wavelength data collected by the spectrum analysis unit is weighted according to the visual response function, and the main wavelength, half-wave width, and color purity parameters are extracted to obtain the spectrum quality index;

[0036] According to the total luminous flux value, the spectral quality index and the input power value obtained by multiplying the real-time current of the light emitting diode by the voltage, a light efficiency calculation formula is applied to perform numerical calculation to obtain real-time light efficiency parameters.

[0037] Optionally, in a fifth implementation of the present invention, the step of adjusting parameters of the multi-stage heat dissipation control system according to the temperature-light efficiency relationship curve to obtain a heat dissipation control instruction sequence includes:

[0038] Comparing and calculating the temperature-light efficiency relationship curve with the optimal operating junction temperature range to obtain a heat dissipation control deviation parameter;

[0039] Constructing a control decision mapping relationship according to the temperature deviation and the light efficiency deviation in the heat dissipation control deviation parameter to obtain a fuzzy control rule table;

[0040] Based on the fuzzy control rule table, dynamically calculate the proportional coefficient, integral time constant and differential time constant of the PID controller to obtain an adaptive PID parameter group;

[0041] According to the adaptive PID parameter group and the heat dissipation control deviation parameter, the control strategy of the multi-stage heat dissipation control system is hierarchically determined to obtain a multi-stage heat dissipation coordinated control scheme;

[0042] Performing power allocation calculation on the multi-stage heat dissipation collaborative control scheme, determining the thermal conductivity adjustment parameter of the first-stage heat dissipation unit, the working liquid flow value of the second-stage heat dissipation unit, the temperature activation threshold of the third-stage heat dissipation unit, and the TEC current and fan speed value of the fourth-stage heat dissipation unit, and obtaining the control parameter set of each stage of the heat dissipation unit;

[0043] The control parameter set is converted into a PWM modulation instruction, a flow control valve opening instruction, a temperature threshold trigger instruction and a cooling fan speed instruction to obtain a cooling control instruction sequence.

[0044] Optionally, in a sixth implementation of the present invention, dynamically compensating the driving current of the light emitting diode based on the heat dissipation control instruction sequence to obtain an optimal driving parameter includes:

[0045] The photoelectric conversion characteristics of light-emitting diodes were measured under different junction temperature and driving current combinations, and a current-light efficiency-junction temperature data model was established;

[0046] Based on the current-light efficiency-junction temperature data model, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed to obtain an optimal operating point query matrix;

[0047] According to the target light output requirement and the current junction temperature state determined by the heat dissipation control instruction sequence, searching for matching conditions in the optimal operating point query matrix to obtain the highest efficiency operating point parameters;

[0048] Configure the working parameters of the PWM drive circuit, and based on the highest efficiency working point parameters, calculate and temperature compensate the duty cycle of the PWM drive signal to obtain the temperature-compensated PWM control parameters;

[0049] The temperature-compensated PWM control parameters are converted into driving control signals, and the rise / fall time of the PWM waveform is modulated to compensate for the color temperature deviation caused by the junction temperature change, thereby obtaining the optimal driving parameters.

[0050] Optionally, in a seventh implementation of the present invention, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed based on the current-light efficiency-junction temperature data model to obtain an optimal operating point query matrix, including:

[0051] Extracting the driving current, forward voltage and luminous flux data in the current-luminous efficiency-junction temperature data model and calculating the photoelectric conversion efficiency to obtain a photoelectric conversion efficiency value set;

[0052] Rearranging the photoelectric conversion efficiency value set according to two independent variables, junction temperature and driving current, to obtain an efficiency distribution point cloud, and performing continuous surface fitting on the efficiency distribution point cloud to obtain a photoelectric conversion efficiency continuous surface function;

[0053] Based on the photoelectric conversion efficiency continuous surface function, searching and calculating the efficiency extreme point at each junction temperature to obtain a set of junction temperature-optimal current correspondence relationships;

[0054] Performing isoluminous flux analysis on the set of junction temperature-optimal current correspondences and the photoelectric conversion efficiency continuous surface function to establish an isoluminous flux optimization path under constant light output;

[0055] The equal luminous flux optimization path is hierarchically indexed and constructed according to the luminous flux output level and the junction temperature range, and an optimal operating point query matrix including the target luminous flux, junction temperature, optimal driving current, expected luminous efficacy and adjustment margin is generated.

[0056] Compared with the prior art, the present application has the following beneficial effects: by establishing an accurate junction temperature-light efficiency mapping model and a multi-level heat dissipation control system, the stable operation of the LED within the optimal working junction temperature range is achieved, and the photoelectric conversion efficiency is significantly improved; the temperature-light efficiency real-time monitoring system and the adaptive heat dissipation control strategy are adopted to effectively reduce the junction temperature fluctuation and extend the service life of the LED; the dynamic current compensation mechanism and the heat dissipation control work together to reduce power consumption while maintaining stable light output, thereby improving the overall energy efficiency of the system; for multi-chip LED arrays, by precisely controlling the performance of the thermal interface material, the junction temperature uniformity is improved, and the uneven light emission and color deviation problems caused by uneven temperature are eliminated; the self-learning optimization and life prediction functions enable the system to continuously adjust the control parameters according to the LED aging characteristics, maintain long-term efficient operation, and reduce maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0058] Figure 1 It is a flow chart of an intelligent heat dissipation control method for improving the light efficiency of a light emitting diode provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0061] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0062] It should be further understood that the term "and / or" used in the specification and appended claims of this application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. Figure 1 In the embodiment of the present application, an embodiment of the intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes includes:

[0063] Step 100, measuring the temperature-light efficiency of the light emitting diode, establishing a junction temperature-light efficiency mapping model and determining the optimal operating junction temperature range;

[0064] It is understandable that the execution subject of the present application can be an intelligent heat dissipation control device for improving the light efficiency of light-emitting diodes, or a terminal or a server, which is not limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0065] Specifically, basic parameters such as the rated power, chip structure type, luminous wavelength, thermal conductivity of the substrate material, and thermal resistance of the packaging structure of the light-emitting diode are obtained. These parameters directly affect the heat dissipation performance and photoelectric conversion efficiency of the LED, and constitute the basic data set for studying the relationship between the junction temperature and light efficiency of the LED. Based on the basic parameter set, the LED is installed on a temperature-controllable test platform, and the photoelectric parameters are recorded within a preset temperature range to ensure that all temperature ranges of the LED are covered, and the original temperature-light efficiency data is obtained. Infrared thermal imaging technology and micro-thermocouple array measurement technology are used to obtain the temperature distribution data of each position of the chip. At the same time, with the help of finite element thermal analysis method, the junction temperature distribution of the LED is simulated and calculated to improve the accuracy and reliability of the data. This method can improve the spatial resolution of junction temperature measurement and effectively capture the dynamic changes of junction temperature over time. Based on the original temperature-light efficiency data and the chip junction temperature distribution data, the relationship between junction temperature and luminous flux is mathematically modeled, and polynomial fitting is used to obtain a junction temperature-light efficiency function model that is more in line with the actual situation. The experimental data is fitted by the least square method to express the light effect as a function of the junction temperature in the form of a quadratic or cubic polynomial, which is convenient for subsequent calculation and optimization. The model intuitively reflects how the LED light effect changes with the junction temperature and provides data support, so that the control of the heat dissipation system can be optimized for different junction temperatures. The junction temperature-light effect function model is extended and analyzed, and the junction temperature is correlated with the quantum efficiency, the electro-optical conversion efficiency and the spectral drift parameters to construct a junction temperature-light effect mapping model. Quantum efficiency is a key indicator for measuring the electron-hole recombination process inside the LED, while the electro-optical conversion efficiency determines how the input electrical energy is converted into light output energy. The spectral drift parameters directly affect the light color stability of the LED. The comprehensive analysis of these factors provides a more comprehensive LED light effect optimization solution, so that the heat dissipation control is not limited to the optimization of the luminous flux, but also takes into account the improvement of light quality. The photoelectric conversion efficiency data in the junction temperature-light effect mapping model is analyzed to determine the temperature range with the highest photoelectric conversion efficiency, and then determine the optimal working junction temperature range. The temperature corresponding to the highest point of photoelectric conversion efficiency is the optimal junction temperature when the LED is running. By analyzing the changing trend of this parameter at different temperatures, the temperature range required for the LED to work at the highest efficiency can be determined.

[0066] Step 200, hierarchically configuring the heat dissipation units based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range to obtain a multi-level heat dissipation control system;

[0067] Specifically, according to the heat conduction requirements in the junction temperature-light efficiency mapping model, the aluminum nitride ceramic substrate is surface treated to form a first-level heat dissipation unit with a microchannel structure. Since the aluminum nitride ceramic substrate itself has a high thermal conductivity, it can effectively diffuse the heat of the chip outward. After the microchannel structure is formed on its surface, the heat exchange efficiency is significantly improved. By enhancing the surface heat exchange capacity, the heat is transferred to the next-level heat dissipation unit faster. Based on the first-level heat dissipation unit, the heat dissipation effect is further optimized, and the capillary microtube array is packaged with an epoxy resin material based on a microchannel structure, and the capillary microtube array is filled with a heat-conducting working liquid to construct a second-level heat dissipation unit. In this process, the role of the capillary microtube array is to utilize the capillary action and phase change characteristics of the liquid to enhance the heat transfer capacity, so that the heat generated by the chip can be quickly diffused outward, and the local overheating phenomenon is reduced through the liquid circulation process. On the basis of the second-level heat dissipation unit, the contact interface thermal resistance is optimized to reduce the thermal resistance loss inside the heat dissipation system. The contact interface is analyzed for materials, and appropriate materials are selected for optimal configuration. Among them, the application of the graphene / phase change material composite layer can significantly improve the heat dissipation performance, thereby forming a third-level heat dissipation unit. Graphene can efficiently conduct heat from the chip due to its ultra-high thermal conductivity, while phase change materials can achieve balanced heat management by absorbing and releasing latent heat when the temperature changes. The combination of the two can reduce thermal resistance, improve heat diffusion efficiency, and achieve dynamic heat regulation to ensure that the LED always remains in a relatively stable temperature range. In order to meet the heat dissipation requirements of higher-power LEDs, active heat dissipation means are added. On the basis of the three-level heat dissipation unit, the TEC cooling sheet and the high-efficiency centrifugal fan are parameter matched and power configured according to the temperature range of the optimal working junction temperature range to form a four-level heat dissipation unit. The TEC cooling sheet, that is, the thermoelectric cooling device, uses the Peltier effect to achieve precise temperature control and provide rapid cooling capabilities when the LED temperature is high, while the high-efficiency centrifugal fan can enhance air convection and accelerate heat dissipation, thereby further reducing the junction temperature of the LED and stabilizing it within the optimal range. The first-level heat dissipation unit, the second-level heat dissipation unit, the third-level heat dissipation unit and the fourth-level heat dissipation unit are physically connected and the contact pressure is optimized to obtain an integrated heat dissipation component, wherein the purpose of optimizing the contact pressure is to ensure close contact between the heat dissipation units at each level, reduce thermal resistance, improve the overall heat dissipation efficiency, and at the same time improve the mechanical stability of the heat dissipation system to prevent the stratification or failure of the heat dissipation device caused by thermal expansion and mechanical stress. The integrated heat dissipation component is connected to the temperature controller, and the start threshold and control logic of the heat dissipation units at each level are set by programming, and a closed-loop feedback control mechanism based on the optimal working junction temperature range is established. The control mechanism dynamically adjusts the operating status of the heat dissipation units at each level according to the real-time temperature data. For example, only the first-level or second-level heat dissipation unit is turned on at a low temperature, and the third-level and fourth-level heat dissipation units are gradually started when the temperature rises, so as to ensure that the heat dissipation system achieves the optimal temperature control effect under the premise of minimum energy consumption.

[0068] Step 300: deploy a temperature sensor array and a light sensor array in the light emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve;

[0069] It should be noted that the layout planning is carried out in the peripheral area of ​​the light-emitting diode to obtain the temperature distribution on the chip surface. By analyzing the heat dissipation path and heat distribution characteristics of the LED, a reasonable temperature sensor layout strategy is determined to ensure the comprehensiveness and accuracy of the measurement data. The temperature sensors are arranged at multiple key positions on the chip surface to capture the changes in temperature gradient and calculate the junction temperature. Since the light intensity distribution of the light-emitting diode is not uniform, in order to accurately measure its luminous flux data, silicon photodiode sensors are arranged around the LED light-emitting surface according to the light intensity distribution law to form a light sensor array. The temperature sensor array and the light sensor array are connected to the data acquisition and processing module. The data acquisition and processing module consists of a high-precision analog-to-digital conversion circuit, a data filtering algorithm, and a wireless transmission module. It receives signals from each sensor in real time and performs preliminary processing on the raw data to improve the stability and anti-interference ability of the data. For the surface temperature data collected by the temperature sensor, further calculations are performed to obtain accurate chip junction temperature values. Since the junction temperature of the LED is one of the core factors affecting its light efficiency, the heat conduction model is used to convert the surface temperature data into the junction temperature, and the calculation results are optimized in combination with the thermal resistance network analysis method to reduce the measurement error. At the same time, the light intensity data and wavelength data collected by the light sensor array are integrated to calculate the real-time light effect parameters. The light intensity distribution of the LED at different angles and positions is obtained by the light sensor, and the mathematical model is used to integrate it to obtain the total luminous flux. At the same time, in order to more comprehensively evaluate the light effect, the spectral data is combined to analyze the luminous characteristics of the LED at different wavelengths, and its spectral power distribution is calculated to optimize the accuracy of the light effect measurement. In this process, the signal processing algorithm is used to filter the light intensity and spectral data to eliminate ambient light interference and improve the stability of the measurement. The chip junction temperature value and the real-time light effect parameter are paired, and the data fitting method is used to construct a temperature-light effect relationship curve that characterizes the working state of the LED. This process involves steps such as data preprocessing, curve fitting and trend analysis, and uses technologies such as polynomial fitting, exponential regression and neural network modeling to ensure that the fitting curve truly reflects the change law between junction temperature and light effect.

[0070] The temperature data collected by the temperature sensor is preprocessed, including noise elimination and abnormal data cleaning. Data filtering and abnormal point elimination algorithms are used to ensure the stability and reliability of the data, and a standardized temperature data matrix is ​​obtained, which contains the temperature information of each key position on the LED surface. The calibrated temperature data matrix is ​​input into the three-dimensional heat conduction model based on the characteristics of the LED package structure, and the thermal distribution field of the chip is obtained through boundary constraint iterative calculation. Since the heat dissipation characteristics of the LED are affected by the substrate material, packaging form and environmental conditions, the heat conduction model considers the thermal resistance characteristics between different materials to ensure the accuracy of the calculation. The temperature distribution inside the LED is obtained through numerical calculation methods, and the temperature change law of each area of ​​the chip is clarified. After obtaining the thermal distribution field, the temperature data of the PN junction area is analyzed, and the junction temperature of the LED is calculated by spatial integration and averaging methods. The PN junction area is the core area of ​​the LED photogenerated carrier recombination, and its temperature directly determines the luminous efficiency and reliability of the LED. By processing the thermal distribution data, the influence of local temperature fluctuations is eliminated, so that the obtained junction temperature value is closer to the actual working state of the LED. At the same time, the data collected by the light sensor array is processed to calculate the light efficiency parameters of the LED. Since the luminous flux of LED is closely related to the light intensity distribution, the light sensor must measure at different angles and directions, and calculate the full spatial luminous flux of LED by the method of spherical integral. In order to ensure the accuracy of measurement, the light intensity correction factor is introduced to compensate for the light intensity attenuation caused by the measurement angle and distance, so as to obtain more accurate luminous flux data. The spectral characteristics of LED are analyzed. The spectral analysis unit collects the luminous data of LED at different wavelengths, and performs weighted calculation according to the visual response function to obtain spectral parameters that are more in line with the visual characteristics of the human eye. And extract indicators such as the dominant wavelength, half-wave width and color purity of LED to evaluate its light color quality. The dominant wavelength is used to describe the main luminous color of LED, the half-wave width indicates the width of the spectrum, and the color purity reflects the saturation of the color. According to the total luminous flux value, spectral quality index and the input power value obtained by multiplying the real-time current of the light-emitting diode by the voltage, the light efficiency calculation formula is used for numerical calculation to obtain the real-time light efficiency parameters. By analyzing these data, the light efficiency changes of LED under different working conditions are monitored, and its working state is optimized so that it is always in the best operating range.

[0071] Step 400, adjusting parameters of the multi-level heat dissipation control system according to the temperature-light efficiency relationship curve to obtain a heat dissipation control instruction sequence;

[0072] Specifically, the temperature-light efficiency data measured in real time is compared and calculated with the preset optimal working junction temperature range to obtain the heat dissipation control deviation parameter, which includes temperature deviation and light efficiency deviation, wherein the temperature deviation indicates the degree of deviation between the current LED junction temperature and the optimal junction temperature range, and the light efficiency deviation reflects the decrease of the current light efficiency of the LED compared with the highest light efficiency. These two parameters jointly determine the adjustment strategy of the heat dissipation system. A control decision mapping relationship is constructed according to the temperature deviation and light efficiency deviation in the heat dissipation control deviation parameter to form a fuzzy control rule table. Since the junction temperature change of the LED is a nonlinear process, and different heat dissipation means have different adjustment effects in different junction temperature ranges, the use of fuzzy control can more flexibly cope with temperature fluctuations and achieve smoother and more accurate heat dissipation adjustment. When constructing the fuzzy control rule table, the fuzzy set of temperature deviation and light efficiency deviation is defined, and the fuzzy rules for controlling the output variables are set. For example, when the temperature deviation is small and the light efficiency deviation is small, the current heat dissipation mode is maintained, and when the temperature deviation is large and the light efficiency deviation decreases significantly, the heat dissipation intensity is increased, and the junction temperature is quickly reduced by controlling the TEC cooling plate or increasing the fan speed. Based on the fuzzy control rule table, the proportional coefficient, integral time constant and differential time constant of the PID controller are dynamically calculated to obtain an adaptive PID parameter group. The adaptive PID control strategy is adopted to adjust its parameters in real time according to the changes in temperature and light efficiency deviation, thereby improving the control accuracy and reducing the overshoot phenomenon. By introducing fuzzy control, the parameter adjustment range of the PID controller is adaptively adjusted according to real-time data. For example, when the temperature deviation is small, the integral effect of the PID is enhanced to reduce the steady-state error, and when the temperature deviation is large, the proportional coefficient is increased to speed up the response speed. According to the adaptive PID parameter group and the heat dissipation control deviation parameter, the control strategy of the multi-level heat dissipation control system is hierarchically determined to form a multi-level heat dissipation coordinated control scheme. Since the LED heat dissipation system is composed of multiple heat dissipation units, including a first-level heat conduction heat dissipation unit, a second-level liquid cooling heat dissipation unit, a third-level phase change heat dissipation unit and a fourth-level active refrigeration unit, different heat dissipation strategies are adopted in different junction temperature ranges. When the LED junction temperature is low, the temperature can be maintained stable only by passive heat conduction of the first-level heat dissipation unit. When the junction temperature gradually rises, the second-level heat dissipation unit is activated to enhance the cooling effect by adjusting the flow of the working liquid. When the junction temperature rises further and approaches the light efficiency drop threshold, the third-level phase change heat dissipation unit needs to be activated to allow the phase change material to absorb excess heat. If the LED junction temperature exceeds the optimal range and enters the high temperature range, the fourth-level heat dissipation unit is activated, that is, the TEC cooling sheet is used to achieve active cooling, and the fan speed is adjusted to improve the heat dissipation capacity. After formulating a multi-level heat dissipation collaborative control plan, power allocation calculations are performed to determine the specific control parameters of each level of heat dissipation unit.Among them, the thermal conductivity adjustment parameter of the first-level heat dissipation unit determines the optimization degree of the thermal interface, the working liquid flow value of the second-level heat dissipation unit directly affects the heat dissipation capacity of the liquid cooling system, the temperature activation threshold of the third-level heat dissipation unit determines the working state of the phase change material, and the TEC current and fan speed value of the fourth-level heat dissipation unit are related to the power consumption and efficiency of active heat dissipation. By optimizing these control parameters, the energy consumption of the heat dissipation system can be reduced while ensuring the stability of the LED light effect, thereby achieving efficient and energy-saving heat dissipation management. The above control parameter set is converted into specific execution instructions to form the final heat dissipation control instruction sequence. The thermal conductivity adjustment parameter of the first-level heat dissipation unit will be converted into a PWM modulation instruction to control the variable thermal conductivity of the thermal interface material; the working liquid flow value of the second-level heat dissipation unit will be converted into an opening instruction of the flow control valve to adjust the flow rate of the coolant; the temperature activation threshold of the third-level heat dissipation unit is used to generate a temperature threshold trigger instruction to determine the start-up time of the phase change material; the TEC current and fan speed value of the fourth-level heat dissipation unit need to be converted into a speed adjustment instruction of the heat dissipation fan to dynamically control the operating state of the air cooling and refrigeration system.

[0073] Step 500: dynamically compensate the driving current of the light emitting diode based on the heat dissipation control instruction sequence to obtain the optimal driving parameters.

[0074] Specifically, the photoelectric conversion characteristics of the light-emitting diode are measured under different junction temperature and driving current combinations, and a current-light efficiency-junction temperature data model is established. By applying different driving currents in the experimental environment and measuring the light output, light efficiency and power conversion efficiency of the LED under various temperature conditions, a series of data points are obtained, and then a complete photoelectric conversion relationship model is established using the curve fitting method to characterize the nonlinear characteristics of the light efficiency of the LED changing with the driving current and junction temperature. Based on the current-light efficiency-junction temperature data model, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated, and its change trend is analyzed through the optimization algorithm to construct the optimal operating point query matrix. The core function of this matrix is ​​to provide a fast query mechanism, so that the system can find the driving current value that can provide the highest light efficiency under any junction temperature condition. Through the analysis of experimental data, it is found that the light efficiency of the LED reaches a peak within a certain driving current range, and after exceeding this range, the light efficiency decreases due to the increase in heat loss. Through optimization calculation, the optimal driving current is accurately located at different junction temperatures, and a query matrix is ​​constructed to quickly retrieve the optimal operating point in practical applications. Combined with the target light output requirements and the current junction temperature state determined by the heat dissipation control instruction sequence, the matching conditions are retrieved in the optimal working point query matrix to obtain the working point parameters with the highest efficiency. Since the light efficiency of LED is not only affected by temperature, but also related to the light output requirements, the driving current that can maximize the light efficiency is preferred under the premise of meeting the target luminous flux, thereby reducing energy consumption and reducing the junction temperature. Through real-time temperature monitoring and query matrix comparison, the current optimal driving parameters are quickly determined to ensure that the LED works in the best operating state. Configure the working parameters of the PWM drive circuit, and calculate and temperature compensate the duty cycle of the PWM drive signal based on the highest efficiency working point parameters to correct the impact of junction temperature changes on the light efficiency of the LED. The PWM drive method controls the average input power of the LED by adjusting the duty cycle, and the change in junction temperature will cause the forward voltage and light efficiency of the LED to fluctuate. During the driving process, the duty cycle of the PWM signal is finely adjusted to ensure that the light output and color temperature of the LED remain stable. In the temperature compensation calculation process, combined with the volt-ampere characteristic curve of the LED, the PWM duty cycle is dynamically corrected to avoid driving errors caused by voltage drift. Convert the corrected PWM control parameters into specific drive control signals, and modulate the rise / fall time of the PWM waveform to compensate for the color temperature shift caused by junction temperature changes. Since the spectral characteristics of LEDs drift with junction temperature changes, especially in high-power LED applications, this color temperature shift can lead to color inconsistency. By controlling the edge characteristics of the PWM signal, the luminous stability of the LED is optimized and the impact of color temperature drift on lighting quality is reduced. Obtaining the optimal drive parameters allows the LED to always maintain efficient and stable light output under different temperature conditions, while reducing power consumption, increasing service life, and ensuring consistency in light quality.

[0075] The driving current, forward voltage and luminous flux data are extracted from the current-luminous efficiency-junction temperature data model, where the driving current determines the input power of the LED, the forward voltage affects the overall energy consumption, and the luminous flux reflects the luminous efficiency of the LED. The photoelectric conversion efficiency, that is, the ratio of the light output of the LED to the electrical input, is calculated to obtain the efficiency value set under different junction temperature and driving current combinations, which describes the photoelectric conversion performance of the LED under different working conditions. The photoelectric conversion efficiency value set is rearranged according to the two independent variables of junction temperature and driving current to form an efficiency distribution point cloud. Since the photoelectric conversion efficiency of the LED does not change linearly, but is complexly affected by multiple factors such as junction temperature and driving current, the data fitting method is used to convert the discrete efficiency distribution point cloud into a continuous photoelectric conversion efficiency surface function. Through surface fitting, a mathematical model for predicting the photoelectric conversion efficiency under arbitrary junction temperature and driving current conditions is obtained. The model reflects the trend of the light efficiency change of the LED under different temperatures and different driving currents. Based on the continuous surface function of the photoelectric conversion efficiency, the efficiency extreme point at each junction temperature is searched and calculated to determine the optimal driving current under different junction temperature conditions. Since the luminous efficiency of LED reaches its maximum value within a specific driving current range, and when the driving current is too high, the luminous efficiency will decrease due to increased heat loss, the optimal driving current value corresponding to each junction temperature is calculated and recorded as a set of junction temperature-optimal current correspondences. This set of relations is used to quickly query the optimal driving parameters of LED at different temperatures. The set of junction temperature-optimal current correspondences and the continuous surface function of photoelectric conversion efficiency are analyzed with equal luminous flux to establish an equal luminous flux optimization path under constant light output. The light output of LED will fluctuate with the change of junction temperature and driving current. In practical applications, it is necessary to ensure that the LED maintains a stable luminous flux under different temperature environments. By calculating the driving current adjustment required to maintain the same luminous flux under different junction temperatures, an equal luminous flux optimization path is constructed to ensure that the LED always maintains a stable light output under different environmental conditions and ensure the optimal luminous efficiency. The equal luminous flux optimization path is hierarchically indexed according to the luminous flux output level and junction temperature range to generate an optimal operating point query matrix containing target luminous flux, junction temperature, optimal driving current, expected luminous efficiency, and adjustment margin. The query matrix provides a fast matching function during the operation of the LED, so that the system can quickly adjust the drive current according to the current junction temperature and luminous flux requirements in real-time operation to ensure that the LED is always in the highest light efficiency working state. At the same time, the matrix provides expected light efficiency information, allowing the system to evaluate the current photoelectric conversion efficiency and further optimize it in combination with the heat dissipation strategy, thereby improving the energy efficiency of the LED, reducing power consumption, and ensuring the stability of light output.

[0076] In the embodiments of the present application, by establishing an accurate junction temperature-light efficiency mapping model and a multi-level heat dissipation control system, stable operation of the LED within the optimal operating junction temperature range is achieved, and the photoelectric conversion efficiency is significantly improved; a temperature-light efficiency real-time monitoring system and an adaptive heat dissipation control strategy are adopted to effectively reduce junction temperature fluctuations and extend the service life of the LED; the dynamic current compensation mechanism and heat dissipation control work together to reduce power consumption while maintaining stable light output, thereby improving the overall energy efficiency of the system; for multi-chip LED arrays, by precisely controlling the performance of the thermal interface material, the junction temperature uniformity is improved, and the uneven light emission and color deviation problems caused by uneven temperature are eliminated; the self-learning optimization and life prediction functions enable the system to continuously adjust the control parameters according to the LED aging characteristics, maintain long-term high-efficiency operation, and reduce maintenance costs.

[0077] In a specific embodiment, the process of executing step 100 may specifically include the following steps:

[0078] Obtain parameters of the rated power, chip structure type, emission wavelength, thermal conductivity of substrate material, and thermal resistance of packaging structure of the light-emitting diode to obtain a basic parameter set;

[0079] Based on the basic parameter set, the light-emitting diode is installed on a temperature-controllable test platform, and the photoelectric parameters are recorded within the preset range to obtain the original data of temperature-light efficiency;

[0080] Apply infrared thermal imaging and micro-thermocouple array measurement to the light-emitting diode and perform finite element thermal analysis to obtain the chip junction temperature distribution data;

[0081] Based on the original data of temperature-luminous efficiency and the distribution data of chip junction temperature, a polynomial fitting model is performed on the relationship between junction temperature and luminous flux to obtain a junction temperature-luminous efficiency function model.

[0082] Expand the analysis of the junction temperature-light efficiency function model, correlate the junction temperature with quantum efficiency, electro-optical conversion efficiency, and spectral drift parameters, and build a junction temperature-light efficiency mapping model.

[0083] The photoelectric conversion efficiency data in the junction temperature-light efficiency mapping model is analyzed to determine the temperature range with the highest photoelectric conversion efficiency and obtain the optimal operating junction temperature range.

[0084] Specifically, the rated power, chip structure type, emission wavelength, thermal conductivity of substrate material and thermal resistance of packaging structure of the light-emitting diode are acquired to obtain the basic parameter set. Among them, the rated power represents the maximum input power of the LED, that is, the product of the driving current and the forward voltage, which is expressed as:

[0085]

[0086] in, is the rated power, is the forward voltage, The chip structure type determines the internal carrier recombination mode and luminous efficiency of the LED. Different epitaxial growth processes and structural designs will affect the photoelectric conversion performance. Determined by the band gap of the semiconductor material, such as GaN LEDs are usually in the blue light band, while InGaP LEDs are mainly used in the red light band. It is a key factor affecting the heat dissipation efficiency of LEDs. Common high thermal conductivity materials include aluminum nitride and silicon carbide. This determines the difficulty of transferring the internal heat of the chip to the external heat sink, using the heat flow path calculation formula:

[0087]

[0088] in, is the junction temperature of the LED, is the ambient temperature, is the power consumption of the LED, is the package thermal resistance. Based on the basic parameter set, the LED is installed on a temperature-controllable test platform, and the photoelectric parameters are measured under different temperature conditions to obtain the original data of temperature-light efficiency. During the experiment, the luminous flux is measured by precisely controlling the temperature of the test environment and adjusting the driving current of the LED. , Light Effect And other key parameters, among which the luminous efficacy is defined as the ratio of luminous flux to input electrical power:

[0089]

[0090] In order to obtain the heat distribution inside the LED chip, infrared thermal imaging and micro-thermocouple arrays are used for temperature measurement, and the finite element thermal analysis method is used to calculate the junction temperature distribution inside the LED. Infrared thermal imaging provides the spatial distribution of the LED surface temperature, while the micro-thermocouple directly measures the temperature at the key position of the LED chip. Combining these two measurement methods, more accurate temperature distribution data can be obtained. The finite element thermal analysis method is used to establish the LED heat conduction model based on the thermal balance equation:

[0091]

[0092] in, is the material density, is the specific heat capacity, is the junction temperature, is the thermal conductivity, is the heat generation power of the LED. By solving this equation, the temperature distribution inside the LED is simulated and the junction temperature of the chip is calculated. Based on the original data of temperature-luminous efficiency and the junction temperature distribution data of the chip, a mathematical relationship model between junction temperature and luminous flux is established. The polynomial fitting method is used to construct a mathematical expression for the change of luminous efficiency with junction temperature:

[0093]

[0094] in, is the fitting coefficient, is the chip junction temperature, is the luminous flux. By fitting the experimental data, the best fitting parameters are determined, so that the model can accurately predict the trend of LED light efficiency under different temperature conditions. The junction temperature-light efficiency function model is extended and analyzed, and the junction temperature is associated with quantum efficiency, electro-optical conversion efficiency and spectral drift parameters to build a more comprehensive junction temperature-light efficiency mapping model. Quantum efficiency The efficiency of photon generation by carrier recombination inside the LED is calculated as follows:

[0095]

[0096] in, represents the quantum efficiency, is the radiative recombination rate, It is the non-radiative recombination rate. As the junction temperature increases, the non-radiative recombination increases, resulting in a decrease in quantum efficiency, which in turn affects the luminous efficacy of the LED. The relationship between electrical input power and optical output power is further considered and the calculation method is:

[0097]

[0098] in, is the external quantum efficiency of the LED, which is affected by the packaging and extraction optical structure. Spectral drift It is also an important parameter for temperature change, and its relationship is determined by the band gap temperature coefficient of the material:

[0099]

[0100] in, is the spectral shift coefficient of the material, is the reference temperature. After building the junction temperature-light efficiency mapping model, the photoelectric conversion efficiency data is analyzed to determine the temperature range with the highest photoelectric conversion efficiency, that is, the optimal operating junction temperature range. By deriving the light efficiency curve of the LED at different junction temperatures, the light efficiency extreme point is found and the optimal junction temperature range is determined. Within this range, the LED can maintain a high light efficiency while avoiding light attenuation and increased non-radiative recombination caused by excessively high temperature.

[0101] In a specific embodiment, the process of executing step 200 may specifically include the following steps:

[0102] According to the heat conduction requirements in the junction temperature-light efficiency mapping model, the aluminum nitride ceramic substrate is surface treated to form a primary heat dissipation unit with a microchannel structure;

[0103] Based on the microchannel structure of the primary heat dissipation unit, the epoxy resin material is packaged into a capillary microtube array, and a heat-conducting working liquid is filled into the capillary microtube array to obtain a secondary heat dissipation unit;

[0104] Conduct material analysis on the contact interface of the secondary heat dissipation unit, select and configure the graphene / phase change material composite layer, and obtain the tertiary heat dissipation unit;

[0105] According to the temperature range of the optimal working junction temperature range, the parameters of the TEC cooling sheet and the high-efficiency centrifugal fan are matched and the power is configured to obtain a four-stage heat dissipation unit;

[0106] Physically connecting and optimizing contact pressure of the primary heat dissipation unit, the secondary heat dissipation unit, the tertiary heat dissipation unit, and the quaternary heat dissipation unit to obtain an integrated heat dissipation assembly;

[0107] The integrated heat dissipation component is connected to the temperature controller, the start threshold and control logic of each level of heat dissipation unit are programmed and set, and a closed-loop feedback control mechanism based on the optimal working junction temperature range is established to obtain a multi-level heat dissipation control system.

[0108] Specifically, according to the heat conduction requirements in the junction temperature-light efficiency mapping model, the aluminum nitride ceramic substrate is surface treated to form a primary heat dissipation unit with a microchannel structure. Since aluminum nitride has a high thermal conductivity and can effectively conduct the heat generated by the chip, designing a microchannel structure on the substrate can significantly improve the heat dissipation efficiency. The role of the microchannel is to increase the heat exchange area and optimize heat transfer through fluid dynamics to reduce the heat flux density on the chip surface. The heat conduction process is described by the Fourier heat conduction equation:

[0109]

[0110] in, represents the heat flux density per unit area, k is the thermal conductivity of the aluminum nitride ceramic substrate, T is the temperature, is the distance in the direction of heat flow. By forming a microchannel structure on the substrate surface, the The transfer efficiency is improved, so that the junction temperature of the LED chip is reduced when it is working. On the basis of the primary heat dissipation unit, in order to optimize the heat transfer effect, the epoxy resin material is encapsulated into a capillary microtube array based on the microchannel structure, and the capillary microtube array is filled with heat-conducting working liquid to form a secondary heat dissipation unit. The function of the capillary microtube is to utilize the capillary effect and liquid phase circulation mechanism to achieve more efficient heat transfer through the evaporation and condensation process of the liquid. The phase change process of the liquid is described by the Clausius-Clapeyron equation:

[0111]

[0112] in, is the steam pressure, is the latent heat of phase change, is the temperature, is the volume per unit mass. By rationally selecting a heat-conducting working liquid such as deionized water, ethanol or fluoride coolant, ensuring high phase change efficiency during heat conduction while maintaining stable liquid circulation, the heat dissipation capacity is significantly enhanced. The contact interface of the secondary heat dissipation unit is analyzed, and a graphene / phase change material composite layer is selected as the thermal interface material to form a tertiary heat dissipation unit. The high thermal conductivity of graphene significantly enhances the heat flux density of the interface, while the phase change material balances the heat dissipation effect when the temperature fluctuates by absorbing and releasing latent heat. The thermal conductivity calculation of graphene is expressed by the following formula:

[0113]

[0114] in, is the area of ​​the heat dissipation interface, is the interface temperature difference, is the heat flow path length. By optimizing the thickness of the graphene coating, the LED can maintain a low junction temperature when working at high power. In order to ensure that the LED can maintain the optimal junction temperature range under different power and ambient temperature conditions, the TEC cooling sheet and high-efficiency centrifugal fan are integrated in the four-stage heat dissipation unit, and parameter matching and power configuration are performed. The TEC cooling sheet uses the Peltier effect to control the temperature difference between the hot and cold ends through current. Its cooling power is calculated using the following formula:

[0115]

[0116] in, is the cooling capacity of the TEC refrigeration sheet, is the Seebeck coefficient, is the input current, is the cold end temperature, is the resistance of the TEC, is the thermal conductivity of TEC, is the temperature difference between the hot and cold ends. By optimizing the current input of the TEC, the temperature of the LED is precisely controlled, and combined with the active heat dissipation function of the centrifugal fan, the system maintains the best light effect under various operating conditions. The heat dissipation units at each level are physically connected and the contact pressure is optimized to form a complete integrated heat dissipation assembly. The optimization of the contact pressure ensures that the thermal interface material can be fully fitted, improves the thermal conductivity, and avoids local overheating caused by poor contact. By accurately calculating the thermal resistance of the contact interface and adjusting the pressure distribution, the overall thermal resistance is minimized, thereby improving the heat dissipation performance. The integrated heat dissipation assembly is connected to the temperature controller, and the start-up threshold and control logic of the heat dissipation units at each level are programmed to establish a closed-loop feedback control mechanism based on the optimal working junction temperature range, and build a complete multi-level heat dissipation control system. The system monitors the junction temperature of the LED in real time and dynamically adjusts the operating mode of the heat dissipation units at each level according to the current working state. For example, when operating at low power, only the first and second heat dissipation units are enabled, while in high power mode, the third and fourth heat dissipation units are gradually activated to ensure that the junction temperature is always in the optimal range. The feedback mechanism of the controller uses a PID algorithm to set the target junction temperature. :

[0117]

[0118] in, , , are the proportional, integral and differential coefficients of PID control respectively, is the error between the current junction temperature and the target junction temperature. By optimizing the control parameters, the stability of the cooling system under different working conditions is ensured, and precise temperature control is achieved.

[0119] In a specific embodiment, the process of executing step 300 may specifically include the following steps:

[0120] The peripheral area of ​​the light-emitting diode is planned to obtain a temperature sensor array for measuring the temperature distribution on the chip surface, and silicon photodiode sensors are arranged around the light-emitting surface of the light-emitting diode according to the light intensity distribution law to obtain a light sensor array for collecting light flux data;

[0121] Connecting the temperature sensor array and the light sensor array to the data acquisition and processing module;

[0122] The surface temperature data collected by the temperature sensor array is calculated to obtain the chip junction temperature value, and the light intensity data and wavelength data collected by the light sensor array are integrated to obtain the real-time light effect parameters;

[0123] The chip junction temperature value and the real-time light efficiency parameter are matched and data fitted to obtain a temperature-light efficiency relationship curve that characterizes the working state of the light-emitting diode.

[0124] Specifically, the peripheral area of ​​the light-emitting diode is planned to obtain a temperature sensor array for measuring the temperature distribution on the chip surface, and silicon photodiode sensors are arranged around the light-emitting surface of the light-emitting diode according to the light intensity distribution law to form a light sensor array. The arrangement of the temperature sensor array is based on the thermal distribution characteristics of the LED chip. Since the junction temperature of the LED chip affects the light efficiency, high-precision thermocouples or thermistors are placed in multiple key areas of the chip to ensure that its surface temperature distribution can be accurately measured. The response time of the temperature sensor should be fast enough to capture temperature fluctuations in real time. In order to characterize the temperature distribution, the Fourier heat conduction equation is used to describe the heat flow transmission inside the LED. By arranging temperature sensors at different positions, the temperature in different areas is measured. The value is used to calculate the heat flux distribution. At the same time, silicon photodiode sensors are arranged around the LED light-emitting surface to obtain light flux data. Since the light intensity distribution of LEDs usually conforms to the Lambert distribution and its light flux changes with angle, the arrangement of light sensors needs to be based on the light intensity distribution law. Light sensors are arranged in a spherical array to collect light intensity data at multiple angles. The calculation of light surge is obtained by the integral method:

[0125]

[0126] in, is the total luminous flux, For the angle and The light intensity in the direction, is the solid angle. By arranging light sensors at different angles and integrating the collected data, the light output of the LED can be accurately obtained. The temperature sensor array and the light sensor array are connected to the data acquisition and processing module to realize real-time data acquisition and transmission. The data acquisition module includes an analog-to-digital conversion circuit, a high-speed signal processing unit, and a wireless or wired transmission module to receive the data of each sensor in real time and perform preliminary processing. The data of the temperature sensor needs to be filtered to remove measurement noise and improve data stability, while the data of the light sensor is gain adjusted to compensate for the nonlinear response of the sensor. After obtaining the temperature data, the junction temperature of the chip is calculated. Since the heat of the LED chip is mainly conducted to the external heat dissipation structure through the substrate, the actual junction temperature of the chip is calculated using the thermal resistance network model, and the surface temperature data is converted into the real junction temperature inside the chip. At the same time, the light intensity data and wavelength data collected by the light sensor are integrated to calculate the real-time light efficiency parameters. In order to more accurately analyze the luminous characteristics of the LED, the main wavelength, half-wave width and color purity of the LED are analyzed in combination with the spectral data. The processing of the spectral data uses a visual response function for weighted calculation to obtain parameters that meet the visual characteristics of the human eye. The half-wave width indicates the width of the spectrum, which is calculated as the wavelength range of the spectrum at half maximum, while the color purity indicates the monochromaticity of the spectrum. The chip junction temperature value and the real-time light efficiency parameter are paired, and the data fitting method is used to construct a temperature-light efficiency relationship curve that characterizes the working state of the LED. Using the polynomial fitting method, the fitting function is expressed as:

[0127]

[0128] in, is the fitting coefficient, is the junction temperature, By fitting the experimental data, the trend of LED light efficiency changing with junction temperature is depicted, and the optimal operating junction temperature range is found to optimize the heat dissipation control strategy of LED.

[0129] In a specific embodiment, the execution step calculates the surface temperature data collected by the temperature sensor array to obtain the chip junction temperature value, and integrates the light intensity data and wavelength data collected by the light sensor array to obtain the real-time light effect parameters. The process may specifically include the following steps:

[0130] The surface temperature data set collected by the temperature sensor array is subjected to noise elimination and abnormal data cleaning to obtain a calibrated temperature data matrix;

[0131] Substitute the calibrated temperature data matrix into the three-dimensional finite element heat conduction equation based on the characteristics of the light-emitting diode package structure, perform boundary constraint iterative calculation, and obtain the heat distribution field function;

[0132] Perform spatial integration and averaging on the temperature values ​​of the corresponding PN junction area in the heat distribution field function to obtain the chip junction temperature value;

[0133] The spherical integral algorithm and the light intensity correction factor are applied to the light intensity data collected by the light sensor array at different solid angles to calculate the total light flux in the whole space and obtain the total light flux value;

[0134] The wavelength data collected by the spectrum analysis unit is weighted according to the visual response function, and the main wavelength, half-wave width, and color purity parameters are extracted to obtain the spectrum quality index;

[0135] According to the total luminous flux value, the spectrum quality index and the input power value obtained by multiplying the real-time current of the light-emitting diode by the voltage, the light efficiency calculation formula is used to perform numerical calculations to obtain the real-time light efficiency parameters.

[0136] Specifically, the surface temperature data set collected by the temperature sensor array is subjected to noise elimination and abnormal data cleaning to obtain a calibrated temperature data matrix. The temperature data is smoothed using low-pass filtering and median filtering methods, where low-pass filtering removes high-frequency noise and median filtering effectively removes mutation data points. Assume that the original temperature data measured by the sensor is , the temperature data matrix after filtering is expressed as:

[0137]

[0138] in, is the filtered temperature value, is the window size, is half of the filter window, through optimization The value of can avoid losing valid information while maintaining data smoothness. For abnormal data points, statistical methods are used to clean them up, such as setting the mean and standard deviation , if a temperature value satisfy ( Usually 3) is taken, it is regarded as an abnormal point, and the neighboring data is used for interpolation compensation to obtain the calibrated temperature data matrix. The calibrated temperature data matrix is ​​substituted into the three-dimensional finite element heat conduction equation based on the characteristics of the light-emitting diode package structure and the boundary constraint iterative calculation is performed to obtain the heat distribution field function. The heat transfer inside the LED is affected by the thermal conductivity of the material, the boundary heat dissipation conditions and the chip power consumption, and is modeled using the three-dimensional steady-state heat conduction equation:

[0139]

[0140] in, are the thermal conductivity of LED in different directions, is the heat power density inside the LED chip, is the temperature distribution function. The equation is solved by the finite element method, and boundary conditions such as convection heat transfer boundary, radiation heat transfer boundary or adiabatic boundary are applied to obtain the heat distribution field function of the LED , which describes the temperature distribution inside the entire LED structure. The temperature values ​​of the PN junction area in the heat distribution field are spatially integrated and averaged to obtain the chip junction temperature value. Since the PN junction area is the core area of ​​carrier recombination inside the LED, its temperature directly determines the photoelectric conversion efficiency, so its average temperature is calculated by the integration method:

[0141]

[0142] in, is the average temperature of the PN junction area, is the volume of the PN junction, is the temperature distribution field function. The accurate chip junction temperature is obtained through numerical integration for subsequent light efficiency calculation. At the same time, the spherical integration algorithm is applied to the light intensity data collected by the light sensor array at different solid angles, and the full-space luminous flux is calculated in combination with the light intensity correction factor. The luminous flux of an LED is the sum of its light intensity in all directions, which is calculated using the following integral formula:

[0143]

[0144] in, is the total luminous flux, The direction angle of the LED The light intensity at It is a small solid angle. By arranging light sensors at different angles and integrating the measured data in spherical coordinates, the total luminous flux value of the LED is obtained. After the luminous flux calculation is completed, the wavelength data collected by the spectral analysis unit is subjected to visual response weighted calculation, and parameters such as the main wavelength, half-wave width and color purity are extracted to obtain the spectral quality index. The calculation formula for the main wavelength of the LED is:

[0145]

[0146] in, is the dominant wavelength, is the spectral power distribution. The half-wave width is defined as the wavelength range of the spectrum at half maximum value, and the color purity is calculated as the contrast between the monochromaticity of the LED and the white light reference light source. These parameters are used to evaluate the light color quality of the LED. According to the calculated total luminous flux value, spectral quality index and input power value obtained by multiplying the real-time current and voltage of the LED, the light efficiency calculation formula is used for numerical calculation to obtain the real-time light efficiency parameters:

[0147]

[0148] in, For the light effect of LED, is the total luminous flux, is the operating voltage, is the operating current. By calculating the luminous efficacy, the energy efficiency conversion of the LED is evaluated and used to optimize its heat dissipation and driving strategy.

[0149] In a specific embodiment, the process of executing step 400 may specifically include the following steps:

[0150] Compare and calculate the temperature-light efficiency relationship curve with the optimal working junction temperature range to obtain the heat dissipation control deviation parameter;

[0151] According to the temperature deviation and light efficiency deviation in the heat dissipation control deviation parameter, a control decision mapping relationship is constructed to obtain a fuzzy control rule table;

[0152] Based on the fuzzy control rule table, the proportional coefficient, integral time constant and differential time constant of the PID controller are dynamically calculated to obtain the adaptive PID parameter group;

[0153] According to the adaptive PID parameter group and the heat dissipation control deviation parameter, the control strategy of the multi-level heat dissipation control system is hierarchically determined to obtain a multi-level heat dissipation coordinated control scheme;

[0154] The power allocation calculation is performed on the multi-stage heat dissipation collaborative control scheme to determine the thermal efficiency adjustment parameters of the first-stage heat dissipation unit, the working liquid flow value of the second-stage heat dissipation unit, the temperature activation threshold of the third-stage heat dissipation unit, and the TEC current and fan speed value of the fourth-stage heat dissipation unit, and the control parameter set of each stage of the heat dissipation unit is obtained;

[0155] The control parameter set is converted into PWM modulation instructions, flow control valve opening instructions, temperature threshold trigger instructions and cooling fan speed instructions to obtain a cooling control instruction sequence.

[0156] Specifically, the temperature-light efficiency relationship curve is compared with the optimal working junction temperature range to obtain the heat dissipation control deviation parameter. The temperature-light efficiency relationship curve represents the change of light efficiency of LED under different junction temperature conditions, and the optimal working junction temperature range is the temperature range in which LED operates in a high-efficiency state, which is measured through experiments. Out of the optimal range , then calculate the temperature deviation ,Right now:

[0157]

[0158] in, Is the best operating temperature for LED. When it is positive, it means that the junction temperature is higher than the ideal value and the heat dissipation intensity needs to be increased; when When it is negative, the heat dissipation needs to be reduced to maintain energy efficiency. The measured light efficiency Expected light effect The calculations show that:

[0159]

[0160] in, is the theoretical luminous efficacy of LED at the optimal junction temperature. If it is too large, it means that the light efficiency is low and the cooling system needs to be adjusted to optimize thermal management. and , construct the control decision mapping relationship, and obtain the fuzzy control rule table. Fuzzy control is a nonlinear control method suitable for processing systems with strong uncertainty. In heat dissipation control, due to the complex dynamic characteristics of LED heat conduction, traditional linear control methods are difficult to accurately adjust. Fuzzy control rule tables are used to classify temperature deviation and light efficiency deviation, such as "high temperature and high deviation", "high temperature and low deviation", "low temperature and high deviation", "low temperature and low deviation", etc., and set corresponding heat dissipation strategies. For example, when and When both are large, a more advanced cooling unit should be started immediately to improve the cooling capacity. Smaller and If the value is also small, the existing heat dissipation state is maintained. The fuzzy control rule table is defined as:

[0161]

[0162] in, is the heat dissipation control quantity. Based on the fuzzy control rule table, the proportional coefficient, integral time constant and differential time constant of the PID controller are dynamically calculated to obtain the adaptive PID parameter group. The PID controller is used to accurately adjust the heat dissipation system, and its control formula is:

[0163]

[0164] in, is the proportionality coefficient, which determines the direct response speed of the cooling system to temperature deviation; is the integration time constant, used to eliminate long-term temperature errors; is the differential time constant, which is used to predict the temperature change trend and adjust the heat dissipation in advance. In order to improve the response speed, adaptive PID control is adopted to dynamically adjust the PID parameters according to the fuzzy control output so that when Increase when too large To speed up the reaction, Increase when the change is faster To suppress overshoot, by adjusting To optimize steady-state error correction. According to the adaptive PID parameter group and the heat dissipation control deviation parameter, the control strategy of the multi-level heat dissipation control system is graded to form a multi-level heat dissipation collaborative control solution. The multi-level heat dissipation system is composed of multiple different heat dissipation units, each of which has a different function. For example, the first-level heat dissipation unit mainly relies on substrate heat conduction, the second-level heat dissipation unit uses liquid cooling, the third-level heat dissipation unit uses phase change materials to absorb heat, and the fourth-level heat dissipation unit combines TEC cooling and fan active heat dissipation. According to and Calculate the current required cooling level, such as when When the heat dissipation is small, the first and second stage heat dissipation is maintained, and when When the temperature is relatively high, the third and fourth heat dissipation units are activated to ensure that the LED operates within the optimal temperature range. After determining the multi-level heat dissipation coordinated control scheme, power allocation calculation is performed to determine the specific control parameters of each level of heat dissipation unit. The thermal conductivity of the first level heat dissipation unit is determined by the thermal resistance of the material. The optimization formula is:

[0165]

[0166] in, is the heat transfer power, is the ambient temperature. Liquid flow rate of the secondary cooling unit Need to match the junction temperature change, the calculation formula is:

[0167]

[0168] in, is the specific heat of the liquid, is the liquid mass flow rate, is the phase change latent heat of the liquid. The activation threshold of the phase change material of the three-stage heat dissipation unit Determined by the phase change temperature, the TEC cooling current of the four-stage cooling unit The calculation is as follows:

[0169]

[0170] in, is the TEC cooling power, is the Seebeck coefficient, is the TEC resistance, is the TEC thermal conductivity, is the temperature difference between the hot and cold ends. The speed of the fan Determined by power requirements:

[0171]

[0172] in, is the fan input power, is the air density, is the cross-sectional area of ​​the fan, The control parameter set is converted into specific execution instructions to form a heat dissipation control instruction sequence. These instructions include PWM modulation instructions for adjusting the power of the TEC cooling plate; flow control valve opening instructions to adjust the heat dissipation capacity of the liquid cooling system; temperature threshold trigger instructions for activating phase change material heat dissipation; and heat dissipation fan speed instructions for dynamically adjusting the air convection rate.

[0173] In a specific embodiment, the process of executing step 500 may specifically include the following steps:

[0174] The photoelectric conversion characteristics of light-emitting diodes were measured under different junction temperature and driving current combinations, and a current-light efficiency-junction temperature data model was established;

[0175] Based on the current-light efficiency-junction temperature data model, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed to obtain the optimal operating point query matrix;

[0176] According to the target light output requirements and the current junction temperature state determined by the heat dissipation control instruction sequence, the matching conditions are retrieved in the optimal operating point query matrix to obtain the highest efficiency operating point parameters;

[0177] Configure the working parameters of the PWM drive circuit, and based on the highest efficiency working point parameters, calculate and temperature compensate the duty cycle of the PWM drive signal to obtain the PWM control parameters after temperature compensation;

[0178] The temperature-compensated PWM control parameters are converted into drive control signals, and the rise / fall time of the PWM waveform is modulated to compensate for the color temperature deviation caused by junction temperature changes to obtain the optimal drive parameters.

[0179] Specifically, a test system is established to accurately control the operating current and junction temperature of the LED and measure its luminous flux, luminous efficiency and electrical power to build a current-luminous efficiency-junction temperature data model. and ambient temperature , measure the luminous flux of LED and input power , light effect Calculated as:

[0180]

[0181] in, is the luminous flux of the LED, is the input power. The input power is determined by the LED drive voltage and drive current The calculations show that:

[0182]

[0183] in, is the forward voltage of the LED, By measuring the luminous efficacy under different junction temperatures and current conditions, a three-dimensional data model is established. , where the junction temperature Affects the internal quantum efficiency of the LED, and the drive current Affects its electro-optical conversion efficiency. Based on the current-luminous efficiency-junction temperature data model, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed to obtain the optimal working point query matrix. Photoelectric conversion efficiency Defined as the ratio of the LED's light output power to its input electrical power:

[0184]

[0185] At a fixed junction temperature Under these conditions, the photoelectric conversion efficiency shows a nonlinear trend with the change of driving current. The maximum value is reached at the junction temperature, so the optimal drive current is calculated at each junction temperature. , which is defined as:

[0186]

[0187] By traversing all junction temperatures And the corresponding optimal drive current , construct the optimal operating point query matrix, which stores the highest light efficiency point and the corresponding driving current at different junction temperatures. According to the target light output requirements and the current junction temperature state determined by the heat dissipation control instruction sequence, the matching conditions are retrieved in the optimal operating point query matrix to obtain the operating point parameters with the highest efficiency. Assuming the current junction temperature is , the target luminous flux is , then find the query matrix that satisfies:

[0188]

[0189] The driving current with the highest light efficiency , and thus determine the optimal driving parameters. After determining the optimal operating point, configure the operating parameters of the PWM drive circuit, and based on the highest efficiency operating point parameters, calculate and temperature compensate the duty cycle of the PWM drive signal to obtain the temperature-compensated PWM control parameters. Driven by target current Sure:

[0190]

[0191] in, The maximum allowable drive current of the PWM drive circuit. Since the volt-ampere characteristic of the LED changes with temperature, the PWM signal is temperature compensated to correct the reduction in light efficiency caused by the increase in junction temperature. The compensated PWM duty cycle Calculated as:

[0192]

[0193] in, is the temperature compensation coefficient, The temperature-compensated PWM control parameters are converted into drive control signals, and the rise / fall time of the PWM waveform is modulated to compensate for the color temperature shift caused by the junction temperature change, and the optimal drive parameters are obtained. Since the spectrum of the LED will redshift as the junction temperature increases, its main wavelength The relationship with temperature is expressed as:

[0194]

[0195] in, is the dominant wavelength at the reference temperature, is the spectral drift coefficient. In order to reduce the impact of color temperature drift, adjust the rise / fall time of the PWM waveform to optimize the pulse current response of the LED. The rise time of the PWM waveform and fall time Adjustments are required to compensate for the effects of spectral drift on light color:

[0196]

[0197]

[0198] in, and are the rise and fall times under reference conditions, is the waveform adjustment factor.

[0199] In a specific embodiment, the execution step is based on the current-light efficiency-junction temperature data model, and the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed. The process of obtaining the optimal working point query matrix can specifically include the following steps:

[0200] The driving current, forward voltage and luminous flux data in the current-luminous efficiency-junction temperature data model are extracted and the photoelectric conversion efficiency is calculated to obtain a photoelectric conversion efficiency value set;

[0201] The photoelectric conversion efficiency value set is rearranged according to the two independent variables of junction temperature and driving current to obtain the efficiency distribution point cloud, and the efficiency distribution point cloud is fitted with a continuous surface to obtain the photoelectric conversion efficiency continuous surface function;

[0202] Based on the continuous surface function of photoelectric conversion efficiency, the efficiency extreme point at each junction temperature is searched and calculated to obtain the set of corresponding relations between junction temperature and optimal current;

[0203] Perform equal luminous flux analysis on the set of junction temperature-optimal current correspondence and the photoelectric conversion efficiency continuous surface function, and establish an equal luminous flux optimization path under constant light output;

[0204] The equal-luminous flux optimization path is hierarchically indexed according to the luminous flux output level and junction temperature range to generate an optimal operating point query matrix including target luminous flux, junction temperature, optimal driving current, expected luminous efficacy and adjustment margin.

[0205] Specifically, key physical quantities are extracted from the current-luminous efficiency-junction temperature data model, including drive current, forward voltage and luminous flux data. The photoelectric conversion efficiency is defined as the ratio of the LED's light output power to its input electrical power, and is calculated using the following formula:

[0206]

[0207] in, is the photoelectric conversion efficiency, is the luminous flux of the LED, is the forward voltage of the LED, is the driving current. By measuring different junction temperatures and drive current Next and , calculate the photoelectric conversion efficiency under different conditions, and form a photoelectric conversion efficiency value set. and drive current As an independent variable, the data is rearranged to construct a complete efficiency distribution point cloud. Since the photoelectric conversion efficiency of LED is a nonlinear function that fluctuates with the junction temperature and driving current, the point cloud data is represented as discrete scattered points on a high-dimensional surface. In order to obtain a continuous representation of the photoelectric conversion efficiency, the efficiency distribution point cloud is fitted, and finally the continuous surface function of the photoelectric conversion efficiency is obtained through polynomial regression, spline interpolation or neural network fitting. Its mathematical expression is expressed as:

[0208]

[0209] in, is the photoelectric conversion efficiency, is the fitting coefficient, is the junction temperature, is the driving current. Through the least squares fitting or gradient optimization method, the optimal fitting parameters are found so that the surface function can better approximate the experimental data. Based on the continuous surface function of the photoelectric conversion efficiency, at each junction temperature The optimal drive current at this temperature is found by searching for the extreme value. , that is, the driving current at which the photoelectric conversion efficiency reaches the maximum value. Mathematically, this process is obtained by solving the partial derivative of the efficiency surface function:

[0210]

[0211] Solve After that, the set of corresponding relations between junction temperature and optimal current is obtained:

[0212]

[0213] This indicates that at different junction temperatures, LEDs should use different driving currents to achieve the highest luminous efficiency. An isoluminous flux analysis is performed on the set of junction temperature-optimal current correspondences and the photoelectric conversion efficiency continuous surface function to establish an optimization path when the luminous flux is constant. Since the luminous flux of an LED is affected by the driving current and junction temperature, it is expressed as a function:

[0214]

[0215] in, It is obtained by fitting the experimental data. In order to keep the luminous flux constant, find all the conditions that satisfy:

[0216]

[0217] in is the target luminous flux value. By solving this equation, the equal luminous flux optimization path is obtained, that is, the optimal driving current required to maintain a constant luminous flux under different junction temperature conditions. In order to facilitate rapid query and control, the equal luminous flux optimization path is hierarchically indexed according to the luminous flux output level and junction temperature range, and the optimal working point query matrix is ​​constructed. The matrix includes multiple key parameters: target luminous flux , Junction temperature , optimal drive current , expected light effect And the adjustment margin , where the adjustment margin represents the allowable drive current adjustment range under the current junction temperature conditions to adapt to different heat dissipation conditions.

[0218] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0219] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0220] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent heat dissipation control method for improving the light efficiency of light-emitting diodes, characterized in that: The method comprises: Measure the temperature-light efficiency of light-emitting diodes, establish a junction temperature-light efficiency mapping model, and determine the optimal operating junction temperature range; Based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range, the heat dissipation units are configured in a hierarchical manner to obtain a multi-level heat dissipation control system; Deploy a temperature sensor array and a light sensor array in the light emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve; According to the temperature-light efficiency relationship curve, the parameters of the multi-level heat dissipation control system are adjusted to obtain a heat dissipation control instruction sequence; Based on the heat dissipation control instruction sequence, the driving current of the light-emitting diode is dynamically compensated to obtain the optimal driving parameters; specifically comprising: measuring the photoelectric conversion characteristics of the light-emitting diode under different junction temperature and driving current combinations to establish a current-light efficiency-junction temperature data model; based on the current-light efficiency-junction temperature data model, calculating and analyzing the photoelectric conversion efficiency under different junction temperature and driving current combinations to obtain an optimal operating point query matrix; according to the target light output requirements and the current junction temperature state determined by the heat dissipation control instruction sequence, searching for matching conditions in the optimal operating point query matrix to obtain the highest efficiency operating point parameters; configuring the operating parameters of the PWM driving circuit, and based on the highest efficiency operating point parameters, calculating and temperature-compensating the duty cycle of the PWM driving signal to obtain the temperature-compensated PWM control parameters; converting the temperature-compensated PWM control parameters into a driving control signal, and modulating the rise / fall time of the PWM waveform to compensate for the color temperature deviation caused by the junction temperature change to obtain the optimal driving parameters.

2. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 1, characterized in that: The temperature-light efficiency measurement of the light emitting diode, establishment of a junction temperature-light efficiency mapping model and determination of an optimal operating junction temperature range include: Obtain parameters of the rated power, chip structure type, emission wavelength, thermal conductivity of substrate material, and thermal resistance of packaging structure of the light-emitting diode to obtain a basic parameter set; Based on the basic parameter set, the light emitting diode is installed on a temperature controllable test platform, and photoelectric parameters are recorded within a preset range to obtain temperature-light efficiency raw data; Apply infrared thermal imaging and micro-thermocouple array measurement to the light-emitting diode and perform finite element thermal analysis to obtain chip junction temperature distribution data; Based on the temperature-light efficiency raw data and the chip junction temperature distribution data, a polynomial fitting model is performed on the relationship between junction temperature and luminous flux to obtain a junction temperature-light efficiency function model; An extended analysis is performed on the junction temperature-light efficiency function model, and a correlation analysis is performed between the junction temperature and the quantum efficiency, the electro-optical conversion efficiency, and the spectrum drift parameter to construct a junction temperature-light efficiency mapping model; The photoelectric conversion efficiency data in the junction temperature-light efficiency mapping model is analyzed to determine the temperature range with the highest photoelectric conversion efficiency, thereby obtaining the optimal operating junction temperature range.

3. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 1, characterized in that: The heat dissipation units are configured in a hierarchical manner based on the junction temperature-light efficiency mapping model and the optimal working junction temperature range to obtain a multi-level heat dissipation control system, including: Performing surface treatment on the aluminum nitride ceramic substrate according to the heat conduction requirements in the junction temperature-light efficiency mapping model to form a primary heat dissipation unit with a microchannel structure; Based on the microchannel structure of the primary heat dissipation unit, epoxy resin material is packaged into a capillary microtube array, and a heat-conducting working liquid is filled into the capillary microtube array to obtain a secondary heat dissipation unit; Conducting material analysis on the contact interface of the secondary heat dissipation unit, selecting and configuring a graphene / phase change material composite layer, and obtaining a tertiary heat dissipation unit; According to the temperature range of the optimal working junction temperature range, parameter matching and power configuration are performed on the TEC cooling sheet and the high-efficiency centrifugal fan to obtain a four-stage heat dissipation unit; Physically connecting and optimizing contact pressure of the primary heat dissipation unit, the secondary heat dissipation unit, the tertiary heat dissipation unit, and the quaternary heat dissipation unit to obtain an integrated heat dissipation assembly; The integrated heat dissipation component is connected to a temperature controller, the start threshold and control logic of each level of heat dissipation units are programmed and set, a closed-loop feedback control mechanism based on the optimal working junction temperature range is established, and a multi-level heat dissipation control system is obtained.

4. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 1, characterized in that: The temperature sensor array and the light sensor array are deployed in the light emitting diode to collect real-time data and obtain a temperature-light efficiency relationship curve, including: Performing point planning on the peripheral area of ​​the light-emitting diode to obtain a temperature sensor array for measuring the temperature distribution on the chip surface, and arranging silicon photodiode sensors around the light-emitting surface of the light-emitting diode according to the light intensity distribution law to obtain a light sensor array for collecting light flux data; Connecting the temperature sensor array and the light sensor array to a data acquisition and processing module; Calculating the surface temperature data collected by the temperature sensor array to obtain the chip junction temperature value, and integrating the light intensity data and wavelength data collected by the light sensor array to obtain real-time light effect parameters; The chip junction temperature value and the real-time light effect parameter are matched and data fitted to obtain a temperature-light effect relationship curve representing the working state of the light emitting diode.

5. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 4, characterized in that: The surface temperature data collected by the temperature sensor array is calculated to obtain the chip junction temperature value, and the light intensity data and wavelength data collected by the light sensor array are integrated to obtain the real-time light effect parameters, including: Eliminating noise and cleaning abnormal data on the surface temperature data set collected by the temperature sensor array to obtain a calibrated temperature data matrix; Substituting the calibrated temperature data matrix into a three-dimensional finite element heat conduction equation based on the structural characteristics of the light-emitting diode package, performing boundary constraint iterative calculations, and obtaining a heat distribution field function; Performing spatial integration and averaging processing on the temperature values ​​of the corresponding PN junction area in the heat distribution field function to obtain the chip junction temperature value; Applying a spherical integral algorithm and a light intensity correction factor to the light intensity data collected by the light sensor array at different solid angles to calculate the total space light flux, thereby obtaining a total light flux value; The wavelength data collected by the spectrum analysis unit is weighted according to the visual response function, and the main wavelength, half-wave width, and color purity parameters are extracted to obtain the spectrum quality index; According to the total luminous flux value, the spectral quality index and the input power value obtained by multiplying the real-time current of the light emitting diode by the voltage, a light efficiency calculation formula is applied to perform numerical calculation to obtain real-time light efficiency parameters.

6. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 3, characterized in that: The step of adjusting the parameters of the multi-stage heat dissipation control system according to the temperature-light efficiency relationship curve to obtain a heat dissipation control instruction sequence includes: Comparing and calculating the temperature-light efficiency relationship curve with the optimal operating junction temperature range to obtain a heat dissipation control deviation parameter; Constructing a control decision mapping relationship according to the temperature deviation and the light efficiency deviation in the heat dissipation control deviation parameter to obtain a fuzzy control rule table; Based on the fuzzy control rule table, dynamically calculate the proportional coefficient, integral time constant and differential time constant of the PID controller to obtain an adaptive PID parameter group; According to the adaptive PID parameter group and the heat dissipation control deviation parameter, the control strategy of the multi-stage heat dissipation control system is hierarchically determined to obtain a multi-stage heat dissipation coordinated control scheme; Performing power allocation calculation on the multi-stage heat dissipation collaborative control scheme, determining the thermal conductivity adjustment parameter of the first-stage heat dissipation unit, the working liquid flow value of the second-stage heat dissipation unit, the temperature activation threshold of the third-stage heat dissipation unit, and the TEC current and fan speed value of the fourth-stage heat dissipation unit, and obtaining the control parameter set of each stage of the heat dissipation unit; The control parameter set is converted into a PWM modulation instruction, a flow control valve opening instruction, a temperature threshold trigger instruction and a cooling fan speed instruction to obtain a cooling control instruction sequence.

7. The intelligent heat dissipation control method for improving the light efficiency of light emitting diodes according to claim 1, characterized in that: Based on the current-light efficiency-junction temperature data model, the photoelectric conversion efficiency under different junction temperature and driving current combinations is calculated and analyzed to obtain the optimal working point query matrix, including: Extracting the driving current, forward voltage and luminous flux data in the current-luminous efficiency-junction temperature data model and calculating the photoelectric conversion efficiency to obtain a photoelectric conversion efficiency value set; Rearranging the photoelectric conversion efficiency value set according to two independent variables, junction temperature and driving current, to obtain an efficiency distribution point cloud, and performing continuous surface fitting on the efficiency distribution point cloud to obtain a photoelectric conversion efficiency continuous surface function; Based on the photoelectric conversion efficiency continuous surface function, searching and calculating the efficiency extreme point at each junction temperature to obtain a set of junction temperature-optimal current correspondence relationships; Performing isoluminous flux analysis on the set of junction temperature-optimal current correspondences and the photoelectric conversion efficiency continuous surface function to establish an isoluminous flux optimization path under constant light output; The equal luminous flux optimization path is hierarchically indexed and constructed according to the luminous flux output level and the junction temperature range, and an optimal operating point query matrix including the target luminous flux, junction temperature, optimal driving current, expected luminous efficacy and adjustment margin is generated.

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