A method for modeling the burn-in of a display device

Abstract

This invention relates to a method for aging and modeling image retention simulation in display devices, belonging to the field of display and reliability simulation technology. It solves the problem that existing static aging modeling separates the aging and recovery processes, only considering threshold voltage drift, and cannot accurately simulate short-term image retention technology in AMOLED displays. The method includes: obtaining the voltage bias state and simulation step size at the current simulation time step; calculating the aging stress component; determining the recovery component by combining the current aging state variables and stress state; simultaneously calculating the aging increment and recovery increment using the equivalent time point method and updating the aging state variables; correcting the TFT electrical parameters and calculating the pixel driving current based on the updated aging state variables; and iteratively completing the full-cycle image retention simulation step by step. This achieves realistic modeling of the synchronous and parallel evolution of pixel-driven TFT aging and recovery, significantly improving the accuracy, numerical stability, and versatility of image retention simulation for display devices, and can accurately reproduce the formation and evolution process of short-term image retention after grayscale switching.

Description

Technical Field

[0001] This invention relates to the field of display and reliability simulation technology, and in particular to a method for aging modeling of display device image retention simulation. Background Technology

[0002] In self-emissive display devices using TFT backplanes, pixel brightness is precisely controlled by the output current driving the TFT. In actual use, when the displayed content frequently switches grayscale levels, some pixels may briefly exhibit a short-term afterimage phenomenon where the brightness is lower or higher than the target grayscale after switching to the same target grayscale. This phenomenon usually lasts for hundreds of milliseconds to several seconds before gradually recovering, seriously affecting the visual experience of high-end display products. It is particularly noticeable when switching from a dark background to light content, such as when a mobile phone screen is turned on after being turned off.

[0003] These short-term image retentions exhibit several key characteristics: first, they are recoverable and gradually diminish over time; second, the magnitude of the retention is closely related to the historical grayscale levels and driving timing of the pixel; and third, the retention primarily occurs within a short timeframe after grayscale switching. Existing research confirms that the generation of short-term image retention is directly related to changes in the electrical parameters of the pixel-driving TFT, primarily threshold voltage drift and subthreshold slope changes. These parameter changes cause a short-term shift in the pixel driving current after grayscale switching, ultimately leading to inconsistent pixel brightness. Therefore, accurately describing the dynamic evolution of pixel-driving TFT parameters over display history during display simulation is crucial for improving the analysis and prediction capabilities of display image retention.

[0004] Currently, regarding the reliability issues of pixel-driven TFTs, existing research and industry-standard models are all based on long-term bias stress experiments, modeling only the static aging behavior of the TFT threshold voltage, and using the final aging amount or average aging amount as the evaluation index of device aging. These existing models contain three implicit assumptions that are divorced from real-world display scenarios: First, they treat the TFT aging process as a quasi-static process, ignoring the dynamic evolution of parameters over short timescales; second, they assume that the aging and recovery processes are completely separable in time and are independent processes occurring sequentially; third, they only consider threshold voltage changes as the core factor affecting pixel current, ignoring the effect of the subthreshold slope.

[0005] However, under actual display driving conditions, none of the above assumptions hold true. On the one hand, the pixel-driving TFT is always in a bias driving environment during grayscale switching, and its electrical parameters continuously and dynamically evolve over a short timescale. On the other hand, in pixel circuits employing threshold voltage compensation structures, considering only threshold voltage drift cannot truly reflect the dynamic changes in pixel current. Taking AMOLED display driving as an example, the gate voltage of the pixel-driving TFT changes dynamically with grayscale. When the gate bias state switches, the effective bias conditions within the TFT channel change synchronously. The variable charge state inside the TFT triggers the recovery characteristics of device parameters, and the aging stress effect and the recovery effect coexist and evolve in parallel over the same timescale, which is not the separate process assumed by existing models.

[0006] In summary, existing static aging modeling methods cannot accurately describe the short-term image retention behavior caused by the dynamic aging characteristics of TFTs at the display simulation level, and are difficult to meet the simulation requirements for image retention evaluation and driving scheme optimization of high-end self-emissive display products. There is an urgent need for a dynamic aging modeling method that can simultaneously describe the parallel evolution of aging stress and recovery effect. Summary of the Invention

[0007] Based on the above analysis, the present invention aims to provide a method for simulating and modeling the aging of display devices to solve the problems of existing technologies that cannot simulate dynamic short-term afterimages, that the aging and recovery modeling is not consistent with actual working conditions, and that single-parameter modeling cannot be adapted to threshold compensation circuits.

[0008] This invention provides a method for simulating and modeling the aging process of display devices to simulate image retention, comprising the following steps: Obtain the display driving conditions at the current simulation time step, including the voltage bias state of the pixel driving thin-film transistor and the simulation time step size; Calculate the aging stress components based on the current voltage bias state; The recovery component is determined based on aging state variables and stress state. The equivalent time point method is used to simultaneously calculate the increments of the aging stress component and the recovery component, and the aging state variables are updated based on the aging increment and the recovery increment. The electrical parameters of the pixel driving thin-film transistor are corrected based on the updated aging state variables, and the pixel driving current is calculated based on the corrected parameters. Proceed to the next simulation time step and repeat the above steps to obtain the pixel drive current for the complete simulation cycle in order to complete the display afterimage simulation.

[0009] Based on a further improvement of the above method, the stress state is characterized by an aging amplitude factor, which is positively correlated with the voltage bias state of the pixel-driving thin-film transistor.

[0010] Based on a further improvement of the above method, the formula for the aging stress components is as follows:

[0011] in, Let A be the aging stress component at time t. str For aging amplitude factor, The aging time constant is The aging elongation index.

[0012] Based on a further improvement of the above method, the formula for the recovery component is as follows:

[0013] in, Let A be the recovered component at time t. rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0014] Based on a further improvement of the above method, the equivalent time point method includes: inversely solving the aging equivalent time according to the current aging state variable and aging amplitude factor; inversely solving the recovery equivalent time according to the current recovery component and recovery amplitude factor; advancing the aging equivalent time and recovery equivalent time by one simulation time step to obtain the aging stress component and recovery component of the next simulation time step; and subtracting the aging stress component and recovery component of the next simulation time step from the aging stress component and recovery component of the current time step to obtain the aging increment and recovery increment.

[0015] Based on a further improvement of the above method, the formulas for the aging stress component and the recovery component in the next simulation time step are as follows:

[0016]

[0017] in, These represent the aging stress component and the recovery component for the next simulation time step, respectively. For the simulation time step, For the aging equivalent time, A str For aging amplitude factor, The aging time constant is The aging tensile index. To restore the equivalent time, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0018] Based on a further improvement of the above method, the aging equivalent time is calculated by the following formula.

[0019] in, P(t) is the aging equivalent time. i-1 A represents the aging state variable from the previous simulation time step. str For aging amplitude factor, The aging time constant is The aging elongation index; The recovery equivalent time is calculated by the following formula.

[0020] in, To restore the equivalent time, For the recovered component of the previous simulation time step, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0021] Based on a further improvement to the above method, the aging state variables are updated based on the aging increment and the recovery increment. The updated aging state variables are:

[0022] in, For the updated aging state variables, The aging state variables are from the previous simulation time step. This represents the net change due to aging.

[0023] in, For aging increments, To restore incremental growth.

[0024] Based on the further improvement of the above method, the calculation formula for the recovery amplitude factor of the current simulation time step is selected according to the net aging change of the previous simulation time step. Specifically: When the net aging change in the previous simulation time step is less than zero, the formula for calculating the recovery amplitude factor in the current simulation time step is as follows:

[0025] Among them, A rec (t) i ) represents the recovery amplitude factor at the current simulation time step, max(P) is the maximum value of the historical aging state variables, and max(A) is the maximum value of the historical aging state variables. str ) represents the maximum value of the historical aging amplitude factor, A str (t) i This represents the aging amplitude factor at the current simulation time step; When the net aging change in the previous simulation time step is greater than or equal to zero, the formula for calculating the recovery amplitude factor is as follows:

[0026] Among them, A rec (t) i ) represents the recovery amplitude factor at the current simulation time step, k rec To restore the proportionality coefficient, A str (t) i A represents the aging amplitude factor at the current simulation time step. str (t) i-1 P(t) represents the aging amplitude factor of the previous simulation time step. i-1 ) represents the aging state variable of the previous simulation time step, [·] + This indicates that the maximum value is taken compared to 0.

[0027] Based on further improvements to the above method, the aging state variables include the threshold voltage change and the subthreshold slope change.

[0028] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: 1. By adopting a dynamic aging modeling approach, the aging stress effect and the recovery effect are calculated synchronously and in parallel. This abandons the assumption that the aging and recovery processes are separated in traditional static modeling, and realizes the true reproduction of the physical process of parallel evolution of aging and recovery of pixel-driven TFTs. This solves the core problem that the traditional model does not match the actual display driving conditions. 2. By simultaneously incorporating the threshold voltage change and subthreshold slope change into the aging state variable system, the traditional modeling method, which only considers the threshold voltage, is broken through. This achieves a complete quantitative characterization of the TFT electrical parameter shift, significantly improving the simulation accuracy of pixel drive current and adapting to the image retention simulation requirements of threshold voltage compensated pixel circuits. 3. By adopting the equivalent time point method to complete the incremental synchronous update of aging and recovery components, continuous and smooth iteration of aging state under different simulation step sizes and display time sequences is realized, improving the numerical stability and versatility of modeling. It can accurately complete the full-time high-precision simulation of short-term afterimages of AMOLED display devices by relying on SPICE simulation. 4. By setting dual judgment logic for the start and stop of the recovery component, which conforms to the real physical mechanism of TFT carrier capture / decapture, reasonable quantitative calculation of the recovery process is realized, avoiding non-physical parameter abrupt changes, and further improving the reliability and physical consistency of display afterimage simulation.

[0029] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0030] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0031] Figure 1 This is a flowchart of a display device image retention simulation aging modeling method according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the dynamic aging and parallel update modeling of pixel-driven thin-film transistors in Embodiment 1 of the present invention. Detailed Implementation

[0032] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0033] Example 1, A specific embodiment of the present invention discloses a method for simulating aging and image retention in display devices, such as... Figure 1 As shown, it includes the following steps: S1: Obtain the display driving conditions of the current simulation time step, including the voltage bias state of the pixel driving thin-film transistor and the simulation time step.

[0034] It should be noted that the voltage bias state obtained in this step refers to the gate-source bias voltage and drain-source bias voltage of the pixel-driven thin-film transistor at the current display grayscale. This directly determines the electrical stress intensity experienced by the device and is a core input parameter for subsequent calculations of the stress amplitude factor, aging stress component, and recovery component. The simulation time step is the time evolution unit of the display simulation, used to match the actual display driving timing scale, ensuring that the aging state variables are continuously and smoothly updated according to the real time dimension. This display driving condition accurately reflects the real-time operating state of the pixel-driven thin-film transistor, providing an accurate external driving basis for the quantitative calculation of the parallel evolution of aging and recovery in dynamic aging modeling.

[0035] It should be noted that this invention abandons the traditional static aging modeling method and adopts a dynamic aging modeling approach. It argues that in the actual display driving process of TFTs, the aging effect and the recovery effect do not occur independently but simultaneously and evolve in parallel. A schematic diagram of parallel aging and recovery modeling is shown below. Figure 2The diagram illustrates the physical mechanism of TFT aging and recovery in parallel under actual driving conditions, using the TFT gate voltage switching condition as an example. The left side of the diagram shows the TFT in the first gate bias condition, with a first bias voltage applied to the gate. At this time, the interface between the TFT channel and the gate insulating layer is subjected to strong bias stress. A large number of carriers in the channel are trapped in the interface and the dielectric layer, exhibiting significant carrier trapping behavior, corresponding to the aging stress effect of the TFT. The aging state inside the device continues to accumulate with the stress.

[0036] The right side of the diagram shows the state after the gate bias voltage is switched from the first bias voltage to the second bias voltage. The amplitude of the second bias voltage is smaller than that of the first bias voltage, and the bias stress on the TFT is significantly reduced. At this time, in addition to retaining some incompletely released carrier trapping behavior at the interface between the TFT channel and the gate insulating layer, obvious carrier detrapping behavior also appears simultaneously. Corresponding to the TFT recovery effect, some trapped carriers are spontaneously released from the trapped state, and the aging state of the device is partially recovered.

[0037] The non-effective bias region marked in the figure indicates that the bias effect of different regions in the TFT channel is different. This region is not affected by the effective gate bias, the carrier state is relatively stable, and its aging evolution behavior is different from that of the region with effective bias.

[0038] In summary, the diagram clearly demonstrates that under the condition of TFT gate bias voltage switching, the aging stress effect and the recovery effect are not separate in time, but occur simultaneously and evolve in parallel. This physical characteristic directly supports the core technical solution of this invention to calculate the aging stress component and the recovery component in parallel, providing key physical mechanism support for achieving high-precision simulation of short-term image retention in display devices.

[0039] It should be noted that before starting the display device afterimage simulation, it is necessary to first establish the aging state variable of the pixel driving thin film transistor. This variable is used to characterize the cumulative aging degree of the electrical parameters of the pixel driving thin film transistor in real time during the actual display driving process. It is the core basic parameter of the dynamic aging modeling of this invention. The aging state variable is initialized based on the initial characteristics of the device to be simulated.

[0040] Specifically, the aging state variables include the threshold voltage change and the subthreshold slope change. These two variables, from the perspectives of device conduction threshold characteristics and channel carrier transport efficiency, respectively, comprehensively quantify the aging state of the TFT, providing necessary state input for the subsequent synchronous calculation of aging stress and recovery components. In the initial state, these aging state variables can be set to zero, corresponding to the pixel driving thin-film transistor being in its brand-new, unaged initial state; alternatively, they can be set to reference values ​​based on the actual factory parameters or measured characteristics of the device to be simulated, matching the actual initial state of the TFT in the simulation scenario and ensuring the accuracy of the initial conditions in the simulation process.

[0041] It should be noted that traditional display device aging modeling methods often only consider the impact of threshold voltage changes on TFT electrical characteristics, completely ignoring the role of subthreshold slope changes. This makes it difficult to accurately reflect the actual aging process of pixel-driving thin-film transistors and the dynamic changes in pixel current. The subthreshold slope, as a key parameter characterizing TFT conduction characteristics and channel carrier transport efficiency, directly relates to the linearity and dynamic response characteristics of the pixel driving current. The lack of characterization of this parameter leads to an incomplete description of electrical parameter shifts during TFT aging, resulting in significant deviations between pixel current simulation results and actual display conditions, and failing to accurately capture the formation mechanism and evolution process of short-term image retention. This invention overcomes the limitations of traditional modeling by simultaneously incorporating threshold voltage changes and subthreshold slope changes into the aging state variable system. Combined with the physical characteristics of the synchronous and parallel evolution of aging and recovery in actual TFT driving, it achieves a complete and realistic characterization of the pixel-driving thin-film transistor aging process, effectively improving the accuracy and reliability of display device image retention simulation and meeting the actual needs of high-precision simulation.

[0042] S2: Calculate the aging stress components based on the current voltage bias state.

[0043] It should be noted that the aging stress component is used to characterize the trend of further degradation of the electrical parameters of thin-film transistors under continuous display driving conditions. Its magnitude is determined by the current voltage bias state, directly reflecting the continuous excitation effect of the current driving bias on device aging. This invention uses a stretched exponential function to construct the aging stress component model. This model fits the physical mechanism of TFTs capturing carriers step by step in the trap state at the gate dielectric and channel interface, and can accurately characterize the evolution characteristics of the aging process gradually approaching saturation over time. An exponential function can also be used to describe the aging stress component.

[0044] Specifically, the formula for the aging stress components is as follows:

[0045] in, Let A be the aging stress component at time t. strFor aging amplitude factor, The aging time constant is The aging elongation index.

[0046] It should be noted that the aging amplitude factor is directly related to the carrier trapping effect of the gate-channel interface traps and gate-dielectric traps in pixel-driven thin-film transistors. The trapping strength of the trapped states determines the saturation amplitude of the aging parameter shift in the device's electrical parameters. In the aging stress component model, when the stress application time approaches infinity, the aging stress component approaches a saturated steady state. This saturated steady-state value is the aging amplitude factor, which is extracted by fitting device-level aging experimental data under different voltage bias conditions. The aging amplitude factor is positively correlated with the voltage bias state of the pixel-driven thin-film transistor. The higher the voltage bias amplitude, the greater the electric field strength at the device channel-gate interface, the more significant the trapped state carrier trapping effect, and the larger the corresponding aging amplitude factor value, used to quantify the aging driving intensity under the current bias conditions. The aging time constant and aging stretching index are inherent characteristic parameters of the device, extracted by fitting device-level aging experimental data under different bias conditions. This can be adapted to various display driving conditions, ensuring the physical rationality and numerical accuracy of the aging stress component calculation.

[0047] S3: Determine the recovery component based on aging state variables and stress state.

[0048] It should be noted that the recovery component characterizes the carrier release process of recoverable defect states at the interface between the channel and the gate insulating layer of a pixel-driven thin-film transistor after changes in display driving conditions. It corresponds to a partial correction and callback of the device's aging state and is a key component for achieving parallel evolution modeling of aging and recovery. The amplitude of the recovery component is determined by the constraints of the current aging state variable and the current stress state, not solely by a single driving condition. This allows it to accurately reflect the evolution of the recoverable aging portion of the device after grayscale switching. Furthermore, the calculation of the recovery component has trigger and stop conditions. Calculation is initiated only when the current stress state is weaker than the previous stress state, and updates stop when the aging increment in this step exceeds the recovery component increment. This ensures that the recovery process conforms to the actual physical characteristics of TFTs, avoids unreasonable parameter mutations, and improves the realism and stability of dynamic aging modeling.

[0049] Specifically, the stress state is characterized by an aging amplitude factor, which is positively correlated with the voltage bias state of the pixel-driving thin-film transistor.

[0050] It should be noted that the aging amplitude factor is a core quantitative parameter characterizing the current stress state, used to intuitively reflect the strength of the electrical stress experienced by the pixel-driving thin-film transistor under current operating conditions. The voltage bias state directly determines the electric field strength at the interface between the TFT channel and the gate insulating layer. The higher the bias amplitude, the stronger the interface electric field, the more significant the carrier trapping effect, and the greater the aging driving intensity of the device. Therefore, the aging amplitude factor is positively correlated with the voltage bias state. This parameter provides a key quantitative basis for the trigger determination and amplitude calculation of the recovery component, ensuring that the calculation of the recovery component conforms to the actual physical evolution law of the TFT.

[0051] Specifically, the formula for the recovery component is as follows:

[0052] in, Let A be the recovered component at time t. rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0053] It should be noted that the recovery component is constructed using a stretching exponential function model. This model is highly consistent with the physical mechanism of the recoverable defect state releasing carriers in pixel-driven thin-film transistors, and can accurately characterize the evolution characteristics of the recovery effect gradually approaching saturation over time. The recovery amplitude factor is the upper limit of the recovery process amplitude, determined by the difference in aging amplitude factors between adjacent simulation steps and the aging state variable of the previous moment, used to constrain the maximum recoverable amplitude in this step. The recovery time constant and recovery stretching exponent are inherent characteristic parameters of the device, extracted through fitting device-level recovery experimental data, and can realistically reflect the recovery rate and evolution characteristics of TFTs under different driving conditions. This model maintains consistency with the aging stress component model, can adapt to the parallel computation logic of the equivalent time point method, and ensures numerical stability and physical consistency when the aging and recovery components are updated synchronously.

[0054] S4: The equivalent time point method is used to simultaneously calculate the increments of the aging stress component and the recovery component, and the aging state variables are updated based on the aging increment and the recovery increment.

[0055] It should be noted that the equivalent time point method maps the currently accumulated aging state to the equivalent evolution time of the corresponding aging / recovery model. By advancing the current simulation time step based on this equivalent time, the aging stress component and recovery component after the current step can be accurately calculated. The aging increment and recovery increment for the current step are obtained by subtracting the aging stress component / recovery component at adjacent time points, enabling parallel solving of the two components within the same simulation step and strictly matching the physical mechanism of synchronous TFT aging and recovery. Updating the aging state variables incrementally avoids numerical oscillations caused by abrupt changes in driving conditions or step size variations, ensuring a continuous and smooth evolution of the aging state and significantly improving the numerical stability and computational versatility of dynamic aging modeling under different display timings and simulation step sizes.

[0056] Specifically, the equivalent time point method includes: inversely solving the aging equivalent time based on the current aging state variables and aging amplitude factor; inversely solving the recovery equivalent time based on the current recovery component and recovery amplitude factor; advancing the aging equivalent time and recovery equivalent time by one simulation time step to obtain the aging stress component and recovery component of the next simulation time step; and subtracting the aging stress component and recovery component of the next simulation time step from the aging stress component and recovery component of the current time step to obtain the aging increment and recovery increment.

[0057] Specifically, the formulas for the aging stress component and the recovery component in the next simulation time step are as follows:

[0058]

[0059] in, These represent the aging stress component and the recovery component for the next simulation time step, respectively. For the simulation time step, For the aging equivalent time, A str For aging amplitude factor, The aging time constant is The aging tensile index. To restore the equivalent time, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0060] If the aging state variable after the previous simulation time step is Then define the aging equivalent time for this step. satisfy

[0061] The aging equivalent time is obtained by inverse solution.

[0062] in, P(t) is the aging equivalent time. i-1 A represents the aging state variable from the previous simulation time step. str For aging amplitude factor, The aging time constant is The aging elongation index; Similarly, if the recovery component of a simulation time step is Then define the recovery equivalent time point for this step. satisfy:

[0063] The inverse solution yields the recovery equivalent time.

[0064] in, To restore the equivalent time, For the recovered component of the previous simulation time step, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

[0065] The aging increment and the recovery increment are respectively

[0066] in, For aging increments, To restore incremental growth, The aging stress components are at the current simulation time step. The recovery component for the current simulation time step. These represent the aging stress component and the recovery component for the next simulation time step, respectively. This is the simulation time step.

[0067] Net aging change is

[0068] The updated aging state variables are

[0069] in, For the updated aging state variables, The aging state variables are from the previous simulation time step. This represents the net change due to aging.

[0070] It should be noted that the aging state variable updated by incremental superposition is the state quantity at the end of the current simulation time step. It is used for the correction of electrical parameters in this step and also serves as the initial state for the next simulation time step in the iterative calculation.

[0071] It should be noted that when 0 When the aging increment is less than the recovery increment, it indicates that the recovery component still dominates in the current simulation time step, and the recovery component continues to participate in updating the aging state variables; in the next simulation time step, the recovery amplitude factor is calculated using the update formula.

[0072] Among them, A rec (t) i+1 ) represents t i+1 The recovery amplitude factor at time t, max(P) is t i+1 The previous maximum value of the aging state variable, max(A) str ) for t i+1 The previous maximum value of the aging amplitude factor, A str (t) i+1 ) represents t i+1 Aging amplitude factor at any given time.

[0073] It should be noted that max(P) records the maximum cumulative aging level in the device's history, directly determining the upper limit of the recovery amplitude. This ensures that the recovery amplitude matches the total number of defect states already formed in the device, avoiding an underestimation of the recovery amplitude due to a decrease in the current aging state; max(A str The system records the strongest stress state experienced by the device, which serves as a normalization benchmark. This allows for a comparison between the current stress state and the historical strongest stress, quantifying the relative degree of stress reduction. Under the combined constraint of these two factors, the recovery amplitude factor accurately reflects the process by which the device gradually releases its defect state as the current stress decreases after experiencing maximum stress. This effectively avoids the problem of the recovery process being suppressed due to excessively low current stress in traditional methods, significantly improving the physical consistency of the recovery component calculation. This enables the simulation results to accurately match the long-term recovery characteristics of AMOLED pixel-driven TFTs under actual display driving conditions, enhancing the model's adaptability and numerical stability to complex dynamic driving conditions.

[0074] when ≥0 When the aging increment is greater than or equal to the recovery increment, it indicates that the net aging of the device in the current simulation time step has re-entered the growth process, and the recovery component is canceled out. At this point, the recovery component stops updating, and the model re-enters the pure stress accumulation stage. In the next simulation time step, the recovery amplitude factor is calculated using the initialization formula.

[0075] Among them, A rec (t) i+1 ) represents t i+1 Recovery amplitude factor at time k rec To restore the proportionality coefficient, A str (t) i ) represents t i Aging amplitude factor at time, A str (t) i+1 ) represents t i+1 Aging amplitude factor at time, P(t) i ) represents t i The aging state variable at time step [·] + This indicates that the maximum value compared to 0 is taken to ensure that the recovery amplitude factor is non-negative and to avoid non-physical negative recovery. When - At 0 o'clock, t i+1 The recovery amplitude factor at time step is not zero, and consequently the recovery increment is not zero. The recovery component affects the update of the aging state variables. - When ≤0, t i+1 The recovery amplitude factor at time step S5 is zero, and consequently the recovery increment is zero. The recovery component does not affect the aging state variable update; only the aging state variable is updated using the aging increment. S5: Based on the updated aging state variable, the electrical parameters of the pixel driving thin-film transistor are corrected, and the pixel driving current is calculated based on the corrected parameters.

[0076] It should be noted that the updated aging state variables include the threshold voltage change and the subthreshold slope change, which can comprehensively characterize the electrical characteristic shift of the pixel-driven thin-film transistor after parallel evolution of aging and recovery. Correcting the two core electrical parameters of the device—threshold voltage and subthreshold slope—based on these variables can simultaneously reflect the combined impact of aging stress and recovery effects on the device's electrical characteristics, overcoming the shortcomings of traditional modeling that only corrects the threshold voltage. Preferably, this step can be executed in the SPICE simulation environment. Calculating the pixel driving current based on the corrected electrical parameters can realistically reproduce the dynamic shift law of AMOLED pixel current during grayscale switching, providing core data support for the quantitative simulation and accurate analysis of display afterimages.

[0077] S6: Proceed to the next simulation time step and repeat the above steps to obtain the pixel drive current for the complete simulation cycle in order to complete the display afterimage simulation.

[0078] It should be noted that by iteratively executing the aforementioned steps step by step in the simulation, the aging state variables can be made to evolve smoothly and continuously with the actual display driving timing, fully reproducing the dynamic aging and recovery process of the pixel-driven thin-film transistor throughout the entire simulation cycle. This method can complete the full-process iterative calculation based on the SPICE simulation platform. Based on the pixel driving current continuously output within the complete simulation cycle, it can accurately capture the formation, evolution, and fading patterns of short-term afterimages after grayscale switching, achieving full-time, high-precision dynamic simulation of the afterimage behavior of display devices, and providing a reliable simulation basis for afterimage evaluation of display panels and optimization of driving schemes.

[0079] Those skilled in the art will understand that all or part of the processes implementing the methods of the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0080] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for simulating aging and modeling image retention in a display device, characterized in that, Includes the following steps: Obtain the display driving conditions at the current simulation time step, including the voltage bias state of the pixel driving thin-film transistor and the simulation time step size; Calculate the aging stress components based on the current voltage bias state; The recovery component is determined based on aging state variables and stress state. The equivalent time point method is used to simultaneously calculate the increments of the aging stress component and the recovery component, and the aging state variables are updated based on the aging increment and the recovery increment. The electrical parameters of the pixel driving thin-film transistor are corrected based on the updated aging state variables, and the pixel driving current is calculated based on the corrected parameters. Proceed to the next simulation time step and repeat the above steps to obtain the pixel drive current for the complete simulation cycle in order to complete the display afterimage simulation.

2. The method according to claim 1, characterized in that, The stress state is characterized by an aging amplitude factor, which is positively correlated with the voltage bias state of the pixel-driven thin-film transistor.

3. The method according to claim 1, characterized in that, The formula for the aging stress component is as follows: in, Let A be the aging stress component at time t. str For aging amplitude factor, The aging time constant is The aging elongation index.

4. The method according to claim 1, characterized in that, The formula for the recovery component is as follows: in, Let A be the recovered component at time t. rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

5. The method according to claim 1, characterized in that, The equivalent time point method includes: inversely solving the aging equivalent time based on the current aging state variables and aging amplitude factor; inversely solving the recovery equivalent time based on the current recovery component and recovery amplitude factor; advancing the aging equivalent time and recovery equivalent time by one simulation time step to obtain the aging stress component and recovery component of the next simulation time step; and subtracting the aging stress component and recovery component of the next simulation time step from the aging stress component and recovery component of the current time step to obtain the aging increment and recovery increment.

6. The method according to claim 5, characterized in that, The formulas for the aging stress component and the recovery component in the next simulation time step are as follows: in, These represent the aging stress component and the recovery component for the next simulation time step, respectively. For the simulation time step, For the aging equivalent time, A str For aging amplitude factor, The aging time constant is The aging tensile index. To restore the equivalent time, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

7. The method according to claim 1, characterized in that, The aging equivalent time is calculated by the following formula. in, P(t) is the aging equivalent time. i-1 A represents the aging state variable from the previous simulation time step. str For aging amplitude factor, The aging time constant is The aging elongation index; The recovery equivalent time is calculated by the following formula. in, To restore the equivalent time, For the recovered component of the previous simulation time step, A rec To recover the amplitude factor, To restore the time constant, To restore the stretch index.

8. The method according to claim 1, characterized in that, The aging state variables are updated based on the aging increment and recovery increment. The updated aging state variables are: in, For the updated aging state variables, The aging state variables are from the previous simulation time step. This represents the net change due to aging. in, For aging increments, To restore incremental growth.

9. The method according to claim 8, characterized in that, The formula for calculating the recovery amplitude factor in the current simulation time step is selected based on the net aging change in the previous simulation time step. Specifically: When the net aging change in the previous simulation time step is less than zero, the formula for calculating the recovery amplitude factor in the current simulation time step is as follows: Among them, A rec (t) i ) represents the recovery amplitude factor at the current simulation time step, max(P) is the maximum value of the historical aging state variables, and max(A) is the maximum value of the historical aging state variables. str ) represents the maximum value of the historical aging amplitude factor, A str (t) i This represents the aging amplitude factor at the current simulation time step; When the net aging change in the previous simulation time step is greater than or equal to zero, the formula for calculating the recovery amplitude factor is as follows: Among them, A rec (t) i ) represents the recovery amplitude factor at the current simulation time step, k rec To restore the proportionality coefficient, A str (t) i A represents the aging amplitude factor at the current simulation time step. str (t) i-1 P(t) represents the aging amplitude factor of the previous simulation time step. i-1 ) represents the aging state variable of the previous simulation time step, [·] + This indicates that the maximum value is taken compared to 0.

10. The method according to claim 1, characterized in that, The aging state variables include the threshold voltage change and the subthreshold slope change.

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