Coolmos structure parameter optimization method and system for high voltage application

Abstract

The application discloses a CoolMOS structure parameter optimization method and system for high-voltage applications, and relates to the technical field of semiconductors.The method comprises the following steps: constructing a structure parameter database, performing matching analysis based on target function requirements, obtaining initial structure parameters, and determining electric field distribution deviation information;determining a structure parameter optimization threshold; performing multiple random adjustments on the initial structure parameters with the structure parameter optimization threshold as a constraint, obtaining multiple adjusted structure parameters, comparing and optimizing the adjusted structure parameters in combination with the electric field distribution deviation information, and determining target structure parameters; obtaining application working condition information, performing design optimization, obtaining simulated electric field distribution in combination with the application working condition information, and obtaining feedback optimization structure parameters based on the simulated electric field distribution.The technical problem of uneven electric field distribution and unstable performance caused by inaccurate selection of structure parameters in the prior art is solved, and the technical effect of improving the performance and stability of CoolMOS in high-voltage applications is achieved.

Description

Technical Field

[0001] This invention relates to the field of semiconductor technology, and more specifically to a method and system for optimizing CoolMOS structural parameters for high-voltage applications. Background Technology

[0002] CoolMOS (High-Performance Metal-Oxide-Semiconductor Field-Effect Transistor) is an important power semiconductor device widely used in power conversion, switching power supplies, and power electronics. CoolMOS features low on-resistance, high breakdown voltage, and good switching performance, giving it significant advantages in high-voltage, high-frequency, and high-current environments. However, with increasingly demanding performance requirements for power devices, traditional CoolMOS design methods have some shortcomings, particularly in the selection of structural parameters. These shortcomings lead to problems such as uneven electric field distribution, localized overheating, and performance instability, severely impacting the stability and efficiency of CoolMOS in high-voltage applications. Summary of the Invention

[0003] This application provides a method and system for optimizing CoolMOS structural parameters for high-voltage applications, which solves the technical problems of uneven electric field distribution and unstable performance caused by inaccurate selection of structural parameters in the prior art.

[0004] The first aspect of this application provides a method for optimizing the structural parameters of CoolMOS for high-voltage applications, the method comprising:

[0005] A CoolMOS structural parameter database is constructed. Matching analysis is performed between the target functional requirements and the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters. Electric field distribution deviation information is determined based on these parameters. A structural parameter optimization threshold is determined based on the CoolMOS structural parameter database. Using this optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times to obtain multiple adjusted CoolMOS structural parameters. These adjusted parameters are then compared and optimized using the electric field distribution deviation information to determine the target CoolMOS structural parameters. Application operating condition information is acquired, and the CoolMOS design is optimized using the target CoolMOS structural parameters. Furthermore, using electric field simulation software, an electric field distribution simulation is performed to obtain the simulated electric field distribution. Feedback optimization of the CoolMOS structural parameters is then obtained based on the simulated electric field distribution.

[0006] A second aspect of this application provides a CoolMOS structure parameter optimization system for high-voltage applications, the system comprising:

[0007] Initial Parameter Matching Module: Constructs a CoolMOS structural parameter database, performs matching analysis between the target functional requirements and the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters, and determines electric field distribution deviation information based on the CoolMOS structural parameters; Threshold Determination Module: Determines structural parameter optimization thresholds based on the CoolMOS structural parameter database; Parameter Optimization Module: Using the structural parameter optimization thresholds as constraints, performs multiple random adjustments to the initial CoolMOS structural parameters to obtain multiple adjusted CoolMOS structural parameters, compares and optimizes these multiple adjusted CoolMOS structural parameters using the electric field distribution deviation information, and determines the target CoolMOS structural parameters; Optimization Feedback Module: Acquires application operating condition information, optimizes the CoolMOS design using the target CoolMOS structural parameters, and simulates the electric field distribution using electric field simulation software based on the application operating condition information to obtain the simulated electric field distribution, and obtains feedback-optimized CoolMOS structural parameters based on the simulated electric field distribution.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] First, a CoolMOS structural parameter database is constructed. Matching analysis is performed between the target functional requirements and the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters, and electric field distribution deviation information is determined based on these parameters. Next, a structural parameter optimization threshold is determined based on the CoolMOS structural parameter database. Then, using the structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times to obtain multiple adjusted CoolMOS structural parameters. These adjusted parameters are compared and optimized using the electric field distribution deviation information to determine the target CoolMOS structural parameters. Finally, application operating condition information is obtained, and CoolMOS design is optimized using the target CoolMOS structural parameters. Furthermore, electric field simulation software is used to simulate the electric field distribution based on the application operating condition information, obtaining the simulated electric field distribution. Feedback is then used to optimize the CoolMOS structural parameters based on the simulated electric field distribution. This approach solves the technical problem of uneven electric field distribution and unstable performance caused by inaccurate structural parameter selection in existing technologies, achieving the technical effect of improving the performance and stability of CoolMOS in high-voltage applications. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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 effort.

[0011] Figure 1 A schematic flowchart of a CoolMOS structure parameter optimization method for high-voltage applications provided in an embodiment of this application;

[0012] Figure 2 This is a schematic diagram of a CoolMOS structural parameter optimization system for high-voltage applications provided in an embodiment of this application.

[0013] Figure labeling: Initial parameter matching module 11, threshold determination module 12, parameter optimization module 13, optimization feedback module 14. Detailed Implementation

[0014] This application provides a method and system for optimizing CoolMOS structural parameters for high-voltage applications, which solves the technical problems of uneven electric field distribution and unstable performance caused by inaccurate selection of structural parameters in the prior art.

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0016] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0017] Example 1, as Figure 1 As shown, this application provides a method for optimizing the structural parameters of CoolMOS for high-voltage applications, wherein the method includes:

[0018] A CoolMOS structural parameter database is constructed. Based on the target functional requirements, a matching analysis is performed with the CoolMOS structural parameter database to obtain the initial CoolMOS structural parameters. The electric field distribution deviation information is then determined based on the CoolMOS structural parameters.

[0019] By collecting performance data of multiple CoolMOS devices under different structural parameter configurations, including but not limited to channel length, drift region doping concentration, channel doping concentration, oxide layer thickness, gate width, gate length, and drift region thickness; and recording key performance indicators such as breakdown voltage, on-resistance, and switching speed that the devices can achieve under the above parameter conditions, a CoolMOS structural parameter database with a complete parameter-performance correspondence is formed.

[0020] Based on the target functional requirements, namely the target breakdown voltage, target on-resistance, and target switching speed, the CoolMOS structural parameter database is accessed. Through multi-dimensional matching analysis, initial CoolMOS structural parameters that meet the target performance indicators are selected. Furthermore, these initial CoolMOS structural parameters are imported as input parameters into electric field simulation software for electric field distribution simulation calculations. This simulates the internal electric field distribution of the CoolMOS device under high-voltage operating conditions. Based on the simulation results, regions of electric field gradient change are identified, and the electric field concentration and distribution non-uniformity are quantified, thereby extracting electric field distribution deviation information.

[0021] Furthermore, the target functional requirements include target breakdown voltage, target on-resistance, and target switching speed.

[0022] The target functional requirements refer to the key performance indicators that CoolMOS devices must achieve, including target breakdown voltage, target on-resistance, and target switching speed. Specifically, the target breakdown voltage ensures the device has sufficient withstand voltage in high-voltage environments to prevent electrical breakdown; the target on-resistance limits the device's resistance in the on-state, thereby controlling conduction losses and improving device efficiency; and the target switching speed characterizes the device's response time when switching between on and off states.

[0023] Furthermore, a CoolMOS structural parameter database is constructed. Based on the target functional requirements, a matching analysis is performed with the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters. Then, electric field distribution deviation information is determined based on these CoolMOS structural parameters, including:

[0024] The CoolMOS structural parameter database is multidimensionally screened based on the target breakdown voltage, target on-resistance, and target switching speed to construct a CoolMOS structural parameter screening set; typical parameter analysis is performed on the CoolMOS structural parameter screening set to determine the initial CoolMOS structural parameters; the initial CoolMOS structural parameters are input into electric field simulation software for simulation to determine the electric field distribution deviation information.

[0025] Specifically, the target breakdown voltage, target on-resistance, and target switching speed are used as constraints for database screening. Structural parameter subsets satisfying each performance requirement are sequentially extracted from the CoolMOS structural parameter database. These subsets are then intersected and summarized to construct a CoolMOS structural parameter screening set that satisfies all target performance requirements. Next, a parameter typicality analysis is performed on multiple candidate parameter combinations in the CoolMOS structural parameter screening set. This involves calculating the approximation of each parameter group with other parameter groups within the set to identify representative structural parameter combinations with strong distribution centrality, which are then used as initial CoolMOS structural parameters. Finally, the initial CoolMOS structural parameters are input into electric field simulation software to simulate the electric field distribution behavior of the CoolMOS device under high-voltage conditions. The simulation results are used to extract information such as the electric field distribution gradient along the vertical and lateral directions, the peak position and intensity of the electric field, etc., quantifying the problem characteristics reflecting the degree of electric field concentration and distribution non-uniformity, thus forming electric field distribution deviation information.

[0026] Furthermore, the CoolMOS structural parameter database is multidimensionally filtered based on the target breakdown voltage, target on-resistance, and target switching speed to construct a CoolMOS structural parameter filtering set, including:

[0027] Using the target breakdown voltage as an index, CoolMOS structure parameters that meet the target breakdown voltage in the CoolMOS structure parameter database are added to the first CoolMOS structure parameter filtering subset; using the target on-resistance as an index, CoolMOS structure parameters that meet the target on-resistance in the CoolMOS structure parameter database are added to the second CoolMOS structure parameter filtering subset; using the target switching speed as an index, CoolMOS structure parameters that meet the target switching speed in the CoolMOS structure parameter database are added to the third CoolMOS structure parameter filtering subset; the first CoolMOS structure parameter filtering subset, the second CoolMOS structure parameter filtering subset, and the third CoolMOS structure parameter filtering subset are summarized to obtain the CoolMOS structure parameter filtering set.

[0028] Preferably, using the target breakdown voltage as an index parameter, all structural parameter combinations are traversed in the CoolMOS structural parameter database to extract structural parameters whose breakdown voltage values ​​are within the allowable deviation range of the target breakdown voltage, and these are included in the first CoolMOS structural parameter screening subset. Using the target on-resistance as an index, structural parameters in the database whose on-resistance values ​​meet the preset range conditions of the target on-resistance are extracted to form the second CoolMOS structural parameter screening subset. Using the target switching speed as an index, structural parameter combinations that meet the requirements of the target switching speed range are extracted to form the third CoolMOS structural parameter screening subset. The first, second, and third CoolMOS structural parameter screening subsets are cross-summarized, and structural parameter combinations that simultaneously meet the performance requirements of all three objectives are preferentially retained, thereby constructing a complete CoolMOS structural parameter screening set.

[0029] Furthermore, a typical parameter analysis is performed on the CoolMOS structure parameter screening set to determine the initial CoolMOS structure parameters, including:

[0030] A first CoolMOS structure parameter is randomly extracted from the CoolMOS structure parameter screening set. CoolMOS structure parameters whose approximation to the first CoolMOS structure parameter is within a preset approximation threshold are added to the neighborhood of the first CoolMOS structure parameter. The CoolMOS structure parameter corresponding to the minimum approximation value in the neighborhood of the first CoolMOS structure parameter is used as the iterative CoolMOS structure parameter, and an iterative CoolMOS structure parameter neighborhood is constructed. A comparative analysis is performed based on the neighborhood of the first CoolMOS structure parameter and the iterative CoolMOS structure parameter neighborhood. Typical analyses are conducted on the first CoolMOS structure parameter and the iterative CoolMOS structure parameter to determine the stage CoolMOS structure parameter and the stage CoolMOS structure parameter neighborhood. This process is repeated, extracting the CoolMOS structure parameter corresponding to the minimum approximation value of the stage CoolMOS structure parameter from the stage CoolMOS structure parameter neighborhood, and performing typical analyses with the stage CoolMOS structure parameter until a preset number of analyses is met to obtain the initial CoolMOS structure parameter.

[0031] A set of structural parameters is randomly extracted from the CoolMOS structural parameter screening set as the first CoolMOS structural parameter. Then, using this first CoolMOS structural parameter as a benchmark, its approximation degree with other structural parameter groups in the screening set is calculated. The approximation degree can be measured based on Euclidean distance, cosine similarity, or weighted performance index differences. Parameter groups with approximation degrees within a preset approximation threshold are selected from all structural parameters to construct the neighborhood of the first CoolMOS structural parameter. Next, the structural parameter with the smallest approximation degree to the first CoolMOS structural parameter is further searched within the neighborhood of the first CoolMOS structural parameter and selected as the iterative CoolMOS structural parameter. A new iterative CoolMOS structural parameter neighborhood is then constructed centered on this parameter. A comparative analysis is performed on the neighborhood of the first CoolMOS structural parameter and the neighborhood of the iterative CoolMOS structural parameter. Combining the distribution characteristics and parameter aggregation degree of the structural parameters within the neighborhood, a neighborhood typicality index is calculated to comprehensively evaluate the representativeness of the first CoolMOS structural parameter and the iterative CoolMOS structural parameter. Based on the evaluation results, the parameter with higher typicality is selected as the stage CoolMOS structural parameter for the current stage, and the neighborhood of the new stage CoolMOS structural parameter is updated based on this stage parameter. The above iterative analysis steps are repeated, each time extracting the parameter with the smallest similarity to the stage CoolMOS structural parameter from the current stage neighborhood, and proceeding to the next round of typicality analysis iteration. By limiting the maximum number of analysis rounds or the neighborhood typicality convergence condition, the iteration terminates when the preset number of analysis rounds or the optimized convergence criterion is reached, and the current stage CoolMOS structural parameter is determined as the initial CoolMOS structural parameter.

[0032] Furthermore, based on a comparative analysis of the neighborhood of the first CoolMOS structure parameters and the neighborhood of the iterative CoolMOS structure parameters, a typical analysis of the first CoolMOS structure parameters and the iterative CoolMOS structure parameters is performed to determine the stage CoolMOS structure parameters and their neighborhoods, including:

[0033] The typicality of the neighborhood of the first CoolMOS structure parameter and the typicality of the iterative CoolMOS structure parameter are calculated separately. When the typicality of the neighborhood of the first CoolMOS structure parameter is less than or equal to the typicality of the neighborhood of the iterative CoolMOS structure parameter, the neighborhood of the iterative CoolMOS structure parameter is taken as the neighborhood of the stage CoolMOS structure parameter, and the neighborhood of the iterative CoolMOS structure parameter is taken as the neighborhood of the stage CoolMOS structure parameter.

[0034] By conducting typical analyses of the parameter neighborhoods of the first CoolMOS structure and the iterative CoolMOS structure, we can determine which structural parameters are representative of the adjustment process at different stages, thereby selecting the optimal combination of structural parameters.

[0035] Specifically, the number of structural parameters in the neighborhood of the first CoolMOS structural parameter and the neighborhood of the iterative CoolMOS structural parameter are counted separately, and this number is used as the typicality of their respective neighborhoods. The larger the typicality of the neighborhood, the more concentrated and representative the structural parameter is in the entire parameter space. The typicality of the first neighborhood is compared with that of the iterative neighborhood. When the typicality of the neighborhood of the first CoolMOS structural parameter is less than or equal to that of the neighborhood of the iterative CoolMOS structural parameter, it indicates that the iterative CoolMOS structural parameter has more aggregation characteristics and is more representative in the current parameter space. Therefore, the iterative CoolMOS structural parameter and its neighborhood are used as the starting basis for the next round of iterative analysis.

[0036] Furthermore, when the neighborhood typicality of the first CoolMOS structure parameter neighborhood is greater than the neighborhood typicality of the iterative CoolMOS structure parameter neighborhood, the CoolMOS structure parameter that is second in the neighborhood of the first CoolMOS structure parameter after arranging the approximations in ascending order is updated to the iterative CoolMOS structure parameter.

[0037] When the neighborhood typicality of the first CoolMOS structural parameter neighborhood is greater than that of the neighborhood typicality of the iterative CoolMOS structural parameter neighborhood, it indicates that the first CoolMOS structural parameter has stronger parameter aggregation and representativeness in the current screening set, while the currently selected iterative CoolMOS structural parameter has failed to significantly improve the typicality of the structural parameter neighborhood.

[0038] To avoid getting trapped in local optima and to expand the search scope, the system performs structural perturbation optimization on the neighborhood of the first CoolMOS structural parameter. Specifically, it first calculates the approximation between all structural parameters in the neighborhood of the first CoolMOS structural parameter and the current first CoolMOS structural parameter, and sorts them in ascending order. Then, it selects the second-ranked CoolMOS structural parameter (i.e., the suboptimal approximation structure) as the new iterative CoolMOS structural parameter to construct the next round of iterative neighborhood and continue typical analysis. If the number of structural parameters in the current neighborhood of the first CoolMOS structural parameter is insufficient to support the replacement (e.g., containing only two or fewer parameters), or if the typicality of the updated neighborhood is lower than that of the original neighborhood twice consecutively, it indicates that the current search has entered the representativeness decay range or is trapped in a local optimum. In this case, the subsequent iterations are terminated, and the current first CoolMOS structural parameter is used as the final initial CoolMOS structural parameter for the next stage of optimization analysis.

[0039] The structural parameter optimization threshold is determined based on the CoolMOS structural parameter database.

[0040] Statistical analysis is performed on the historical structural parameter samples calibrated in the CoolMOS structural parameter database to extract the distribution range of each parameter dimension (such as drift region doping concentration, channel length, oxide layer thickness, etc.) under the condition of meeting specific target functional requirements (such as breakdown voltage, on-resistance, switching speed). The statistical boundaries of each parameter dimension within the target functional range are calculated, including statistical indicators such as mean, standard deviation, maximum and minimum values. Based on the preset tolerance strategy and combined with the key sensitive parameters of the target functional requirements, the maximum acceptable fluctuation range of each structural parameter dimension is set to form the structural parameter optimization threshold range.

[0041] Using the structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times to obtain multiple adjusted CoolMOS structural parameters. The multiple adjusted CoolMOS structural parameters are compared and optimized in combination with the electric field distribution deviation information to determine the target CoolMOS structural parameters.

[0042] Under the constraint of the structural parameter optimization threshold, the initial CoolMOS structural parameters are randomly adjusted multiple times to generate several candidate adjusted CoolMOS structural parameters. These adjusted CoolMOS structural parameters are then input into electric field simulation software to simulate the electric field distribution of the device under high voltage conditions. By observing and comparing key electric field characteristics in each set of simulation results, such as the electric field peak position, maximum electric field strength, electric field gradient distribution, and changes in the electric field concentration region, it is determined which set of parameters corresponds to a more uniform electric field distribution without obvious electric field concentration regions, thereby reducing the risk of breakdown. Based on the above intuitive and quantifiable comparison of electric field characteristics, the parameter set with the optimal electric field distribution is selected as the target CoolMOS structural parameters.

[0043] Furthermore, using the aforementioned structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times to obtain multiple adjusted CoolMOS structural parameters. These multiple adjusted CoolMOS structural parameters are then compared and optimized using the electric field distribution deviation information to determine the target CoolMOS structural parameters, including:

[0044] Using the structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times according to a preset adjustment method to obtain multiple adjusted CoolMOS structural parameters; with the goal of minimizing the electric field distribution deviation information, the electric field distribution is simulated by traversing the multiple adjusted CoolMOS structural parameters to determine the target CoolMOS structural parameters.

[0045] Specifically, within the range of structural parameter optimization thresholds, the initial CoolMOS structural parameters are randomly perturbed multiple times according to a preset adjustment method to generate multiple different combinations of adjusted CoolMOS structural parameters. Then, each set of adjusted parameters is input into electric field simulation software to simulate the corresponding electric field distribution under high-voltage application conditions, and the electric field distribution deviation information corresponding to each set of parameters is calculated. This deviation information is used to reflect the uniformity of the electric field and local electric field strength anomalies. Subsequently, the simulation results of all adjusted parameters are iterated, sorted according to the magnitude of the electric field distribution deviation information, and the parameter set that minimizes the electric field distribution deviation is selected as the target CoolMOS structural parameters.

[0046] Furthermore, the preset adjustment method involves randomly increasing or decreasing any parameter in the initial CoolMOS structure parameters by a preset amount.

[0047] The preset adjustment method involves randomly increasing or decreasing any parameter in the initial CoolMOS structure parameters within a preset range. This means that, while ensuring the structural parameter optimization threshold constraint, each parameter is independently perturbed randomly in both positive and negative directions with a certain step size or percentage amplitude. By randomly fine-tuning within the parameter neighborhood, multiple differentiated combinations of adjustment parameters are generated, ensuring the diversity and coverage of the search space, while avoiding excessive parameter adjustments that could lead to performance deviations from target requirements or unacceptable electric field anomalies.

[0048] The application operating condition information is obtained, the target CoolMOS structure parameters are used to optimize the CoolMOS design, and the electric field distribution is simulated using electric field simulation software in conjunction with the application operating condition information to obtain the simulated electric field distribution. Based on the simulated electric field distribution, feedback optimization of the CoolMOS structure parameters is obtained.

[0049] Application operating condition information refers to the collection of key operating parameters of CoolMOS devices in actual working environments, including but not limited to operating voltage level, ambient temperature range, load current characteristics, switching frequency, and continuous operating time.

[0050] Based on the target CoolMOS structural parameters and specific application conditions, the design of CoolMOS devices is optimized. This mainly includes optimizing the device's geometric dimensions, doping concentration distribution, and process parameter configuration to meet the electrical performance and thermal stability requirements under actual operating conditions. The optimized structural parameters and corresponding application condition information are input into professional electric field simulation software to simulate the electric field distribution. The simulation focuses on the spatial distribution of the internal electric field of the device under actual operating conditions, paying particular attention to key indicators such as the electric field peak location, electric field gradient changes, and electric field concentration regions. Based on the simulation results, the uniformity of the electric field distribution and local electric field intensity are evaluated, and abnormal electric field regions that may lead to breakdown or performance degradation are identified. Electric field deviations or anomalies discovered in the simulation are fed back to the structural parameter optimization module for targeted adjustments and improvements to relevant structural parameters, such as adjusting the drift region thickness, doping concentration, or channel length, to obtain feedback optimization of CoolMOS structural parameters, thus forming a closed-loop optimization design process.

[0051] In summary, the embodiments of this application have at least the following technical effects:

[0052] First, a CoolMOS structural parameter database is constructed. Matching analysis is performed between the target functional requirements and the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters, and electric field distribution deviation information is determined based on these parameters. Next, a structural parameter optimization threshold is determined based on the CoolMOS structural parameter database. Then, using the structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times to obtain multiple adjusted CoolMOS structural parameters. These adjusted parameters are compared and optimized using the electric field distribution deviation information to determine the target CoolMOS structural parameters. Finally, application operating condition information is obtained, and CoolMOS design is optimized using the target CoolMOS structural parameters. Furthermore, electric field simulation software is used to simulate the electric field distribution based on the application operating condition information, obtaining the simulated electric field distribution. Feedback is then used to optimize the CoolMOS structural parameters based on the simulated electric field distribution. This approach solves the technical problem of uneven electric field distribution and unstable performance caused by inaccurate structural parameter selection in existing technologies, achieving the technical effect of improving the performance and stability of CoolMOS in high-voltage applications.

[0053] Example 2, based on the same inventive concept as the CoolMOS structure parameter optimization method for high-voltage applications in the previous examples, such as... Figure 2 As shown, this application provides a CoolMOS structure parameter optimization system for high-voltage applications, wherein the system includes:

[0054] Initial parameter matching module 11: Constructs a CoolMOS structural parameter database, performs matching analysis between the target functional requirements and the CoolMOS structural parameter database to obtain initial CoolMOS structural parameters, and determines electric field distribution deviation information based on the CoolMOS structural parameters; Threshold determination module 12: Determines structural parameter optimization thresholds based on the CoolMOS structural parameter database; Parameter optimization module 13: Using the structural parameter optimization thresholds as constraints, performs multiple random adjustments to the initial CoolMOS structural parameters to obtain multiple adjusted CoolMOS structural parameters, compares and optimizes the multiple adjusted CoolMOS structural parameters in conjunction with the electric field distribution deviation information, and determines the target CoolMOS structural parameters; Optimization feedback module 14: Obtains application operating condition information, optimizes CoolMOS design using the target CoolMOS structural parameters, and simulates electric field distribution using electric field simulation software in conjunction with the application operating condition information to obtain simulated electric field distribution, and obtains feedback optimized CoolMOS structural parameters based on the simulated electric field distribution.

[0055] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0056] The target functional requirements include target breakdown voltage, target on-resistance, and target switching speed.

[0057] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0058] The CoolMOS structural parameter database is multidimensionally screened based on the target breakdown voltage, target on-resistance, and target switching speed to construct a CoolMOS structural parameter screening set; typical parameter analysis is performed on the CoolMOS structural parameter screening set to determine the initial CoolMOS structural parameters; the initial CoolMOS structural parameters are input into electric field simulation software for simulation to determine the electric field distribution deviation information.

[0059] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0060] Using the target breakdown voltage as an index, CoolMOS structure parameters that meet the target breakdown voltage in the CoolMOS structure parameter database are added to the first CoolMOS structure parameter filtering subset; using the target on-resistance as an index, CoolMOS structure parameters that meet the target on-resistance in the CoolMOS structure parameter database are added to the second CoolMOS structure parameter filtering subset; using the target switching speed as an index, CoolMOS structure parameters that meet the target switching speed in the CoolMOS structure parameter database are added to the third CoolMOS structure parameter filtering subset; the first CoolMOS structure parameter filtering subset, the second CoolMOS structure parameter filtering subset, and the third CoolMOS structure parameter filtering subset are summarized to obtain the CoolMOS structure parameter filtering set.

[0061] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0062] A first CoolMOS structure parameter is randomly extracted from the CoolMOS structure parameter screening set. CoolMOS structure parameters whose approximation to the first CoolMOS structure parameter is within a preset approximation threshold are added to the neighborhood of the first CoolMOS structure parameter. The CoolMOS structure parameter corresponding to the minimum approximation value in the neighborhood of the first CoolMOS structure parameter is used as the iterative CoolMOS structure parameter, and an iterative CoolMOS structure parameter neighborhood is constructed. A comparative analysis is performed based on the neighborhood of the first CoolMOS structure parameter and the iterative CoolMOS structure parameter neighborhood. Typical analyses are conducted on the first CoolMOS structure parameter and the iterative CoolMOS structure parameter to determine the stage CoolMOS structure parameter and the stage CoolMOS structure parameter neighborhood. This process is repeated, extracting the CoolMOS structure parameter corresponding to the minimum approximation value of the stage CoolMOS structure parameter from the stage CoolMOS structure parameter neighborhood, and performing typical analyses with the stage CoolMOS structure parameter until a preset number of analyses is met to obtain the initial CoolMOS structure parameter.

[0063] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0064] The typicality of the neighborhood of the first CoolMOS structure parameter and the typicality of the iterative CoolMOS structure parameter are calculated separately. When the typicality of the neighborhood of the first CoolMOS structure parameter is less than or equal to the typicality of the neighborhood of the iterative CoolMOS structure parameter, the neighborhood of the iterative CoolMOS structure parameter is taken as the neighborhood of the stage CoolMOS structure parameter, and the neighborhood of the iterative CoolMOS structure parameter is taken as the neighborhood of the stage CoolMOS structure parameter.

[0065] Furthermore, the initial parameter matching module 11 is used to perform the following method:

[0066] When the neighborhood typicality of the first CoolMOS structure parameter neighborhood is greater than the neighborhood typicality of the iterative CoolMOS structure parameter neighborhood, the CoolMOS structure parameter that is second in the neighborhood of the first CoolMOS structure parameter after arranging the approximations in ascending order is updated to the iterative CoolMOS structure parameter.

[0067] Furthermore, the parameter optimization module 13 is used to perform the following method:

[0068] Using the structural parameter optimization threshold as a constraint, the initial CoolMOS structural parameters are randomly adjusted multiple times according to a preset adjustment method to obtain multiple adjusted CoolMOS structural parameters; with the goal of minimizing the electric field distribution deviation information, the electric field distribution is simulated by traversing the multiple adjusted CoolMOS structural parameters to determine the target CoolMOS structural parameters.

[0069] Furthermore, the parameter optimization module 13 is used to perform the following method:

[0070] The preset adjustment method involves randomly increasing or decreasing any parameter in the initial CoolMOS structure parameters by a preset amount.

[0071] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0072] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0073] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for optimizing the parameters of a CoolMOS structure for high voltage applications, characterized in that, The method comprises: constructing a CoolMOS structure parameter database, performing matching analysis on the target function requirement and the CoolMOS structure parameter database to obtain initial CoolMOS structure parameters, and determining electric field distribution deviation information according to the CoolMOS structure parameters; determining a structure parameter optimization threshold based on the CoolMOS structure parameter database; constraining the initial CoolMOS structure parameters with the structure parameter optimization threshold, performing multiple random adjustments on the initial CoolMOS structure parameters to obtain multiple adjusted CoolMOS structure parameters, comparing and optimizing the multiple adjusted CoolMOS structure parameters in combination with the electric field distribution deviation information to determine target CoolMOS structure parameters; obtaining application working condition information, performing CoolMOS design optimization using the target CoolMOS structure parameters, and combining the application working condition information to perform electric field distribution simulation using electric field simulation software to obtain simulated electric field distribution, and obtaining feedback optimized CoolMOS structure parameters based on the simulated electric field distribution.

2. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 1, wherein, The target function requirement comprises a target breakdown voltage, a target on-resistance, and a target switching speed.

3. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 2, wherein, The method comprises: performing multi-dimensional screening on the CoolMOS structure parameter database based on the target breakdown voltage, the target on-resistance, and the target switching speed to construct a CoolMOS structure parameter screening set; performing parameter typical analysis on the CoolMOS structure parameter screening set to determine initial CoolMOS structure parameters; inputting the initial CoolMOS structure parameters into electric field simulation software for simulation to determine electric field distribution deviation information.

4. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 3, wherein, The method comprises: indexing the target breakdown voltage, adding CoolMOS structure parameters in the CoolMOS structure parameter database that meet the target breakdown voltage into a first CoolMOS structure parameter screening sub-set; indexing the target on-resistance, adding CoolMOS structure parameters in the CoolMOS structure parameter database that meet the target on-resistance into a second CoolMOS structure parameter screening sub-set; indexing the target switching speed, adding CoolMOS structure parameters in the CoolMOS structure parameter database that meet the target switching speed into a third CoolMOS structure parameter screening sub-set; combining the first CoolMOS structure parameter screening sub-set, the second CoolMOS structure parameter screening sub-set, and the third CoolMOS structure parameter screening sub-set to obtain a CoolMOS structure parameter screening set.

5. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 3, wherein, Performing parameter typical analysis on the CoolMOS structure parameter screening set to determine initial CoolMOS structure parameters, including: Randomly extracting a first CoolMOS structure parameter from the CoolMOS structure parameter screening set, and adding CoolMOS structure parameters with an approximation degree within a preset approximation threshold to the first CoolMOS structure parameter neighborhood; Taking the CoolMOS structure parameter corresponding to the minimum approximation degree in the first CoolMOS structure parameter neighborhood as an iterative CoolMOS structure parameter, and constructing an iterative CoolMOS structure parameter neighborhood; Performing comparison analysis based on the first CoolMOS structure parameter neighborhood and the iterative CoolMOS structure parameter neighborhood, and performing typical analysis on the first CoolMOS structure parameter and the iterative CoolMOS structure parameter to determine a stage CoolMOS structure parameter and a stage CoolMOS structure parameter neighborhood; Similarly, extracting a CoolMOS structure parameter corresponding to a minimum approximation degree of a stage CoolMOS structure parameter from a stage CoolMOS structure parameter neighborhood, and performing typical analysis on the stage CoolMOS structure parameter until a preset analysis number is met to obtain an initial CoolMOS structure parameter.

6. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 5, wherein, Performing comparison analysis based on the first CoolMOS structure parameter neighborhood and the iterative CoolMOS structure parameter neighborhood, and performing typical analysis on the first CoolMOS structure parameter and the iterative CoolMOS structure parameter to determine a stage CoolMOS structure parameter and a stage CoolMOS structure parameter neighborhood, including: Respectively, statistically analyzing the neighborhood typical degrees of the first CoolMOS structure parameter neighborhood and the iterative CoolMOS structure parameter neighborhood; When the neighborhood typical degree of the first CoolMOS structure parameter neighborhood is less than or equal to that of the iterative CoolMOS structure parameter neighborhood, taking the iterative CoolMOS structure parameter neighborhood as the stage CoolMOS structure parameter neighborhood, and taking the iterative CoolMOS structure parameter neighborhood as the stage CoolMOS structure parameter neighborhood.

7. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 6, wherein, When the neighborhood typical degree of the first CoolMOS structure parameter neighborhood is greater than that of the iterative CoolMOS structure parameter neighborhood, updating the CoolMOS structure parameter in the second position in the first CoolMOS structure parameter neighborhood in ascending order of approximation degree to the iterative CoolMOS structure parameter.

8. The method of optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 1, wherein, Taking the structure parameter optimization threshold as a constraint, performing multiple random adjustments on the initial CoolMOS structure parameter to obtain multiple adjusted CoolMOS structure parameters, and performing comparison optimization on the multiple adjusted CoolMOS structure parameters in combination with the electric field distribution deviation information to determine a target CoolMOS structure parameter, including: With the structure parameter optimization threshold as a constraint, the initial CoolMOS structure parameter is adjusted multiple times in a preset adjustment mode to obtain multiple adjusted CoolMOS structure parameters; With the minimum electric field distribution deviation information as a target, the multiple adjusted CoolMOS structure parameters are simulated for electric field distribution to determine a target CoolMOS structure parameter.

9. The method for optimizing CoolMOS structure parameters for high voltage applications as claimed in claim 8, wherein, The preset adjustment mode is to randomly increase or decrease any parameter in the initial CoolMOS structure parameter by a preset amplitude.

10. A CoolMOS structure parameter optimization system for high voltage applications, characterized by, A system for implementing the CoolMOS structure parameter optimization method for high-voltage applications according to any one of claims 1-9, the system comprising: An initial parameter matching module: a CoolMOS structure parameter database is constructed, matching analysis is performed based on a target functional requirement and the CoolMOS structure parameter database, an initial CoolMOS structure parameter is obtained, and electric field distribution deviation information is determined based on the CoolMOS structure parameter; A threshold determination module: a structure parameter optimization threshold is determined based on the CoolMOS structure parameter database; A parameter optimization module: with the structure parameter optimization threshold as a constraint, the initial CoolMOS structure parameter is adjusted multiple times to obtain multiple adjusted CoolMOS structure parameters, the multiple adjusted CoolMOS structure parameters are compared and optimized in combination with the electric field distribution deviation information, and a target CoolMOS structure parameter is determined; An optimization feedback module: application working condition information is obtained, CoolMOS design optimization is performed using the target CoolMOS structure parameter, electric field distribution simulation is performed using electric field simulation software in combination with the application working condition information, simulated electric field distribution is obtained, and feedback optimized CoolMOS structure parameters are obtained based on the simulated electric field distribution.

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