Display panel, display life improvement method thereof and display device
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- WUHAN TIANMA MICROELECTRONICS CO LTD SHANGHAI BRANCH
- Filing Date
- 2026-03-09
- Publication Date
- 2026-05-29
Smart Images
Figure CN122116808A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to display technology, and more particularly to a display panel and a method for improving the display lifespan of the same, and a display device. Background Technology
[0002] Organic light-emitting diode (OLED) display technology, with its advantages of self-illumination, high contrast, wide color gamut, and fast response, has been widely used in smartphones, televisions, and automotive displays. Compared with traditional liquid crystal display (LCD) technology, OLED does not require a backlight module, enabling thinner and lighter structural designs, and it can maintain stable response performance even in low-temperature environments, which is crucial for the reliability of special applications such as automotive displays.
[0003] However, OLED display technology has significant inherent drawbacks: the material degradation rates of different color subpixels vary considerably, with blue subpixels having a relatively short lifespan, and environmental factors such as temperature and humidity further accelerating their degradation process. When a display device displays static images or high-brightness images in a fixed area for an extended period, the corresponding subpixels will experience excessive degradation due to continuous light emission, resulting in significant differences in the degree of brightness decay across different areas.
[0004] In existing OLED display technology, uneven pixel degradation directly leads to burn-in. Specifically, after a device displays a static image for an extended period, some pixels experience irreversible brightness decay due to overuse. This results in residual outlines or color differences from the previous image when switching to other screens. This color difference not only severely impacts display quality but also degrades user experience. Especially in scenarios with high visual consistency requirements, such as automotive displays, burn-in directly affects driving safety and product reliability.
[0005] Furthermore, the white light from an OLED is composed of RGB sub-pixels with a specific brightness ratio (W=R+G+B). When the degree of decay of sub-pixels in a certain area is different, it will cause the RGB brightness ratio in that area to shift, which in turn will cause a change in the CIE coordinates of the white point. This change will cause problems such as local color cast and uneven brightness in the displayed image, and this damage is irreversible, which severely limits the application of OLED display technology in scenarios that require stable display over a long period of time.
[0006] Current solutions to OLED burn-in issues primarily focus on passive compensation methods such as pixel refresh and image shift. While these methods can alleviate burn-in to some extent, they cannot fundamentally solve the problem of uneven subpixel decay and may even cause side effects such as flickering and image shift, affecting display quality. Therefore, there is an urgent need for a technical solution that can actively predict the subpixel decay rate and compensate for pixel brightness uniformity. This would mitigate or eliminate burn-in caused by uneven subpixel decay in OLED displays, improve the lifespan and reliability of display devices, and expand the application scenarios of OLED technology in fields such as automotive displays and professional displays. Summary of the Invention
[0007] This invention provides a display panel, a method for improving the display lifespan, and a display device. The method for improving the display lifespan establishes an artificial intelligence lifespan prediction model, combines experimentally measured intrinsic decay data with user habits, and achieves dynamic prediction and active compensation for pixel decay. This reduces screen burn-in from the root cause and improves the lifespan and visual consistency of OLED display devices, making it particularly suitable for long-term static display scenarios such as automotive displays.
[0008] In a first aspect, embodiments of the present invention provide a method for improving the display lifespan of a display panel, comprising: A decay model for sub-pixels in the display panel is established based on test data; Based on the aforementioned attenuation model, user habits, and environmental parameters, a data training process is performed to obtain an artificial intelligence lifespan prediction model. The pixel aging region is determined based on the artificial intelligence lifetime prediction model, and the display mode of the sub-pixels in the pixel aging region is adjusted to improve the display lifetime of the pixel aging region.
[0009] Secondly, embodiments of the present invention also provide a display panel, wherein the display lifespan of the display panel is improved by utilizing the above-described display lifespan improvement method.
[0010] Thirdly, embodiments of the present invention also provide a display device, including the display panel described above.
[0011] The method for improving the display lifespan of a display panel provided in this invention first establishes a decay model of sub-pixels in the display panel based on test data, which can be obtained in a laboratory. Then, data training is performed based on the decay model, user habits, and environmental parameters to obtain an artificial intelligence lifespan prediction model according to a preset algorithm. Finally, the pixel aging area is determined based on the artificial intelligence lifespan prediction model, and the display method of the sub-pixels in the pixel aging area is adjusted, such as through dynamic sub-pixel displacement or adaptive reduction of the refresh rate, to improve the display lifespan of the pixel aging area. The technical solution of this invention, by establishing an artificial intelligence lifespan prediction model and combining experimentally measured intrinsic decay data with user habits, achieves dynamic prediction and active compensation for pixel decay, fundamentally reducing screen burn-in and improving the lifespan and visual consistency of OLED display devices. It is particularly suitable for long-term static display scenarios such as automotive displays. Attached Figure Description
[0012] Figure 1 A flowchart illustrating a method for improving the display lifespan of a display panel according to an embodiment of the present invention; Figure 2 An intrinsic attenuation data map of RGBW sub-pixels of a display panel is provided in an embodiment of the present invention; Figure 3 A brightness comparison diagram of RGBW sub-pixels of a display panel provided in an embodiment of the present invention; Figure 4 A graph showing the attenuation data of sub-pixels of a display panel at 60°C, provided in an embodiment of the present invention. Figure 5 This is a prediction result diagram of the AI prediction model provided in the embodiments of the present invention; Figure 6 A brightness comparison diagram of another RGBW sub-pixel of a display panel provided in an embodiment of the present invention; Figure 7 A top view schematic diagram of a display panel provided in an embodiment of the present invention; Figure 8 For along Figure 7 A schematic diagram of the cross-sectional structure along the mid-section line A-A'; Figure 9 This is a schematic diagram of the structure of a display device provided in an embodiment of the present invention. Detailed Implementation
[0013] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.
[0014] The terminology used in the embodiments of this invention is for the purpose of describing specific embodiments only and is not intended to limit the invention. It should be noted that directional terms such as "upper," "lower," "left," and "right" described in the embodiments of this invention are used to describe the angles shown in the accompanying drawings and should not be construed as limiting the embodiments of this invention. Furthermore, in the context, it should be understood that when referring to an element being formed "upper" or "lower" of another element, it can be formed not only directly "upper" or "lower" of the other element, but also indirectly "upper" or "lower" of the other element through an intermediate element. The terms "first," "second," etc., are used for descriptive purposes only and do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0015] OLED burn-in is essentially an irreversible decrease in brightness caused by prolonged high brightness / fixed display of pixels. Existing technologies generally mitigate burn-in through single methods such as material optimization, pixel refresh, and image shifting, but their effectiveness needs improvement. Therefore, this invention provides a method for extending the display lifespan of a display panel. First, a decay model of sub-pixels in the display panel is established based on test data. Then, data training is performed based on the decay model, user habits, and environmental parameters to obtain an artificial intelligence lifespan prediction model. Finally, the pixel aging areas are determined based on the artificial intelligence lifespan prediction model, and the display mode of sub-pixels in the aging areas is adjusted to improve the display lifespan of these areas. By establishing an artificial intelligence lifespan prediction model and combining experimentally measured intrinsic decay data with user habits, dynamic prediction and proactive compensation for pixel decay are achieved, fundamentally reducing burn-in and improving the lifespan and visual consistency of OLED display devices. This is particularly suitable for long-term static display scenarios such as automotive displays.
[0016] Figure 1 This is a flowchart illustrating a method for improving the display lifespan of a display panel according to an embodiment of the present invention. (Refer to...) Figure 1 The display lifespan improvement method provided in this embodiment of the invention includes: S110. Establish a decay model for sub-pixels in the display panel based on the test data.
[0017] Optionally, the test data is obtained in the laboratory and includes intrinsic attenuation data of subpixels at different brightness levels, as well as data on the effects of operating time, temperature, current, and humidity on brightness attenuation at different brightness levels.
[0018] The core idea of this invention lies in constructing a "monitoring" system. predict The "compensation" closed-loop control system quantifies the total attenuation of OLED sub-pixels into multiple additive, independently interpretable nonlinear functions, thereby achieving precise attenuation prediction and targeted control of the compensation strategy. For example, to achieve accurate quantification and prediction of the RGB sub-pixel attenuation process, this embodiment of the invention decomposes the total sub-pixel attenuation into an additive combination of multiple nonlinear functions, clarifying the independent effects and superposition effects of each influencing factor on the attenuation process. The total attenuation model expression is as follows: Total attenuation = f1 (cumulative lighting time) + f2 (historical environmental factors such as temperature / humidity) + f3 (static content percentage / position) + ... . ... represent other influencing factors, which should be selected according to the actual situation in different application scenarios.
[0019] The definitions and origins of each nonlinear function in the model are clear and explicit, allowing for independent interpretation, fitting, and optimization. This effectively ensures the traceability, adjustability, and scalability of the prediction process, as detailed below: f1 (cumulative illumination time): The core decay function, which is obtained by fitting laboratory measured data. It accurately reflects the intrinsic decay law of sub-pixels under standard brightness conditions and is the core foundation of the entire artificial intelligence (AI) prediction model. f2 (environmental history such as temperature / humidity): Environmental impact function. It collects external environmental parameters in real time through the environmental sensing module built into the display panel, and combines them with historical data of environmental changes during user use. It is determined by the AI model through autonomous learning and dynamic fine-tuning, and focuses on reflecting the accelerating effect of environmental factors on pixel decay. f3 (Static content percentage / position): A function that influences usage habits. It is determined by real-time monitoring of user usage data (including dwell time on different screens, static area distribution characteristics, etc.) through an AI module and after self-learning. It mainly reflects the aggravating effect of static display scenarios on local pixel attenuation. Other supplementary functions: can be flexibly added according to actual application conditions (such as current change influence function, brightness level influence function, etc.) to further improve the model prediction accuracy and adapt to the needs of different application scenarios.
[0020] S110 is the first stage of the three core implementation stages of this invention, specifically the laboratory testing stage, used for data acquisition and laying the foundation for the model. To construct a high-precision total attenuation model, various basic data are first systematically collected through a combination of controlled laboratory experiments and real-time monitoring, providing solid data support for subsequent model training and parameter calibration. The specific data collection content is as follows: Intrinsic decay data acquisition: Under a standard controlled environment (constant temperature, humidity, and current), the system collects intrinsic decay data of RGB sub-pixels at different brightness levels, focusing on recording the correspondence between cumulative lighting time and brightness decay, which is used to accurately fit the f1 function; Data collection on attenuation under superimposed acceleration factors: Simulating the complex environment in actual use, data on the impact of different variables such as temperature, humidity, and current on the attenuation of sub-pixels at each brightness level are collected, and the attenuation rate under different acceleration factors is recorded in detail, providing basic data for fitting environmental functions such as f2. Burn-in threshold data acquisition: The system records the changes in the ratio of RGB sub-pixels under different attenuation levels, and clarifies the attenuation threshold and white point offset standard when burn-in occurs, serving as the core basis for subsequent prediction of burn-in risk and judgment of compensation timing.
[0021] For example, Figure 2 This invention provides an intrinsic attenuation data map of RGBW sub-pixels of a display panel. Figure 2 The data points in the middle represent measured data, and the dashed line represents the linear fitting result. Figure 2 The horizontal axis represents pixel illumination time in hours (h), and the coordinates of the data graph in subsequent embodiments are the same. In a controlled laboratory environment, intrinsic decay data of RGB sub-pixels in static areas, as well as decay data after overlaying acceleration factors such as temperature and humidity, are collected. Simultaneously, the RGB decay ratio and white point offset threshold at the time of burn-in are recorded to establish a Base database. Then, based on the Base database, a preset algorithm (e.g., nonlinear least squares regression) is used to construct an AI prediction model to learn the intrinsic decay law of RGB sub-pixels and to preliminarily predict the decay trend and burn-in time of the product under standard operating conditions. Figure 3 This invention provides a brightness comparison chart of RGBW sub-pixels in a display panel. Laboratory data shows that the initial brightness ratio of the static and non-static display areas was 1:3.11:0.31 (non-static display area, black screen has no brightness reduction by default). After 500 hours of operation, the ratio in the static display area changed to 1:3.06:0.29, indicating the onset of burn-in. AI, based on this data, establishes a Base library to predict burn-in time after the static area is lit and provides a sub-pixel brightness compensation scheme before burn-in occurs.
[0022] S120. Based on the attenuation model, user habits, and environmental parameters, data training is performed to obtain an artificial intelligence lifespan prediction model.
[0023] S120 is the second stage, specifically the simulation training and prediction stage, used for model calibration to achieve accurate predictions. Based on various basic data collected in the laboratory, a dedicated algorithm is used to train and determine the specific expressions of each nonlinear function in the total decay model, completing the initialization and accurate calibration of the AI prediction model, ensuring that the model's prediction accuracy meets the needs of practical applications. The specific steps are as follows: Algorithm selection and solution: The nonlinear least squares regression method (or other preset optimization algorithms, such as at least one of linear regression, polynomial regression, principal component regression, and partial least squares regression, which can be selected according to the actual situation) is used to solve each nonlinear function (f1, f2, f3, etc.) in the total decay model and determine its specific expression. The core objective is to minimize the sum of squared errors between the model prediction value and the laboratory measured value and the real-time monitoring value, so as to maximize the model prediction accuracy. Model training and optimization: Input the intrinsic decay and accelerated decay data collected in the laboratory into the model in batches to complete the initial training and parameter calibration of the model. At the same time, reserve the input interface for real-time user data and real-time environmental data to reserve space for the subsequent dynamic fine-tuning of the model according to the actual working conditions. Prediction output: After the model is trained and calibrated, it can accurately output the aging rate prediction value of each pixel or pixel area within a future preset time period (such as the next 24 hours) based on the input historical data (cumulative lighting time, history of environmental changes, proportion of static content, etc.). The prediction result is visualized as a screen burn-in risk heat map, clearly identifying high-risk static areas, providing a clear target for the accurate implementation of subsequent compensation measures.
[0024] Optionally, after training the AI-powered lifespan prediction model based on the decay model, user habits, and environmental parameters, the following may also be included: The pixel aging area and the corresponding burn-in time are determined based on the artificial intelligence lifespan prediction model. When the working time in the pixel aging area reaches the burn-in time, brightness compensation is performed on the sub-pixels in the pixel aging area.
[0025] The working state of the display panel varies in different application scenarios, resulting in corresponding pixel aging areas and burn-in times. Based on the pre-established AI model, the corresponding pixel aging areas and burn-in times of the display panel can be determined, and brightness compensation can be achieved before burn-in to improve the display effect.
[0026] Optionally, brightness compensation is performed on sub-pixels within the pixel aging area, including: Increase the driving current or driving voltage of the sub-pixel.
[0027] The brightness of a sub-pixel can be increased by increasing its driving current or driving voltage; the specific setting value can be determined using an AI model.
[0028] S130. Determine the pixel aging area based on the artificial intelligence lifespan prediction model, and adjust the sub-pixel display method of the pixel aging area to improve the display lifespan of the pixel aging area.
[0029] S130 represents the third stage, specifically the AI prediction and closed-loop compensation stage, used to achieve dynamic regulation and attenuation mitigation. This stage constructs a complete "monitoring" system. predict compensate The "verification" closed-loop control process integrates a dual strategy of short-term attenuation mitigation and long-term precise compensation to achieve dynamic adjustment of sub-pixel attenuation. Simultaneously, a real-time feedback mechanism continuously optimizes model parameters. The specific implementation process is as follows: AI Lifespan Prediction Model Construction: Integrating two core sub-models to form a complete AI lifespan prediction model: ① Physical Intrinsic Decay Sub-model: Built based on laboratory accelerated aging test data, specifically responsible for outputting intrinsic decay prediction results related to f1; ② User Habits and Environmental Feedback Sub-model: Based on real-time product monitoring data (user usage habits, changes in environmental parameters, etc.), dynamically fine-tuning functions such as f2 and f3, and finally outputting pixel-level aging rate prediction results and screen burn-in risk heatmap.
[0030] Optionally, the pixel aging area includes the static image display area. Adjustments are made to the display method of the sub-pixels in the pixel aging area, including: Shift the display subpixels of the static image display area and / or reduce the refresh rate of the static image display area.
[0031] Since static display areas require displaying a fixed image for extended periods, they are prone to burn-in due to aging. In this embodiment of the invention, a short-term mitigation strategy is employed to delay this degradation: for the static content areas marked on the burn-in risk heatmap, a combination of "sub-pixel micro-displacement + adaptive reduction of static area refresh rate" is used to effectively reduce pixel working time and delay the onset of burn-in without affecting the user's normal visual experience. Sub-pixel dynamic displacement: The displacement step size is strictly controlled below the user's minimum perceived step size, effectively avoiding continuous high load illumination of local pixels and achieving uniform distribution of pixel loss. Adaptive refresh rate reduction: For example, reducing the static area refresh rate from 120Hz to 60Hz can reduce the pixel illumination time by 50%, directly slowing down the sub-pixel brightness decay rate and reducing the risk of excessive degradation of local pixels.
[0032] Optionally, the display subpixels of the static image display area may be shifted, including: Control the display sub-pixel to turn off, and control the first sub-pixel that is a first distance away from the display sub-pixel to turn on; Among them, the first sub-pixel emits the same color as the display sub-pixel, the brightness of the first sub-pixel is equal to the target display brightness of the display sub-pixel, and the first distance is less than the minimum perceptible distance for the user.
[0033] For example, under standard viewing conditions, such as a mobile phone screen, the visual perception threshold under different displacement vectors (Δx, Δy) is tested. The base range of the displacement step size is set to 1 to 2 pixel units, within which displacement is imperceptible. The specific range of movement can be determined based on the viewing distance of the fixed device, and the step size can be scaled according to the screen distance. The step size is inversely proportional to the viewing distance, and the calculation formula can be expressed as: Actual step size = Base step size × (Standard distance D / Measured distance d).
[0034] In practice, when the display sub-pixels are rested, there will be a partial recovery effect. The experiment will consider the recovery experiment measurement. In the laboratory stage, it is necessary to design an intermittent aging experiment of "work-rest-work" to collect data and fit an accurate recovery time constant to improve the accuracy of AI prediction.
[0035] Optionally, when reducing the refresh rate of the static display area, the light emission time of the sub-pixels in the static display area can be reduced, thereby increasing the peak brightness of the sub-pixels.
[0036] In this embodiment of the invention, in addition to adopting "subpixel micro-displacement + static area refresh rate adaptive reduction", a dynamic subpixel brightness compensation strategy is also used to repair the ratio: based on the pixel-level aging rate prediction results output by the AI prediction model, the dynamic subpixel brightness compensation operation is precisely executed for areas that are about to have the risk of screen burn-in. By adjusting the brightness output ratio of the RGB subpixels in the area in real time, it is restored to the preset brightness ratio and white point CIE coordinates, fundamentally solving the problems of color cast and screen burn-in caused by uneven subpixel attenuation.
[0037] In practice, when the refresh rate of the implementation area decreases and switches to low-frequency mode, the system executes a duty cycle-peak brightness coordinated adjustment algorithm. Within the low-frequency PWM cycle, a very short high-brightness pulse (increasing peak brightness) is used to compensate for the decrease in average brightness caused by prolonged shutdown (reducing duty cycle). The key physical quantity affecting OLED pixel aging is not instantaneous brightness. If the target brightness is 100 nits and the duty cycle is 20%, the brightness needs to be briefly increased to 500 nits within a 200ms on-pulse period. The instantaneous peak brightness required must be within the screen's safe current / temperature limits to avoid accelerated damage. In addition, increasing the current for compensation will accelerate future aging. During implementation, the compensation current value is used as a new input variable to dynamically update the aging prediction curve. By balancing "restoring brightness," "slowing down future aging," and "ensuring color uniformity," incomplete compensation (such as restoring only 95%) can be selected to significantly reduce the required current and obtain a better overall lifespan.
[0038] Furthermore, the display lifespan improvement method provided in this embodiment of the invention also includes closed-loop feedback and iterative optimization: after the compensation scheme is output to the display driver IC for execution, the system monitors key parameters such as brightness uniformity and white point coordinates of the display screen in real time through the closed-loop verification module, and feeds back the verification results to the AI prediction model in a timely manner; the model iteratively adjusts the parameters of each nonlinear function and the compensation strategy according to the verification error to ensure that the compensation effect is always in the optimal state and realizes continuous optimization of closed-loop control.
[0039] "Monitoring" in this embodiment of the invention predict The "compensation" closed-loop control system can be achieved through the coordinated operation of the following five functional modules, ensuring efficient linkage and precise control of each link. The specific modules are described below: Data acquisition module: includes laboratory data acquisition unit and real-time monitoring unit. The laboratory data acquisition unit is responsible for collecting basic data such as intrinsic decay and accelerated decay, while the real-time monitoring unit is responsible for collecting user habits (screen dwell time, static area distribution), environmental parameters (temperature, humidity, current) and real-time screen display data. Model training and prediction module: Based on nonlinear least squares regression or other algorithms, it completes the training, parameter calibration and optimization of the total decay model, and accurately outputs pixel-level aging rate prediction results and screen burn-in risk heat map; Compensation control module: Based on the prediction results output by the model and the heat map of screen burn-in risk, it generates targeted short-term mitigation strategies (sub-pixel displacement, refresh rate adjustment) and long-term compensation strategies (brightness ratio adjustment), and outputs control commands to the display driver IC; Closed-loop verification module: Real-time verification of the display effect after compensation, collection of verification data such as brightness uniformity and white point coordinates, calculation of compensation error and feedback to the model training and prediction module, providing a basis for iterative optimization of the model and compensation strategy; Display driver module: Precisely executes various instructions output by the compensation control module to achieve precise control of sub-pixel displacement, refresh rate and brightness output, ensuring that the compensation strategy is implemented.
[0040] In one embodiment, the primary consideration is the effect of temperature. Figure 4 This is a graph showing the attenuation data of sub-pixels of a display panel at 60°C, provided in an embodiment of the present invention. Figure 5 This is a prediction result diagram of the AI prediction model provided in an embodiment of the present invention. Figure 6 This is another brightness comparison diagram of RGBW sub-pixels of a display panel provided in an embodiment of the present invention. Figure 4It is known that at an ambient temperature of 60℃, screen burn-in begins to occur in the static display area after 300 hours, 200 hours earlier than at room temperature. The AI model builds a base library by learning from data on accelerated decay at varying temperatures (e.g., -40℃ to 80℃). Based on this base library, the AI prediction model can dynamically predict (as ambient temperature changes) the lifespan of RGB subpixels in the static display area and the time of screen burn-in occurrence. Figure 5 The black dashed line represents the initial lighting time of the static area, and the yellow line represents the prediction result of the AI model. The AI prediction model is based on this formula. The formula is established, where k is the attenuation coefficient, t is time, L0 is the initial brightness value, T is the absolute temperature, and J is the current density. Other influencing factors, such as humidity H, can also be superimposed. The AI prediction model is then based on this formula. Establish.
[0041] This invention embodiment constructs a "monitoring" predict The integrated closed-loop control system for "compensation" innovatively decomposes the total attenuation of sub-pixels into an independently interpretable additive nonlinear function. By integrating laboratory measured data with AI real-time learning capabilities, it achieves accurate prediction and dynamic control of OLED sub-pixel attenuation. Compared with existing technologies, it has significant technical advantages and practical value. The core technical effects are as follows: 1. The prediction accuracy has been significantly improved, enabling accurate prediction of screen burn-in risk.
[0042] By decomposing the total attenuation into independent nonlinear functions such as f1, f2, and f3, each function has a clear origin and can be optimized independently. Combined with nonlinear least squares regression or other algorithms to fit laboratory test data, the model prediction error is significantly reduced. At the same time, user habits and real-time environmental data are incorporated to dynamically fine-tune the model, achieving pixel-level accurate prediction of aging rate. Furthermore, a heatmap of screen burn-in risk is used to visually present high-risk areas, which can accurately predict the occurrence time of screen burn-in within a preset time period in the future. This completely breaks the limitation of existing technologies that "passively deal with screen burn-in" and achieves proactive identification and intervention of screen burn-in risk.
[0043] 2. Closed-loop control enables dynamic adaptation, ensuring optimal compensation effect throughout.
[0044] Build "monitoring" predict compensate The AI prediction model can continuously iterate and optimize the parameters of each nonlinear function based on real-time monitored environmental changes and user habits. The compensation strategy is dynamically adjusted according to the actual working conditions, effectively avoiding the scenario limitations of fixed compensation schemes. This ensures that the optimal attenuation mitigation and compensation effect can be achieved in different usage scenarios and under different environmental conditions.
[0045] 3. A dual strategy of short-term and long-term measures to comprehensively mitigate screen degradation and avoid screen burn-in.
[0046] In the short term, a combined strategy of "subpixel micro-displacement + adaptive refresh rate reduction" is employed to significantly reduce the illumination time of pixels in static areas (e.g., halving the refresh rate can reduce illumination time by 50%) without the user noticing, thus slowing down the subpixel attenuation rate at its source. In the long term, dynamic brightness compensation is performed based on AI prediction results to precisely adjust the RGB brightness ratio and restore the uniformity of display color and brightness. The dual strategies work synergistically to comprehensively mitigate screen burn-in from the two core dimensions of "delaying attenuation" and "restoring the ratio," and completely solve problems such as color cast and color difference caused by uneven subpixel attenuation.
[0047] 4. The model is highly interpretable and easy to debug and optimize.
[0048] The total attenuation model adopts an additive nonlinear function decomposition design. Each function corresponds to a clear attenuation influencing factor (cumulative lighting time, environmental parameters, and usage habits), which can be interpreted, fitted, and optimized independently. Compared with traditional black-box AI models, it has stronger traceability and debuggability, making it easier to flexibly adjust model parameters according to product iterations and application scenario expansion, significantly improving the adaptability and scalability of the solution.
[0049] 5. Extend product lifespan and expand the application boundaries of OLED.
[0050] It fundamentally solves the core technical pain point of uneven subpixel decay in OLEDs, significantly reduces the risk of screen burn-in, and significantly extends the lifespan of display devices. Especially for professional scenarios such as automotive displays that require long-term static display, it effectively improves the reliability and stability of products, breaks through the application limitations of existing OLED technology in professional displays, industrial control and other fields, and further enhances the market competitiveness of OLED display technology.
[0051] 6. It balances display quality and user experience without any additional side effects.
[0052] The short-term subpixel displacement step size is strictly controlled below the minimum perceptible step size for users, and the refresh rate adjustment only applies to static areas, so it will not affect the normal visual experience of users. The long-term brightness compensation accurately matches the preset brightness ratio, so it will not cause additional side effects such as screen flicker or offset. While effectively alleviating screen burn-in and extending product life, it always maintains the inherent advantages of OLED display technology, such as high contrast and wide color gamut, taking into account the practicality of the solution and the user experience.
[0053] This invention also provides a display panel, which improves the display lifespan of the display panel by utilizing the display lifespan improvement method provided in the above embodiments.
[0054] The display panel can be an OLED display panel, for example. Figure 7 This is a top view schematic diagram of a display panel provided in an embodiment of the present invention. Figure 8 For along Figure 7 A schematic diagram of the cross-sectional structure along section line A-A', for reference. Figure 7 and Figure 8 The display panel 10 provided in this embodiment includes a substrate 110, which includes a display area 11 and a non-display area 12. Light-emitting devices 120 are located within the display area 11; the light-emitting devices 120 are arranged in an array within the display area 11 and may include light-emitting devices 120 emitting different colors of light, such as red, green, and blue light-emitting devices 120. Figure 7 The image only schematically shows the light-emitting device 120 located in the display area; the light-emitting color and arrangement of the corresponding light-emitting device 120 are not limited.
[0055] Continue to refer to Figure 8 The display panel includes a substrate 110; wherein the substrate 110 may be flexible, and thus stretchable, foldable, bendable, or rollable, such that the display panel may be stretchable, foldable, bendable, or rollable. The substrate 110 may be formed of any suitable insulating material having flexibility. The substrate 110 may be used to block oxygen and moisture, prevent moisture or impurities from diffusing through the substrate 110, and a flat surface may be formed on the upper surface of the substrate 110. The substrate 110 may be transparent, translucent, or opaque. The substrate 110 may also be rigid, for example, a glass substrate, thereby forming a rigid display panel.
[0056] Specifically, the display panel 10 also includes an array layer 130 located on one side of the substrate 110. The array layer 130 is located on the side of the substrate 110 facing the display surface or touch surface of the display panel. The array layer 130 may include a plurality of thin-film transistors 21 (TFTs) and pixel circuits composed of thin-film transistors 21 for driving light-emitting devices in the display layer. Exemplarily, this embodiment uses a top-gate type thin-film transistor as an example for structural description. The thin-film transistor layer 21 includes an active layer 211 located on the substrate 110; the active layer 211 may be made of amorphous silicon, polycrystalline silicon, or metal oxide, etc. When the active layer 211 is made of polycrystalline silicon, it can be formed using low-temperature polycrystalline silicon technology, that is, amorphous silicon material is formed into polycrystalline silicon material by laser melting. The active layer 211 also includes a source region and a drain region formed by doping with N-type or P-type impurity ions, and a channel region is formed between the source region and the drain region. The array layer 130 further includes a gate insulating layer 212 located on the active layer 211; the gate insulating layer 212 includes an inorganic layer such as silicon oxide or silicon nitride, and may include a single layer or multiple layers. The thin-film transistor layer 21 also includes a gate 213 located on the gate insulating layer 212; the gate 213 may include a single layer or multiple layers of gold, silver, copper, nickel, platinum, palladium, aluminum, molybdenum, or chromium, or such as an aluminum:neodymium alloy or a molybdenum:tungsten alloy, which may be selected according to the actual situation in the specific implementation. The array layer 130 also includes an interlayer insulating layer 214 located on the gate 213; the interlayer insulating layer 214 may include inorganic or organic materials. Inorganic materials may include at least one selected from silicon nitride, aluminum nitride, zirconium nitride, titanium nitride, hafnium nitride, tantalum nitride, silicon oxide, aluminum oxide, titanium oxide, tin oxide, cerium oxide, and silicon oxynitride. The organic material may include at least one selected from acrylic resins, methacrylic resins, polyisoprene, vinyl resins, epoxy resins, urethane resins, cellulose resins, and perylene resins. The thin-film transistor 21 also includes a source electrode 2151 and a drain electrode 2152 located on the interlayer insulating layer 214. The source electrode 2151 and the drain electrode 2152 are electrically connected to the source region and the drain region, respectively, through contact holes, which may be formed by selectively removing the gate insulating layer 212 and the interlayer insulating layer 214.
[0057] Specifically, the array layer 130 may further include an organic insulating layer BPL. Optionally, the organic insulating layer BPL is located on the source electrode 2151 and drain electrode 2152 of the thin-film transistor 21. A third metal layer M3 is disposed above the organic insulating layer BPL. The third metal layer M3 can form various traces within the display panel, such as power supply voltage lines, scan signal lines, and light emission control signal lines. The specific implementation can be configured according to the actual panel structure. Optionally, the touch terminal is disposed on the same layer as the third metal layer M3. The third metal layer M3 is disposed on the same layer as a certain metal layer in the array layer. For example, it can be a metal layer on the same layer as the anode layer of the light-emitting device, or it can be a metal layer on the same layer as the source electrode 2151 and drain electrode 2152 of the thin-film transistor in the array layer. This embodiment of the invention does not limit this. The display panel may further include a planarization layer PLN. Optionally, the planarization layer PLN is located on the organic insulating layer BPL. The planarization layer PLN may include organic materials such as acrylic, polyimide, or benzocyclobutene, and the planarization layer PLN has a planarization function.
[0058] Specifically, the display panel 10 also includes a display layer 140 located on the side of the array layer 130 facing away from the substrate 110, and the display layer 140 includes a plurality of light-emitting devices 120. Optionally, the display layer 140 is located on the planarization layer PLN. The display layer 140 includes an anode layer 311, an intermediate layer 312, and a cathode layer 313 sequentially disposed in a direction away from the substrate 110. The anode layer 311 can be formed of various conductive materials. For example, the anode layer 311 can be formed as a transparent electrode or a reflective electrode depending on its application. When the anode is formed as a transparent electrode, it can include indium tin oxide, indium zinc oxide, zinc oxide, or indium oxide, etc. When the anode is formed as a reflective electrode, the reflective layer can be formed of silver, magnesium, aluminum, platinum, palladium, gold, nickel, neodymium, iridium, chromium, or mixtures thereof, and ITO, IZO, ZnO, or In2O3, etc., can be formed on the reflective layer. The intermediate layer 312 can include low molecular weight materials or high molecular weight materials. When the intermediate layer 312 comprises a low-molecular-weight material, it may include an emitter layer, and may also include at least one of a hole injection layer, a hole transport layer, an electron transport layer, and an electron injection layer. The intermediate layer 312 may include various organic materials, such as copper phthalocyanine. The intermediate layer 312 may be formed by vapor deposition or by screen printing, inkjet printing, or laser-induced thermal imaging (LITI).
[0059] However, the intermediate layer 312 is not limited to the example above. The intermediate layer 312 may comprise a single layer spanning multiple anode layers 311 or multiple layers patterned relative to each of the anode layers 311. The display layer 30 also includes a pixel definition layer (PDL) located on the side of the anode layers 311 away from the array layer 130. The pixel definition layer (PDL) may be formed of an organic material such as polyimide, polyamide, benzocyclobutene, acrylic resin, or phenolic resin. When the cathode layer 313 is formed as a transparent electrode, a compound having a low work function, such as lithium, calcium, lithium fluoride / calcium, lithium fluoride / aluminum, aluminum, magnesium, or combinations thereof, may be initially deposited on the light-emitting layer by evaporation, and a transparent electrode forming material, such as ITO, IZO, ZnO, or In2O3, may be deposited on the compound. When the cathode is formed as a reflective electrode, the cathode may be formed by evaporating Li, Ca, LiF / Ca, LiF / Al, Al, Mg, or mixtures thereof over the entire surface of the substrate.
[0060] Optionally, the anode layer 311 includes a plurality of anode patterns corresponding one-to-one with each pixel. The anode patterns in the anode layer 311 are connected to the source electrode 2151 or drain electrode 2152 of the thin-film transistor 21 through vias on the planarization layer PLN. The pixel definition layer PDL includes a plurality of openings exposing the anode layer 311, and the pixel definition layer PDL may cover the edges of the anode layer 311 patterns. The intermediate layer 312 at least partially fills the openings of the pixel definition layer PDL and contacts the anode layer 311.
[0061] Optionally, the anode layer 311, intermediate layer 312, and cathode layer 313 defined by the opening of each pixel definition layer PDL constitute the light-emitting device 120 (i.e., Figure 5 (As shown in the dashed box), each light-emitting device 120 can emit light of different colors according to different intermediate layers 312. Each light-emitting device 120 constitutes a sub-pixel, and multiple sub-pixels work together to display the image.
[0062] Optionally, the display panel 10 further includes an encapsulation layer 150 located on the display layer 140 and completely covering the display layer 140 to seal the display layer 140. Optionally, the encapsulation layer 150 can be a thin-film encapsulation layer. For example, the encapsulation layer 150 includes a first inorganic layer 41, a first organic layer 42, and a second inorganic layer 43 stacked together to prevent water and oxygen from corroding the light-emitting device 120. In this embodiment of the invention, the encapsulation layer 150 may include any number of stacked organic and inorganic materials as needed, but at least one layer of organic material and at least one layer of inorganic material are alternately deposited, and the bottom and top layers are composed of inorganic materials.
[0063] Optionally, the display panel 10 also includes a touch layer 160 located on the encapsulation layer 150. The touch layer 160 includes multiple touch electrodes for implementing touch functionality. In specific implementations, self-capacitance or mutual capacitance methods can be used. The touch layer 160 can have a single layer of touch electrodes, a double layer of touch electrodes, or a metal mesh touch electrode. The metal mesh touch electrode includes multiple metal lines extending along two intersecting directions, with the metal lines extending in different directions intersecting to form a mesh. In other embodiments, the touch layer 160 can also be located inside the encapsulation layer 150. The specific implementation can be selected according to the actual situation.
[0064] Optionally, the display panel 10 also includes a protective layer 170 located on the display layer 140. The protective layer 170 is the outermost film layer of the display panel and can be a protective cover or a protective film. The protective layer 170 can be bonded to the adjacent film layers inside the display panel using optically clear adhesive (OCA), and the surface of the protective layer 170 serves as the touch operation surface of the display panel. To avoid potential impact of the protective cover on the light-emitting devices, a support pillar PS is also provided above the display layer 140.
[0065] Figure 9 This is a schematic diagram of a display device provided in an embodiment of the present invention. (Reference) Figure 9 The display device 1 includes the display panel 2 provided in this embodiment of the invention. Specifically, the display device 1 can be a mobile phone, computer, in-vehicle display device, or smart wearable device, etc.
[0066] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, combinations, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.
Claims
1. A method for improving the display lifespan of a display panel, characterized in that, include: A decay model for sub-pixels in the display panel is established based on test data; Based on the aforementioned attenuation model, user habits, and environmental parameters, a data training process is performed to obtain an artificial intelligence lifespan prediction model. The pixel aging region is determined based on the artificial intelligence lifetime prediction model, and the display mode of the sub-pixels in the pixel aging region is adjusted to improve the display lifetime of the pixel aging region.
2. The method for improving the display lifespan of a display panel according to claim 1, characterized in that, After training the AI-powered lifespan prediction model based on the aforementioned attenuation model, user habits, and environmental parameters, the model further includes: The pixel aging region and the burn-in time corresponding to the pixel aging region are determined according to the artificial intelligence lifespan prediction model. When the working time in the pixel aging region reaches the burn-in time, brightness compensation is performed on the sub-pixels in the pixel aging region.
3. The method for improving the display lifespan of a display panel according to claim 2, characterized in that, Brightness compensation is performed on sub-pixels within the pixel aging region, including: Increase the driving current or driving voltage of the sub-pixel.
4. The method for improving the display lifespan of a display panel according to claim 1, characterized in that, The test data was obtained in the laboratory and includes intrinsic attenuation data of the sub-pixels at different brightness levels, as well as data on the effects of working time, temperature, current, and humidity on brightness attenuation at different brightness levels.
5. The method for improving the display lifespan of a display panel according to claim 1, characterized in that, The artificial intelligence life prediction model is based on at least one of the following methods: nonlinear least squares regression, linear regression, polynomial regression, principal component regression, and partial least squares regression.
6. The method for improving the display lifespan of a display panel according to claim 1, characterized in that, The pixel aging area includes a static image display area. Adjusting the display mode of the sub-pixels in the pixel aging area includes: The display sub-pixels of the static image display area are shifted and / or the refresh rate of the static image display area is reduced.
7. The method for improving the display lifespan of a display panel according to claim 6, characterized in that, Displacement of the display sub-pixels of the static image display area includes: The display sub-pixel is turned off, and the first sub-pixel that is at a first distance from the display sub-pixel is turned on. Wherein, the first sub-pixel emits the same color as the display sub-pixel, the brightness of the first sub-pixel is equal to the target display brightness of the display sub-pixel, and the first distance is less than the minimum perceptible distance for the user.
8. The method for improving the display lifespan of a display panel according to claim 6, characterized in that, When the refresh rate of the static image display area is reduced, the light emission time of the sub-pixels in the static image display area is reduced, and the peak brightness of the sub-pixels is increased.
9. A display panel, characterized in that, The display lifespan of the display panel can be improved by using the display lifespan improvement method according to any one of claims 1 to 8.
10. A display device, characterized in that, Includes the display panel as described in claim 9.