High-performance silicon carbide MOSFET switching characteristics optimization method and device

Abstract

The present invention relates to the technical field of MOSFET performance optimization, and discloses a high-performance silicon carbide MOSFET switch characteristic optimization method and device. The present invention collects data of working parameters of MOSFET switches, obtains working monitoring data, collects parameter data of voltage drive units and resistance adjustment units, obtains voltage drive data and resistance adjustment data, analyzes the working state of the switch according to the collected data, obtains working state characteristics, performs gradient analysis based on the working state characteristics, formulates several optimization test schemes, executes the optimization test schemes of each gradient in turn, obtains the optimization test characteristics, and determines whether to execute the optimization scheme of the next gradient according to the test characteristics. Through this method, the switching characteristics of silicon carbide MOSFET can be systematically and accurately optimized. Real-time data analysis and gradient optimization steps improve optimization efficiency, reduce trial and error costs, and enhance the performance stability and reliability of MOSFET.

Description

Technical Field

[0001] The present invention relates to the technical field of MOSFET performance optimization, and in particular to a method and device for optimizing the switching characteristics of a high-performance silicon carbide MOSFET. Background Art

[0002] Silicon carbide (SiC) MOSFET has been widely used in the field of power electronics due to its high switching speed, high voltage blocking capability and high temperature operating performance. The switching characteristics of the MOSFET switch are affected by the driving voltage and its own resistance. Maintaining a higher voltage and lower resistance within a reasonable limit will improve its performance. However, if the limit is exceeded, the MOSFET diode will be damaged, and the higher voltage will produce voltage spikes and thus affect the switching performance. In the existing technology, it is difficult to balance the driving voltage and switch resistance to ensure the optimization of the performance of the silicon carbide MOSFET switch. Summary of the invention

[0003] The purpose of the present invention is to provide a high-performance silicon carbide MOSFET switch characteristic optimization method and device, aiming to solve the problem in the prior art that it is difficult to achieve performance optimization by controlling the voltage resistance of the MOSFET switch.

[0004] The present invention is implemented in this way. In a first aspect, the present invention provides a method for optimizing the switching characteristics of a high-performance silicon carbide MOSFET, comprising:

[0005] Collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch;

[0006] Collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit;

[0007] Analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain working state characteristics of the MOSFET switch;

[0008] Performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics to obtain several optimized test schemes of executing gradients of the MOSFET switch;

[0009] The voltage driving unit and the resistance adjustment unit are optimized and tested in sequence according to the optimization test schemes of each execution gradient. When performing the optimization test processing of each execution gradient, the optimization test characteristics of the optimization test processing are obtained, and it is determined whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

[0010] In a second aspect, the present invention provides a high-performance silicon carbide MOSFET switching characteristic optimization device, which is used to implement a high-performance silicon carbide MOSFET switching characteristic optimization method as described in any one of the first aspects, comprising:

[0011] A data monitoring module, used for collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch;

[0012] A data acquisition module, used for collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, and obtaining voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit;

[0013] A state analysis module, used for analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data, so as to obtain the working state characteristics of the MOSFET switch;

[0014] A scheme analysis module, used for performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics, and obtaining several optimized test schemes of execution gradients of the MOSFET switch;

[0015] A test execution module is used to perform optimization test processing on the voltage driving unit and the resistance adjustment unit in sequence according to the optimization test schemes of each execution gradient, obtain the optimization test characteristics of the optimization test processing when performing the optimization test processing of each execution gradient, and decide whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

[0016] The present invention provides a high-performance silicon carbide MOSFET switching characteristic optimization method, which has the following beneficial effects:

[0017] The present invention collects data of working parameters of MOSFET switches, obtains working monitoring data, collects parameter data of voltage drive units and resistance adjustment units, obtains voltage drive data and resistance adjustment data, analyzes the working state of the switch according to the collected data, obtains working state characteristics, performs gradient analysis based on the working state characteristics, formulates several optimization test schemes, sequentially executes the optimization test schemes of each gradient, obtains the optimization test characteristics, and determines whether to execute the optimization scheme of the next gradient according to the test characteristics. Through this method, the switching characteristics of silicon carbide MOSFET can be systematically and accurately optimized. Real-time data analysis and gradient optimization steps improve optimization efficiency, reduce trial and error costs, and enhance the performance stability and reliability of MOSFET. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the steps of a method for optimizing the switching characteristics of a high-performance silicon carbide MOSFET provided by an embodiment of the present invention;

[0019] Figure 2 It is a structural schematic diagram of a high-performance silicon carbide MOSFET switching characteristic optimization device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0021] The implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0022] Reference Figure 1 , Figure 2 As shown, a preferred embodiment of the present invention is provided.

[0023] In a first aspect, the present invention provides a method for optimizing the switching characteristics of a high-performance silicon carbide MOSFET, comprising:

[0024] S1: collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch;

[0025] S2: collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit;

[0026] S3: analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain working state characteristics of the MOSFET switch;

[0027] S4: performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics, and obtaining several optimized test schemes of executing gradients of the MOSFET switch;

[0028] S5: According to the optimization test schemes of each execution gradient, the voltage driving unit and the resistance adjustment unit are optimized and tested in turn. When performing the optimization test processing of each execution gradient, the optimization test characteristics of the optimization test processing are obtained, and according to the optimization test characteristics, it is determined whether to execute the optimization test scheme of the next gradient, so as to optimize the switching characteristics of the MOSFET switch.

[0029] Specifically, in step S1 of the embodiment provided by the present invention, data of switch operating parameters are collected for the MOSFET switch, and the collected data are continuously recorded and integrated to obtain operating monitoring data of the MOSFET switch.

[0030] More specifically, the collected data includes the switching state of the MOSFET switch at various times, the circuit parameters in the on state, the circuit parameters in the off state, and the circuit parameters when the switching state is switched. The performance of the MOSFET switch is related to the voltage and current applied to it. The closer the voltage and current applied to the MOSFET switch are to the theoretical limit values, the higher its performance. Based on the working monitoring data of the MOSFET switch, the driving voltage applied to the MOSFET switch can be increased, or the MOSFET switch's own resistance can be reduced, thereby achieving the effect of improving the switching characteristics.

[0031] It should be noted that the circuit parameters of the MOSFET switch will change during the transition between the open state and the closed state, and voltage spikes will occur during the change process. This phenomenon will affect the performance of the MOSFET switch. Therefore, when increasing the driving voltage or reducing the resistance, it is necessary to consider avoiding increasing the voltage spike phenomenon.

[0032] Specifically, in step S2 of the embodiment provided by the present invention, data collection of unit working parameters is performed on the voltage driving unit and the resistance adjusting unit connected to the MOSFET switch to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit.

[0033] More specifically, the operation of the MOSFET switch requires the connection of a driving voltage. At the same time, the MOSFET switch can be connected in parallel with an external resistor to reduce the resistance value of the MOSFET switch itself. By reducing the resistance value of the MOSFET switch, the switching characteristics can be improved. At the same time, increasing the driving voltage can also achieve the same technical effect.

[0034] More specifically, when executing the specific steps to improve the switching characteristics of the MOSFET switch, the specific path and the extent of execution need to be determined based on a comprehensive analysis of the current parameters of the voltage driving unit and the resistance adjustment unit, as well as the current characteristics exhibited by the MOSFET switch. Therefore, it is necessary to collect data on the unit working parameters of the voltage driving unit and the resistance adjustment unit that are circuit-connected to the MOSFET switch to obtain the voltage driving data of the voltage driving unit and the resistance adjustment data of the resistance adjustment unit.

[0035] Specifically, in step S3 of the embodiment provided by the present invention, the switch working state of the MOSFET switch is analyzed and processed according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain the working state characteristics of the MOSFET switch.

[0036] It should be noted that the MOSFET switch is affected by voltage and current during operation. The gate-source voltage of the MOSFET switch has a minimum gate-source voltage for starting conduction. When the driving voltage exceeds the minimum gate-source voltage, the MOSFET switch turns to the on state.

[0037] More specifically, if the gate-source voltage is too high, it may cause the MOSFET to enter the saturation region, increase conduction losses, and may cause damage to the gate oxide layer. If the gate-source voltage is insufficient, the MOSFET may not be fully turned on, resulting in higher on-resistance, increased losses and heat generation.

[0038] More specifically, the drain-source voltage of a MOSFET switch has a breakdown voltage, which is the maximum drain-source voltage that the MOSFET can withstand. When the breakdown voltage is exceeded, the MOSFET may be damaged by breakdown. If the MOSFET switch is too low, it may cause the MOSFET to operate in the linear region instead of the saturation region and fail to switch effectively. The drain current capability of the MOSFET switch determines the maximum current that can be passed when it is turned on. If it exceeds the rated value, it will cause the MOSFET switch to heat up and potentially thermal runaway. Too little current means that the MOSFET is not fully utilized.

[0039] More specifically, the on-resistance is the resistance from drain to source when the MOSFET switch is turned on, which directly affects the conduction loss of the MOSFET. Lower on-resistance means lower conduction loss and heat generation, and higher efficiency.

[0040] It is understandable that the switching characteristics of a MOSFET switch are closely related to the voltage and current it is subjected to as well as its own resistance. By controlling the driving voltage and switch resistance within the limit range, the performance of the MOSFET switch can be optimized as much as possible while ensuring the safety of the switch.

[0041] Specifically, in step S4 of the embodiment provided by the present invention, a gradient analysis process of a driving optimization scheme is performed on the MOSFET switch according to the working state characteristics to obtain several optimization test schemes of executing the gradient of the MOSFET switch.

[0042] More specifically, the current working environment of the MOSFET switch is analyzed according to the working state characteristics, and then the optimal driving voltage and switch resistance of the MOSFET switch that adapts to the current working state are inferred, and the optimization plan is analyzed according to the actual state of the MOSFET switch and the inferred results to obtain an optimized test plan.

[0043] It should be noted that the optimization of the MOSFET switch can be to increase the driving voltage, or to reduce the switch resistance, or both. Different optimization directions lead to several final optimization schemes. In order to select one of the several final optimization schemes to execute, a lower-gradient optimization test scheme is designed for the several final optimization schemes. The lower-gradient optimization test scheme is executed first to determine how to perform a higher-gradient optimization test scheme in the future, until the switching characteristics of the MOSFET switch are optimized.

[0044] Specifically, in step S5 of the embodiment provided by the present invention, optimization test processing is performed on the voltage driving unit and the resistance adjustment unit in sequence according to the optimization test schemes of each execution gradient. When performing the optimization test processing of each execution gradient, the optimization test characteristics of the optimization test processing are obtained, and it is determined whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

[0045] More specifically, in the optimization test scheme that first executes the gradient, it can be expanded to various specific schemes in the optimization test schemes that subsequently execute the gradient. By executing and analyzing the optimization test scheme that first executes the gradient, it is determined which specific scheme in the optimization test schemes in the subsequent gradient execution is suitable for continued execution, and this behavior is repeated until the driving voltage received by the MOSFET and its own resistance are adjusted to the limit state, thereby obtaining the maximum degree of optimization. The gradient progressive optimization method avoids the risk of failure due to exceeding the limit state caused by direct optimization.

[0046] The present invention provides a high-performance silicon carbide MOSFET switching characteristic optimization method, which has the following beneficial effects:

[0047] The present invention collects data of working parameters of MOSFET switches, obtains working monitoring data, collects parameter data of voltage drive units and resistance adjustment units, obtains voltage drive data and resistance adjustment data, analyzes the working state of the switch according to the collected data, obtains working state characteristics, performs gradient analysis based on the working state characteristics, formulates several optimization test schemes, sequentially executes the optimization test schemes of each gradient, obtains the optimization test characteristics, and determines whether to execute the optimization scheme of the next gradient according to the test characteristics. Through this method, the switching characteristics of silicon carbide MOSFET can be systematically and accurately optimized. Real-time data analysis and gradient optimization steps improve optimization efficiency, reduce trial and error costs, and enhance the performance stability and reliability of MOSFET.

[0048] Preferably, the step of collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch comprises:

[0049] S11: collecting data on the switch state of the MOSFET switch to obtain the switch state of the MOSFET at each moment;

[0050] S12: sequentially arranging the switch states of the MOSFET switches at various moments to obtain a switch state sequence;

[0051] S13: collecting data on the state switching of the MOSFET switch to obtain voltage and current parameters of the MOSFET switch at each switch state switching;

[0052] S14: adding the voltage and current parameters of the MMOSFET switch at each switching state switching to the corresponding position in the switching state sequence to obtain the working monitoring data of the MOSFET switch.

[0053] Specifically, data acquisition equipment (such as oscilloscopes, current probes, and voltage probes) is configured and connected to the MOSFET switching circuit. Through high-frequency sampling, data on the switching state of the MOSFET at each moment is collected, the on and off states of the MOSFET are recorded, and each switching operation is timestamped to ensure the synchronization of subsequent data processing.

[0054] More specifically, the collected switching state data are arranged in chronological order to form a complete switching state sequence. Each switching state change point (from on to off or from off to on) is marked in the sequence. During each switching state switching process, the voltage and current parameters of the MOSFET are collected in detail to ensure that the sampling frequency at the moment of state switching is high enough to capture the rapidly changing voltage and current parameters.

[0055] More specifically, the voltage and current parameters collected at each state switching are added to the corresponding position in the switch state sequence to generate a complete working monitoring data set including the switch state and the state switching voltage and current parameters.

[0056] It can be understood that through high-frequency sampling and timestamp recording, the switching state and instantaneous voltage and current changes of MOSFET can be monitored in real time. The precise switching state sequence and state switching parameters provide a comprehensive and detailed understanding of the MOSFET switching performance. Through the switching state sequence and voltage and current parameters, the various characteristics of MOSFET during dynamic switching can be analyzed, such as switching loss, conduction loss, and recovery characteristics. Based on the detailed monitoring data, targeted optimization adjustments can be made to improve the overall performance and reliability of the MOSFET switch.

[0057] Preferably, the step of collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit comprises:

[0058] S21: collecting data of unit working parameters of a voltage driving unit connected to the MOSFET switch in a circuit, and obtaining driving voltage parameters of the voltage driving unit at various moments;

[0059] S22: sequentially arranging the driving voltage parameters at each moment to obtain voltage driving data of the voltage driving unit;

[0060] S23: collecting data of unit working parameters of a resistance adjustment unit connected to the MOSFET switch in a circuit, and obtaining resistance adjustment parameters of the resistance adjustment unit at various moments;

[0061] S24: sequentially arranging the resistance adjustment parameters at each moment to obtain resistance adjustment data of the resistance adjustment unit.

[0062] Specifically, connect an appropriate voltage sensor or probe to the voltage driving unit to collect voltage, continuously collect the driving voltage parameters of the voltage driving unit at each moment, record the timestamp of each collection, arrange the collected driving voltage parameters in chronological order to form a continuous voltage driving data sequence, perform preliminary verification and filtering on the collected data, remove noise and abnormal data, and ensure the accuracy and reliability of the data.

[0063] More specifically, connect an appropriate resistance sensor or measuring device to the resistance adjustment unit to prepare for resistance parameter collection, continuously collect the resistance adjustment parameters of the resistance adjustment unit at various times, record the timestamp of each collection, arrange the collected resistance adjustment parameters in chronological order to form a continuous resistance adjustment data sequence, perform preliminary verification and filtering on the collected data, remove noise and abnormal data, and ensure the accuracy and reliability of the data.

[0064] It can be understood that by real-time acquisition of the driving voltage parameters of the voltage driving unit, its dynamic response under different working conditions can be monitored to ensure precise control of the driving signal. By analyzing the voltage driving data, the design of the driving circuit can be optimized, the driving efficiency of the MOSFET switch can be improved, and the switching loss can be reduced. By real-time acquisition of the resistance adjustment parameters of the resistance adjustment unit, the change of resistance under different working conditions can be monitored to ensure the accuracy of the resistance adjustment. Accurate resistance adjustment data helps to ensure the stability of the circuit and avoid circuit performance fluctuations caused by changes in resistance values. Through systematic data acquisition and analysis, data support can be provided for circuit design, targeted optimization and improvement can be carried out, and the overall circuit performance can be improved. Real-time data feedback helps to achieve closed-loop control, dynamically adjust the driving voltage and resistance parameters, and optimize the dynamic performance of the circuit.

[0065] Preferably, the step of analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain the working state characteristics of the MOSFET switch includes:

[0066] S31: analyzing the switching state switching frequency of the MOSFET switch according to the working monitoring data to obtain the state switching frequency characteristics of the MOSFET switch;

[0067] S32: Analyze and process the duration of the on state and the off state of the MOSFET switch according to the work monitoring data to obtain a state continuous distribution feature of the MOSFET switch;

[0068] S33: Analyzing the time relationship of the work monitoring data, the voltage driving data and the resistance adjustment data to obtain a time correlation distribution; wherein the time correlation distribution is used to describe the time relationship between the work monitoring data, the voltage driving data and the resistance adjustment data;

[0069] S34: performing circuit parameter analysis of the working monitoring data, the voltage driving data and the resistance adjustment data in an on-state and an off-state according to the time-correlated distribution, to obtain circuit parameter characteristics of an on-state and circuit parameter characteristics of an off-state of the MOSFET switch; wherein the circuit parameters include voltage parameters, current parameters and resistance parameters;

[0070] S35: analyzing the circuit parameter changes before and after the switch state is switched on the working monitoring data, the voltage driving data, and the resistance adjustment data according to the time-correlated distribution, to obtain circuit parameter change characteristics of the MOSFET switch before and after the switch state is switched;

[0071] S36: Combine and process the state switching frequency characteristics, state continuous distribution characteristics, on-state circuit parameter characteristics, off-state circuit parameter characteristics and circuit parameter change characteristics of the MOSFET switch to obtain the working state characteristics of the MOSFET switch.

[0072] Specifically, the switching time points of the MOSFET switch are extracted from the working monitoring data, the time intervals of these switching time points are calculated, the state switching frequency is obtained, the obtained frequency data is analyzed, and the switching state switching frequency characteristics are extracted, including the average switching frequency, maximum and minimum switching frequencies, etc.

[0073] More specifically, the on state and the off state in the work monitoring data are identified, the duration of each on state and the off state is calculated, and these duration data are analyzed to obtain the state duration distribution characteristics, including the average duration, distribution range, etc.

[0074] More specifically, the working monitoring data, voltage driving data and resistance adjustment data are aligned in time, and the correlation between these data on the time axis is analyzed to obtain the time correlation distribution, describe the time connection between these data, and identify the change pattern of voltage and resistance when the switch state is switched.

[0075] More specifically, according to the time-correlated distribution, the circuit parameters (voltage, current, resistance) in the on state and the off state are extracted respectively, and these parameter data are analyzed to obtain the on-state circuit parameter characteristics and the off-state circuit parameter characteristics.

[0076] More specifically, the circuit parameter data before and after the switch state switching is extracted from the time-related distribution, and the changes of these data are analyzed to obtain the circuit parameter change characteristics before and after the switch state switching. The state switching frequency characteristics, state continuous distribution characteristics, on-state circuit parameter characteristics, off-state circuit parameter characteristics and circuit parameter change characteristics are combined and processed, and these characteristics are comprehensively analyzed to obtain the overall working state characteristics of the MOSFET switch.

[0077] It is understandable that by analyzing the switching frequency and duration of the switch state, the working state of the MOSFET switch can be monitored in real time, and abnormal switching frequency or duration can be discovered in time, which is helpful for early fault warning. By extracting the circuit parameter characteristics of the on / off state, the performance of the MOSFET in different states can be accurately described. These parameter characteristics provide detailed data support for circuit design optimization. By analyzing the changes in circuit parameters before and after the switch state is switched, the behavior of the MOSFET in the dynamic switching process can be deeply understood. Based on these analysis results, more accurate driving and adjustment strategies can be formulated to improve the response speed and stability of the system.

[0078] Preferably, the step of performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics to obtain several optimization test schemes of execution gradients of the MOSFET switch comprises:

[0079] S41: Obtaining performance specification characteristics of the MOSFET switch;

[0080] S42: Analyze and process the performance specification characteristics by limiting circuit parameters according to the state switching frequency characteristics and the state continuous distribution characteristics, and obtain the limiting circuit parameter characteristics of the MOSFET switch corresponding to the current state switching frequency characteristics and the state continuous distribution characteristics; wherein the limiting circuit parameter characteristics include an on-state limiting characteristic, an off-state limiting characteristic, and a switching state limiting characteristic;

[0081] S43: performing difference analysis on the on-state circuit parameter feature, the off-state circuit parameter feature and the circuit parameter change feature according to the limit circuit parameter feature to obtain a theoretical difference feature;

[0082] S44: performing planning analysis on unit parameter adjustment of the voltage driving unit and the resistance adjustment unit connected to the MOSFET switch in a circuit based on the theoretical difference characteristics, and obtaining several unit parameter adjustment plans;

[0083] S45: performing gradient analysis processing according to several unit parameter adjustment plans to obtain several optimization test plans for executing the gradient.

[0084] Specifically, the performance specification characteristics of the MOSFET switch are collected and organized, including but not limited to the maximum rated current, voltage range, turn-on voltage threshold, on-resistance, etc. These performance specification characteristics are recorded in a data table as the basis for subsequent analysis.

[0085] More specifically, relevant data is extracted from the state switching frequency characteristics and state continuous distribution characteristics obtained from the previous analysis, and the limit circuit parameters under the current state switching frequency characteristics and state continuous distribution characteristics are calculated according to the performance specification characteristics. These parameters include: on-state limit characteristics: maximum on-current, minimum on-resistance, etc., off-state limit characteristics: maximum off-voltage, minimum leakage current, etc., switching state limit characteristics: maximum switching speed, minimum switching loss, etc.

[0086] More specifically, the limit circuit parameter characteristics are compared with the actual on-state circuit parameter characteristics, the off-state circuit parameter characteristics and the circuit parameter change characteristics, the theoretical difference characteristics are calculated, and the difference value between the actual parameter and the limit parameter is determined.

[0087] More specifically, the parameters of the voltage driving unit connected to the MOSFET switching circuit are analyzed, such as the driving voltage amplitude, pulse width, etc., and the parameters of the resistance adjustment unit are analyzed, such as the adjustment resistance value, adjustment speed, etc. Based on the theoretical difference characteristics, several unit parameter adjustment plans are formulated. These plans include adjustment strategies such as different driving voltages and different resistance values.

[0088] More specifically, different gradients are set for each adjustment plan, such as small adjustment, medium adjustment, large adjustment, etc. These gradient adjustment plans are simulated through simulation or actual testing, and their impact on the MOSFET switching performance is observed. The test results are analyzed to determine the advantages and disadvantages of each gradient adjustment plan and find the best execution gradient optimization plan.

[0089] It can be understood that by precisely adjusting the voltage driving unit and the resistance adjustment unit, the performance of the MOSFET switch can be optimized and its on- and off-characteristics can be improved. The optimized driving scheme can effectively reduce switching losses and improve the energy efficiency of the system. Through the extreme circuit parameter analysis, the overload and damage of the MOSFET switch under extreme conditions can be avoided, and the reliability of the system can be improved. Difference analysis and gradient optimization can ensure that the MOSFET switch maintains stable performance under various working conditions.

[0090] Preferably, the steps of performing gradient analysis processing according to several unit parameter adjustment plans to obtain several optimization test plans for executing gradients include:

[0091] S451: Performing test scheme conversion processing on various unit parameter adjustment schemes to obtain optimized test strategies corresponding to various unit parameter adjustment schemes, and combining various optimized test strategies to obtain the optimized test scheme for the final execution gradient;

[0092] S452: extracting the adjustment interaction parts based on the various unit parameter adjustment plans to obtain the adjustment interaction parts of the various unit parameter adjustment plans, and converting the adjustment interaction parts into test plans to obtain the optimization test strategy corresponding to the adjustment interaction parts, and using the optimization test strategy corresponding to the adjustment interaction parts as the optimization test plan for first executing the gradient;

[0093] S453: Performing an intermediate tendency analysis according to the optimization test scheme of the last executed gradient and the optimization test scheme of the first executed gradient, obtaining the test result pointing of each of the optimization test strategies in the optimization test scheme of the first executed gradient and the optimization test scheme of the last executed gradient; wherein the test result pointing is used to describe the pointing relationship between the optimization test characteristics of the optimization test scheme of the first executed gradient and each of the optimization test strategies in the optimization test scheme of the last executed gradient;

[0094] S454: Perform transition test strategy analysis on each of the optimization test strategies in the optimization test scheme of the first execution gradient and the optimization test scheme of the last execution echelon according to each of the test results to obtain each transition test strategy, and combine each of the transition test strategies to obtain the optimization test scheme of the intermediate execution gradient.

[0095] Specifically, the test scheme conversion process is performed on various unit parameter adjustment plans, and each adjustment plan is converted into a specific optimization test strategy. These strategies may involve different specific adjustment parameters such as different driving voltages, adjustment resistance values, switching frequencies, etc., and each optimization test strategy is combined to form multiple combination schemes. Each combination scheme represents a different execution gradient optimization test scheme.

[0096] More specifically, based on various unit parameter adjustment plans, the adjustment interaction parts are extracted. These interaction parts refer to the possible influences and interactions between different adjustment plans. The extracted adjustment interaction parts are converted into test plans to obtain the corresponding optimized test strategies for the adjustment interaction parts. The optimized test strategies for these interaction parts are used as the optimized test plans for executing the gradient first.

[0097] More specifically, an intermediate tendency analysis is performed based on the optimization test scheme that executes the gradient first and the optimization test scheme that executes the gradient last. By comparing and analyzing the various optimization test strategies in the schemes that execute the gradient first and last, their test result directions are determined. The test result directions describe the relationship between the optimization test characteristics of the optimization test scheme that executes the gradient first and the various optimization test strategies in the optimization test scheme that executes the gradient last. These relationships indicate which strategy performs and functions in different gradient tests.

[0098] More specifically, according to the directions of various test results, a transition test strategy analysis is performed on each optimization test scheme in the optimization test scheme that executes the gradient first and the optimization test scheme that executes the gradient last, and each transition test strategy is obtained. These strategies define the transition path and specific adjustment method from the first gradient execution to the last gradient execution.

[0099] More specifically, various transition test strategies are combined to obtain optimized test schemes for intermediate execution gradients, and these intermediate execution gradient schemes include methods such as gradually adjusting the driving voltage and adjusting the resistance value to achieve optimized transition.

[0100] It can be understood that the optimization test scheme of executing the gradient first, the gradient in the middle and the gradient at the end comprehensively covers the whole process from initial adjustment to final optimization, ensuring the performance improvement at each stage. The transition test strategy analysis and the intermediate tendency analysis ensure the smooth transition from the first to the last execution of the gradient, avoiding the instability caused by the jump adjustment. By refining and combining the unit parameter adjustment plan, the precise control of the MOSFET switch is achieved, and the response speed and stability of the switch are improved. The test results provide a clear optimization direction, making the adjustment plan and optimization strategy more targeted and efficient. The extraction of the interaction part and the conversion of the optimization test strategy ensure the coordination between different adjustment plans, reduce potential conflicts and incompatibilities, and the transition test strategy analysis ensures a smooth transition from initial adjustment to final optimization, improving the overall reliability of the system.

[0101] Preferably, the voltage driving unit and the resistance adjusting unit are sequentially optimized and tested according to the optimization test schemes of each execution gradient, and when performing the optimization test processing of each execution gradient, the optimization test characteristics of the optimization test processing are obtained, and it is determined whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch. The step includes:

[0102] S51: adjusting the parameter configuration of the voltage driving unit and the resistance adjusting unit according to the optimization test scheme of the gradient that is executed first, collecting circuit parameters of the on state, the off state and the state switching of the MOSFET switch after the parameter configuration adjustment, and using the collected circuit parameters as optimization test features;

[0103] S52: performing matching processing on the optimized test feature according to each of the test result directions, and obtaining a matching degree between the optimized test feature and each of the test result directions;

[0104] S53: selecting a transition test strategy of the optimization test scheme of the intermediate execution gradient according to the matching degree to adjust the parameter configuration of the voltage driving unit and the resistance adjustment unit, and collecting circuit parameters of the on state, the off state and the state switching of the MOSFET switch after the parameter configuration adjustment, and using the collected circuit parameters as optimization test features;

[0105] S54: performing matching processing on the optimization test features according to the test results, and determining whether to execute the optimization test scheme of the final execution gradient according to the matching processing results.

[0106] Specifically, according to the optimization test scheme of the gradient that is executed first, the voltage driving unit (such as setting different driving voltages) and the resistance adjustment unit (such as adjusting the resistance value) are adjusted, and circuit parameters of the adjusted MOSFET switch are collected in the on state, off state and state switching, respectively. These parameters include current, voltage, switching time, power consumption, etc. The collected circuit parameters are used as optimization test features, and these features are recorded and analyzed to evaluate the optimization effect of the current gradient.

[0107] More specifically, matching processing is performed based on the optimization test characteristics of the gradient that is first executed. The specific steps include: comparing these optimization test characteristics with the preset test results, calculating the degree of matching, and selecting an appropriate optimization test scheme for the intermediate execution gradient and its transition test strategy based on the degree of matching. The transition test strategy involves gradually adjusting the voltage and resistance to ensure a smooth transition.

[0108] More specifically, according to the selected optimization test scheme of the intermediate execution gradient, the parameter configuration of the corresponding voltage driving unit and the resistance adjustment unit is adjusted, and the circuit parameters of the adjusted MOSFET switch are collected again in the on state, the off state and the state switching. The new circuit parameters are used as optimization test features, and these features are recorded and analyzed to evaluate the optimization effect of the intermediate execution gradient. The new optimization test features are matched and their matching degree with the test results is calculated.

[0109] More specifically, based on the degree of match between the optimization test characteristics of the intermediate execution gradient and the test results, it is determined whether the optimization test scheme of the final execution gradient needs to be executed. If it is necessary to execute the optimization test scheme of the final execution gradient, the corresponding parameter configuration adjustment is performed, the circuit parameters of the MOSFET switch after the final adjustment are collected, and the optimization test characteristics are extracted. The final optimization test characteristics are evaluated to ensure that the switching characteristics of the MOSFET switch reach the optimal state.

[0110] It can be understood that the systematic and comprehensive nature of the optimization process is ensured through the phased optimization test of the first, middle and final execution gradients. The application of the transition test strategy makes the parameter adjustment process smooth and avoids the instability caused by large parameter changes. Through multiple parameter configuration adjustments and circuit parameter acquisition, fine control of the MOSFET switch is ensured, the response speed and performance stability of the switch are improved, and the matching processing of the test characteristics and the test results is optimized, ensuring that each step of the optimization adjustment has a clear direction and basis.

[0111] Reference Figure 2 As shown, in a second aspect, the present invention provides a high-performance silicon carbide MOSFET switching characteristic optimization device, which is used to implement a high-performance silicon carbide MOSFET switching characteristic optimization method described in any one of the first aspects, including:

[0112] A data monitoring module, used for collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch;

[0113] A data acquisition module, used for collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, and obtaining voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit;

[0114] A state analysis module, used for analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data, so as to obtain the working state characteristics of the MOSFET switch;

[0115] A scheme analysis module, used for performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics, and obtaining several optimized test schemes of execution gradients of the MOSFET switch;

[0116] A test execution module is used to perform optimization test processing on the voltage driving unit and the resistance adjustment unit in sequence according to the optimization test schemes of each execution gradient, obtain the optimization test characteristics of the optimization test processing when performing the optimization test processing of each execution gradient, and decide whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

[0117] In this embodiment, for the specific implementation of each module in the above-mentioned device embodiment, please refer to the above-mentioned method embodiment, which will not be described in detail here.

[0118] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing the switching characteristics of a high-performance silicon carbide MOSFET, characterized in that: include: Collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch; Collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit; Analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain working state characteristics of the MOSFET switch; Performing a gradient analysis process on the driving optimization scheme of the MOSFET switch according to the working state characteristics to obtain several optimized test schemes of the execution gradient of the MOSFET switch; The voltage driving unit and the resistance adjustment unit are optimized and tested in sequence according to the optimization test schemes of each execution gradient. When performing the optimization test processing of each execution gradient, the optimization test characteristics of the optimization test processing are obtained, and it is determined whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

2. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 1, characterized in that: The step of collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch includes: Collecting data on the switching state of the MOSFET switch to obtain the switching state of the MOSFET at each moment; The switch states of the MOSFET switches at various moments are sequentially arranged to obtain a switch state sequence; Collecting data on the state switching of the MOSFET switch to obtain voltage and current parameters of the MOSFET switch at each switch state switching; The voltage and current parameters of the MOSFET switch at each switching state are added to the corresponding position in the switching state sequence to obtain the working monitoring data of the MOSFET switch.

3. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 1, characterized in that: The step of collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit to obtain voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit comprises: Collecting data of unit working parameters of a voltage driving unit connected to the MOSFET switch in a circuit to obtain driving voltage parameters of the voltage driving unit at various times; The driving voltage parameters at each moment are sequentially arranged to obtain voltage driving data of the voltage driving unit; Performing data collection of unit working parameters on a resistance adjustment unit connected to the MOSFET switch in a circuit to obtain resistance adjustment parameters of the resistance adjustment unit at various moments; The resistance adjustment parameters at each moment are arranged in sequence to obtain resistance adjustment data of the resistance adjustment unit.

4. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 2, characterized in that: The step of analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data to obtain the working state characteristics of the MOSFET switch includes: Analyze the switching state switching frequency of the MOSFET switch according to the work monitoring data to obtain the state switching frequency characteristics of the MOSFET switch; According to the working monitoring data, the on state and the off state of the MOSFET switch are respectively subjected to duration analysis and processing to obtain a state continuous distribution feature of the MOSFET switch; Analyzing the time relationship of the work monitoring data, the voltage driving data and the resistance adjustment data to obtain a time correlation distribution; wherein the time correlation distribution is used to describe the time relationship between the work monitoring data, the voltage driving data and the resistance adjustment data; Performing circuit parameter analysis of the working monitoring data, the voltage driving data and the resistance adjustment data in the on-state and off-state according to the time-correlated distribution, to obtain on-state circuit parameter characteristics and off-state circuit parameter characteristics of the MOSFET switch; wherein the circuit parameters include voltage parameters, current parameters and resistance parameters; According to the time-correlated distribution, the circuit parameter change analysis of the working monitoring data, the voltage driving data and the resistance adjustment data before and after the switch state is switched is performed to obtain the circuit parameter change characteristics of the MOSFET switch before and after the switch state is switched; The state switching frequency characteristics, state continuous distribution characteristics, on-state circuit parameter characteristics, off-state circuit parameter characteristics and circuit parameter change characteristics of the MOSFET switch are combined and processed to obtain the working state characteristics of the MOSFET switch.

5. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 4, characterized in that: The step of performing a gradient analysis process on the driving optimization scheme of the MOSFET switch according to the working state characteristics to obtain several optimization test schemes for executing the gradient of the MOSFET switch comprises: Obtaining performance specification characteristics of the MOSFET switch; According to the state switching frequency characteristics and the state continuous distribution characteristics, the performance specification characteristics are subjected to limit circuit parameter analysis and processing, so as to obtain limit circuit parameter characteristics of the MOSFET switch corresponding to the current state switching frequency characteristics and the state continuous distribution characteristics; wherein the limit circuit parameter characteristics include an on-state limit characteristic, an off-state limit characteristic and a switching state limit characteristic; Performing difference analysis on the on-state circuit parameter feature, the off-state circuit parameter feature, and the circuit parameter change feature according to the limit circuit parameter feature to obtain a theoretical difference feature; Based on the theoretical difference characteristics, a planning analysis is performed on the unit parameter adjustment of the voltage driving unit and the resistance adjustment unit which are circuit-connected to the MOSFET switch, to obtain several unit parameter adjustment plans; Gradient analysis is performed according to several unit parameter adjustment plans to obtain several optimization test plans for executing the gradient.

6. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 5, characterized in that: The steps of performing gradient analysis according to several unit parameter adjustment plans to obtain several optimization test plans for executing gradients include: Performing test scheme conversion processing on various unit parameter adjustment schemes to obtain optimized test strategies corresponding to various unit parameter adjustment schemes, and combining various optimized test strategies to obtain the optimized test scheme for the final execution gradient; Extracting and processing the adjustment interaction parts based on the various unit parameter adjustment plans to obtain the adjustment interaction parts of the various unit parameter adjustment plans, and converting the adjustment interaction parts into test plans to obtain the optimization test strategy corresponding to the adjustment interaction parts, and using the optimization test strategy corresponding to the adjustment interaction parts as the optimization test plan for first executing the gradient; An intermediate tendency analysis is performed based on the optimization test scheme of the last executed gradient and the optimization test scheme of the first executed gradient, to obtain the test result orientation of each of the optimization test strategies in the optimization test scheme of the first executed gradient and the optimization test scheme of the last executed gradient; wherein the test result orientation is used to describe the orientation relationship between the optimization test characteristics of the optimization test scheme of the first executed gradient and each of the optimization test strategies in the optimization test scheme of the last executed gradient; According to each of the test results, a transition test strategy analysis is performed on each of the optimization test strategies in the optimization test scheme of the first execution gradient and the optimization test scheme of the last execution echelon to obtain each transition test strategy, and each of the transition test strategies is combined to obtain the optimization test scheme of the intermediate execution gradient.

7. The high performance silicon carbide MOSFET switching characteristics optimization method according to claim 6, characterized in that: The steps of sequentially performing optimization test processing on the voltage driving unit and the resistance adjusting unit according to the optimization test schemes of each execution gradient, obtaining optimization test characteristics of the optimization test processing when performing the optimization test processing of each execution gradient, and determining whether to perform the optimization test scheme of the next gradient according to the optimization test characteristics to optimize the switching characteristics of the MOSFET switch include: According to the optimization test scheme that first executes the gradient, parameter configurations of the voltage driving unit and the resistance adjustment unit are adjusted, and circuit parameters of the MOSFET switch after the parameter configuration adjustment are collected in the on state, the off state, and the state switching, and the collected circuit parameters are used together as optimization test features; Matching the optimized test feature according to each of the test result directions to obtain a matching degree between the optimized test feature and each of the test result directions; According to the matching degree, a transition test strategy of the optimization test scheme of the intermediate execution gradient is selected to adjust the parameter configuration of the voltage driving unit and the resistance adjustment unit, and the circuit parameters of the on state, the off state and the state switching of the MOSFET switch after the parameter configuration adjustment are collected, and the collected circuit parameters are used as optimization test features; A matching process is performed on the optimized test feature according to the test result, and it is determined whether to execute the optimization test scheme of the final execution gradient according to the result of the matching process.

8. A high performance silicon carbide MOSFET switching characteristics optimization device, characterized in that: A method for optimizing the switching characteristics of a high-performance silicon carbide MOSFET according to any one of claims 1 to 7, comprising: A data monitoring module, used for collecting data of switch operating parameters of the MOSFET switch to obtain operating monitoring data of the MOSFET switch; A data acquisition module, used for collecting data of unit working parameters of a voltage driving unit and a resistance adjusting unit connected to the MOSFET switch in a circuit, and obtaining voltage driving data of the voltage driving unit and resistance adjusting data of the resistance adjusting unit; A state analysis module, used for analyzing and processing the switch working state of the MOSFET switch according to the working monitoring data, the voltage driving data and the resistance adjustment data, so as to obtain the working state characteristics of the MOSFET switch; A scheme analysis module, used for performing a gradient analysis process of a driving optimization scheme on the MOSFET switch according to the working state characteristics, and obtaining several optimized test schemes of execution gradients of the MOSFET switch; A test execution module is used to perform optimization test processing on the voltage driving unit and the resistance adjustment unit in sequence according to the optimization test schemes of each execution gradient, obtain the optimization test characteristics of the optimization test processing when performing the optimization test processing of each execution gradient, and decide whether to execute the optimization test scheme of the next gradient according to the optimization test characteristics, so as to optimize the switching characteristics of the MOSFET switch.

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