Driving circuit parameter optimization method and device, electronic device and storage medium

Abstract

The present application provides a method and device for optimizing driving circuit parameters, which relate to the field of display technology, and solve the problem that the current GOA device simulation and optimization require manual repeated iterations with high error rates. The method comprises obtaining current driving circuit parameter information of the current GOA device; performing an initial simulation on the current GOA device to obtain an initial simulation result; determining abnormal parameter information in the current driving circuit parameter information according to the initial simulation result; optimizing the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result. In the present application, the abnormal parameter information in the current driving circuit parameter information is determined according to the simulation result, and the abnormal parameter information is optimized, so as to realize intelligent simulation and optimization in the design process of the GOA device, avoid manual simulation and manual adjustment, reduce the workload in the simulation and tuning stage, and reduce the error rate.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to a method, device, electronic device and storage medium for optimizing drive circuit parameters. Background Art

[0002] Due to the demand for thinner display panels and narrower bezels, array substrate row driving technology (GOA, Gate Driver On Array) has also become popular. This technology integrates the gate array driver chip (Gate Driver IC) on the array (Array) glass substrate, removes the Gate Driver IC, and uses thin film transistor (Thin Film Transistor, TFT) wiring to form a gate circuit to form a GOA unit to replace the external driver chip to realize the driving function of the Gate Driver IC.

[0003] When developing new products, the length and width data of each TFT are preliminarily determined based on the resolution, size, etc., and then the layout is preliminarily designed based on the circuit diagram, and then RC is extracted. In order to verify the performance of GOA, the GOA device needs to be simulated and optimized several times until a qualified GOA layout is obtained. The GOA device simulation requires that all simulation conditions are met at the same time, and the GOA design is considered to be up to standard, resulting in a lot of repetitive work. The current existing technology usually obtains results through manual adjustment and manual simulation, which is cumbersome to operate, requires repeated iterations, and has a high error rate. Summary of the invention

[0004] The present application provides a method, device, electronic device and storage medium for optimizing driving circuit parameters, which can automatically simulate and adjust the GOA layout in the design process, realize intelligent simulation and optimization of the GOA layout, avoid manual simulation and manual adjustment, reduce the workload in the simulation and tuning stage, and reduce the error rate.

[0005] On the one hand, the present application provides a method for optimizing driving circuit parameters, comprising:

[0006] Get the current driving circuit parameter information of the current GOA device;

[0007] Performing an initial simulation on the current GOA device to obtain an initial simulation result;

[0008] Determining abnormal parameter information in the current drive circuit parameter information according to the initial simulation result;

[0009] The abnormal parameter information is optimized according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result.

[0010] In a possible implementation of the present application, optimizing the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result includes:

[0011] Acquire target parameter information matching the current drive circuit parameter information;

[0012] According to the current driving circuit parameter information, the initial simulation result and the target parameter information, the abnormal parameter information in the current driving circuit parameter information is optimized through a preset abnormal parameter prediction model to obtain an optimized target parameter optimization result.

[0013] In a possible implementation of the present application, performing an initial simulation on the current GOA device to obtain an initial simulation result includes:

[0014] Acquire a simulation condition information set and simulation configuration information related to the current GOA device;

[0015] According to the simulation condition information set and the simulation configuration information, an initial simulation is performed on the current GOA device to obtain an initial simulation result.

[0016] In a possible implementation of the present application, the simulation condition information set includes N first simulation condition information, where N is a natural number greater than or equal to 1;

[0017] Before performing an initial simulation on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result, the method includes:

[0018] According to a preset simulation condition sorting strategy, sorting the N first simulation condition information in the simulation condition information set to obtain sorted N first simulation condition information;

[0019] The sorted N pieces of the first simulation condition information are used as a sorted simulation condition set.

[0020] In a possible implementation of the present application, performing an initial simulation on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result includes:

[0021] According to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of the N first simulation condition information, N initial simulations are performed on the current GOA device in sequence to obtain initial simulation results.

[0022] In a possible implementation of the present application, each of the first simulation condition information includes a first default condition value and a first target condition value, and according to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of the N first simulation condition information, the current GOA device is initially simulated N times in sequence to obtain an initial simulation result, including:

[0023] In the Kth simulation process, K is a natural number less than or equal to N;

[0024] Determine the Kth first simulation condition information in the sorted simulation condition set as a first target condition value;

[0025] Determine that (N-1) pieces of the first simulation condition information in the sorted simulation condition set except the Kth piece of the first simulation condition information are all first default condition values;

[0026] Using the first target condition value and (N-1) first default condition values ​​as Kth target simulation condition information;

[0027] According to the Kth target simulation condition information and the simulation configuration information, the current driving circuit parameter information is simulated for the Kth time to obtain the Kth simulation result;

[0028] The Kth simulation result is used as the initial simulation result.

[0029] In a possible implementation of the present application, after taking the Kth simulation result as the initial simulation result, the method further includes:

[0030] Determine whether the initial simulation result meets the preset target simulation result to obtain a first determination result;

[0031] If the first judgment result is that the initial simulation result meets the preset target simulation result, it is judged whether K is less than N, if so, the current GOA device is subjected to the K+1th initial simulation, otherwise, the current GOA device is subjected to the final simulation, and the current final simulation result is obtained as the target parameter optimization result;

[0032] If the first judgment result is that the initial simulation result does not meet the preset target simulation result, the abnormal parameter information in the current driving circuit parameter information is optimized according to the current GOA device and the initial simulation result, and after the value of K is set to 1, the Kth initial simulation is continued for the optimized current GOA device.

[0033] In a possible implementation of the present application, the simulation condition information set includes M second simulation condition information, each of the second simulation condition information includes a second default condition value and a second target condition value, wherein M is a natural number greater than or equal to 1;

[0034] The final simulation of the current GOA device is performed, and the obtained final simulation result is used as the target parameter optimization result, including:

[0035] Determine that the M pieces of second simulation condition information are all second default condition values;

[0036] According to the M default condition values ​​and the simulation configuration information, a final simulation is performed on the current driving circuit parameter information to obtain a final simulation result;

[0037] The final simulation result is used as the target parameter optimization result.

[0038] In a possible implementation of the present application, before optimizing the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result, the method includes:

[0039] Obtain sample parameter information of multiple sample GOA devices;

[0040] Performing initial simulation using the plurality of sample parameter information as input to obtain a plurality of sample initial simulation results;

[0041] Model training is performed according to the plurality of sample parameter information and the plurality of sample initial simulation results to obtain a trained abnormal parameter prediction model.

[0042] On the other hand, the present application also provides a driving circuit parameter optimization device, the device comprising:

[0043] An acquisition module is used to obtain current driving circuit parameter information of the current GOA device;

[0044] A simulation module, used for performing an initial simulation on the current GOA device to obtain an initial simulation result;

[0045] A determination module, configured to determine abnormal parameter information in the current drive circuit parameter information according to the initial simulation result;

[0046] The optimization module is used to optimize the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result.

[0047] The optimization module is specifically:

[0048] Used to obtain target parameter information matching the current drive circuit parameter information;

[0049] It is used to optimize the abnormal parameter information in the current driving circuit parameter information through a preset abnormal parameter prediction model according to the current driving circuit parameter information, the initial simulation result and the target parameter information, so as to obtain an optimized target parameter optimization result.

[0050] The simulation module is specifically:

[0051] Used to obtain a set of simulation condition information and simulation configuration information related to the current GOA device;

[0052] Used to perform initial simulation on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result.

[0053] The simulation condition information set includes N first simulation condition information, wherein N is a natural number greater than or equal to 1, and the device further includes a sorting module, and the sorting module is specifically:

[0054] Used to sort the N first simulation condition information in the simulation condition information set according to a preset simulation condition sorting strategy to obtain sorted N first simulation condition information;

[0055] Used to use the sorted N pieces of the first simulation condition information as a sorted simulation condition set.

[0056] The simulation module is specifically:

[0057] Used to perform N initial simulations on the current GOA device in sequence according to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of N pieces of the first simulation condition information, to obtain initial simulation results.

[0058] Each of the first simulation condition information includes a first default condition value and a first target condition value, and the simulation module is specifically:

[0059] In the Kth simulation process, K is a natural number less than or equal to N;

[0060] Used to determine that the Kth first simulation condition information in the sorted simulation condition set is a first target condition value;

[0061] Used to determine that (N-1) pieces of the first simulation condition information except the Kth piece of the first simulation condition information in the sorted simulation condition set are all first default condition values;

[0062] for using the first target condition value and (N-1) first default condition values ​​as Kth target simulation condition information;

[0063] for performing a K-th simulation on the current driving circuit parameter information according to the K-th target simulation condition information and the simulation configuration information to obtain a K-th simulation result;

[0064] Used to use the Kth simulation result as the initial simulation result.

[0065] The simulation module is specifically:

[0066] Used to determine whether the initial simulation result meets the preset target simulation result, and obtain a first determination result;

[0067] If the first judgment result is that the initial simulation result meets the preset target simulation result, it is judged whether K is less than N, if so, the current GOA device is subjected to the K+1th initial simulation, otherwise, the current GOA device is subjected to the final simulation, and the current final simulation result is obtained as the target parameter optimization result;

[0068] If the first judgment result is that the initial simulation result does not meet the preset target simulation result, the abnormal parameter information in the current driving circuit parameter information is optimized according to the current GOA device and the initial simulation result, and after the value of K is set to 1, the Kth initial simulation is continued for the optimized current GOA device.

[0069] The simulation condition information set includes M pieces of second simulation condition information, each piece of the second simulation condition information includes a second default condition value and a second target condition value, wherein M is a natural number greater than or equal to 1;

[0070] The simulation module is specifically:

[0071] Used to determine that the M second simulation condition information are all second default condition values;

[0072] Used to perform a final simulation on the current driving circuit parameter information according to the M default condition values ​​and the simulation configuration information to obtain a final simulation result;

[0073] Used to use the final simulation result as the target parameter optimization result.

[0074] The device also includes a model training module, which is specifically:

[0075] Used to obtain sample parameter information of multiple sample GOA devices;

[0076] Used to perform initial simulation using the plurality of sample parameter information as input to obtain a plurality of sample initial simulation results;

[0077] It is used to perform model training according to the plurality of sample parameter information and the plurality of sample initial simulation results to obtain a trained abnormal parameter prediction model.

[0078] In the present application, after obtaining the current driving circuit parameter information of the current GOA device, the current GOA device is simulated, and the abnormal parameter information in the current driving circuit parameter information is determined according to the simulation results, and the abnormal parameter information is optimized to obtain the optimized target parameter optimization result, thereby realizing intelligent simulation and optimization in the GOA device design process, avoiding manual simulation and manual adjustment, reducing the workload in the simulation tuning stage, and reducing the error rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0080] Figure 1 This is a schematic flow chart of an embodiment of a method for optimizing drive circuit parameters in an embodiment of the present application;

[0081] Figure 2 This is a schematic flow chart of an embodiment of a method for optimizing drive circuit parameters in an embodiment of the present application;

[0082] Figure 3 This is a schematic flow chart of an embodiment of a method for optimizing drive circuit parameters in an embodiment of the present application;

[0083] Figure 4 This is a schematic flow chart of an embodiment of a method for optimizing drive circuit parameters in an embodiment of the present application;

[0084] Figure 5 This is a schematic diagram of the structure of an embodiment of a drive circuit parameter optimization device in an embodiment of the present application;

[0085] Figure 6 It is a schematic diagram of the structure of an embodiment of an electronic device provided in the embodiments of the present application. DETAILED DESCRIPTION

[0086] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0087] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first," "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0088] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that one of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0089] The embodiments of the present application provide a method, device, electronic device and storage medium for optimizing drive circuit parameters, which are described in detail below.

[0090] like Figure 1 FIG. 1 is a flow chart of an embodiment of a method for optimizing parameters of a driving circuit in an embodiment of the present application. The method for optimizing parameters of a driving circuit includes the following steps 101 to 104:

[0091] 101. Obtain current driving circuit parameter information of the current GOA device.

[0092] The current GOA device is the GOA device to be optimized at present. The current driving circuit parameter information of the current GOA device includes the Layout information of the current GOA device, the electrical parameters of the driving circuit simulation potential point, and the layout line width and line spacing. In the actual application process, the parameter file for generating the layout of the current GOA device is configured on the system, and the Layout information of the current GOA device, the electrical parameters of the driving circuit simulation potential point, and the layout line width and line spacing are obtained according to the parameter file of the layout of the current GOA device. Exemplarily, the current GOA device includes a plurality of thin film transistors (Thin Film Transistor, TFT), and the current driving circuit parameter information is the potential point parameter information of the TFT and the layout line width and line spacing of the TFT. The potential point parameter information of the TFT includes the voltage information, voltage rise time information, and voltage fall time information of each node of the TFT under set conditions.

[0093] 102. Perform an initial simulation on the current GOA device to obtain an initial simulation result.

[0094] After the Layout information of the current GOA device is obtained, the Layout information of the current GOA device is input into the system for automatic simulation, that is, the current GOA device is initially simulated to obtain an initial simulation result.

[0095] The initial simulation of the current GOA device specifically includes at least the following 6 types: high temperature simulation (High temperature), low temperature simulation (Low temperature), forward threshold voltage shift simulation (P Vth shift), forward threshold voltage shift simulation (N Vth shift), normal operation simulation of VGH at the lowest voltage (VGH Margin) and normal operation simulation of VSS at the highest voltage (VSS Margin). In this embodiment, after the system acquires the Layout information of the current GOA device, the simulation module automatically performs an initial simulation of the Layout information of the current GOA device, or the Layout information of the current GOA device can be manually imported into the simulation module for simulation.

[0096] 103. Determine abnormal parameter information in the current drive circuit parameter information according to the initial simulation result.

[0097] After completing the simulation of the current GOA device, the initial simulation results are analyzed, the range value information of each electrical parameter in the current GOA device is evaluated, and according to the preset target parameter information, it is determined whether the current driving circuit parameter information of the current GOA device meets the design standard. If it meets, it is determined that there is no abnormal parameter information in the current driving circuit parameter information of the current GOA device. If it does not meet, the abnormal parameter information that affects the key electrical parameter range value information of the current GOA device is determined accordingly. In this embodiment, the preset target parameter information can be manually pre-set in the system.

[0098] 104. According to the current driving circuit parameter information and the initial simulation result, the abnormal parameter information is optimized to obtain the target parameter optimization result.

[0099] When there is abnormal parameter information in the current driving circuit parameter information, the abnormal parameter information is optimized based on a preset optimization strategy and according to the current driving circuit parameter information and the initial simulation results to obtain a target parameter optimization result, which is a parameter result that can achieve successful simulation of the current GOA device.

[0100] According to the current drive circuit parameter information and the initial simulation results, the abnormal parameter information is optimized to obtain the target parameter optimization results, including:

[0101] Specifically, the preset optimization strategy includes: obtaining target parameter information that matches the current driving circuit parameter information, optimizing the abnormal parameter information in the current driving circuit parameter information through a preset abnormal parameter prediction model according to the current driving circuit parameter information, the initial simulation results and the target parameter information, and obtaining the optimized target parameter optimization result.

[0102] The target parameter information is the pre-set electrical parameter range value information. Before performing the initial simulation of the current GOA device, the electrical parameter range value information of the current GOA device is pre-set, that is, the electrical parameter range value information of each potential point of the TFT of the current GOA device is set. For example, as shown in Table 1, the G point voltage of the TFT is set to be greater than or equal to a target value, that is, under the set simulation conditions, in the simulation result obtained, if the G point voltage of the TFT is greater than or equal to a target value, it means that the G point voltage simulation meets the requirements. For another example, the rising time voltage of the G point of the TFT is set to be less than or equal to a target value, that is, under the set simulation conditions, in the simulation result obtained, if the rising time of the G point of the TFT is less than or equal to the target value, it means that the rising time simulation of the G point meets the requirements. The same is true for other potential points of the TFT of the current GOA device, and the target value can be set according to the specific situation.

[0103] When abnormal parameter information exists in the current driving circuit parameter information, target parameter information corresponding to the current driving circuit parameter information of the current GOA device is matched, and the abnormal parameter information in the current driving circuit parameter information is optimized through a pre-trained abnormal parameter prediction model, based on the current driving circuit parameter information, the initial simulation results and the matched target parameter information, to obtain an optimized target parameter optimization result, thereby realizing intelligent optimization of the current GOA device in the design process.

[0104] Table 1 Electrical parameter range information for each potential point of TFT

[0105] Electrical parameters Require Electrical parameters Require G point voltage ≥ Target value P point ripple ≤ Target value G-spot Rising time ≤ Target value STn point Rising time ≤ Target value G-spot falling time ≤ Target value STn point falling time ≤ Target value G-spot ripple up ≤ Target value STn point ripple ≤ Target value G spot ripple dowm ≥ Target value K point Rising time ≤ Target value VQ1 ≥ Target value K point falling time ≤ Target value VQ2 ≥ Target value K point ripple ≤ Target value Q point ripple up ≤ Target value S point Rising time ≤ Target value Q point ripple dowm ≥ Target value S point falling time ≤ Target value data rising time ≤ Target value S point ripple ≤ Target value data falling time ≤ Target value T point Rising time ≤ Target value P point Rising time ≤ Target value T point falling time ≤ Target value P point falling time ≤ Target value T point ripple ≤ Target value

[0106] In the present application, after obtaining the current driving circuit parameter information of the current GOA device, the current GOA device is simulated, and the abnormal parameter information in the current driving circuit parameter information is determined according to the simulation results, and the abnormal parameter information is optimized to obtain the optimized target parameter optimization result, thereby realizing intelligent simulation and optimization in the GOA device design process, avoiding manual simulation and manual adjustment, reducing the workload in the simulation tuning stage, and reducing the error rate.

[0107] In some embodiments of the present application, Figure 2 As shown, the current GOA device is initially simulated to obtain an initial simulation result, including steps 201 to 202:

[0108] 201. Obtain a simulation condition information set and simulation configuration information related to the current GOA device.

[0109] Since different GOA devices correspond to different simulation condition information, in order to realize intelligent simulation of GOA devices, before simulating the GOA devices, the corresponding different simulation condition information is collected, and the multiple different simulation condition information are grouped according to the corresponding GOA devices to obtain corresponding multiple simulation condition information sets.

[0110] When performing the initial simulation of the current GOA device, the corresponding simulation condition information set is matched according to the current driving circuit parameter information of the current GOA device, and the simulation configuration information is obtained at the same time. The simulation configuration information is a simulation file for the system to implement the simulation of the current GOA device. In this embodiment, the simulation configuration file includes an initial version ini file, a DRC file, an Itf file, a netlist file, a model file, a map file, a parameter file, an LVS rule file, and an LVS netlist file. Among them, the initial version ini file refers to a parameter file for generating a layout of the current GOA device; the DRC file is a rule file for checking the layout line width and line spacing of the current GOA device; the Itf file is a file for extracting the resistance and capacitance load (RC loading) of the current GOA device; the netlist file, the model file, the map file, and the parameter file are files required by the system for simulating the current GOA device, and the LVS rule file and the LVS netlist The file is a file used to compare and check the layout and circuit diagram of the current GOA device. In this embodiment, the simulation configuration information can be set in the system in the form of a file path, and the corresponding simulation configuration information is obtained by calling the corresponding file path through the system.

[0111] 202. Perform an initial simulation on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result.

[0112] After obtaining the corresponding simulation condition set and simulation configuration information, the current GOA device is simulated through the simulation module to obtain an initial simulation result.

[0113] In some embodiments of the present application, a simulation condition information set includes N first simulation condition information, where N is a natural number greater than or equal to 1. Exemplarily, the simulation condition information set may include 6 first simulation condition information, that is, the simulation condition information set may be 6 first simulation condition information consisting of the values ​​of High temperature, Low temperature, P Vth shift, N Vthshift, VGH Margin and VSS Margin, or it may be a set consisting of other simulation conditions, which is not specifically limited here.

[0114] During the simulation process, multiple driving circuit simulation potential points of the current GOA device are simulated based on one of the simulation condition information in the simulation condition information set, and multiple driving circuit simulation potential points of the current GOA device need to be simulated once based on each simulation condition information in the simulation condition information set. In order to improve the simulation efficiency of the current GOA device, therefore, Figure 3 As shown, before the initial simulation is performed on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain the initial simulation result, steps 301 to 302 are included:

[0115] 301. Sort N first simulation condition information in a simulation condition information set according to a preset simulation condition sorting strategy to obtain sorted N first simulation condition information.

[0116] Exemplarily, if the simulation condition information set is composed of the values ​​of High temperature, Low temperature, P Vthshift, N Vth shift, VGH Margin and VSS Margin, according to the preset simulation condition sorting strategy, High temperature can be used as the first first simulation condition information in the simulation condition information set, Lowtemperature can be used as the second first simulation condition information in the simulation condition information set, and so on, VGHMargin can be used as the sixth first simulation condition information in the simulation condition information set to obtain the six first simulation condition information after sorting. In this embodiment, the simulation condition sorting strategy is pre-set in the system. The simulation condition sorting strategy can be to sort multiple first simulation condition information based on the order of the names of the simulation conditions, or to sort multiple first simulation condition information according to the importance of the simulation conditions, or it can be a simulation condition sorting strategy defined by other means, which is not specifically limited here.

[0117] 302. Use the sorted N first simulation condition information as a sorted simulation condition set.

[0118] The sorted 6 first simulation condition information are used as a sorted simulation condition set for simulating the current GOA device.

[0119] In some embodiments of the present application, an initial simulation is performed on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result, including:

[0120] According to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of the N first simulation condition information, N initial simulations are performed on the current GOA device in sequence to obtain initial simulation results.

[0121] Each first simulation condition information includes a first default condition value and a first target condition value.

[0122] The first default condition value is the default simulation condition initial value pre-set in the system, and the first target condition value is the simulation condition target value set according to the current GOA device. For example, the first default condition value of High temperature is 25 degrees Celsius, and the first target condition value set according to the current GOA device is 30 degrees Celsius.

[0123] In this embodiment, as shown in Table 2, the values ​​of High temperature, Low temperature, P Vth shift, N Vth shift, VGH Margin and VSS Margin used in the simulation process are set by setting target values, and each first simulation condition information is called in a path manner.

[0124] Table 2 First simulation condition information

[0125] Serial number First simulation condition information First simulation condition information location Require 1 High temperature "Temper" in ini Target value 2 Low temperature "Temper" in ini Target value 3 P Vth shift "vths_all" in Parameter file Target value 4 N Vth shift "vths_all" in Parameter file Target value 5 VGH Margin "V_H" in Parameter file Target value 6 VSS Margin "V_L and VSSG" in the parameter file Target value 7 Adjustment multiple Section ini:[T21], value: "W" Target value 8 T21 Adjustment upper limit Section ini:[T21], value: "W" Target value 9 T21 adjusts the lower limit Section ini:[T21], value: "W" Target value

[0126] In the process of simulating the current GOA device, when the matched simulation condition information set includes N first simulation condition information, it is necessary to perform N+1 simulations on the current GOA device.

[0127] Specifically, Figure 4 As shown, according to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of the N first simulation condition information, the current GOA device is initially simulated N times in sequence to obtain an initial simulation result, including:

[0128] In the Kth simulation process, K is a natural number less than or equal to N;

[0129] Determine the Kth first simulation condition information in the sorted simulation condition set as the first target condition value;

[0130] Determine that (N-1) first simulation condition information except the Kth first simulation condition information in the sorted simulation condition set are all first default condition values;

[0131] The first target condition value and (N-1) first default condition values ​​are used as K-th target simulation condition information;

[0132] According to the Kth target simulation condition information and simulation configuration information, the current driving circuit parameter information is simulated for the Kth time to obtain the Kth simulation result;

[0133] The Kth simulation result is taken as the initial simulation result.

[0134] After taking the Kth simulation result as the initial simulation result, the method further includes:

[0135] Determine whether the initial simulation result meets the preset target simulation result to obtain a first determination result;

[0136] If the first judgment result is that the initial simulation result meets the preset target simulation result, it is judged whether K is less than N. If so, the current GOA device is subjected to the K+1th initial simulation. Otherwise, the current GOA device is subjected to the final simulation, and the current final simulation result is used as the target parameter optimization result.

[0137] If the first judgment result is that the initial simulation result does not meet the preset target simulation result, the abnormal parameter information in the current driving circuit parameter information is optimized according to the current GOA device and the initial simulation result, and after the value of K is set to 1, the optimized current GOA device continues to perform the Kth initial simulation.

[0138] The simulation condition information set includes M second simulation condition information, each second simulation condition information includes a second default condition value and a second target condition value, wherein M is a natural number greater than or equal to 1; wherein, when the first judgment result is that the initial simulation result meets the preset target simulation result, and it is judged that K is not less than N, the current GOA device is finally simulated.

[0139] In this embodiment, the current GOA device is finally simulated, and the current final simulation result obtained is used as the target parameter optimization result, which specifically includes:

[0140] Determine that the M second simulation condition information are all second default condition values;

[0141] According to the M default condition values ​​and simulation configuration information, a final simulation is performed on the current driving circuit parameter information to obtain a final simulation result;

[0142] The final simulation results are used as the target parameter optimization results.

[0143] In this embodiment, exemplarily, when the matched simulation condition information set includes 6 first simulation condition information, it is necessary to perform 7 simulations on the current GOA device. After obtaining the sorted simulation condition set according to the simulation condition information set, for the first 6 simulations of the current GOA device, according to the sorting order of the 6 first simulation condition information in the sorted simulation condition set, in the Nth simulation process, the value of the corresponding Nth first simulation condition information is modified to the first target condition value in turn, and the values ​​of the remaining 5 simulation condition information are all modified to the first default condition value, and then based on the Nth simulation condition information being the first target condition value and the values ​​of the remaining 5 simulation condition information being the first default condition value, the current GOA device is simulated.

[0144] For example, when the sorting simulation condition set is composed of High temperature, Low temperature, P Vthshift, N Vth shift, VGH Margin and VSS Margin in sequence, then in the third simulation process, the value of the third first simulation condition information is modified to the first target condition value, that is, the value of P Vth shift is set to the first target condition value, and the values ​​of the remaining five first simulation condition information in the sorting simulation condition set are modified to the first default condition value, and then based on the value of P Vth shift being the first target condition value and the remaining five first simulation condition information being the first default condition values, the current GOA device is simulated to obtain an initial simulation result, and so on, to complete the first six initial simulations of the current GOA device.

[0145] After completing the first 6 initial simulations, if the initial simulation results obtained from any of the initial simulations do not meet the preset target simulation results, the next simulation of the current GOA device will be stopped, and the optimization program of the current GOA device will be directly entered. If after completing the first 6 initial simulations, the initial simulation results obtained from each initial simulation meet the preset target simulation results, the current GOA device will continue to be simulated for the 7th time. For the 7th time, the 6 first simulation condition information in the sorted simulation condition set are all set to the first default condition values, and the current GOA device is simulated based on the 6 first default condition values. The final simulation result obtained can be used as the target parameter optimization result.

[0146] In some embodiments of the present application, before optimizing the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain the target parameter optimization result, the method includes:

[0147] Get sample parameter information for multiple sample GOA devices.

[0148] The sample parameter information is the sample Layout information of the sample GOA device, the electrical parameters of the simulated potential points of the sample driving circuit, and the line width and line spacing of the sample layout. Before training the abnormal parameter prediction model, multiple different sample parameter information corresponding to multiple different sample GOA devices are collected.

[0149] The multiple sample parameter information is used as input for initial simulation to obtain multiple sample initial simulation results.

[0150] Based on the initial simulation method of the current GOA device, multiple sample parameter information is used as input of the simulation module for simulation, and multiple sample initial simulation results corresponding to the multiple sample parameter information are obtained.

[0151] Model training is performed according to multiple sample parameter information and multiple sample initial simulation results to obtain a trained abnormal parameter prediction model.

[0152] After determining the model to be trained, multiple sample parameter information and multiple sample initial simulation results are used as input data of the model to be trained. During the training process, multiple sample parameter information is input into the model to be trained to obtain multiple trained initial simulation results to be verified. Multiple initial simulation results to be verified are verified based on multiple sample initial simulation results to obtain verification results. According to the verification results, the weights of the model to be trained are continuously adjusted to finally obtain a trained abnormal parameter prediction model. In this embodiment, a genetic algorithm can be used to build a model to be trained, and other algorithms can also be used to build a training model, which is not specifically limited here.

[0153] In this embodiment, in the actual application process, after obtaining the trained abnormal parameter prediction model, when the initial simulation result of the current GOA device does not meet the preset target simulation result, the abnormal parameter prediction model can be used to locate the abnormal parameter information in the current driving circuit parameter information that affects the current GOA device, and the abnormal parameter information of the current GOA device can be modified in real time to achieve a fast feedback effect. In addition, in this embodiment, when modifying the abnormal parameter information of the current GOA device, it can be that multiple TFTs in the current GOA device are batch modified according to certain rules at the same time to improve the optimization efficiency, or each TFT in the current GOA device can be adjusted separately, so as to achieve accurate optimization of the current GOA device.

[0154] Table 3 TFT channel length W

[0155] Serial number parameter Section Parameter name 1 T11 [T11] W 2 T21 [T21] W 3 T22 [T22] W 4 T31 [T31] W 5 T32 / T33 [T32T33] W 6 T41 [T41] W 7 T42 / T43 [T42T43] W 8 T44 [T44] W 9 T51 / T61 [T51T61] W 10 T52 / T62 [T52T62] W 11 T53 / T63 [T53T63] W 12 T54 / T64 [T54T64] W 13 T72 [T72] W 14 T73 [T73] W

[0156] Exemplarily, when the abnormal parameter prediction model identifies that the parameter affecting the electrical characteristics of the current GOA device is the channel length W of the TFT of the current GOA device, the abnormal parameter prediction model can batch adjust the channel lengths W of multiple TFTs in the current GOA device, that is, scale the channel lengths W of multiple TFTs by the same multiple. For example, the abnormal parameter prediction model is pre-set to have a scaling range of plus or minus 5000 for the TFT channel length W, and a multiple step of 1000, as shown in Table 3. Taking the TFT with the parameter "T21" in the current GOA device as the standard, when T21 is 10000, the maximum adjustment range of T21 is 15000 and the minimum adjustment range is 20000. is 5000, then the adjustment range of the channel length W of the other multiple TFTs of the current GOA device is a maximum of 15000 / 10000=1.5, and a minimum of 5000 / 10000=0.5, that is, the adjustment range is 0.5-1.5, and the multiple step of the channel length W of the other multiple TFTs of the current GOA device is 1000 / 10000=0.1. At this time, when the multiple step is 0.1, if T11 is 1000, T11 is adjusted to 100, and so on. The same adjustment is made to other TFTs of the current GOA device. If each TFT is adjusted individually, it will be more accurate.

[0157] In order to better implement the drive circuit parameter optimization method in the embodiment of the present application, based on the drive circuit parameter optimization method, the embodiment of the present application also provides a drive circuit parameter optimization device, such as Figure 5 As shown, the 400 includes:

[0158] An acquisition module 401 is used to acquire current driving circuit parameter information of a current GOA device;

[0159] A simulation module 402 is used to perform an initial simulation on the current GOA device to obtain an initial simulation result;

[0160] A determination module 403 is used to determine abnormal parameter information in the current driving circuit parameter information according to the initial simulation result;

[0161] The optimization module 404 is used to optimize the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain the target parameter optimization result.

[0162] The optimization module 404 is specifically:

[0163] Used to obtain target parameter information that matches the current drive circuit parameter information;

[0164] It is used to optimize the abnormal parameter information in the current driving circuit parameter information through a preset abnormal parameter prediction model according to the current driving circuit parameter information, the initial simulation results and the target parameter information, and obtain the optimized target parameter optimization result.

[0165] The simulation module 402 is specifically:

[0166] Used to obtain the simulation condition information set and simulation configuration information related to the current GOA device;

[0167] It is used to perform initial simulation on the current GOA device according to the simulation condition information set and simulation configuration information to obtain initial simulation results.

[0168] The simulation condition information set includes N first simulation condition information, where N is a natural number greater than or equal to 1. The device also includes a sorting module, which is specifically:

[0169] Used to sort the N first simulation condition information in the simulation condition information set according to a preset simulation condition sorting strategy to obtain sorted N first simulation condition information;

[0170] Used to use the sorted N first simulation condition information as a sorted simulation condition set.

[0171] The simulation module 402 is specifically:

[0172] It is used to perform N initial simulations on the current GOA device in sequence according to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of the N first simulation condition information, to obtain an initial simulation result.

[0173] Each first simulation condition information includes a first default condition value and a first target condition value. The simulation module 402 is specifically:

[0174] In the Kth simulation process, K is a natural number less than or equal to N;

[0175] Used to determine that the Kth first simulation condition information in the sorted simulation condition set is the first target condition value;

[0176] Used to determine that (N-1) first simulation condition information except the Kth first simulation condition information in the sorted simulation condition set are all first default condition values;

[0177] Used to use the first target condition value and (N-1) first default condition values ​​as K-th target simulation condition information;

[0178] Used to simulate the current driving circuit parameter information for the Kth time according to the Kth target simulation condition information and simulation configuration information to obtain the Kth simulation result;

[0179] The Kth simulation result is taken as the initial simulation result.

[0180] The simulation module 402 is specifically:

[0181] Used to determine whether the initial simulation result meets the preset target simulation result, and obtain a first determination result;

[0182] If the first judgment result is that the initial simulation result meets the preset target simulation result, it is judged whether K is less than N. If so, the current GOA device is subjected to the K+1th initial simulation. Otherwise, the current GOA device is subjected to the final simulation, and the current final simulation result is used as the target parameter optimization result.

[0183] If the first judgment result is that the initial simulation result does not meet the preset target simulation result, the abnormal parameter information in the current driving circuit parameter information is optimized according to the current GOA device and the initial simulation result, and after the value of K is set to 1, the optimized current GOA device continues to perform the Kth initial simulation.

[0184] The simulation condition information set includes M second simulation condition information, each second simulation condition information includes a second default condition value and a second target condition value, wherein M is a natural number greater than or equal to 1;

[0185] The simulation module 402 is specifically:

[0186] Used to determine that the M second simulation condition information are all second default condition values;

[0187] Used to perform final simulation on the current driving circuit parameter information according to M default condition values ​​and simulation configuration information to obtain a final simulation result;

[0188] Used to use the final simulation results as target parameter optimization results.

[0189] The device also includes a model training module, which is specifically:

[0190] Used to obtain sample parameter information of multiple sample GOA devices;

[0191] Used to take multiple sample parameter information as input for initial simulation, and obtain multiple sample initial simulation results;

[0192] It is used to perform model training based on multiple sample parameter information and multiple sample initial simulation results to obtain a trained abnormal parameter prediction model.

[0193] In another embodiment of the present application, Figure 6As shown, the present application further provides an electronic device 500, which shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically:

[0194] The electronic device may include components such as a processor 501 with one or more processing cores, a memory 502 with one or more computer-readable storage media, a power supply 503, and an input unit 504. Those skilled in the art will appreciate that Figure 6 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0195] The processor 501 is the control center of the electronic device, and uses various interfaces and lines to connect the various parts of the entire electronic device. By running or executing the software programs and / or modules stored in the memory 502, and calling the data stored in the memory 502, the processor 501 performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 501 may include one or more processing cores; the processor 501 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Preferably, the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 501.

[0196] The memory 502 can be used to store software programs and modules. The processor 501 executes various functional applications and data processing by running the software programs and modules stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 502 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 502 may also include a memory controller to provide the processor 501 with access to the memory 502.

[0197] The electronic device also includes a power supply 503 for supplying power to various components. Preferably, the power supply 503 can be logically connected to the processor 501 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 503 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0198] The electronic device may further include an input unit 504, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0199] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 501 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 502 according to the following instructions, and the processor 501 will run the application programs stored in the memory 502, thereby realizing various functions, as follows:

[0200] Get the current driving circuit parameter information of the current GOA device;

[0201] Perform an initial simulation on the current GOA device to obtain an initial simulation result;

[0202] Determine abnormal parameter information in the current drive circuit parameter information according to the initial simulation result;

[0203] According to the current driving circuit parameter information and the initial simulation results, the abnormal parameter information is optimized to obtain the target parameter optimization result.

[0204] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0205] In some embodiments of the present application, the present application further provides a computer-readable storage medium, which may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the drive circuit parameter optimization method provided in the embodiment of the present application. For example, the computer program is loaded by a processor to execute the following steps:

[0206] Get the current driving circuit parameter information of the current GOA device;

[0207] Perform an initial simulation on the current GOA device to obtain an initial simulation result;

[0208] Determine abnormal parameter information in the current drive circuit parameter information according to the initial simulation result;

[0209] According to the current driving circuit parameter information and the initial simulation results, the abnormal parameter information is optimized to obtain the target parameter optimization result.

[0210] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the detailed description of other embodiments above, and will not be repeated here.

[0211] The above is a detailed introduction to a driving circuit parameter optimization method and device provided in an embodiment of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for optimizing drive circuit parameters, characterized in that: include: Get the current driving circuit parameter information of the current GOA device; Performing an initial simulation on the current GOA device to obtain an initial simulation result; Determining abnormal parameter information in the current drive circuit parameter information according to the initial simulation result; Optimizing the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result; Wherein, the step of obtaining the initial simulation result includes: Acquire a simulation condition information set and simulation configuration information related to the current GOA device; Performing an initial simulation on the current GOA device according to the simulation condition information set and the simulation configuration information to obtain an initial simulation result; The simulation condition information set includes N first simulation condition information, where N is a natural number greater than 1, and the steps before obtaining the initial simulation result include: According to a preset simulation condition sorting strategy, sorting the N first simulation condition information to obtain a sorted simulation condition set; Wherein, the step of obtaining the initial simulation result includes: According to the sorted simulation condition set and the simulation configuration information, and based on the sorting order of N pieces of the first simulation condition information, perform N initial simulations on the current GOA device in sequence to obtain an initial simulation result; Wherein, each of the first simulation condition information includes a first default condition value and a first target condition value, and the step of obtaining the initial simulation result includes: In the Kth simulation process, K is a natural number less than or equal to N; Determine the Kth first simulation condition information in the sorted simulation condition set as a first target condition value; Determine that N-1 pieces of the first simulation condition information except the Kth piece of the first simulation condition information in the sorted simulation condition set are all first default condition values; Using the first target condition value and N-1 first default condition values ​​as Kth target simulation condition information; According to the Kth target simulation condition information and the simulation configuration information, the current driving circuit parameter information is simulated for the Kth time to obtain the Kth simulation result; The Kth simulation result is used as the initial simulation result.

2. The driving circuit parameter optimization method according to claim 1, characterized in that: The step of obtaining the target parameter optimization result includes: Acquire target parameter information matching the current drive circuit parameter information; According to the current driving circuit parameter information, the initial simulation result and the target parameter information, the abnormal parameter information in the current driving circuit parameter information is optimized through a preset abnormal parameter prediction model to obtain an optimized target parameter optimization result.

3. The driving circuit parameter optimization method according to claim 2, characterized in that: The steps before obtaining the target parameter optimization result include: Obtain sample parameter information of multiple sample GOA devices; Performing initial simulation using the plurality of sample parameter information as input to obtain a plurality of sample initial simulation results; Model training is performed according to the plurality of sample parameter information and the plurality of sample initial simulation results to obtain a trained abnormal parameter prediction model.

4. The driving circuit parameter optimization method according to claim 1, characterized in that: The step after taking the Kth simulation result as the initial simulation result further includes: Determine whether the initial simulation result meets the preset target simulation result to obtain a first determination result; If the first judgment result is that the initial simulation result meets the preset target simulation result, it is judged whether K is less than N, if so, the current GOA device is subjected to the K+1th initial simulation, otherwise, the current GOA device is subjected to the final simulation, and the current final simulation result is obtained as the target parameter optimization result; If the first judgment result is that the initial simulation result does not meet the preset target simulation result, the abnormal parameter information in the current driving circuit parameter information is optimized according to the current GOA device and the initial simulation result, and after the value of K is set to 1, the Kth initial simulation is continued for the optimized current GOA device.

5. The driving circuit parameter optimization method according to claim 4, characterized in that: The simulation condition information set includes M pieces of second simulation condition information, each piece of the second simulation condition information includes a second default condition value and a second target condition value, and M is a natural number greater than 1; The step of performing a final simulation on the current GOA device and using the obtained current final simulation result as the target parameter optimization result comprises: Determine that the M pieces of second simulation condition information are all second default condition values; According to the M default condition values ​​and the simulation configuration information, a final simulation is performed on the current driving circuit parameter information to obtain a final simulation result as the target parameter optimization result.

6. A drive circuit parameter optimization device, characterized in that: The method for optimizing driving circuit parameters as claimed in any one of claims 1 to 5 comprises: An acquisition module is used to obtain current driving circuit parameter information of the current GOA device; A simulation module, used for performing an initial simulation on the current GOA device to obtain an initial simulation result; A determination module, configured to determine abnormal parameter information in the current drive circuit parameter information according to the initial simulation result; The optimization module is used to optimize the abnormal parameter information according to the current driving circuit parameter information and the initial simulation result to obtain a target parameter optimization result.

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