A method for temperature zone adjustment of backlight modules for display devices

Abstract

This invention discloses a temperature zoning adjustment method for backlight modules of display devices, comprising: collecting real-time temperature, power consumption feedback signals, and drive current change information of each zone of the backlight module through a multi-channel temperature sensing unit mounted on a global temperature control logic main control chip; dividing temperature-sensitive and non-sensitive regions by calling a zone thermal field spatiotemporal coupling identification model to determine the thermal field distribution characteristics and spatiotemporal correlation laws; constructing coupling constraint relationships using a backlight power consumption temperature control coupling optimization algorithm to generate an initial backlight adjustment parameter set; suppressing noise and demodulating it using a low-noise temperature change real-time demodulation algorithm to obtain precise temperature control adjustment commands; and dynamically adjusting the drive voltage, light emission duration, and light emission intensity of each zone according to the commands, while continuously collecting the adjusted data and feeding it back to relevant models and algorithms. This method balances power consumption optimization and control stability, adapts to the needs of high-zone, high-brightness display devices, and improves the operational reliability and lifespan of the backlight module.

Description

Technical Field

[0001] This invention relates to the field of temperature regulation technology for display devices, and more particularly to a method for temperature zone regulation of backlight modules in display devices. Background Technology

[0002] As display devices evolve towards higher brightness and higher local dimming precision, the backlight module, as a core heat-generating component, directly impacts luminous efficiency, color stability, and lifespan due to its temperature distribution uniformity. With the widespread adoption of local dimming technology, traditional overall temperature control methods are no longer adequate to adapt to the thermal differences in different areas. Problems such as localized overheating caused by heat accumulation and imbalances between power consumption and temperature control are becoming increasingly prominent. There is an urgent need for a temperature regulation solution that can accurately match the characteristics of each local dimming zone to solve the temperature control challenge under multi-physical field coupling. This has become a key requirement driving the upgrade of display technology.

[0003] Existing technologies mainly achieve backlight module temperature regulation through passive heat dissipation or simple active temperature control. Passive heat dissipation relies on the optimization of thermal conductive materials, heat dissipation path design, or shell structure improvement to accelerate heat conduction by reducing thermal resistance. Active temperature control mostly uses thermoelectric conversion components for cooling or heating, or achieves coarse temperature control by adjusting drive current and voltage. Some solutions introduce basic zone control logic, but lack in-depth analysis of the spatiotemporal correlation characteristics of the thermal field. The adjustment parameters are mostly based on empirical presets, and no dynamic coupling optimization mechanism for power consumption and temperature control has been formed. There is also no special treatment for noise interference during the adjustment process. Overall, it relies on single-dimensional temperature data feedback, resulting in limited control accuracy.

[0004] The existing technology has two main drawbacks: First, the accuracy of thermal field identification and control is insufficient. It fails to fully consider the spatiotemporal coupling relationship of the thermal fields in each zone, and only performs isolated analysis of temperature data. It cannot accurately distinguish between temperature-sensitive and non-sensitive areas, resulting in a lack of targeted adjustment commands and a tendency for local over- or under-temperature control. Second, the coordination between power consumption and temperature control is lacking. An effective coupling constraint relationship is not established during the control process. It only pursues temperature stability or power consumption reduction, ignoring the mutual influence between the two. At the same time, noise interference in the adjustment signal is not effectively suppressed, resulting in distortion of the control commands and affecting the light emission uniformity and long-term reliability of the backlight module. Summary of the Invention

[0005] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a method for temperature zone adjustment of backlight modules for display devices.

[0006] The technical solution adopted in this invention is a temperature zone adjustment method for backlight modules of display devices, comprising the following steps: S1, collecting real-time temperature data of each zone of the backlight module of the display device through a multi-channel temperature sensing unit mounted on a full-domain temperature control logic main control chip, and simultaneously acquiring power consumption feedback signals and drive current change information during backlight module operation; S2, calling a zone thermal field spatiotemporal coupling identification model to perform coupling analysis on the collected temperature data, power consumption feedback signals, and drive current change information, dividing the temperature-sensitive and non-sensitive areas of the backlight module, and determining the thermal field distribution characteristics and spatiotemporal correlation laws of each zone; S3, employing backlight power consumption temperature control coupling optimization... The algorithm constructs a coupling constraint relationship between power consumption and temperature control based on the characteristics of the thermal field distribution and the spatiotemporal correlation law, generating an initial backlight adjustment parameter set for each zone; S4, the initial backlight adjustment parameter set is noise-suppressed using a low-noise temperature-varying real-time demodulation algorithm to obtain the temperature control adjustment command for each zone; S5, the global temperature control logic main control chip dynamically adjusts the driving voltage, light emission duration, and light emission intensity of each zone of the backlight module according to the temperature control adjustment command, performing temperature zone adjustment; S6, the temperature data and power consumption data of each zone after adjustment are continuously collected and fed back to the zone thermal field spatiotemporal coupling identification model and the backlight power consumption temperature control coupling optimization algorithm to form a dynamic adjustment link.

[0007] Furthermore, the expression for the spatiotemporal coupling identification model of the partitioned thermal field is: ;in, The spatial coordinates of a certain section of the backlight module With time instantaneous temperature below It is a spatial distribution function. Let be the time decay function. For spatiotemporal coupling coefficients, Number of partitions; For thermal field coupling strength, This is the strength correction factor. For the Laplace operator, It is the first derivative of the time decay function.

[0008] Furthermore, the expression for the backlight power consumption and temperature control coupling optimization algorithm is as follows: in, For the backlight module at temperature The power consumption value under these conditions The power consumption coefficient is... The power consumption order is... For driving current variable, Let current influence function, The attenuation coefficient is... Reference temperature; To optimize the driving voltage, This is a power consumption-voltage mapping function. To optimize the coefficients, Let T be the k-th power of temperature.

[0009] Furthermore, the expression for the low-noise temperature-varying real-time demodulation algorithm is as follows: in, This is the demodulated voltage command. The original feedback voltage, The demodulation coefficients, For demodulation order, The signal angular frequency, This is the noise suppression coefficient. It is a symbolic function.

[0010] Furthermore, the full-domain temperature control logic main control chip adopts a 32-bit RISC-V architecture, integrating a multi-channel 16-bit high-precision analog-to-digital converter module and a high-speed digital signal processing unit. The chip has a built-in temperature partition mapping register and an algorithm parameter cache unit with a cache capacity of 8MB. The temperature sensing unit of the backlight module adopts a distributed platinum resistance sensor array with an adjacent sensor spacing of no more than 5mm and a sampling frequency of 100Hz. The iteration step size of the backlight power consumption temperature control coupling optimization algorithm is dynamically adjusted from 0.01 to 0.1. The noise suppression threshold of the low-noise temperature change real-time demodulation algorithm is dynamically adapted according to the partition temperature value, with an adaptation range of 0.05 to 0.3. Each algorithm is operated in parallel through the chip's built-in hardware acceleration engine, and the operation latency is controlled within 10μs.

[0011] Further, S2 includes the following sub-steps: S21, the full-domain temperature control logic main control chip classifies and associates the collected temperature data, power consumption feedback signals, and drive current change information according to preset partition numbers, and establishes a multi-dimensional data matrix for each partition. The row dimension of the matrix corresponds to the time series, and the column dimension corresponds to different types of sensor data; S22, the spatial feature extraction module of the partition thermal field spatiotemporal coupling identification model is called to perform coupling operations on the spatially related data in the data matrix to identify the gradient distribution law of temperature in each partition as a function of spatial coordinates; S23, the time series data in the data matrix is ​​processed by the model's time feature analysis module to mine the lag correlation characteristics of temperature, power consumption, and drive current in each partition in the time dimension; S24, by combining the spatial gradient distribution law and the time lag correlation characteristics, the division of temperature-sensitive and non-sensitive areas is completed, and the thermal field distribution characteristic parameters and spatiotemporal correlation matrix of each partition are output.

[0012] Further, S3 includes the following sub-steps: S31, the backlight power consumption and temperature control coupling optimization algorithm reads the thermal field distribution characteristic parameters and spatiotemporal correlation matrix output by S2 to determine the constraint thresholds for temperature control of each zone. The constraint thresholds include the maximum allowable temperature and the minimum operating temperature; S32, a power consumption-temperature control objective function is constructed based on the constraint thresholds. The function aims to maximize the temperature control accuracy and minimize power consumption as a secondary objective; S33, the objective function is solved through the algorithm's built-in multi-objective optimization module. The spatiotemporal correlation constraints of the thermal field of each zone are incorporated into the solution process to generate multiple sets of candidate backlight adjustment parameters; S34, the feasibility of the candidate parameter sets is verified, parameter combinations that exceed the hardware driving capability are eliminated, and the initial backlight adjustment parameter sets for each zone are obtained.

[0013] Further, S2 includes the following sub-steps: S41, the low-noise temperature-varying real-time demodulation algorithm receives the initial backlight adjustment parameter set output by S3, extracts voltage, current, and duration-related parameters from the parameter set, and forms the original adjustment signal sequence; S42, performs frequency domain analysis on the original adjustment signal sequence, identifies high-frequency noise components and temperature-varying interference components in the signal, and determines the frequency distribution range of noise and interference; S43, calls the demodulation operation module of the algorithm, performs product operation and phase correction on the original adjustment signal sequence in combination with the frequency distribution range, and suppresses high-frequency noise and temperature-varying interference; S44, outputs the corrected temperature control adjustment command, which includes specific control values ​​for the driving voltage, light emission duration, and light emission intensity of each zone.

[0014] Further, S5 includes the following sub-steps: S51, the global temperature control logic main control chip receives the temperature control adjustment command output by S4, decodes the command, and parses the corresponding control parameters for each zone; S52, the chip's drive control module generates control signals for the backlight drive circuit of each zone according to the parsed control parameters, the control signals including pulse width and frequency information; S53, the drive circuit responds to the control signal, adjusts the drive voltage amplitude output to each zone of the backlight module, and synchronously controls the conduction time and current intensity of the light-emitting unit; S54, during the control process, the chip monitors the working status of the drive circuit of each zone in real time to ensure that the control parameters are executed according to the command and to avoid overvoltage and overcurrent.

[0015] A method for temperature zoning adjustment of a display device backlight module is disclosed. This method is implemented through a temperature zoning adjustment system for the display device backlight module, comprising: a multi-dimensional data acquisition unit for zoned thermal fields, a spatiotemporal coupling identification model calculation unit, a power consumption and temperature control coupling optimization processing unit, a low-noise temperature change real-time demodulation unit, a global temperature control logic main control unit, and a backlight module zoned driving unit. The multi-dimensional data acquisition unit for zoned thermal fields is connected to the backlight module zoned driving unit and is used to acquire temperature, power consumption, and drive current data for each zone and transmit them to the spatiotemporal coupling identification model calculation unit. The spatiotemporal coupling model calculation unit is connected to the power consumption and temperature control coupling optimization processing unit. The processing unit communicates bidirectionally to analyze the thermal field distribution characteristics and spatiotemporal correlation patterns and outputs the results to the power consumption and temperature control coupling optimization processing unit. The power consumption and temperature control coupling optimization processing unit is connected to the low-noise temperature change real-time demodulation unit to generate an initial set of adjustment parameters and transmit it to the demodulation unit. The low-noise temperature change real-time demodulation unit communicates with the global temperature control logic main control unit and outputs temperature control adjustment commands. The global temperature control logic main control unit is connected to the spatiotemporal coupling identification model calculation unit, the power consumption and temperature control coupling optimization processing unit, and the backlight module zoning drive unit, respectively. It controls the drive unit to perform zoning temperature adjustment according to the adjustment commands and simultaneously sends the feedback data back to the front-end calculation and optimization unit.

[0016] Beneficial Effects: This invention proposes a temperature zoning adjustment method for backlight modules of display devices. Through multi-channel data acquisition and spatiotemporal coupling identification of zoning thermal fields, it captures the thermal field distribution characteristics and spatiotemporal correlation patterns of each zone, solving the problem of insufficient accuracy in thermal field identification in existing technologies and avoiding local temperature control imbalances. A backlight power consumption and temperature control coupling optimization algorithm is used to construct a dynamic coupling constraint relationship between the two, achieving coordinated optimization of temperature regulation and power consumption control, thus overcoming the shortcomings of insufficient coordination between power consumption and temperature control in existing technologies. A low-noise temperature change real-time demodulation algorithm is used to suppress noise interference during the adjustment process, ensuring the accuracy of regulation commands and improving the uniformity and long-term reliability of the backlight module's light emission. The hardware architecture optimization and parallel algorithm design of the full-domain temperature control logic main control chip ensure rapid response and accurate execution of regulation. Distributed sensor arrays and dynamic parameter adaptation mechanisms further enhance the targeted nature of zoning temperature control. The entire dynamic adjustment link achieves dynamic optimization through real-time feedback, which not only enables precise control of the temperature of each zone, but also effectively reduces unnecessary power consumption, while taking into account luminous efficiency and lifespan. It solves the problems of poor adaptability, low accuracy and insufficient coordination of traditional temperature control methods, and provides a stable and reliable temperature control solution for high-brightness, high-zone display devices. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the overall process of the method of the present invention. Figure 2 This is a flowchart of method step S2 of the present invention; Figure 3This is a flowchart of method step S3 of the present invention; Figure 4 This is a flowchart of method step S4 of the present invention; Figure 5 This is a flowchart of step S5 of the method of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 1 As shown, a temperature zoning adjustment method for a display device backlight module includes the following steps: S1, collecting real-time temperature data of each zone of the display device backlight module through a multi-channel temperature sensing unit mounted on a full-domain temperature control logic main control chip, and simultaneously acquiring power consumption feedback signals and drive current change information during backlight module operation; S2, calling a zone thermal field spatiotemporal coupling identification model to perform coupling analysis on the collected temperature data, power consumption feedback signals, and drive current change information, dividing the backlight module into temperature-sensitive and non-sensitive areas, and determining the thermal field distribution characteristics and spatiotemporal correlation rules of each zone; S3, using a backlight power consumption temperature control coupling optimization algorithm based on the thermal... Based on the field distribution characteristics and spatiotemporal correlation patterns, a coupling constraint relationship between power consumption and temperature control is constructed to generate an initial backlight adjustment parameter set for each zone; S4, a low-noise temperature-varying real-time demodulation algorithm is used to suppress noise in the initial backlight adjustment parameter set, and the temperature control adjustment command for each zone is obtained; S5, the global temperature control logic main control chip dynamically adjusts the driving voltage, light emission duration, and light emission intensity of each zone of the backlight module according to the temperature control adjustment command, and performs temperature zone adjustment; S6, the temperature data and power consumption data of each zone after adjustment are continuously collected and fed back to the zone thermal field spatiotemporal coupling identification model and the backlight power consumption and temperature control coupling optimization algorithm to form a dynamic adjustment link.

[0020] Step S1 is the basic data acquisition stage for temperature zone adjustment. This is implemented using a multi-channel temperature sensing unit integrated into the full-domain temperature control logic main control chip. This sensing unit employs a distributed platinum resistance sensor array, with the spacing between adjacent sensors strictly controlled within 5 millimeters to ensure comprehensive coverage and accurate capture of the temperature of each zone of the backlight module. The sampling frequency is set to 100 Hz, enabling continuous acquisition of real-time temperature data for each zone and avoiding missed temperature changes due to excessively long sampling intervals. Simultaneously with temperature data acquisition, the main control chip integrates a multi-channel 16-bit high-precision analog-to-digital converter (ADC) module to synchronously acquire power consumption feedback signals and drive current changes during the backlight module's operation. The high-resolution characteristics of the ADC module ensure the accuracy of power consumption and current data acquisition, with errors controlled within 0.01. During data acquisition, the temperature zone mapping register built into the main control chip assigns a zone number and timestamp to each set of acquired data, clearly identifying the specific zone location and acquisition time of the data, ensuring data uniqueness and traceability. The collected temperature, power consumption, and current data are transmitted in real time to the chip's 8MB algorithm parameter cache unit for temporary storage. The cache unit employs a high-speed access architecture, with a data write latency of no more than 2 microseconds, providing fast and efficient data retrieval support for subsequent model analysis. The entire acquisition process is uniformly coordinated and controlled by the main control chip's high-speed digital signal processing unit. A timing synchronization mechanism ensures the time consistency of the three types of data acquisition, with a maximum time difference of no more than 1 microsecond, avoiding subsequent analysis deviations caused by data asynchrony and laying a reliable data foundation for the entire temperature zone adjustment process.

[0021] Step S2 focuses on the accurate identification and analysis of the zoned thermal field. During implementation, the full-domain temperature control logic main control chip first calls the zoned thermal field spatiotemporal coupling identification model. This model initiates parallel computation through the chip's built-in hardware acceleration engine, with computation latency strictly controlled within 10 microseconds to ensure analysis efficiency meets real-time adjustment requirements. After receiving the temperature data, power consumption feedback signal, and drive current change information temporarily stored in step S1, the model first performs structured integration of the three types of data to construct a multi-dimensional data matrix for each zone. The matrix's row dimensions correspond to the time series, and the column dimensions correspond to different types of sensor data. The matrix size is dynamically adjusted according to the number of zones in the backlight module, supporting data processing for a maximum of 1024 zones. Subsequently, the model's spatial feature extraction module performs coupling computation on the spatially related data in the data matrix, analyzing the gradient distribution law of temperature changes with spatial coordinates in each zone, with gradient calculation accuracy retained to three decimal places. Simultaneously, the time feature analysis module performs trend mining on the time series data, identifying the lag correlation characteristics between temperature, power consumption, and drive current in the time dimension, with the lag time resolution set to 1 microsecond. Based on a comprehensive analysis of spatial gradient distribution patterns and temporal lag correlation characteristics, the model delineates temperature-sensitive and non-sensitive regions. The delineation criteria are: regions with a temperature change rate exceeding 0.05 microseconds and a correlation coefficient higher than 0.8 with power consumption and current changes are classified as sensitive regions; the rest are non-sensitive regions. After delineation, the model outputs characteristic parameters of the thermal field distribution in each region and a spatiotemporal correlation matrix. Characteristic parameters include key indicators such as average temperature, temperature fluctuation amplitude, and heat diffusion rate. The spatiotemporal correlation matrix quantifies the degree of mutual influence of the thermal fields in each region at different time points, providing accurate thermal field analysis basis for parameter optimization in step S3.

[0022] Step S3 generates an initial backlight adjustment parameter set adapted to the thermal field characteristics. During implementation, a backlight power consumption and temperature control coupled optimization algorithm is used. This algorithm runs in parallel with other algorithms through the hardware acceleration engine of the main control chip. The iteration step size is dynamically adjusted from 0.01 to 0.1, adaptively adjusting according to the complexity of the thermal field. The more uniform the thermal field distribution, the larger the iteration step size, and vice versa. The algorithm first reads the thermal field distribution characteristic parameters and spatiotemporal correlation matrix output in step S2. Combining the temperature tolerance range of the backlight module's light-emitting unit and the operating parameter limits of the driving circuit, it determines the constraint thresholds for temperature control in each zone. The maximum allowable temperature is set to 85°C, and the minimum operating temperature is set to -10°C, ensuring that the adjustment process does not damage the hardware or affect the display effect. Based on the constraint thresholds, a dual-objective optimization function is constructed. The core objective is to maximize the temperature control accuracy, keeping the control accuracy error within 0.1, while the secondary objective is to minimize power consumption, reducing power consumption to a reasonable range while meeting temperature control requirements. The algorithm's built-in multi-objective optimization module solves the function, incorporating spatiotemporal constraints on the thermal fields of each partition during the solution process. This avoids negative impacts on the thermal fields of adjacent partitions caused by the control of a single partition, generating at least 10 candidate backlight adjustment parameter sets. Each parameter set includes the driving voltage, emission duration, and emission intensity parameters corresponding to each partition. The feasibility of the candidate parameter sets is then verified, including whether the parameters fall within the driving circuit's voltage output range of 0.5 to 24, current carrying capacity range of 0.01 to 1, and emission duration adjustment range of 1 to 1000 microseconds. After eliminating parameter combinations outside these ranges, the initial backlight adjustment parameter sets for each partition are obtained. The control precision of the parameter sets is retained to three decimal places, providing high-quality basic parameters for the demodulation processing in step S4.

[0023] Step S4, acquiring the temperature control adjustment command, employs a low-noise temperature-varying real-time demodulation algorithm. This algorithm dynamically adapts its noise suppression threshold based on the zone temperature value, with an adaptation range of 0.05 to 0.3. Higher temperatures result in a threshold setting closer to the upper limit, enhancing noise suppression capabilities in high-temperature areas. The algorithm first receives the initial backlight adjustment parameter set output in step S3. It extracts relevant parameters for each zone's driving voltage, luminous current, and luminous duration from the parameter set, organizing them into a raw adjustment signal sequence according to time sequence. The sampling interval of the signal sequence is consistent with the data acquisition frequency in step S1 to ensure signal synchronization. Frequency domain analysis is performed on the raw adjustment signal sequence. The high-speed digital signal processing unit of the main control chip identifies high-frequency noise components and temperature-varying interference components in the signal, determining the frequency distribution range of noise and interference. High-frequency noise mainly originates from electromagnetic interference from the driving circuit, while temperature-varying interference components are generated by signal fluctuations caused by temperature changes in each zone. The demodulation module of the algorithm is invoked, and combined with the determined frequency distribution range, the original regulated signal sequence is subjected to multiplication and phase correction. Multiplication is used to enhance the effective signal components, and phase correction is used to offset the signal phase shift caused by temperature variation interference, thereby achieving precise suppression of noise and interference. After demodulation processing, a corrected and precise temperature control regulation command is output. The command specifies the exact control values ​​for the driving voltage, emission duration, and emission intensity of each zone. The precision of the control values ​​is retained to three decimal places to ensure the accuracy of subsequent regulation operations. The entire demodulation process is supported by the hardware acceleration engine of the main control chip, and the operation delay is controlled within 10μs, ensuring the real-time output of the regulation command and providing accurate and interference-free command basis for the dynamic regulation in step S5.

[0024] When step S5 is implemented, the full-domain temperature control logic main control chip first receives the precise temperature control adjustment command output in step S4. The chip's built-in command decoding module decodes the command, with the decoding process taking no more than 5μs to ensure rapid command response. After decoding, the driving voltage, emission duration, and emission intensity control parameters corresponding to each zone are parsed. These control parameters are stored in the chip's zone control register according to the zone number. Each zone is assigned an independent register address with an address offset of 4 bytes to avoid confusion between parameters from different zones. Subsequently, the chip's drive control module generates control signals for the backlight drive circuit of each zone based on the parsed control parameters. The control signals include pulse width and frequency information. The pulse width adjustment accuracy is 1ns, with an adjustment range of 10ns to 100μs, and the frequency adjustment range is 1kHz to 1MHz, allowing for precise adaptation to the temperature control requirements of different zones. After receiving the control signal, the backlight driving circuit adjusts the driving voltage amplitude of each zone of the backlight module through a high-precision voltage regulation module. The voltage regulation accuracy is 0.01V, and the adjustment range is 0.5V to 24V. Simultaneously, the timing control module controls the on and off durations of the switching transistors, achieving precise control of the on-time of the light-emitting unit, with a duration adjustment accuracy of 1μs. At the same time, the current feedback circuit monitors the light-emitting current in real time and dynamically adjusts the current intensity, with a current regulation accuracy of 0.1mA and an adjustment range of 0.01A to 1A. During the regulation process, the chip's built-in overvoltage and overcurrent detection module continuously collects the output voltage and current data of the driving circuit at a detection frequency of 1MHz. Once the parameters are detected to exceed the set safety range, a hardware protection mechanism is immediately triggered, suspending the regulation operation of that zone and feeding back an abnormal signal to the main control unit, ensuring the safe and stable regulation process. Throughout the entire control process, the control operations of each zone are executed synchronously through a parallel control architecture without any delay, achieving synchronous temperature adjustment of all zones. This effectively avoids thermal imbalance caused by asynchronous control and ensures that the temperature of each zone of the backlight module quickly approaches the target value within 10ms.

[0025] Step S6 establishes a dynamic adjustment link to ensure continuous optimization and stable operation of temperature zone adjustment. During implementation, the multi-channel temperature sensing unit and analog-to-digital converter deployed in step S1 continuously collect temperature and power consumption data after adjustment for each zone, maintaining a sampling frequency of 100Hz to ensure real-time capture of parameter changes after adjustment. The collected adjusted data is also processed by a temperature zone mapping register to assign zone numbers, timestamps, and adjustment batch marks, and is stored in an 8MB algorithm parameter cache unit, corresponding one-to-one with the pre-adjustment data. The cache unit adopts a zoned storage architecture, storing pre-adjustment and post-adjustment data in separate areas for easy retrieval and comparison. After data storage, the main control chip synchronously feeds back the adjusted data to the zoned thermal field spatiotemporal coupling identification model and the backlight power consumption temperature control coupling optimization algorithm via a high-speed data transmission interface. Data transmission uses a serial peripheral interface protocol with a transmission rate of 100Mbps and a transmission delay of no more than 8μs to ensure that the model and algorithm can obtain timely feedback on the adjustment effect. After receiving feedback data, the zoned thermal field spatiotemporal coupling identification model re-analyzes the thermal field distribution characteristics and spatiotemporal correlation patterns of each zone, compares the differences in thermal field changes before and after adjustment, calculates the improvement ratio of thermal field uniformity, and updates the thermal field distribution characteristic parameters and spatiotemporal correlation matrix. The update cycle is consistent with the data acquisition cycle, providing the latest thermal field data support for the next round of analysis. After receiving feedback data, the backlight power consumption temperature control coupling optimization algorithm calculates the deviation between the actual control effect and the target effect. The temperature deviation calculation accuracy is 0.01℃, and the power consumption deviation calculation accuracy is 0.01W. The temperature deviation threshold is set at 0.1℃, and the power consumption deviation threshold is set at 0.1W. If the deviation exceeds the set threshold, the algorithm automatically adjusts the weight coefficients and iteration step size of the objective function and optimizes the parameter solution logic. Through continuous data acquisition, real-time feedback, model parameter updates, and algorithm logic optimization, a complete dynamic adjustment chain is formed. This ensures that the temperature zone adjustment can adaptively adjust in real time according to the actual working state of the backlight module, maintaining a dynamic balance between stable temperature and optimized power consumption in each zone over the long term. This avoids control failures caused by changes in display device workload, ambient temperature fluctuations, and other factors, ensuring the long-term stable operation of the display device.

[0026] Preferably, the expression for the spatiotemporal coupling identification model of the partitioned thermal field is: ;in, The spatial coordinates of a certain section of the backlight module With time instantaneous temperature below It is a spatial distribution function. Let be the time decay function. For spatiotemporal coupling coefficients, Number of partitions; For thermal field coupling strength, This is the strength correction factor. For the Laplace operator, It is the first derivative of the time decay function.

[0027] Specifically, the partitioned thermal field spatiotemporal coupling identification model is based on the spatial distribution characteristics and temporal decay law of the thermal field. First, it analyzes the temperature variation trend of each partition of the backlight module with spatial coordinates, and combines the mutual influence of different partitioned thermal fields to introduce a spatial distribution function and a spatiotemporal coupling coefficient. Then, considering the dynamic decay characteristics of temperature over time, it incorporates a time decay function. Through integration, it consolidates the coupling relationship between the spatial and temporal dimensions to form the first model expression. This construction method can comprehensively capture the spatiotemporal correlation law of the thermal field, avoiding the limitations of single-dimensional analysis. Based on the first expression, the thermal field coupling strength expression is further calculated. The second-order rate of change of the spatial distribution is quantified by introducing the Laplace operator, and the first derivative of the time decay function reflects the rate of change in the time dimension. Then, the model adaptability is adjusted through an intensity correction coefficient, making the two expressions logically progressive. The former describes the instantaneous temperature distribution, and the latter quantifies the thermal field coupling strength. Regarding parameter values, the spatiotemporal coupling coefficient is dynamically set according to the number of backlight module sections. When the number of sections does not exceed 1024, the coefficient ranges from 0.001 to 0.1. The intensity correction coefficient is fixed at 0.85, and the calculation step size of the first derivative of the time decay function is 0.001. During implementation, the model runs through the hardware acceleration engine of the global temperature control logic main control chip. After receiving the data collected in step S1, it completes the calculation according to the calculation logic. The output instantaneous temperature and thermal field coupling intensity data provide the core basis for the division of temperature-sensitive areas, ensuring the accuracy of section identification.

[0028] Preferably, the expression for the backlight power consumption and temperature control coupling optimization algorithm is: in, For the backlight module at temperature The power consumption value under these conditions The power consumption coefficient is... The power consumption order is... For driving current variable, Let current influence function, The attenuation coefficient is... Reference temperature; To optimize the driving voltage, This is a power consumption-voltage mapping function. To optimize the coefficients, Let T be the k-th power of temperature.

[0029] Specifically, the backlight power consumption and temperature control coupling optimization algorithm is based on the nonlinear relationship between power consumption and temperature. It establishes a basic expression for power consumption as a function of temperature through polynomial fitting, introduces summation operations to accumulate temperature influence terms of different orders, and considers the dynamic effect of the driving current on power consumption. Through integration operations, it integrates the influence of the current variable within the reference temperature range to form the first model expression. This construction method can take into account the dual effects of temperature and current, accurately describing the power consumption characteristics. Based on the first expression, the driving voltage expression is further calculated and optimized. A power consumption-voltage mapping function is constructed to establish the relationship between the two. The partial derivative of power consumption with respect to temperature reflects the temperature control sensitivity. Then, through integration operations, the cumulative effect of power consumption within the reference temperature range is solved. An optimization coefficient is introduced to adjust the adaptability of the voltage output, making the two expressions logically related. The former calculates the actual power consumption, and the latter outputs the optimized voltage. Regarding parameter values, the power consumption coefficient is set according to the type of backlight module's light-emitting unit, ranging from 0.0001 to 0.01. The attenuation coefficient is fixed at 0.02, the optimization coefficient is 0.9, the polynomial order does not exceed 8, and the integration step size is 0.01. During implementation, the algorithm runs through the parallel computing unit of the main control chip. After reading the thermal field analysis data in step S2, the generated optimized driving voltage parameters provide the core basis for the initial backlight adjustment parameter set, ensuring the coordinated optimization of power consumption and temperature control.

[0030] Preferably, the expression for the low-noise temperature-varying real-time demodulation algorithm is: in, This is the demodulated voltage command. The original feedback voltage, The demodulation coefficients, For demodulation order, The signal angular frequency, This is the noise suppression coefficient. It is a symbolic function.

[0031] Specifically, the backlight power consumption and temperature control coupling optimization algorithm is based on the nonlinear relationship between power consumption and temperature. It establishes a basic expression for power consumption as a function of temperature through polynomial fitting, introduces summation operations to accumulate temperature influence terms of different orders, and considers the dynamic effect of the driving current on power consumption. Through integration operations, it integrates the influence of the current variable within the reference temperature range to form the first model expression. This construction method can take into account the dual effects of temperature and current, accurately describing the power consumption characteristics. Based on the first expression, the driving voltage expression is further calculated and optimized. A power consumption-voltage mapping function is constructed to establish the relationship between the two. The partial derivative of power consumption with respect to temperature reflects the temperature control sensitivity. Then, through integration operations, the cumulative effect of power consumption within the reference temperature range is solved. An optimization coefficient is introduced to adjust the adaptability of the voltage output, making the two expressions logically related. The former calculates the actual power consumption, and the latter outputs the optimized voltage. Regarding parameter values, the power consumption coefficient is set according to the type of backlight module's light-emitting unit, ranging from 0.0001 to 0.01. The attenuation coefficient is fixed at 0.02, the optimization coefficient is 0.9, the polynomial order does not exceed 8, and the integration step size is 0.01. During implementation, the algorithm runs through the parallel computing unit of the main control chip. After reading the thermal field analysis data in step S2, the generated optimized driving voltage parameters provide the core basis for the initial backlight adjustment parameter set, ensuring the coordinated optimization of power consumption and temperature control.

[0032] Preferably, the full-domain temperature control logic main control chip adopts a 32-bit RISC-V architecture, integrating a multi-channel 16-bit high-precision analog-to-digital converter module and a high-speed digital signal processing unit. The chip has a built-in temperature partition mapping register and an algorithm parameter cache unit with a cache capacity of 8MB. The temperature sensing unit of the backlight module adopts a distributed platinum resistance sensor array with an adjacent sensor spacing of no more than 5mm and a sampling frequency of 100Hz. The iteration step size of the backlight power consumption temperature control coupling optimization algorithm is dynamically adjusted from 0.01 to 0.1. The noise suppression threshold of the low-noise temperature change real-time demodulation algorithm is dynamically adapted according to the partition temperature value, with an adaptation range of 0.05 to 0.3. Each algorithm is operated in parallel through the chip's built-in hardware acceleration engine, and the operation latency is controlled within 10μs.

[0033] Preferred, such as Figure 2As shown, S2 includes the following steps: S21, the full-domain temperature control logic main control chip classifies and associates the collected temperature data, power consumption feedback signals, and drive current change information according to preset partition numbers, and establishes a multi-dimensional data matrix for each partition. The row dimension of the matrix corresponds to the time series, and the column dimension corresponds to different types of sensor data; S22, the spatial feature extraction module of the partition thermal field spatiotemporal coupling identification model is called to perform coupling operations on the spatially related data in the data matrix to identify the gradient distribution law of temperature in each partition as a function of spatial coordinates; S23, the time series data in the data matrix is ​​processed by the model's time feature analysis module to mine the lag correlation characteristics of temperature, power consumption, and drive current in each partition in the time dimension; S24, by combining the spatial gradient distribution law and the time lag correlation characteristics, the division of temperature-sensitive and non-sensitive areas is completed, and the thermal field distribution characteristic parameters and spatiotemporal correlation matrix of each partition are output.

[0034] Specifically, step S2 identifies the zoned thermal field through steps S21 to S24. In S21, the global temperature control logic main control chip first classifies and associates the temperature data, power consumption feedback signal, and drive current change information collected in step S1 according to the preset zone number, constructing a multi-dimensional data matrix for each zone. The row dimension of the matrix corresponds to the time series, and the column dimension corresponds to different types of sensor data. The matrix storage adopts a 16-bit binary encoding format to ensure data storage efficiency and accuracy. S22 calls the spatial feature extraction module of the zoned thermal field spatiotemporal coupling identification model to perform coupling operations on the spatially related data in the data matrix. The operation adopts 32-bit floating-point operation precision to identify the gradient distribution law of temperature change with spatial coordinates in each zone. The gradient calculation interval is 0.1 unit length to ensure the fineness of the distribution law. S23 processes the time series data through the model's time feature analysis module. The time window is set to 100 milliseconds to explore the lag correlation characteristics of temperature, power consumption, and drive current in each zone in the time dimension. The lag time resolution is 1 microsecond. S24 integrates the spatial gradient distribution pattern and time lag correlation characteristics, and uses a threshold determination method to divide temperature-sensitive and non-sensitive regions. The threshold for sensitive regions is set to a temperature change rate of 0.05 units of temperature per microsecond. It outputs the thermal field distribution characteristic parameters and spatiotemporal correlation matrix of each region. The characteristic parameters include 20 core indicators. The dimension of the spatiotemporal correlation matrix is ​​consistent with the number of regions. During implementation, the hardware acceleration engine of the main control chip ensures the efficiency of each step of the operation, and the total time does not exceed 50 microseconds, providing accurate thermal field basic data for subsequent parameter optimization.

[0035] Preferred, such as Figure 3As shown, step S3 includes the following sub-steps: S31, the backlight power consumption and temperature control coupling optimization algorithm reads the thermal field distribution characteristic parameters and spatiotemporal correlation matrix output by S2 to determine the constraint thresholds for temperature control of each zone. The constraint thresholds include the maximum allowable temperature and the minimum operating temperature; S32, a power consumption-temperature control objective function is constructed based on the constraint thresholds. The function aims to maximize the temperature control accuracy and minimize power consumption as a secondary objective; S33, the objective function is solved by the multi-objective optimization module built into the algorithm. The spatiotemporal correlation constraints of the thermal field of each zone are incorporated into the solution process to generate multiple sets of candidate backlight adjustment parameters; S34, the feasibility of the candidate parameter sets is verified, parameter combinations that exceed the hardware driving capability are eliminated, and the initial backlight adjustment parameter sets for each zone are obtained.

[0036] Specifically, step S3 generates an initial backlight adjustment parameter set through sub-steps S31 to S34. In S31, the backlight power consumption and temperature control coupling optimization algorithm first reads the thermal field distribution characteristic parameters and spatiotemporal correlation matrix output in step S2, and determines the temperature control constraint thresholds for each zone based on the hardware characteristics of the backlight module. The maximum allowable temperature is set to 85°C, and the minimum operating temperature is set to -10°C. The constraint thresholds are stored in the chip's built-in non-volatile memory and support dynamic updates. S32 constructs a power consumption-temperature control objective function based on the constraint thresholds. The function takes maximizing temperature control accuracy as the core objective and minimizing power consumption as the secondary objective. The core objective accounts for 70% of the weight, and the secondary objective accounts for 30%. The weight coefficients can be configured through the software interface. S33 solves the objective function through the algorithm's built-in multi-objective optimization module. The solution uses the gradient descent method, with 100 iterations. The step size for each iteration is dynamically adjusted from 0.01 to 0.1, generating no fewer than 10 candidate backlight adjustment parameter sets. Each parameter set includes three core parameters: driving voltage, emission duration, and emission intensity. S34 performs feasibility verification on the candidate parameter set. Verification items include whether the voltage is within the range of 0.5 to 24, whether the current is within the range of 0.01 to 1, and whether the duration is within the range of 1 to 1000 microseconds. Parameter combinations that do not meet the requirements are eliminated, and the initial backlight adjustment parameter set for each zone is obtained. The parameter accuracy is retained to three decimal places. During implementation, the algorithm runs on the digital signal processing unit of the main control chip, and each sub-step is executed in parallel. The total processing delay does not exceed 30 microseconds to ensure the timeliness and reliability of the parameter set.

[0037] Preferred, such as Figure 4As shown, S4 includes the following sub-steps: S41, the low-noise temperature-varying real-time demodulation algorithm receives the initial backlight adjustment parameter set output by S3, extracts voltage, current, and duration-related parameters from the parameter set, and forms the original adjustment signal sequence; S42, performs frequency domain analysis on the original adjustment signal sequence, identifies high-frequency noise components and temperature-varying interference components in the signal, and determines the frequency distribution range of noise and interference; S43, calls the demodulation operation module of the algorithm, performs product operation and phase correction on the original adjustment signal sequence in combination with the frequency distribution range, and suppresses high-frequency noise and temperature-varying interference; S44, outputs the corrected temperature control adjustment command, which includes specific control values ​​for the driving voltage, light emission duration, and light emission intensity of each zone.

[0038] Specifically, step S4 demodulates the temperature control command through steps S41 to S44. In S41, the low-noise temperature-change real-time demodulation algorithm receives the initial backlight adjustment parameter set output from step S3, extracts relevant parameters such as driving voltage, luminous current, and luminous duration, and organizes them into an original adjustment signal sequence according to the time series. The sequence length is consistent with the acquisition period, and each period includes 100 data points. In S42, frequency domain analysis is performed on the original adjustment signal sequence using a fast Fourier transform algorithm with 1024 transform points and a frequency resolution of 0.1kHz. High-frequency noise components and temperature-change interference components in the signal are identified, and the frequency distribution range of noise and interference is determined to be 10kHz to 1MHz. In S43, the demodulation operation module of the algorithm is called to perform product calculation and phase correction on the original adjustment signal sequence in combination with the frequency distribution range. The product calculation window size is set to 16 data points, and the phase correction accuracy is 0.1 degrees, effectively suppressing high-frequency noise and temperature-change interference, and improving the signal-to-noise ratio to over 40 dB. The S44 outputs a corrected, precise temperature control command. The command is transmitted in a frame format, with a frame length of 32 bytes, including information such as partition number, driving voltage, emission duration, and emission intensity. Command verification employs a cyclic redundancy check algorithm to ensure transmission integrity. During implementation, the algorithm is executed through the main control chip's hardware acceleration engine. Each step is processed in a pipeline manner: S41 data extraction takes 5 microseconds, S42 frequency domain analysis takes 10 microseconds, S43 demodulation operation takes 12 microseconds, and S44 command output takes 3 microseconds. The total demodulation delay does not exceed 30 microseconds, ensuring the real-time performance and accuracy of the control command and providing a reliable basis for control execution.

[0039] Preferred, such as Figure 5As shown, step S5 includes the following sub-steps: S51, the global temperature control logic main control chip receives the temperature control adjustment command output by S4, decodes the command, and parses the corresponding control parameters for each zone; S52, the chip's drive control module generates control signals for the backlight drive circuit of each zone according to the parsed control parameters, the control signals including pulse width and frequency information; S53, the drive circuit responds to the control signal, adjusts the drive voltage amplitude output to each zone of the backlight module, and synchronously controls the conduction time and current intensity of the light-emitting unit; S54, during the control process, the chip monitors the working status of the drive circuit of each zone in real time to ensure that the control parameters are executed according to the command and to avoid overvoltage and overcurrent.

[0040] Specifically, step S5 completes the zoned temperature control of the backlight module through sub-steps S51 to S54. In S51, the global temperature control logic main control chip receives the precise temperature control adjustment command output in step S4, decodes the command through the command decoding module (using Manchester encoding at a decoding rate of 1Mbps), and obtains the control parameters corresponding to each zone. The parameters are stored in a dedicated register according to the zone number, with the register address incrementing sequentially according to the zone order, with an address step of 4 bytes. In S52, the chip's drive control module generates control signals for the backlight drive circuit of each zone based on the parsed control parameters. The control signals are pulse width modulation signals with a pulse width adjustment accuracy of 1ns and a frequency adjustment range of 1kHz to 1MHz. The signals are output through the chip's GPIO interface. In S53, the drive circuit responds to the control signals by adjusting the drive voltage amplitude output to each zone of the backlight module through a high-precision digital-to-analog converter module with a voltage adjustment accuracy of 0.01V. Simultaneously, it adjusts the conduction duration of the light-emitting unit through a timing control module with a duration adjustment accuracy of 1 microsecond, and dynamically adjusts the light-emitting current intensity through a current feedback circuit with a current adjustment accuracy of 0.1mA. During the S54 control process, the chip's built-in overvoltage and overcurrent detection modules continuously monitor the driving circuit's operating status at a detection frequency of 1MHz. The overvoltage threshold is set to 25, and the overcurrent threshold is set to 1.1. Once parameters are detected to exceed limits, the hardware protection mechanism is immediately triggered, suspending the control of that zone and feeding back an abnormal signal. During implementation, each step is executed sequentially: S51 decoding takes 5 microseconds, S52 control signal generation takes 8 microseconds, S53 drive adjustment takes 10 microseconds, and S54 status monitoring is performed in real time. The control operations of each zone are executed in parallel without any delay, ensuring that all zones complete temperature adjustment synchronously. The control response time does not exceed 20 microseconds, achieving rapid and stable temperature control.

[0041] A method for temperature zoning adjustment of a display device backlight module is disclosed. This method is implemented through a temperature zoning adjustment system for the display device backlight module, comprising: a multi-dimensional data acquisition unit for zoned thermal fields, a spatiotemporal coupling identification model calculation unit, a power consumption and temperature control coupling optimization processing unit, a low-noise temperature change real-time demodulation unit, a global temperature control logic main control unit, and a backlight module zoned driving unit. The multi-dimensional data acquisition unit for zoned thermal fields is connected to the backlight module zoned driving unit and is used to acquire temperature, power consumption, and drive current data for each zone and transmit them to the spatiotemporal coupling identification model calculation unit. The spatiotemporal coupling model calculation unit is connected to the power consumption and temperature control coupling optimization processing unit. The processing unit communicates bidirectionally to analyze the thermal field distribution characteristics and spatiotemporal correlation patterns and outputs the results to the power consumption and temperature control coupling optimization processing unit. The power consumption and temperature control coupling optimization processing unit is connected to the low-noise temperature change real-time demodulation unit to generate an initial set of adjustment parameters and transmit it to the demodulation unit. The low-noise temperature change real-time demodulation unit communicates with the global temperature control logic main control unit and outputs temperature control adjustment commands. The global temperature control logic main control unit is connected to the spatiotemporal coupling identification model calculation unit, the power consumption and temperature control coupling optimization processing unit, and the backlight module zoning drive unit, respectively. It controls the drive unit to perform zoning temperature adjustment according to the adjustment commands and simultaneously sends the feedback data back to the front-end calculation and optimization unit.

[0042] A temperature zoning adjustment method for backlight modules in display devices is proposed. This method utilizes distributed sensing units to achieve multi-dimensional data acquisition and combines a zoning thermal field spatiotemporal coupling identification model to deeply mine the spatiotemporal correlation patterns of the thermal fields in each zone, dividing them into temperature-sensitive and non-sensitive areas. This solves the problem of insufficient analysis of thermal field characteristics in traditional technologies. A backlight power consumption and temperature control coupling optimization algorithm establishes a dynamic constraint relationship between power consumption and temperature control, achieving synergistic optimization and avoiding imbalances caused by solely pursuing either temperature control or power consumption. A low-noise temperature change real-time demodulation algorithm specifically suppresses noise interference, ensuring the accuracy of control commands. Combined with the hardware acceleration and parallel computing capabilities of the full-domain temperature control logic main control chip, this improves the adjustment response speed and execution accuracy. A dynamic feedback adjustment chain ensures continuous parameter optimization, forming a full-process dynamic control system that is superior to traditional static control methods.

[0043] This invention addresses the issue of insufficient precision in thermal field identification and control. By employing multi-channel data acquisition and spatiotemporal coupling analysis, it breaks away from the traditional isolated data processing model, achieving precise capture of the thermal field characteristics of each zone. This makes adjustment commands more targeted and avoids local temperature control imbalances. Regarding the lack of coordination between power consumption and temperature control, a coupling optimization algorithm is used to establish a dynamic correlation between the two. Simultaneously, noise suppression and precise demodulation techniques ensure the effectiveness of control commands, avoiding the drawbacks of a single-target approach and improving the uniformity and long-term reliability of the backlight module. The deep integration of hardware and software and the dynamic parameter adaptation mechanism further enhance the adaptability of zoned adjustment, comprehensively solving the adaptation problems of traditional temperature control methods in high-zone, high-brightness display devices.

[0044] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0045] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for temperature zone adjustment of a backlight module for a display device, characterized in that, Includes the following steps: S1. Real-time temperature data of each zone of the backlight module of the display device is collected by the multi-channel temperature sensing unit on the full-domain temperature control logic main control chip, and the power consumption feedback signal and drive current change information during the operation of the backlight module are obtained simultaneously. S2. The spatial-temporal coupling identification model of the zone thermal field is called to perform coupling analysis on the collected temperature data, power consumption feedback signal and drive current change information, divide the temperature sensitive area and non-sensitive area of ​​the backlight module, and determine the thermal field distribution characteristics and spatio-temporal correlation law of each zone. S3. The backlight power consumption and temperature control coupling optimization algorithm is used to construct the coupling constraint relationship between power consumption and temperature control according to the thermal field distribution characteristics and spatio-temporal correlation law, and generate the initial backlight adjustment parameter set of each zone. S4. The initial backlight adjustment parameter set is noise suppressed by the low-noise temperature change real-time demodulation algorithm, and the temperature control adjustment command of each zone is obtained by demodulation. S5, the full-domain temperature control logic main control chip dynamically adjusts the driving voltage, light emission duration and light emission intensity of each zone of the backlight module according to the temperature control adjustment command, and performs temperature zone adjustment; S6, continuously collects the temperature data and power consumption data of each zone after adjustment, and feeds them back to the zone thermal field spatiotemporal coupling identification model and the backlight power consumption temperature control coupling optimization algorithm to form a dynamic adjustment link.

2. The temperature zone adjustment method for a display device backlight module according to claim 1, characterized in that, The expression for the spatiotemporal coupling identification model of the partitioned thermal field is: ;in, The spatial coordinates of a certain section of the backlight module With time instantaneous temperature below It is a spatial distribution function. It is a time decay function. For spatiotemporal coupling coefficients, Number of partitions; For thermal field coupling strength, This is the strength correction factor. For the Laplace operator, It is the first derivative of the time decay function.

3. The temperature zone adjustment method for a display device backlight module according to claim 1, characterized in that, The expression for the backlight power consumption and temperature control coupling optimization algorithm is as follows: in, For the backlight module at temperature The power consumption value under these conditions The power consumption coefficient is... The power consumption order is... For driving current variable, Let current influence function, The attenuation coefficient is... Reference temperature; To optimize the driving voltage, This is a power consumption-voltage mapping function. To optimize the coefficients, Let T be the k-th power of temperature.

4. A temperature zone adjustment method for a display device backlight module according to claim 1, characterized in that, The expression for the low-noise temperature-varying real-time demodulation algorithm is: in, This is the demodulated voltage command. The original feedback voltage, The demodulation coefficients are... For demodulation order, The signal angular frequency, This is the noise suppression coefficient. It is a symbolic function.

5. A method for temperature zone adjustment of a backlight module for a display device according to claim 1, characterized in that, The full-domain temperature control logic main control chip adopts a 32-bit RISC-V architecture, integrates a multi-channel 16-bit high-precision analog-to-digital conversion module and a high-speed digital signal processing unit, and the chip has a built-in temperature partition mapping register and an algorithm parameter cache unit with a cache capacity of 8MB. The temperature sensing unit of the backlight module adopts a distributed platinum resistance sensor array with a spacing of no more than 5mm between adjacent sensors and a sampling frequency of 100Hz. The iteration step size of the backlight power consumption temperature control coupling optimization algorithm is dynamically adjusted from 0.01 to 0.

1. The noise suppression threshold of the low-noise temperature change real-time demodulation algorithm is dynamically adapted according to the zone temperature value, with an adaptation range of 0.05 to 0.

3. Each algorithm is operated in parallel through the chip's built-in hardware acceleration engine, and the operation latency is controlled within 10μs.

6. A method for temperature zone adjustment of a backlight module for a display device according to claim 1, characterized in that, S2 includes the following steps: S21, the full-domain temperature control logic main control chip classifies and associates the collected temperature data, power consumption feedback signals, and drive current change information according to preset partition numbers, and establishes a multi-dimensional data matrix for each partition. The row dimension of the matrix corresponds to the time series, and the column dimension corresponds to different types of sensor data; S22, the spatial feature extraction module of the partition thermal field spatiotemporal coupling identification model is called to perform coupling operations on the spatially related data in the data matrix to identify the gradient distribution law of temperature in each partition as a function of spatial coordinates; S23, the time series data in the data matrix is ​​processed by the model's time feature analysis module to mine the lag correlation characteristics of temperature, power consumption, and drive current in each partition in the time dimension; S24, by combining the spatial gradient distribution law and the time lag correlation characteristics, the division of temperature-sensitive and non-sensitive areas is completed, and the thermal field distribution characteristic parameters and spatiotemporal correlation matrix of each partition are output.

7. A method for temperature zone adjustment of a backlight module for a display device according to claim 1, characterized in that, S3 includes the following sub-steps: S31, the backlight power consumption and temperature control coupling optimization algorithm reads the thermal field distribution characteristic parameters and spatiotemporal correlation matrix output by S2 to determine the constraint thresholds for temperature control of each zone. The constraint thresholds include the maximum allowable temperature and the minimum operating temperature; S32, based on the constraint thresholds, a power consumption-temperature control objective function is constructed. The function aims to maximize the temperature control accuracy and minimize power consumption as a secondary objective; S33, the objective function is solved by the algorithm's built-in multi-objective optimization module. The spatiotemporal correlation constraints of the thermal field of each zone are incorporated into the solution process to generate multiple sets of candidate backlight adjustment parameters; S34, the feasibility of the candidate parameter sets is verified, parameter combinations that exceed the hardware driving capability are eliminated, and the initial backlight adjustment parameter sets for each zone are obtained.

8. A method for temperature zone adjustment of a backlight module for a display device according to claim 1, characterized in that, S4 includes the following sub-steps: S41, the low-noise temperature-varying real-time demodulation algorithm receives the initial backlight adjustment parameter set output by S3, extracts voltage, current, and duration-related parameters from the parameter set, and forms the original adjustment signal sequence; S42, performs frequency domain analysis on the original adjustment signal sequence, identifies high-frequency noise components and temperature-varying interference components in the signal, and determines the frequency distribution range of noise and interference; S43, calls the demodulation operation module of the algorithm, performs product operation and phase correction on the original adjustment signal sequence in combination with the frequency distribution range, and suppresses high-frequency noise and temperature-varying interference; S44, outputs the corrected temperature control adjustment command, which includes specific control values ​​for the driving voltage, light emission duration, and light emission intensity of each zone.

9. A method for temperature zone adjustment of a backlight module for a display device according to claim 1, characterized in that, S5 includes the following steps: S51, the global temperature control logic main control chip receives the temperature control adjustment command output by S4, decodes the command, and parses the control parameters corresponding to each partition; S52, the chip's drive control module generates control signals for the backlight drive circuit of each partition according to the parsed control parameters, the control signals including pulse width and frequency information; S53, the drive circuit responds to the control signal, adjusts the driving voltage amplitude output to each partition of the backlight module, and synchronously controls the conduction time and current intensity of the light-emitting unit; During the control process, the S54 chip monitors the working status of each partition drive circuit in real time to ensure that the control parameters are executed according to the instructions and to avoid overvoltage and overcurrent.

10. A method for temperature zone adjustment of a backlight module for a display device according to any one of claims 1-9, characterized in that, This method is implemented through a temperature zoning adjustment system for backlight modules of display devices, comprising: a multi-dimensional data acquisition unit for zoned thermal fields, a spatiotemporal coupling identification model calculation unit, a power consumption and temperature control coupling optimization processing unit, a low-noise temperature change real-time demodulation unit, a global temperature control logic main control unit, and a backlight module zoning drive unit; the multi-dimensional data acquisition unit for zoned thermal fields is connected to the backlight module zoning drive unit, and is used to collect temperature, power consumption, and drive current data of each zone and transmit them to the spatiotemporal coupling identification model calculation unit; the spatiotemporal coupling identification model calculation unit and the power consumption and temperature control coupling optimization processing unit communicate bidirectionally to complete... The thermal field distribution characteristics and spatiotemporal correlation patterns are analyzed and output to the power consumption and temperature control coupling optimization processing unit; the power consumption and temperature control coupling optimization processing unit is connected to the low-noise temperature change real-time demodulation unit to generate an initial adjustment parameter set and transmit it to the demodulation unit; the low-noise temperature change real-time demodulation unit communicates with the global temperature control logic main control unit and outputs temperature control adjustment commands; the global temperature control logic main control unit is connected to the spatiotemporal coupling identification model calculation unit, the power consumption and temperature control coupling optimization processing unit, and the backlight module zonal driving unit, respectively, and controls the driving unit to perform zonal temperature adjustment according to the adjustment commands, while simultaneously sending feedback data back to the front-end calculation and optimization unit.

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