Method and device for improving performance of electronic devices with trench Schottky structure

Abstract

The present invention discloses a method and device for improving the performance of electronic devices for a trench Schottky structure, and relates to the field of electronic device optimization. The method comprises: constructing a performance optimization objective function according to the performance status information of the electronic device to be optimized; collecting optimizable variables for N trench Schottky structural components; randomly generating candidate solutions with N initial trench parameter combinations as the starting point to obtain M initial candidate solutions; performing performance simulation, and using the objective function to evaluate the performance simulation results; iteratively executing the update process of the candidate solutions according to the search update rules and the M initial performance deviations until the electronic device structural parameters that meet the expected performance of the device are obtained. The method solves the technical problems that the existing electronic devices for trench Schottky structures have a single optimization direction, limited optimization effect, and it is difficult to achieve the optimal overall performance, and achieves the technical effect of improving the optimization effect and the overall performance state of the device through collaborative optimization.

Description

Technical Field

[0001] The present application relates to the field related to electronic device optimization, and in particular to a method and device for improving the performance of electronic devices with a trench Schottky structure. Background Art

[0002] Trench Schottky structure electronic devices have been widely used in the semiconductor field due to their unique structure and superior performance, especially in high frequency, high voltage and other application scenarios, where such devices have shown excellent performance. However, with the continuous advancement of technology and the increase in application needs, the performance requirements for trench Schottky structure electronic devices are also getting higher and higher. In the prior art, the main method used to improve the performance of trench Schottky structure electronic devices is to optimize a single component. However, since the performance of the device is determined by multiple components, only optimizing a single component often leads to an imbalance in the overall performance. For example, if a low forward voltage drop is excessively pursued, the reverse breakdown voltage of the device may be sacrificed. Due to the complexity and interdependence within the device, the optimization of a single component can often only bring limited performance improvements. In addition, over-optimization of a component may also lead to a decline in the performance of other components, and even cause new problems.

[0003] In the current related technologies, the performance improvement method for electronic devices with trench Schottky structures has a single optimization direction, resulting in limited optimization effect and difficulty in achieving the optimal overall performance. Summary of the invention

[0004] The present application provides a method and apparatus for improving the performance of electronic devices with a trench Schottky structure, constructs an optimization objective function that can reflect the overall performance based on the performance status information of the electronic device to be optimized, collects optimizable variables for N trench Schottky structure components, randomly generates multiple candidate solutions with an initial trench parameter combination as the starting point, and performs performance simulation on these candidate solutions. According to predefined search update rules and performance simulation results, the candidate solution update process is iteratively executed, the optimizable variables of the N trench Schottky structure components are continuously adjusted and optimized, and the overall optimal performance solution is obtained. The technical effect of improving the optimization effect and the overall performance status of the device through collaborative optimization is achieved.

[0005] The present application provides a method for improving the performance of an electronic device with a trench Schottky structure, comprising: constructing a performance optimization objective function according to performance status information of an electronic device to be optimized, wherein the electronic device to be optimized includes N trench Schottky structure components; collecting optimizable variables for the N trench Schottky structure components to obtain N initial trench parameter combinations; randomly generating candidate solutions with the N initial trench parameter combinations as starting points to obtain M initial candidate solutions, wherein each candidate solution includes N updated trench parameter combinations; performing performance simulation on the M initial candidate solutions, and evaluating the performance simulation results using the performance optimization objective function to obtain M initial performance deviations; predefining search update rules, and iteratively executing the update process of the candidate solutions according to the search update rules and the M initial performance deviations, and continuously optimizing the optimizable variables of the N trench Schottky structure components until the electronic device structural parameters that meet the expected performance of the device are obtained.

[0006] In a possible implementation, a performance optimization objective function is constructed based on the performance status information of the electronic device to be optimized, and the following processing is performed: a performance test is performed on the electronic device to be optimized to obtain N measured performance information, wherein the measured performance information includes measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage; the expected device performance of the electronic device to be optimized is interactively obtained, wherein the expected device performance includes expected global information and N expected performance information, wherein the expected global information includes power consumption expectation and breakdown voltage expectation, and the expected performance information includes current expectation, voltage expectation and heat expectation; the expected device performance and the N measured performance information are integrated as the performance status information; an updated deviation weight set is calculated based on the performance status information, and the performance optimization objective function is defined according to the updated deviation weight set.

[0007] In a possible implementation, an updated deviation weight set is calculated based on the performance status information, and the performance optimization objective function is defined according to the updated deviation weight set, and the following processing is performed: performance deviation is calculated based on the expected performance of the device and N measured performance information to obtain a performance deviation set, wherein the performance deviation set includes current distribution deviation, voltage distribution deviation, heat distribution deviation, power consumption deviation and breakdown voltage deviation; a predefined performance weight set is defined, wherein the performance weight set includes initial current distribution weights, initial voltage distribution weights, initial heat distribution weights, initial power consumption weights and initial breakdown voltage weights; the performance weight set is updated by mapping the performance deviation set to obtain the updated deviation weight set, wherein the updated deviation weight set includes current distribution update weights, voltage distribution update weights, heat distribution update weights, power consumption update weights and breakdown voltage update weights; the performance optimization objective function is constructed according to the performance deviation set and the updated deviation weight set.

[0008] In a possible implementation, the performance optimization objective function is as follows: in, is the performance deviation quantification value, Update the weights for the current distribution, Update the weights for the voltage distribution, Update the weights for heat distribution, Update the weights for power consumption, Update the weights for the breakdown voltage, is the current distribution deviation, is the voltage distribution deviation, is the heat distribution deviation, is the power consumption deviation, is the breakdown voltage deviation; where, To optimize the variables, is the candidate value of the groove depth, is the candidate value of the groove width, is the candidate value of the side wall angle, The feasible range of the optimization variable.

[0009] In a possible implementation, a search update rule is predefined to perform the following processing: preset power consumption limit and breakdown voltage limit; obtain the groove depth interval, groove width interval and sidewall angle interval by performing indicator aggregation and extreme value extraction on the N initial groove parameter combinations; use 1 / K of the groove depth interval, groove width interval and sidewall angle interval as the initial variable adjustment scale; the power consumption limit, breakdown voltage limit, initial variable adjustment scale and feasible range of optimized variables constitute the search update rule.

[0010] In a possible implementation, according to the search update rule and the M initial performance deviations, the update process of the candidate solutions is iteratively executed, and the optimizable variables of the N trench Schottky structural components are continuously optimized until the electronic device structural parameters that meet the expected performance of the device are obtained, and the following processing is performed: according to the search update rule and the M initial performance deviations, the positions of the M initial candidate solutions are updated to obtain M first updated candidate solutions; based on the performance optimization objective function, the M first updated performance deviations of the M first updated candidate solutions are calculated to obtain M second updated candidate solutions; according to the search update rule and the M first updated performance deviations, the positions of the M first updated candidate solutions are updated to obtain M second updated candidate solutions; according to the updated performance deviations and the search update rule, the update process of the candidate solutions is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained.

[0011] In a possible implementation, the updating process of the candidate solutions is repeatedly executed according to the updated performance deviation and the search update rule to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained, and the following processing is performed: according to the M initial performance deviations, the initial variable adjustment scale is directed updated to obtain M first directional adjustment scales; with the feasible range of the optimization variable as a constraint, the position of the M initial candidate solutions is updated according to the M first directional adjustment scales to obtain the M first updated candidate solutions; a virtual device model of the electronic device to be optimized is constructed; the M first updated candidate solutions are imported into the virtual device model for performance simulation testing to obtain M groups of simulated performance information; the M groups The simulation performance information is loaded into the performance optimization objective function, and M performance deviation quantization values ​​are calculated as the M first updated performance deviations of the M first updated candidate solutions; the initial variable adjustment scale is directed updated according to the M first updated performance deviations to obtain M second directed adjustment scales; with the feasible range of the optimization variable as a constraint, the position of the M first updated candidate solutions is updated according to the M second directed adjustment scales to obtain the M second updated candidate solutions; according to the updated performance deviation and the search update rule, the candidate solution update process is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the obtained performance deviation quantization value fluctuates stably within the preset fluctuation scale, and the electronic device structural parameters that meet the expected performance of the device are output.

[0012] In a possible implementation, the following processing is performed: determine whether the M groups of simulation performance information meet the power consumption limit and the breakdown voltage limit; if the M groups of simulation performance information meet the power consumption limit and the breakdown voltage limit, load the M groups of simulation performance information into the performance optimization objective function; if the M groups of simulation performance information do not meet the power consumption limit and the breakdown voltage limit, discard the M first update candidate solutions.

[0013] The present application also provides a performance improvement device for an electronic device with a groove Schottky structure, comprising: a performance optimization objective function construction module, which is used to construct a performance optimization objective function according to the performance status information of the electronic device to be optimized, wherein the electronic device to be optimized includes N groove Schottky structure components; an optimizable variable collection module, which is used to collect optimizable variables for the N groove Schottky structure components to obtain N initial groove parameter combinations; a candidate solution random generation module, which is used to randomly generate candidate solutions with the N initial groove parameter combinations as the starting point to obtain M initial candidate solutions, wherein each candidate solution includes N updated groove parameter combinations; a performance simulation module, which is used to perform performance simulation on the M initial candidate solutions, and use the performance optimization objective function to evaluate the performance simulation results to obtain M initial performance deviations; a candidate solution update iteration module, which is used to predefine search update rules, and iteratively execute the update process of the candidate solutions according to the search update rules and the M initial performance deviations, and continuously optimize the optimizable variables of the N groove Schottky structure components until the electronic device structure parameters that meet the expected performance of the device are obtained.

[0014] The method and device for improving the performance of electronic devices with a trench Schottky structure proposed in the present application first construct a performance optimization objective function based on the performance status information of the electronic device to be optimized, wherein the electronic device to be optimized includes N trench Schottky structural components, then the N trench Schottky structural components are subjected to optimizable variable collection to obtain N initial trench parameter combinations, and then candidate solutions are randomly generated with the N initial trench parameter combinations as the starting point to obtain M initial candidate solutions, wherein each candidate solution includes N updated trench parameter combinations, and then the M initial candidate solutions are subjected to performance simulation, and the performance optimization objective function is used to evaluate the performance simulation results to obtain M initial performance deviations, and finally a search update rule is predefined, and according to the search update rule and the M initial performance deviations, the candidate solution update process is iteratively executed, and the optimizable variables of the N trench Schottky structural components are continuously optimized until the electronic device structural parameters that meet the expected performance of the device are obtained, thereby achieving the technical effect of improving the optimization effect and the overall performance status of the device through collaborative optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the accompanying drawings of the embodiment of the present invention will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0016] Figure 1 A schematic flow chart of a method for improving the performance of an electronic device with a trench Schottky structure provided in an embodiment of the present application.

[0017] Figure 2 A schematic diagram of the structure of a device for improving the performance of electronic devices with a trench Schottky structure provided in an embodiment of the present application.

[0018] Explanation of the reference numerals: performance optimization objective function construction module 10 , optimizable variable acquisition module 20 , candidate solution random generation module 30 , performance simulation module 40 , candidate solution update iteration module 50 . DETAILED DESCRIPTION

[0019] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0020] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0021] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0022] The present application embodiment provides a method for improving the performance of an electronic device with a trench Schottky structure, such as Figure 1 As shown, the method includes:

[0023] Step S100, constructing a performance optimization objective function according to performance status information of an electronic device to be optimized, wherein the electronic device to be optimized includes N trench Schottky structure components.

[0024] Specifically, the electronic device to be optimized refers to an electronic assembly component with multiple (N) trench Schottky structures. Through professional testing equipment or simulation software, a comprehensive performance test is performed on the electronic device to be optimized, and the test results are recorded and organized to obtain its current actual performance status information, that is, the actual performance of the electronic device under the current working state. This information includes key indicators such as current, voltage, heat, power consumption and breakdown voltage. Then, based on the expected performance of the device (such as expected current, voltage, power consumption and breakdown voltage, etc.), and the measured performance information obtained from the performance test, a mathematical method (such as weighted summation, minimization of the sum of squares, etc.) is used to construct an objective function that can reflect the performance deviation, that is, the performance optimization objective function. This function is a mathematical expression and a quantitative indicator for evaluating the performance of candidate solutions. It calculates a quantitative performance deviation value based on the difference between the measured performance and the expected performance.

[0025] In a possible implementation, a performance optimization objective function is constructed according to the performance status information of the electronic device to be optimized, and step S100 further includes step S110, in which a performance test is performed on the electronic device to be optimized to obtain N measured performance information, wherein the measured performance information includes measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage. Specifically, a comprehensive performance test is performed on the electronic device to be optimized using professional testing equipment or simulation software, which can accurately measure key performance indicators such as current, voltage, heat, power consumption and breakdown voltage of the electronic device under specific working conditions. The specific testing process is: according to the working conditions and test requirements of the electronic device, the parameters of the testing equipment or software are set. Then, the electronic device to be optimized is connected to the testing equipment or software, and the test program is started to perform performance testing. During the test process, the testing equipment or software will record and output the measured performance information of the electronic device in real time, including measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage.

[0026] Step S120, interactively obtain the expected device performance of the electronic device to be optimized, wherein the expected device performance includes expected global information and N expected performance information, wherein the expected global information includes power consumption expectation and breakdown voltage expectation, and the expected performance information includes current expectation, voltage expectation and heat expectation. Specifically, the expected performance of the electronic device to be optimized is obtained by interacting with the user or designer. These expected performances are determined according to the application requirements, performance index requirements and design goals of the electronic device. Among them, the expected performance information includes expected global information and N expected performance information (different expectations for each component), wherein the expected global information refers to the expected performance indicators for the entire electronic device, including power consumption expectation and breakdown voltage expectation, and the expected performance information refers to the expected performance indicators for each trench Schottky structure component, including current expectation, voltage expectation and heat expectation.

[0027] Step S130, integrating the expected performance of the device and N measured performance information as the performance status information. Specifically, align and match the measured performance information and the expected performance information to ensure that the corresponding relationship between them is correct. Merge and organize the corresponding performance indicators to form complete performance status information. This information includes the measured performance and expected performance of each trench Schottky structure component, as well as the expected global information of the entire electronic device, which is used for the subsequent construction of the performance optimization objective function and the evaluation of candidate solutions.

[0028] Step S140, based on the performance status information, calculate and obtain an updated deviation weight set, and define the performance optimization objective function according to the updated deviation weight set. Specifically, the weight of each performance indicator is determined according to the degree of influence of each performance indicator on the overall performance optimization, and these weights are combined into an updated deviation weight set. Based on this weight set and the performance status information, a mathematical expression that can reflect the performance deviation is defined as the performance optimization objective function, and this function is used in the subsequent evaluation and optimization process of candidate solutions. This implementation method forms accurate performance status information by integrating the measured performance information and the expected performance information, thereby ensuring the accuracy and effectiveness of the performance optimization objective function.

[0029] In a possible implementation, an updated deviation weight set is calculated based on the performance state information, and the performance optimization objective function is defined according to the updated deviation weight set. Step S140 further includes step S141, performing performance deviation calculation based on the expected performance of the device and N measured performance information to obtain a performance deviation set, wherein the performance deviation set includes current distribution deviation, voltage distribution deviation, heat distribution deviation, power consumption deviation and breakdown voltage deviation. Specifically, for each trench Schottky structure component and the entire device, the actual measured performance information (such as measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage) is compared with the expected performance information (such as current expectation, voltage expectation, heat expectation, power consumption expectation and breakdown voltage expectation). Then, the deviations of these performance indicators are calculated to form a performance deviation set. This set includes current distribution deviation, voltage distribution deviation, heat distribution deviation, power consumption deviation and breakdown voltage deviation, which respectively reflect the degree of deviation of the device from the expected value in different performance indicators.

[0030] The calculation formula of current distribution deviation is as follows: ,in, Characterize the current distribution deviation, Characterization The measured current of a trench Schottky structure component, Characterization The target current of each trench Schottky structure component is calculated. Similarly, the distribution deviation of voltage and heat indicators is calculated.

[0031] The breakdown voltage deviation is calculated as follows: ,in, Characterizes the breakdown voltage deviation, Characterize the measured overall breakdown voltage, which is determined by the worst withstand voltage among all trench Schottky structure components, i.e. is the minimum value among the N measured breakdown voltages, Characterize the target breakdown voltage.

[0032] The power consumption deviation is calculated as follows: ,in, Characterize power consumption deviation, is the measured total power consumption, i.e. the sum of the power consumption of N trench Schottky structure components, Characterizes the target power consumption (desired power consumption value).

[0033] Step S142, predefine a performance weight set, wherein the performance weight set includes initial weights for current distribution, initial weights for voltage distribution, initial weights for heat distribution, initial weights for power consumption, and initial weights for breakdown voltage. Specifically, according to the design requirements, application scenarios, and importance of performance indicators of the device, initial weights are assigned to performance indicators such as current distribution, voltage distribution, heat distribution, power consumption, and breakdown voltage. These weights reflect the proportion or priority of each performance indicator during the optimization process, and are used to balance the importance of different performance indicators during the optimization process.

[0034] Step S143, using the performance deviation set mapping to update the performance weight set, to obtain the updated deviation weight set, wherein the updated deviation weight set includes current distribution update weights, voltage distribution update weights, heat distribution update weights, power consumption update weights, and breakdown voltage update weights. Specifically, each deviation in the performance deviation set is mapped to the initial weight in the corresponding performance weight set, and the initial weight is adjusted according to the size and importance of the deviation to form an updated deviation weight set. The updated weights in this set reflect the new weights or priorities of each performance indicator during the optimization process.

[0035] Step S144, constructing and obtaining the performance optimization objective function according to the performance deviation set and the updated deviation weight set. Specifically, according to the performance deviation set and the updated deviation weight set, construct a mathematical expression that can reflect the relationship between the device performance deviation and the weight. Then, use this expression as the performance optimization objective function to evaluate the performance of the candidate solutions in the subsequent optimization process and guide the direction of the optimization process. This implementation method analyzes the degree of deviation of the device from the expected value in various performance indicators through performance deviation calculation, provides accurate guidance for the performance weight update, and realizes precise optimization of device performance.

[0036] In a possible implementation, step S144 further includes step S1441, and the performance optimization objective function is as follows: in, is the performance deviation quantification value, Update the weights for the current distribution, Update the weights for the voltage distribution, Update the weights for heat distribution, Update the weights for power consumption, Update the weights for the breakdown voltage, is the current distribution deviation, is the voltage distribution deviation, is the heat distribution deviation, is the power consumption deviation, is the breakdown voltage deviation; where, To optimize the variables, is the candidate value of the groove depth, is the candidate value of the groove width, is the candidate value of the side wall angle, is the feasible range of the optimization variable.

[0037] Specifically, this step uses a weighted summation approach to construct a performance optimization objective function, combining various performance deviations and their corresponding update deviation weights to find the optimal electronic device structural parameters by minimizing the objective function, thereby meeting the expected performance of the device. Among them, the performance deviation quantification value is obtained by quantifying each performance deviation, and these deviations reflect the difference between the measured performance and the expected performance. The update weight reflects the relative importance of different performance deviations in the optimization process. Optimization variables are parameters that can be adjusted during the optimization process, and the feasible range of these variables defines the range of values ​​they can take. Among them, For the Candidate values ​​of trench depth for trench Schottky structure components, , and are the minimum and maximum values ​​of the groove depth within the value range, and are the minimum and maximum values ​​of the groove width within the value range, and are the minimum and maximum values ​​of the side wall angle within the value range, respectively. This implementation method constructs the performance optimization objective function by weighted summation, which is simple and clear, and easy to perform mathematical processing and optimization. By minimizing the objective function value, the optimal combination of electronic device structural parameters can be found, thereby achieving performance optimization.

[0038] Step S200 , collecting optimizable variables for the N trench Schottky structural components to obtain N initial trench parameter combinations.

[0039] Specifically, for each trench Schottky structure component in the electronic device, the optimizable variables (parameters that can be adjusted to improve performance, such as trench depth, trench width, sidewall angle, etc.) are identified, and the current values ​​of these variables are obtained through physical measurement (such as using microscopes, measuring instruments and other tools) or consulting design documents to form an initial trench parameter combination.

[0040] Step S300 , randomly generating candidate solutions with the N initial groove parameter combinations as starting points, and obtaining M initial candidate solutions, wherein each candidate solution includes N updated groove parameter combinations.

[0041] Specifically, based on the initial groove parameter combination, each parameter is randomly changed to a certain extent through a randomization method (such as adding or subtracting a random number, multiplying a random factor, etc.) to generate multiple candidate solutions. Each candidate solution contains N updated groove parameter combinations, representing a set of groove parameter combinations that may improve the performance of electronic devices. Among them, the candidate solution can be expressed as follows: Candidate solution = , where each Corresponding to i Step S400: Perform performance simulation on the M initial candidate solutions, and use the performance optimization objective function to evaluate the performance simulation results to obtain M initial performance deviations.

[0042] Specifically, the performance of each initial candidate solution is simulated using electronic device simulation software or a physical model to obtain simulation results. Then, these simulation results are substituted into the performance optimization objective function for calculation to obtain the performance deviation value of each initial candidate solution, which refers to the quantitative value of the difference between the performance of the initial candidate solution and the expected performance.

[0043] Step S500, predefine search update rules, and iteratively execute the update process of candidate solutions according to the search update rules and M initial performance deviations, and continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained.

[0044] Specifically, a set of search update rules are set, which define how to generate new candidate solutions based on the performance deviation of the current candidate solution. Then, the parameter values ​​of the candidate solution are adjusted according to the initial performance deviation and the search update rules (such as increasing or decreasing the value of a parameter, changing the adjustment direction of the parameter, etc.) to generate a new candidate solution. Then, the performance simulation and performance deviation calculation are performed on the updated candidate solution. Next, the parameter values ​​of the candidate solution are adjusted again according to the new performance deviation value. This process involves multiple iterative cycles, and each cycle adjusts the parameter values ​​of the candidate solution according to the performance deviation. Repeat this process until the structural parameters of the electronic device that meet the expected performance are found. The embodiment of the present application adopts a method of constructing an optimization objective function that can reflect the overall performance based on the performance status information of the electronic device to be optimized, collecting optimizable variables for N groove Schottky structural components, randomly generating multiple candidate solutions with the initial groove parameter combination as the starting point, and performing performance simulation on these candidate solutions. According to predefined search update rules and performance simulation results, the candidate solution update process is iteratively executed, and the optimizable variables of the N groove Schottky structural components are continuously adjusted and optimized to obtain the optimal solution for the overall performance. The technical effect of improving the optimization effect and the overall performance status of the device through collaborative optimization is achieved.

[0045] In one possible implementation, the search update rules are predefined, and step S500 further includes step S510, which presets the power consumption limit and the breakdown voltage limit. Specifically, according to the actual application scenario and performance requirements of the electronic device to be optimized, the thresholds of power consumption and breakdown voltage are pre-set. These restrictions are determined based on the reliability and energy efficiency requirements of the device. For example, if the electronic device is used in a low-power device, the power consumption limit will be set lower; if the device needs to withstand a higher voltage, the breakdown voltage limit will be increased accordingly. Among them, the power consumption limit refers to the maximum power consumption value allowed by the device when it is working, which is used to ensure that the device operates under conditions that do not exceed its thermal tolerance. The breakdown voltage limit refers to the highest voltage value that the device can withstand, and the device may be damaged if this value is exceeded.

[0046] Step S520, by performing index aggregation and extreme value extraction on the N initial groove parameter combinations, the groove depth interval, groove width interval and sidewall angle interval are obtained. Specifically, the initial groove parameters (such as depth, width and sidewall angle) are statistically analyzed to determine their respective ranges of variation. Through the aggregation analysis of these parameters, the maximum and minimum values ​​of the groove depth are extracted to form the groove depth interval; similarly, the groove width interval and sidewall angle interval are obtained. Among them, index aggregation refers to the process of merging multiple initial parameter values ​​into one or a few statistics (such as maximum value, minimum value, etc.). Extreme value extraction refers to the process of finding the maximum and minimum values ​​from a set of data.

[0047] Step S530, taking 1 / K of the groove depth interval, groove width interval and sidewall angle interval as the initial variable adjustment scale. Specifically, the interval obtained in step S520 is subdivided to determine the adjustment amplitude of the parameters at each iteration. K is a preset constant, which represents the number of parts each interval is subdivided into. The initial variable adjustment scale is the amplitude or step size of the parameter adjustment at each iteration. By setting the initial variable adjustment scale, the algorithm can adjust the parameters with a smaller step size at each iteration, thereby searching for the optimal solution more finely.

[0048] Step S540, the power consumption limit, breakdown voltage limit, initial variable adjustment scale and feasible range of optimized variables constitute the search update rule. Specifically, all the above constraints and parameters are integrated into a unified search update rule. This rule guides the generation and update process of candidate solutions, ensuring that all generated candidate solutions meet the power consumption and breakdown voltage limits, and the adjustment range of parameters is within a reasonable range. During the iteration process, the algorithm will continuously update the candidate solutions according to this rule until the structural parameters of the electronic device that meet the expected performance are found. This implementation method ensures that the optimized electronic device will not fail in actual applications due to excessive power consumption or too low breakdown voltage by presetting power consumption and breakdown voltage limits. Through index aggregation and extreme value extraction, the reasonable range of parameter changes is quickly determined, the search space is narrowed, and the search efficiency is improved. By setting the initial variable adjustment scale, it is ensured that the adjustment range of parameters is moderate in each iteration, avoiding excessive or too small adjustments that cause the search process to fall into a local optimum or the search speed is too slow. Integrating power consumption limits, breakdown voltage limits, initial variable adjustment scales, and feasible ranges of optimized variables into the search update rules ensures that the algorithm integrates multiple performance indicators during the search process, thereby finding electronic device structural parameters that meet the global optimum.

[0049] In a possible implementation, according to the search update rule and the M initial performance deviations, the update process of the candidate solution is iteratively executed, and the optimizable variables of the N trench Schottky structural components are continuously optimized until the electronic device structural parameters that meet the expected performance of the device are obtained. Step S500 further includes step S550, according to the search update rule and the M initial performance deviations, the position of the M initial candidate solutions is updated to obtain M first updated candidate solutions. Specifically, the algorithm updates the position of each candidate solution (i.e., the parameters such as the groove depth, width and sidewall angle contained therein) according to the predefined search update rule (including power consumption limit, breakdown voltage limit, initial variable adjustment scale and feasible range of optimization variables) and the performance deviation of the M initial candidate solutions, that is, checks its performance deviation (such as power consumption deviation, breakdown voltage deviation, etc.), and calculates the new parameter value according to these deviations and the initial variable adjustment scale in the search update rule. The new parameter value will be within the feasible range of the optimization variable and as close to the expected performance as possible. Among them, the position update refers to the adjustment or update of the parameter value in the candidate solution.

[0050] Step S560, based on the performance optimization objective function, calculate and obtain the M first updated performance deviations of the M first updated candidate solutions. Specifically, after the position of the candidate solution is updated, the algorithm uses the performance optimization objective function to calculate the performance deviation of each updated candidate solution. These performance deviations are used to evaluate whether the updated candidate solution is closer to the expected performance and serve as the basis for subsequent iterative updates.

[0051] Step S570, update the positions of the M first updated candidate solutions according to the search update rules and the M first updated performance deviations to obtain M second updated candidate solutions. Specifically, similar to step S550, a second position update is performed based on the updated performance deviations and search update rules. By continuously iterating and updating the positions of the candidate solutions, the algorithm can gradually approach the optimal solution that meets the expected performance. In each iteration, the algorithm adjusts the parameter values ​​of the candidate solutions according to the current performance deviations and search update rules in order to obtain better performance. This process will continue until the structural parameters of the electronic device that meet the expected performance are found.

[0052] Step S580, according to the updated performance deviation and the search update rule, the candidate solution update process is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained. Specifically, this step is a continuation of steps S550 and S570, and is used to describe the continuity and repeatability of iterative updates. In each iteration, the algorithm updates the position of the candidate solution according to the current updated performance deviation and search update rule, and evaluates the updated performance. This process is repeated until a certain stop condition is met (such as reaching a preset number of iterations, the performance deviation is less than a certain threshold, etc.). Finally, the algorithm outputs the electronic device structural parameters that meet the expected performance as the optimization result. This implementation method can gradually approach the optimal solution that meets the expected performance by continuously iteratively updating the position of the candidate solution. At the same time, through the iterative update strategy and performance evaluation method, the algorithm can quickly find the electronic device structural parameters that meet the expected performance within limited computing resources, thereby improving the search efficiency.

[0053] In a possible implementation, the updating process of the candidate solutions is repeatedly performed according to the updated performance deviation and the search update rule to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained, and step S580 further includes step S581, performing a directional update of the initial variable adjustment scale according to the M initial performance deviations to obtain M first directional adjustment scales. Specifically, the algorithm adjusts the initial variable adjustment scale according to the performance deviation of the M initial candidate solutions (i.e., the deviation between them and the expected performance). This adjustment scale determines the amplitude or step size of the candidate solution parameter update in subsequent iterations. Specifically, the algorithm analyzes the distribution of performance deviations, and for parameters with larger deviations, a larger adjustment scale is selected to speed up the optimization process; for parameters with smaller deviations, a smaller adjustment scale is selected for fine adjustment. This directional update strategy is used for the algorithm to converge to the optimal solution faster.

[0054] Step S582, taking the feasible range of the optimization variable as a constraint, the positions of the M initial candidate solutions are updated according to the M first directional adjustment scales to obtain the M first updated candidate solutions. Specifically, the algorithm updates the positions of the initial candidate solutions according to the updated variable adjustment scale (i.e., the first directional adjustment scale), that is, each parameter of each candidate solution is updated, and the updated parameter value is equal to the current parameter value plus an increment determined by the first directional adjustment scale. This increment can be a positive number or a negative number, depending on the direction of the deviation between the current parameter and the expected performance. The update process will be constrained by the feasible range of the optimization variable to ensure that the new candidate solution is still valid.

[0055] Step S583, constructing a virtual device model of the electronic device to be optimized. Specifically, constructing a geometric structure model of the electronic device to be optimized according to the parameters of the trench Schottky structure (such as depth, width, sidewall angle, etc.), constructing a virtual device model, and using the virtual device model for performance simulation testing, importing semiconductor material parameters (such as breakdown electric field, electrical conductivity, thermal conductivity, etc.) into the simulation software to simulate the actual working conditions of the device.

[0056] Step S584, import the M first updated candidate solutions into the virtual device model for performance simulation test, and obtain M sets of simulated performance information. Specifically, import the updated candidate solution (i.e., the first updated candidate solution) into the virtual device model, and perform performance simulation test, and record the performance indicators such as current, voltage, heat, power consumption and breakdown voltage of each trench Schottky structure component, which are used for subsequent performance deviation calculation and candidate solution update.

[0057] Step S585, load the M groups of simulated performance information into the performance optimization objective function, and calculate M performance deviation quantization values ​​as the M first updated performance deviations of the M first updated candidate solutions. Specifically, the algorithm loads the simulated performance information obtained by the simulation test into the performance optimization objective function, and calculates the performance deviation quantization value of each candidate solution, which is used to evaluate the degree of deviation between the candidate solution and the expected performance.

[0058] Step S586, perform a directional update of the initial variable adjustment scale according to the M first updated performance deviations to obtain M second directional adjustment scales; step S587, take the feasible range of the optimization variable as a constraint, perform a position update of the M first updated candidate solutions according to the M second directional adjustment scales to obtain the M second updated candidate solutions. Specifically, these two steps are similar to steps S581 and S582, but they are the second directional update and position update based on the updated performance deviation (i.e., the performance deviation of the first updated candidate solution). In step S586, the algorithm will adjust the variable adjustment scale (i.e., the second directional adjustment scale) according to the updated performance deviation. In step S587, the algorithm will update the position of the candidate solution according to the adjusted variable adjustment scale (i.e., obtain the second updated candidate solution).

[0059] Step S588, according to the updated performance deviation and the search update rule, the update process of the candidate solution is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the obtained performance deviation quantization value fluctuates stably within the preset fluctuation scale, and the electronic device structural parameters that meet the expected performance of the device are output. Specifically, the algorithm will repeat the update process of the candidate solution according to the updated performance deviation and search update rule. This process will continue until the electronic device structural parameters that meet the expected performance are found. That is, the algorithm will continuously update the position and variable adjustment scale of the candidate solution, and evaluate the updated performance. When the performance deviation quantization value fluctuates stably within the preset fluctuation scale, the algorithm will stop iterating and output the electronic device structural parameters that meet the expected performance. Among them, the preset fluctuation scale is a threshold for judging whether the performance deviation quantization value is stable. In this implementation, the algorithm can dynamically adjust the variable adjustment scale according to the distribution of the current performance deviation, improve the adaptability of the algorithm, and gradually approach the optimal solution that meets the expected performance.

[0060] In one possible implementation, step S584 further includes step S5841, determining whether the M groups of analog performance information meet the power consumption limit and breakdown voltage limit. Specifically, after the performance simulation test is completed, verify whether the obtained M groups of analog performance information (each group contains analog performance information of N components) meet the preset power consumption limit and breakdown voltage limit to ensure that the candidate solutions in the optimization process not only have superior performance, but also meet the basic safety and use requirements of electronic devices. Specific values ​​of power consumption and breakdown voltage are extracted from each group of analog performance information. These values ​​are compared one by one with the preset power consumption limit and breakdown voltage limit. If the power consumption and breakdown voltage of all candidate solutions meet the restriction conditions, step S5842 is executed; if any candidate solution does not meet the restriction conditions, step S5843 is executed.

[0061] Step S5842, if the M groups of simulated performance information meet the power consumption limit and the breakdown voltage limit, the M groups of simulated performance information are loaded into the performance optimization objective function. Specifically, when the simulated performance information meets the power consumption and breakdown voltage limits, the performance information is deemed valid and can be used for further performance optimization. The M groups of simulated performance information that meet the conditions are input into the performance optimization objective function, and the performance optimization objective function is used to calculate the deviation between each group of simulated performance information and the expected performance. Based on these deviations, the position of the candidate solution is updated according to the search update rule to further approach the expected performance.

[0062] Step S5843, if the M groups of analog performance information do not meet the power consumption limit and the breakdown voltage limit, the M first updated candidate solutions are discarded. Specifically, when the analog performance information does not meet the power consumption and breakdown voltage limits, these candidate solutions are deemed invalid, and they do not meet the basic requirements of electronic devices. At this time, the first updated candidate solution that does not meet the conditions is directly discarded. According to the search update rules and the currently known valid information, new candidate solutions are regenerated, and the performance simulation test process is repeated. This implementation method ensures that all candidate solutions meet the basic safety and use requirements of electronic devices by judging whether the analog performance information meets the power consumption limit and the breakdown voltage limit, avoiding the waste of time and resources in the subsequent optimization process, and making the final electronic device structural parameters not only superior in performance, but also safe and reliable.

[0063] In the above, refer to Figure 1 The method for improving the performance of an electronic device with a trench Schottky structure according to an embodiment of the present invention is described in detail. Figure 2 A device for improving the performance of an electronic device with a trench Schottky structure according to an embodiment of the present invention is described.

[0064] The electronic device performance improvement device for a trench Schottky structure according to an embodiment of the present invention is used to solve the technical problem that the existing electronic device performance improvement for a trench Schottky structure has a single optimization direction, resulting in limited optimization effect and difficulty in achieving the optimal state of the overall performance, so as to achieve the technical effect of improving the optimization effect and the overall performance state of the device through collaborative optimization. The electronic device performance improvement device for a trench Schottky structure includes: a performance optimization objective function construction module 10, an optimizable variable acquisition module 20, a candidate solution random generation module 30, a performance simulation module 40, and a candidate solution update iteration module 50.

[0065] A performance optimization objective function construction module 10 is used to construct a performance optimization objective function according to the performance status information of the electronic device to be optimized, wherein the electronic device to be optimized includes N groove Schottky structural components; an optimizable variable collection module 20 is used to collect optimizable variables for the N groove Schottky structural components to obtain N initial groove parameter combinations; a candidate solution random generation module 30 is used to randomly generate candidate solutions based on the N initial groove parameter combinations to obtain M initial candidate solutions, wherein each candidate solution includes N updated groove parameter combinations; a performance simulation module 40 is used to perform performance simulation on the M initial candidate solutions, and use the performance optimization objective function to evaluate the performance simulation results to obtain M initial performance deviations; a candidate solution update iteration module 50 is used to predefine a search update rule, and iteratively execute the candidate solution update process according to the search update rule and the M initial performance deviations, and continuously optimize the optimizable variables of the N groove Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained.

[0066] The specific configuration of the performance optimization objective function construction module 10 will be described in detail below. As described above, the performance optimization objective function is constructed according to the performance status information of the electronic device to be optimized, and the performance optimization objective function construction module 10 may further include: an electronic device performance testing unit is used to perform performance testing on the electronic device to be optimized, and obtain N measured performance information, wherein the measured performance information includes measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage; a device expected performance acquisition unit is used to interactively obtain the device expected performance of the electronic device to be optimized, wherein the device expected performance includes expected global information and N expected performance information, wherein the expected global information includes power consumption expectation and breakdown voltage expectation, and the expected performance information includes current expectation, voltage expectation and heat expectation; a performance status information generation unit is used to integrate the device expected performance and N measured performance information as the performance status information; an updated deviation weight set calculation unit is used to calculate and obtain an updated deviation weight set based on the performance status information, and define the performance optimization objective function according to the updated deviation weight set.

[0067] Wherein, an updated deviation weight set is calculated based on the performance status information, and the performance optimization objective function is defined according to the updated deviation weight set. The updated deviation weight set calculation unit may further include: a performance deviation calculation subunit is used to perform performance deviation calculation based on the expected performance of the device and N measured performance information to obtain a performance deviation set, wherein the performance deviation set includes current distribution deviation, voltage distribution deviation, heat distribution deviation, power consumption deviation and breakdown voltage deviation; a performance weight set predefinition subunit is used to predefine a performance weight set, wherein the performance weight set includes current distribution initial weight, voltage distribution initial weight, heat distribution initial weight, power consumption initial weight and breakdown voltage initial weight; a performance weight set update subunit is used to update the performance weight set using the performance deviation set mapping to obtain the updated deviation weight set, wherein the updated deviation weight set includes current distribution update weight, voltage distribution update weight, heat distribution update weight, power consumption update weight and breakdown voltage update weight; a performance optimization objective function construction subunit is used to construct and obtain the performance optimization objective function according to the performance deviation set and the updated deviation weight set.

[0068] The performance optimization objective function construction subunit may further include: a performance optimization objective function storage microunit for the performance optimization objective function as follows: in, is the performance deviation quantification value, Update the weights for the current distribution, Update the weights for the voltage distribution, Update the weights for heat distribution, Update the weights for power consumption, Update the weights for the breakdown voltage, is the current distribution deviation, is the voltage distribution deviation, is the heat distribution deviation, is the power consumption deviation, is the breakdown voltage deviation; where, To optimize the variables, is the candidate value of the groove depth, is the candidate value of the groove width, is the candidate value of the side wall angle, To optimize the feasible range of variables. Below, the specific configuration of the candidate solution update iteration module 50 will be described in detail. As described above, the search update rules are predefined, and the candidate solution update iteration module 50 may further include: a limitation preset unit is used to preset power consumption limits and breakdown voltage limits; an indicator aggregation unit is used to obtain the groove depth interval, groove width interval and sidewall angle interval by performing indicator aggregation and extreme value extraction on the N initial groove parameter combinations; an initial variable adjustment scale setting unit is used to use 1 / K of the groove depth interval, groove width interval and sidewall angle interval as the initial variable adjustment scale; a search update rule generation unit is used to form the search update rules with the power consumption limit, breakdown voltage limit, initial variable adjustment scale and the feasible range of optimized variables.

[0069] Among them, according to the search update rule and M initial performance deviations, the update process of the candidate solution is iteratively executed, and the optimizable variables of the N groove Schottky structural components are continuously optimized until the electronic device structural parameters that meet the expected performance of the device are obtained. The candidate solution update iteration module 50 may further include: an initial candidate solution position update unit is used to update the positions of the M initial candidate solutions according to the search update rule and the M initial performance deviations, and obtain M first updated candidate solutions; an updated performance deviation calculation unit is used to calculate and obtain M first updated performance deviations of the M first updated candidate solutions based on the performance optimization objective function; a candidate solution iterative update unit is used to update the positions of the M first updated candidate solutions according to the search update rule and the M first updated performance deviations, and obtain M second updated candidate solutions. According to the updated performance deviations and the search update rule, the update process of the candidate solution is repeatedly executed to continuously optimize the optimizable variables of the N groove Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained.

[0070] Among them, according to the updated performance deviation and the search update rule, the update process of the candidate solution is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained, and the candidate solution iterative update unit can further include: an initial variable adjustment scale directional update subunit is used to perform a directional update of the initial variable adjustment scale according to the M initial performance deviations to obtain M first directional adjustment scales; an initial candidate solution position update subunit is used to update the position of the M initial candidate solutions according to the M first directional adjustment scales with the feasible range of the optimization variable as a constraint to obtain the M first updated candidate solutions; a virtual device model construction subunit is used to construct a virtual device model of the electronic device to be optimized; a performance simulation test subunit is used to import the M first updated candidate solutions into the virtual device model for performance simulation testing to obtain M groups of simulated performance information; update performance The deviation calculation subunit is used to load the M groups of simulation performance information into the performance optimization objective function, and calculate M performance deviation quantization values ​​as the M first updated performance deviations of the M first updated candidate solutions; the initial variable adjustment scale directional update subunit is used to perform directional update of the initial variable adjustment scale according to the M first updated performance deviations, and obtain M second directional adjustment scales; the updated candidate solution position update subunit is used to perform position update of the M first updated candidate solutions according to the M second directional adjustment scales with the feasible range of the optimization variable as a constraint, and obtain the M second updated candidate solutions; the candidate solution iterative update subunit is used to repeatedly execute the candidate solution update process according to the updated performance deviation and the search update rule, so as to continuously optimize the optimizable variables of the N trench Schottky structural components, until the obtained performance deviation quantization value fluctuates stably within the preset fluctuation scale, and outputs the electronic device structural parameters that meet the expected performance of the device.

[0071] Among them, the performance simulation test sub-unit may further include: a judgment micro-unit used to judge whether the M groups of simulated performance information meet the power consumption limit and the breakdown voltage limit; a judgment result processing micro-unit is used to load the M groups of simulated performance information into the performance optimization objective function if the M groups of simulated performance information meet the power consumption limit and the breakdown voltage limit, and discard the M first updated candidate solutions if the M groups of simulated performance information do not meet the power consumption limit and the breakdown voltage limit.

[0072] The device for improving the performance of an electronic device with a trench Schottky structure provided in an embodiment of the present invention can execute the method for improving the performance of an electronic device with a trench Schottky structure provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0073] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0074] The above specific implementation manner does not constitute a limitation to the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and can still achieve the desired results. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for improving the performance of an electronic device with a trench Schottky structure, characterized in that: The method comprises: Constructing a performance optimization objective function according to the performance status information of the electronic device to be optimized, wherein the electronic device to be optimized includes N trench Schottky structure components; Collecting optimizable variables for the N trench Schottky structure components to obtain N initial trench parameter combinations; Randomly generate candidate solutions with the N initial groove parameter combinations as starting points to obtain M initial candidate solutions, wherein each candidate solution includes N updated groove parameter combinations; Performing performance simulation on the M initial candidate solutions, and evaluating the performance simulation results using the performance optimization objective function to obtain M initial performance deviations; Predefine a search update rule, and iteratively execute an update process of the candidate solution according to the search update rule and the M initial performance deviations, and continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained; The performance optimization objective function is as follows: in, is the performance deviation quantification value, Update the weights for the current distribution, Update the weights for the voltage distribution, Update the weights for heat distribution, Update the weights for power consumption, Update the weights for the breakdown voltage, is the current distribution deviation, is the voltage distribution deviation, is the heat distribution deviation, is the power consumption deviation, is the breakdown voltage deviation; where, To optimize the variables, is the candidate value of the groove depth, is the candidate value of the groove width, is the candidate value of the side wall angle, To optimize the feasible range of variables; Predefined search update rules, the method comprises: Preset power consumption limit and breakdown voltage limit; By performing index aggregation and extreme value extraction on the N initial groove parameter combinations, a groove depth interval, a groove width interval and a sidewall angle interval are obtained; Using 1 / K of the groove depth interval, the groove width interval and the sidewall angle interval as the initial variable adjustment scale; The power consumption limit, breakdown voltage limit, initial variable adjustment scale and feasible range of optimized variables constitute the search update rule; According to the search update rule and the M initial performance deviations, the candidate solution update process is iteratively executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained, the method comprising: Update the positions of the M initial candidate solutions according to the search update rule and the M initial performance deviations to obtain M first updated candidate solutions; Obtaining M first updated performance deviations of the M first updated candidate solutions based on the performance optimization objective function calculation; Performing position update of the M first update candidate solutions according to the search update rule and the M first update performance deviations to obtain M second update candidate solutions; Repeating the updating process of the candidate solutions according to the updated performance deviation and the search update rule to continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained; According to the updated performance deviation and the search update rule, the updating process of the candidate solution is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structure components until the electronic device structure parameters that meet the expected performance of the device are obtained, the method comprising: Performing a directional update of the initial variable adjustment scale according to the M initial performance deviations to obtain M first directional adjustment scales; Taking the feasible range of the optimization variable as a constraint, updating the positions of the M initial candidate solutions according to the M first directional adjustment scales to obtain the M first updated candidate solutions; Constructing a virtual device model of the electronic device to be optimized; Importing the M first updated candidate solutions into the virtual device model to perform performance simulation test to obtain M groups of simulation performance information; Loading the M groups of simulation performance information into the performance optimization objective function, and calculating and obtaining M performance deviation quantization values ​​as M first updated performance deviations of the M first updated candidate solutions; Performing a directional update of the initial variable adjustment scale according to the M first update performance deviations to obtain M second directional adjustment scales; Taking the feasible range of the optimization variable as a constraint, updating the positions of the M first updated candidate solutions according to the M second directional adjustment scales to obtain the M second updated candidate solutions; According to the updated performance deviation and the search update rule, the updating process of the candidate solution is repeatedly executed to continuously optimize the optimizable variables of the N trench Schottky structural components until the obtained performance deviation quantization value fluctuates stably within a preset fluctuation scale, and the electronic device structural parameters that meet the expected performance of the device are output.

2. The method for improving the performance of an electronic device for a trench Schottky structure according to claim 1, characterized in that: Constructing a performance optimization objective function according to the performance status information of the electronic device to be optimized, the method comprising: Performing performance testing on the electronic device to be optimized to obtain N pieces of measured performance information, wherein the measured performance information includes measured current, measured voltage, measured heat, measured power consumption and measured breakdown voltage; Interactively obtaining the device expected performance of the electronic device to be optimized, wherein the device expected performance includes expected global information and N expected performance information, wherein the expected global information includes power consumption expectation and breakdown voltage expectation, and the expected performance information includes current expectation, voltage expectation and heat expectation; Integrating the expected performance of the device and N pieces of measured performance information as the performance status information; An updated deviation weight set is calculated based on the performance status information, and the performance optimization objective function is defined according to the updated deviation weight set.

3. The method for improving the performance of an electronic device for a trench Schottky structure according to claim 2, characterized in that: An updated deviation weight set is calculated based on the performance status information, and the performance optimization objective function is defined according to the updated deviation weight set. The method includes: Calculating performance deviation based on the expected performance of the device and N pieces of measured performance information to obtain a performance deviation set, wherein the performance deviation set includes current distribution deviation, voltage distribution deviation, heat distribution deviation, power consumption deviation and breakdown voltage deviation; Predefine a performance weight set, wherein the performance weight set includes an initial weight for current distribution, an initial weight for voltage distribution, an initial weight for heat distribution, an initial weight for power consumption, and an initial weight for breakdown voltage; The performance weight set is updated by using the performance deviation set mapping to obtain the updated deviation weight set, wherein the updated deviation weight set includes a current distribution update weight, a voltage distribution update weight, a heat distribution update weight, a power consumption update weight, and a breakdown voltage update weight; The performance optimization objective function is constructed based on the performance deviation set and the update deviation weight set.

4. The method for improving the performance of an electronic device for a trench Schottky structure according to claim 1, characterized in that: The method comprises: Determining whether the M groups of simulation performance information meet the power consumption limit and breakdown voltage limit; If the M groups of simulation performance information meet the power consumption limit and the breakdown voltage limit, then loading the M groups of simulation performance information into the performance optimization objective function; If the M groups of simulation performance information do not meet the power consumption limit and the breakdown voltage limit, the M first updated candidate solutions are discarded.

5. A device for improving the performance of electronic devices with a trench Schottky structure, characterized in that: The device is used to implement the method for improving the performance of an electronic device with a trench Schottky structure according to any one of claims 1 to 4, and the device comprises: A performance optimization objective function construction module is used to construct a performance optimization objective function according to the performance status information of the electronic device to be optimized, wherein the electronic device to be optimized includes N trench Schottky structure components; An optimizable variable collection module is used to collect optimizable variables for the N trench Schottky structure components to obtain N initial trench parameter combinations; A candidate solution random generation module, used to randomly generate candidate solutions with the N initial groove parameter combinations as starting points to obtain M initial candidate solutions, wherein each candidate solution includes N updated groove parameter combinations; A performance simulation module, used to perform performance simulation on the M initial candidate solutions, and use the performance optimization objective function to evaluate the performance simulation results to obtain M initial performance deviations; The candidate solution update iteration module is used to predefine the search update rules, and iteratively execute the candidate solution update process according to the search update rules and M initial performance deviations, and continuously optimize the optimizable variables of the N trench Schottky structural components until the electronic device structural parameters that meet the expected performance of the device are obtained.

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