Fault detection method and system for gallium nitride power device

Abstract

The invention provides a fault detection method and system for a gallium nitride power device, and relates to the technical field of fault detection, and the method comprises the steps: determining the safe operation parameters of the gallium nitride power device under a preset working condition according to the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device; extracting state response characteristics of the gallium nitride power device under a preset working condition; constructing a fault evidence matrix of the gallium nitride power device under a preset working condition based on the safe operation parameters and the state response characteristics; and performing fault state evaluation on the gallium nitride power device according to the fault evidence matrix to obtain a fault state factor of the gallium nitride power device, and further determining the fault probability of grid degradation of the gallium nitride power device based on the fault state factor. According to the scheme, the operation safety and the state response of the gallium nitride power device under the high-frequency switching working condition can be comprehensively analyzed, so that the evaluation accuracy of the device fault state is improved.

Description

Technical Field

[0001] The present application relates to the technical field of fault detection, and more specifically, to a fault detection method and system for gallium nitride power devices. Background Art

[0002] Gallium nitride power devices, due to their high electron mobility and wide bandgap characteristics, are widely used in high-frequency, high-power electronic systems. However, these devices are prone to transient voltage spikes and high-frequency loss accumulation under high-frequency switching conditions, leading to faults such as gate degradation and on-resistance variation, thus affecting system reliability and lifespan. Therefore, fault detection of gallium nitride power devices has important engineering significance and application value for ensuring the stable operation of power electronic systems, improving device reliability, and extending device lifespan.

[0003] Existing technologies often rely on single electrical parameters or simple thermal analysis for fault detection of GaN power devices, typically monitoring only a single indicator such as drain voltage, current, or junction temperature. This ignores the device's dynamic response characteristics and multi-dimensional coupling effects under high-frequency switching conditions. This leads to delayed or misidentified identification of potential faults such as gate degradation, and fails to fully reflect the device's operational safety under complex operating conditions. Furthermore, the lack of comprehensive quantitative analysis of key indicators such as transient voltage fluctuations, high-frequency losses, and on-resistance changes prevents accurate quantification of fault status assessments, hindering reliability prediction and preventive maintenance. Therefore, the industry faces the challenge of comprehensively analyzing the operational safety and status response of GaN power devices under high-frequency switching conditions to improve the accuracy of device fault status assessments. Summary of the Invention

[0004] The present application provides a fault detection method and system for a gallium nitride power device, which can perform a comprehensive analysis of the operating safety and state response of the gallium nitride power device under high-frequency switching conditions, thereby improving the accuracy of the assessment of the device fault state.

[0005] In a first aspect, the present application provides a fault detection method for a gallium nitride power device, comprising the following steps: determining safe operating parameters of the GaN power device under preset operating conditions based on rated electrical parameters, chip structure parameters, and packaging characteristics of the GaN power device, wherein the preset operating conditions include a high-frequency switching state, and the safe operating parameters include a transient voltage threshold and a high-frequency loss threshold; Extracting state response characteristics of the gallium nitride power device under the preset operating conditions, wherein the state response characteristics include switching transient voltage fluctuation, drain current fluctuation, and on-resistance change; constructing a failure evidence matrix of the gallium nitride power device under the preset working condition based on the safe operation parameter and the state response feature; performing failure state evaluation on the gallium nitride power device according to the failure evidence matrix, obtaining a failure state factor of the gallium nitride power device, and then determining a failure probability of the gallium nitride power device from gate degradation based on the failure state factor.

[0006] In some embodiments, the safe operation parameter of the gallium nitride power device under the preset working condition is determined according to the rated electrical parameter, the chip structure parameter and the packaging characteristic of the gallium nitride power device, specifically comprising: obtaining the rated electrical parameter, the chip structure parameter and the packaging characteristic of the gallium nitride power device, wherein the rated electrical parameter includes rated voltage and rated current, the chip structure parameter includes gate length and epitaxial layer thickness, and the packaging characteristic includes parasitic inductance and heat dissipation coefficient; substituting the rated electrical parameter, the chip structure parameter and the packaging characteristic into a device simulation model, and then determining a transient voltage threshold and a high-frequency loss threshold under the preset working condition; integrating the transient voltage threshold and the high-frequency loss threshold to obtain the safe operation parameter of the gallium nitride power device under the preset working condition.

[0007] In some embodiments, the transient voltage threshold refers to the maximum voltage spike critical value that the gallium nitride power device can withstand during the switching process.

[0008] In some embodiments, the high-frequency loss threshold refers to the maximum energy loss critical value allowed by the gallium nitride power device during continuous high-frequency operation.

[0009] In some embodiments, the state response feature of the gallium nitride power device under the preset working condition is extracted specifically by: building a high-frequency switching state simulation test environment, connecting the gallium nitride power device to the environment and making it work under the preset high-frequency switching working condition; collecting voltage signals and drain current signals of the gallium nitride power device during the switching process in real time through voltage sensors and current sensors, and collecting resistance signals of the gallium nitride power device when it is turned on through a resistance test module; extracting voltage fluctuation data of the switching transient stage from the collected voltage signals, calculating the switching transient voltage fluctuation amount, extracting current fluctuation data from the drain current signals, calculating the drain current fluctuation amount, and extracting the change data of the on-resistance from the resistance signals, calculating the on-resistance change amount; the switching transient voltage fluctuation amount, the drain current fluctuation amount and the on-resistance change amount as the state response feature of the gallium nitride power device under the preset working condition.

[0010] In some embodiments, constructing the failure evidence matrix of the gallium nitride power device under the preset working condition based on the safe operation parameters and the state response characteristics specifically includes: Taking parameters in the safe operation parameters and the state response characteristics as fuzzy variables; Defining three fuzzy subsets of normal, slight deviation and serious deviation for each fuzzy variable, and setting membership functions of the fuzzy subsets respectively; Calculating the membership degrees of each fuzzy variable to the fuzzy subsets to which it belongs according to the membership functions; Establishing a fuzzy reasoning rule base, which contains the corresponding relationship between the fuzzy state combination of the fuzzy variables and the failure evidence strength; Performing fuzzy reasoning according to the membership degrees of the fuzzy variables and the fuzzy reasoning rule base to obtain the failure evidence strength corresponding to each fuzzy variable; Arranging the failure evidence strength according to the row-column correspondence relationship with the fuzzy variables as columns and the evidence categories related to the gate degradation failure as rows to obtain the failure evidence matrix of the gallium nitride power device.

[0011] In some embodiments, the failure state evaluation of the gallium nitride power device according to the failure evidence matrix specifically includes: Presetting key indicators for failure state evaluation; Standardizing the elements in the failure evidence matrix to make the evidence strength values of different types in the same numerical range; According to the importance of each key indicator in the gate degradation failure evaluation, giving the corresponding weight; Classifying the standardized matrix elements according to the key indicators, respectively calculating the weighted sum of each type of indicator to obtain the evaluation value of each key indicator; Comprehensively operating the evaluation values of each key indicator to obtain a comprehensive numerical value that can reflect the overall failure state of the gallium nitride power device, and taking the comprehensive numerical value as the failure state factor.

[0012] In some embodiments, the key indicators include voltage stability indicators, current consistency indicators and resistance change rate indicators.

[0013] In some embodiments, determining the failure probability of the gallium nitride power device occurring gate degradation based on the failure state factor specifically includes: Collecting historical data of the gallium nitride power device under different failure states; statistical analysis is performed on the historical data to establish a corresponding relation model between the fault state factor and the gate degradation failure probability, and different intervals of the fault state factor and corresponding gate degradation failure probability ranges are divided; The current obtained fault state factor is substituted into the corresponding relation model to determine the interval in which the fault state factor is located. According to the failure probability range corresponding to the interval and the probability distribution characteristics in the interval, the failure probability of the gallium nitride power device occurring gate degradation is calculated.

[0014] In a second aspect, the application provides a gallium nitride power device fault detection system, comprising: The acquisition module is configured to determine the safe operation parameters of the gallium nitride power device under the preset working condition according to the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device. The feature processing module is configured to extract the state response features of the gallium nitride power device under the preset working condition. The feature processing module is further configured to construct a fault evidence matrix of the gallium nitride power device under the preset working condition based on the safe operation parameters and the state response features. The execution module is configured to perform fault state evaluation on the gallium nitride power device according to the fault evidence matrix to obtain a fault state factor of the gallium nitride power device, and further determine the failure probability of the gallium nitride power device occurring gate degradation based on the fault state factor.

[0015] The technical scheme provided by the embodiments of the application has the following beneficial effects: First, the safe operation parameters of the gallium nitride power device under the preset working condition are determined according to the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device, wherein the preset working condition includes a high-frequency switching state, and the safe operation parameters include a transient voltage threshold and a high-frequency loss threshold. The state response features of the gallium nitride power device under the preset working condition are extracted, including the switching transient voltage fluctuation, the drain current fluctuation and the on-resistance change. The fault evidence matrix of the gallium nitride power device under the preset working condition is constructed based on the safe operation parameters and the state response features. The fault state of the gallium nitride power device is evaluated according to the fault evidence matrix to obtain a fault state factor of the gallium nitride power device, and the failure probability of the gallium nitride power device occurring gate degradation is determined based on the fault state factor.

[0016] It can be seen that, according to the fault evidence matrix, the fault state of the gallium nitride power device is evaluated, the fault state factor of the gallium nitride power device is obtained, and then the fault probability of the gate degradation of the gallium nitride power device is determined based on the fault state factor. First, by obtaining the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device, and combining the simulation model to calculate the transient voltage threshold and high-frequency loss threshold, the benchmark parameters for the safe operation of the device under high-frequency switching state are established, so that the subsequent evaluation of the actual operating state has a clear quantitative standard, and the warning can be given before the irreversible damage of the device occurs. Secondly, by building a high-frequency switching state simulation test environment and real-time collecting switching transient voltage, drain current and on-resistance and other state response characteristics, the actual behavior of the device under dynamic working conditions is converted into a quantifiable data set, so that the fault detection is no longer dependent on a single indicator, thereby fully reflecting the multi-dimensional coupling effect and transient response characteristics of the device under complex working conditions. Thirdly, based on the fault evidence matrix constructed based on the safe operation parameters and state response characteristics, the mapping of fuzzy variables and membership functions is combined with the fuzzy reasoning rule base to comprehensively analyze each variable, realize the quantitative expression of the potential gate degradation fault evidence strength, and convert the qualitative judgment of the fault state into a quantifiable matrix form, providing a reliable foundation for accurate evaluation. Then, based on the fault evidence matrix, key indicators are introduced for weighting and comprehensive operation, and multi-dimensional information such as transient voltage fluctuation, current consistency and on-resistance change is fused to generate a fault state factor, so that the overall fault state can be accurately and comprehensively quantitatively evaluated, and the key control of the safety and operating state of the device is realized. Finally, by establishing the mapping relationship between the fault state factor and the gate degradation probability, the direct derivation from the operating data to the fault probability is realized, so that the device reliability prediction and maintenance decision are more scientific and operable. In summary, the scheme of the present application realizes the all-around fault monitoring and reliability evaluation of the gallium nitride power device under high-frequency switching working condition by establishing safe operation parameters, collecting state response characteristics, constructing fault evidence matrix and calculating fault state factor, thereby improving the accuracy of fault warning and the safety of device operation. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only the embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Figure 1 is a flow chart of the fault detection method of the gallium nitride power device provided by the present application; Figure 2is an example flow chart for determining a state response characteristic according to the present application; Figure 3 is an example flow chart for determining a failure state factor according to the present application; Figure 4 is a module structure diagram of a failure detection system of a gallium nitride power device according to the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0020] The embodiments of the present application provide a failure detection method and system of a gallium nitride power device, the core of which is to determine the safe operation parameters of the gallium nitride power device under a preset working condition according to the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device; to extract the state response characteristic of the gallium nitride power device under the preset working condition; to construct a failure evidence matrix of the gallium nitride power device under the preset working condition based on the safe operation parameters and the state response characteristic; to evaluate the failure state of the gallium nitride power device according to the failure evidence matrix, to obtain the failure state factor of the gallium nitride power device, and then to determine the failure probability of the gate degradation of the gallium nitride power device based on the failure state factor. The present application can realize comprehensive analysis on the running safety and state response of the gallium nitride power device under high-frequency switching working condition, thereby improving the evaluation accuracy of the failure state of the device.

[0021] Embodiment one, in order to better understand the above technical solutions, the above technical solutions will be described in detail below in combination with the drawings in the specification and specific embodiments, referring to Figure 1 The figure is an example flow chart of a failure detection method of a gallium nitride power device according to the present embodiment, the failure detection method of the gallium nitride power device comprises the following steps: In step S1, the safe operation parameters of the gallium nitride power device under a preset working condition are determined according to the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device, wherein the preset working condition includes a high-frequency switching state, and the safe operation parameters include a transient voltage threshold and a high-frequency loss threshold.

[0022] It should be noted that the transient voltage threshold in the present application refers to the maximum voltage peak critical value that the gallium nitride power device can withstand during switching process; the high-frequency loss threshold refers to the maximum energy loss critical value that the gallium nitride power device can allow when continuously working at high frequency.

[0023] In some embodiments, determining the safe operation parameters of the gallium nitride power device under the preset working condition according to the rated electrical parameters, the chip structure parameters and the packaging characteristics of the gallium nitride power device specifically comprises: obtaining the rated electrical parameters, the chip structure parameters and the packaging characteristics of the gallium nitride power device, wherein the rated electrical parameters include rated voltage and rated current, the chip structure parameters include gate length and epitaxial layer thickness, and the packaging characteristics include parasitic inductance and heat dissipation coefficient; substituting the rated electrical parameters, the chip structure parameters and the packaging characteristics into a device simulation model to determine a transient voltage threshold and a high-frequency loss threshold under the preset working condition; integrating the transient voltage threshold and the high-frequency loss threshold to obtain the safe operation parameters of the gallium nitride power device under the preset working condition.

[0024] It should be noted that the parasitic inductance in the present application refers to the stray inductance inevitably generated by the conductor geometric structure in the device packaging and circuit interconnection; the heat dissipation coefficient refers to the ability parameter of the device to transfer heat to the external environment under unit temperature difference; the transient voltage threshold refers to the maximum voltage peak critical value that the gallium nitride power device can reliably withstand in the switching transient process; and the high-frequency loss threshold refers to the maximum energy loss critical value allowed by the gallium nitride power device when continuously working at high frequency.

[0025] In a specific implementation, first, the rated voltage / current, gate length, and epitaxial layer thickness are obtained by querying product data books and device structure materials, and the parasitic inductance of the package and loop is measured by an impedance analyzer, and the heat dissipation coefficient and equivalent thermal resistance are extracted from the transient thermal resistance curve provided by the manufacturer. It needs to be further explained that the gate length refers to the geometric size of the gate in the channel direction, which determines the channel on-resistance and switching speed in this application. The epitaxial layer thickness refers to the thickness of the semiconductor functional layer grown epitaxially on the substrate, which determines the breakdown voltage and current spreading capability of the device in this application. Then, a device model is constructed by a semiconductor device simulation tool (such as Sentaurus TCAD), and the safety threshold is calculated by substituting the basic parameters. First, in the Sentaurus TCAD software, a three-dimensional physical model is constructed based on the chip structure parameters obtained in the first step, i.e., taking the substrate as the base, growing a GaN / AlGaN heterojunction layer according to the epitaxial layer thickness, and then drawing the gate electrode according to the gate length. At the same time, the parasitic inductance of the model is added, i.e., the parasitic inductance value obtained by testing is equivalent to an inductance element connected in series to the device source and drain pins, which meets the known principle of "parasitic parameter equivalence" in circuit simulation. Further, the heat dissipation coefficient is converted into the thermal boundary condition of the model, i.e., the thermal conductivity parameter is set on the surface of the package shell, which is derived from the heat dissipation coefficient, thereby ensuring that the device temperature change in the simulation conforms to the actual heat dissipation situation. Then, the preset working condition parameters are set, i.e., in the excitation source module of the simulation software, the input voltage is set to the rated voltage of the device, the switching frequency is set to a preset high frequency value, such as 1 MHz, which covers the high frequency range of the actual application scenario, and the duty cycle is set to 50%, which is a typical value of the conventional high-frequency switching working condition. A high-frequency switching signal is generated by a pulse generator to control the gate voltage, for example, the gate on-voltage is 2V and the gate off-voltage is -5V, which meets the gate drive characteristics of GaN devices. Further, the simulation calculation is performed. In calculating the transient voltage threshold, the switching transient simulation is run, and the drain-source voltage waveform during the device off process is recorded. The drain-source voltage waveform is the voltage spike caused by the parasitic inductance during off. The maximum voltage value in the waveform is extracted and taken as the transient voltage threshold, which corresponds to the maximum voltage spike that the device can tolerate during switching. Exceeding it may cause breakdown. In calculating the high-frequency loss threshold, the steady-state high-frequency simulation is run for 1 minute, which aims to ensure that multiple switching cycles are covered to achieve thermal steady state. Then, the energy integration function of the software is used to calculate the on-state loss and switching loss, respectively. The on-state loss is the integral product of the drain current square and the on-resistance during conduction, and the switching loss is the energy integral of the overlapping area of the drain voltage and the drain current during switching. The total high-frequency loss is obtained by summing up the on-state loss and the switching loss. At the same time, the chip junction temperature is monitored in real time through the simulation. When the junction temperature reaches the maximum allowed junction temperature marked in the device Datasheet, the corresponding total high-frequency loss value is taken as the high-frequency loss threshold.Finally, the transient voltage threshold and the high-frequency loss threshold are combined, and the resulting parameter set is used as the safe operating parameters of the gallium nitride power device under preset operating conditions.

[0026] In step S2, the state response characteristics of the gallium nitride power device under the preset working condition are extracted, where the state response characteristics include switching transient voltage fluctuation, drain current fluctuation, and on-resistance change.

[0027] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining the state response characteristics in an embodiment of the present application. In this embodiment, extracting the state response characteristics of the gallium nitride power device under the preset working conditions specifically includes: In step S21, a high-frequency switching state simulation test environment is built, and the gallium nitride power device is connected to the environment and operates under a preset high-frequency switching condition; In step S22, the voltage signal and drain current signal of the GaN power device during the switching process are collected in real time by the voltage sensor and the current sensor, and the resistance signal of the GaN power device when it is turned on is collected by the resistance test module; In step S23, the voltage fluctuation data of the switching transient stage is extracted from the collected voltage signal to calculate the switching transient voltage fluctuation amount, the current fluctuation data is extracted from the drain current signal to calculate the drain current fluctuation amount, and the on-resistance change data is extracted from the resistance signal to calculate the on-resistance change amount; In step S24, the switching transient voltage fluctuation, the drain current fluctuation, and the on-resistance change are used as state response characteristics of the gallium nitride power device under the preset working condition.

[0028] It should be noted that the state response characteristics in this application are a set of characteristics that reflect the dynamic change characteristics of voltage, current and resistance of the GaN power device under preset operating conditions; the switching transient voltage fluctuation refers to the instantaneous deviation amplitude of the actual voltage waveform of the GaN power device relative to the steady-state voltage during the switching process; the drain current fluctuation refers to the instantaneous change amplitude of the drain current relative to the steady-state current during the switching process of the GaN power device; and the on-resistance change refers to the deviation amplitude of the actual resistance of the GaN power device in the on state relative to the rated on-resistance.

[0029] In a specific implementation, first, in the process of building a high-frequency switching state simulation test environment, a programmable DC power supply can be used as a drain power supply, the output voltage is set according to a preset working condition, a high-frequency gate driver is selected to generate a switching control signal, the switching frequency is set through the frequency adjustment knob of the driver or the upper computer software, for example, the preset working condition is 1 MHz, the duty cycle is set to 50%, and the amplitude of the output voltage of the driver is adjusted to the range allowed by the device. An adjustable resistance load, such as Chroma63200, is used as a load, the load resistance value is set according to the rated current of the device, the circuit is connected, the gate pin of the gallium nitride power device (for example, TO-247 package) is connected to the output end of the gate driver through a coaxial cable, the drain pin is connected to the positive pole of the DC power supply in series with a current sampling element (such as a shunt), the source pin is directly grounded, the voltage sampling probe is connected in parallel between the drain and the source, and the load resistance is connected in parallel between the drain and the source. This wiring mode is a standard topology for high-frequency switching test of the power device, which can ensure that the device works in the preset high-frequency switching state, and the signals at each test point can be effectively collected. Second, the voltage sensor and the current sensor are used to collect the voltage signal and the drain current signal of the gallium nitride power device during the switching process, and the resistance test module is used to collect the resistance signal of the gallium nitride power device when it is turned on. The resistance test module specifically includes a voltage probe for collecting the voltage signal when the device is turned on, a current sampling element such as a shunt or a current sensor for collecting the current signal, and a signal processing unit (such as an integrated operational amplifier and a data conversion circuit) for calculating the on-resistance by the voltage-current method. Then, the difference between the voltage peak value at the switching moment (within 1 μs after turning on / off) and the steady-state voltage is obtained from the voltage signal, and the switching transient voltage fluctuation is obtained. The difference between the transient current peak value and the steady-state current is obtained from the current signal, and the drain current fluctuation is obtained. The on-resistance change amount is obtained by subtracting the initial on-resistance of the device from the current on-resistance measured by the power analyzer, and the initial on-resistance is the factory test value. Finally, all the switching transient voltage fluctuation, the drain current fluctuation and the on-resistance change amount are combined to form a set as the state response characteristics of the gallium nitride power device under the preset working condition.

[0030] In step S3, a fault evidence matrix of the gallium nitride power device under the preset working condition is constructed based on the safe operation parameters and the state response characteristics.

[0031] In some embodiments, constructing the fault evidence matrix of the gallium nitride power device under the preset working condition based on the safe operation parameters and the state response characteristics specifically includes: The parameters in the safe operation parameters and the state response characteristics are taken as fuzzy variables. three fuzzy subsets of normal, slight deviation and serious deviation are defined for each fuzzy variable, and membership functions of the fuzzy subsets are set respectively; membership degrees of each fuzzy variable to the fuzzy subset to which it belongs are calculated according to the membership functions; a fuzzy reasoning rule base is established, and the rule base contains corresponding relationships between fuzzy state combinations of fuzzy variables and fault evidence strengths; fuzzy reasoning is performed according to the membership degrees of each fuzzy variable and the fuzzy reasoning rule base, and the fault evidence strengths corresponding to each fuzzy variable are obtained; a fault evidence matrix of the gallium nitride power device is obtained by arranging the fault evidence strengths according to the corresponding relationship between rows and columns, with fuzzy variables as columns and evidence categories related to gate degeneration faults as rows.

[0032] It should be noted that the fault evidence strength in the present application is an index for measuring the contribution of the abnormal degree of each state response characteristic of the gallium nitride power device to fault determination; the fault evidence matrix refers to a characteristic matrix for comprehensively evaluating the fault state of the device, which is organized according to categories and variables of the fault evidence strengths of each state response characteristic of the gallium nitride power device.

[0033] In a specific implementation, first, five parameters, i.e., the safety operation parameters (i.e., the transient voltage threshold, the high-frequency loss threshold) and the state response characteristics (i.e., the switching transient voltage fluctuation, the drain current fluctuation, and the on-resistance change) are taken as fuzzy variables to ensure the key dimensions of the device safety benchmark and the actual operation response; second, three fuzzy subsets, i.e., normal, slight deviation, and serious deviation, are defined for each fuzzy variable, for example, for the switching transient voltage fluctuation, the normal corresponds to a fluctuation of ≤80% of the transient voltage threshold, the slight deviation corresponds to 80%-120%, and the serious deviation corresponds to >120%, and a triangular membership function is set for each subset, and the mapping relationship between the variable value and the membership is determined, which can be obtained according to the correlation analysis between the historical data; third, the actual measurement value of each fuzzy variable is substituted into the corresponding membership function, for example, if the switching transient voltage fluctuation is 90% of the transient voltage threshold, the triangular membership function of the slight deviation corresponding subset is substituted, and the membership of the variable to the slight deviation subset is calculated, and the memberships to other subsets are obtained in the same way, and then all the memberships are combined into a vector as the membership vector of the variable, and the membership vector of each variable can be obtained in the above manner; then, in the process of establishing the fuzzy reasoning rule base, the fuzzy rules can be established based on the device failure mechanism, for example, the gate degradation will cause the on-resistance to increase and the voltage fluctuation to intensify, for example, "if the on-resistance change is'serious deviation' and the switching transient voltage fluctuation is'slight deviation', the gate degradation failure evidence strength is 0.8", and the rule base needs to cover all typical combinations of the fuzzy states of the variables; further, according to the membership vectors of the variables and the rule base, the maximum-minimum composition method is used for operation, for example, the membership of a certain variable to "serious deviation" is 0.9 and to "slight deviation" is 0.1, and after matching the rules, the maximum membership is taken to participate in the reasoning, and finally the failure evidence strength corresponding to each variable is output, for example, the on-resistance change corresponds to the evidence strength of 0.85; finally, taking the five fuzzy variables as columns and taking the "electric parameter anomaly", "performance attenuation", and "potential failure" three types of evidence categories of the gate degradation failure as rows, the failure evidence strengths corresponding to the variables are filled in according to the row and column positions to form a 3-row and 5-column matrix, i.e., the failure evidence matrix.

[0034] It should be noted that the present application scheme uses the safe operating parameters and state response characteristics of gallium nitride power devices as fuzzy variables, introduces fuzzy subsets and membership functions, and combines the fuzzy reasoning rule base to construct a fault evidence matrix to achieve quantitative fusion of the multi-dimensional abnormal characteristics of the device. Compared with the existing methods based on a single threshold or simple superposition, this scheme can effectively handle the nonlinearity and uncertainty of high-frequency switching transient fluctuations, current inconsistency and on-resistance changes, avoid missed judgments or misjudgments, and improve the accuracy of fault judgment; by presenting the contribution of each state response characteristic to gate degradation in a matrix form, it can accurately identify potential failure modes, achieve early warning and reliability assessment, and thus improve the operating safety and service life of gallium nitride power devices under complex high-frequency working conditions.

[0035] In step S4, a fault state assessment is performed on the GaN power device according to the fault evidence matrix to obtain a fault state factor of the GaN power device, and then a fault probability of gate degradation of the GaN power device is determined based on the fault state factor.

[0036] In some embodiments, reference Figure 3 As shown in FIG. 1 , this figure is an exemplary flow chart for determining a fault state factor in an embodiment of the present application. In this embodiment, the fault state of the gallium nitride power device is evaluated according to the fault evidence matrix to obtain the fault state factor of the gallium nitride power device, which specifically includes: In step S41, key indicators for fault status assessment are preset; In step S42, the elements in the fault evidence matrix are normalized so that the strength values ​​of different types of evidence are in the same numerical range; In step S43, a corresponding weight is assigned to each key indicator according to its importance in the gate degradation fault assessment; In step S44, the standardized matrix elements are classified according to key indicators, and the weighted sum of each type of indicator is calculated to obtain the evaluation value of each key indicator; In step S45, the evaluation values ​​of the key indicators are comprehensively calculated to obtain a comprehensive value that can reflect the overall fault state of the gallium nitride power device, and the comprehensive value is used as the fault state factor.

[0037] It should be noted that the key indicators in this application include voltage stability index, current consistency index and resistance change rate index; the voltage stability index is a measure of the degree to which the actual switching transient voltage fluctuation of the gallium nitride power device deviates from the transient voltage threshold in the safe operating parameters under high-frequency switching conditions; the current consistency index is a measure of the degree to which the actual drain current fluctuation of the gallium nitride power device deviates from the steady-state current reference corresponding to the safe operating parameters under high-frequency switching conditions; the resistance change rate index is a measure of the deviation ratio between the actual on-resistance change and the initial on-resistance of the gallium nitride power device under high-frequency switching conditions; the fault state factor is a comprehensive indicator for measuring the overall fault degree and health status of the gallium nitride power device.

[0038] In specific implementation, three key evaluation indicators, namely voltage stability, current consistency, and resistance change rate, can be pre-set based on the core influencing factors of gate degradation failures. Voltage stability corresponds to the evidence element related to transient voltage in the matrix, current consistency corresponds to the evidence element related to drain current, and resistance change rate corresponds to the evidence element related to on-resistance, ensuring that the indicators accurately correlate with fault characteristics. Secondly, when standardizing the elements in the fault evidence matrix, a linear normalization method can be used to uniformly map all elements in the fault evidence matrix to the interval [0, 1]. For example, if the original value of an element is 0.6, and the maximum value of similar elements in the matrix is ​​1.0 and the minimum value is 0, the normalized value is 0.6, eliminating evaluation bias caused by differences in dimension or numerical range between different evidence types. Thirdly, when assigning weights, expert experience can be used to determine weights based on the gate degradation failure mechanism. For example, on-resistance changes are more sensitive to gate degradation, so for example, the resistance change rate weight can be set to 0. 4. The voltage stability is set to 0.35, the current consistency is set to 0.25, and the sum of the weights of the three indicators is 1, so as to ensure that the weight distribution is consistent with the degree of fault impact; then, the standardized matrix elements can be classified according to the preset key indicators, and all elements under each indicator category are multiplied by the weight of the corresponding indicator and summed. For example, there are two standardized elements 0.8 and 0.7 under the resistance change rate indicator. After multiplying them by the weight 0.4, the sum is (0.8+0.7)×0.4=0.6, which is the evaluation value of the resistance change rate. The evaluation values ​​of voltage stability and current consistency can be calculated similarly. Finally, the evaluation values ​​of the three key indicators can be directly added together. Since their weights have been normalized, the added value can be used as the comprehensive value. For example, the evaluation value of voltage stability is 0.28, the evaluation value of current consistency is 0.15, and the evaluation value of resistance change rate is 0.6. The sum of the three is 1.03. It should be noted that the comprehensive value can be subsequently truncated to the [0, 1] interval. The comprehensive value is the fault status factor, which can intuitively reflect the overall fault degree of the device.

[0039] It should be noted that the scheme of the present application forms a fault state factor reflecting the overall fault state of the gallium nitride power device by standardizing the fault evidence matrix, weighting and classifying according to the key indicators, and performing comprehensive operation. Compared with the existing method which only relies on a single indicator or threshold, the comprehensive influence of different types of fault information on the performance of the device can be quantified, the problems of multi-dimensional feature heterogeneity and unclear weight distribution are solved, the method realizes high-precision and comparable overall fault evaluation, the potential failure such as gate degradation can be identified in advance, and thus the accuracy of device reliability evaluation and the operation safety are improved.

[0040] In some embodiments, determining the failure probability of the gallium nitride power device occurring gate degradation based on the fault state factor specifically comprises: collecting historical data of the gallium nitride power device under different fault states; statistically analyzing the historical data, establishing a corresponding relationship model between the fault state factor and the failure probability of gate degradation, and dividing different intervals of the fault state factor and the corresponding failure probability range of gate degradation; substituting the obtained fault state factor into the corresponding relationship model to determine the interval of the fault state factor; according to the failure probability range corresponding to the interval and the probability distribution characteristics in the interval, the failure probability of the gallium nitride power device occurring gate degradation is calculated.

[0041] It should be noted that the historical data in the present application contains the fault state factor and the corresponding occurrence of gate degradation; the failure probability in the present application is a quantitative indicator measuring the possibility of the gallium nitride power device occurring gate degradation or failure under a specific working condition.

[0042] In a specific implementation, first, a large amount of historical operation data of gallium nitride power devices is collected, the data needs to include fault state factors (such as 0.2, 0.5, 0.8, etc. comprehensive numerical values) in different fault states, and the actual results (occurrence / non-occurrence) of whether the corresponding device has gate degradation, the sample size needs to meet the statistical effectiveness (such as no less than 100 groups), and ensure that the data covers the common value range of the fault state factor; second, interval division method can be used for statistical analysis of historical data, that is, the fault state factor is divided into multiple continuous intervals according to the numerical value, for example, [0, 0.2), [0.2, 0.4), [0.4, 0.6), [0.6, 0.8), [0.8, 1], then the number of devices with gate degradation in each interval accounts for the total sample number in the interval, and the proportion is taken as the fault probability range of the corresponding interval (such as [0.6, 0.8) interval corresponds to 60%-90%), and the corresponding relationship model of the fault state factor interval-gate degradation fault probability range is obtained; then, the fault state factor of the gallium nitride power device obtained by the current test, for example, 0.72, is compared with the interval in the corresponding relationship model to determine its belonging interval, for example, 0.72 belongs to [0.6, 0.8) interval; finally, according to the probability distribution characteristics of the belonging interval, for example, through historical data statistics, the fault probability in the interval is linearly distributed, linear interpolation method can be used to calculate the specific probability, for example, in [0.6, 0.8) interval, factor 0.6 corresponds to 60%, 0.8 corresponds to 90%, then factor 0.72 corresponds to the probability of 60%+(0.72-0.6) / (0.8-0.6)×(90%-60%)=78%, the value is the fault probability of the device with gate degradation.

[0043] It can be seen that the present application evaluates the fault state of the gallium nitride power device according to the fault evidence matrix, obtains the fault state factor of the gallium nitride power device, and then determines the failure probability of gate degradation of the gallium nitride power device based on the fault state factor; first, by obtaining the rated electrical parameters, chip structure parameters and packaging characteristics of the gallium nitride power device, and combining the simulation model to calculate the transient voltage threshold and high-frequency loss threshold, a benchmark parameter is established for the safe operation of the device in the high-frequency switching state, so that the subsequent evaluation of the actual operating state has a clear quantitative standard, and can provide an early warning before the device has irreversible damage; secondly, by building a high-frequency switching state simulation test environment and collecting state response characteristics such as switching transient voltage, drain current and on-resistance in real time, the actual behavior of the device under dynamic working conditions is converted into a quantifiable data set, so that fault detection no longer relies on a single indicator, thereby fully reflecting the multi-dimensional coupling effect and transient response characteristics of the device under complex working conditions; thirdly, based on the fault evidence matrix constructed with safe operating parameters and state response characteristics, through fuzzy The mapping of variables to membership functions is combined with a fuzzy inference rule base to conduct a comprehensive analysis of each variable, thereby achieving a quantitative expression of the strength of evidence for potential gate degradation faults, converting the qualitative judgment of the fault state into a quantifiable matrix form, and providing a reliable basis for accurate evaluation. Then, based on the fault evidence matrix, key indicator weighting and comprehensive operations are introduced to fuse multi-dimensional information such as transient voltage fluctuations, current consistency, and on-resistance changes to generate a fault state factor, so that the overall fault state can be accurately and comprehensively quantitatively evaluated, reflecting the key control of device safety and operating status. Finally, by establishing a mapping relationship between the fault state factor and the gate degradation probability, a direct deduction from operating data to the fault probability is achieved, making device reliability prediction and maintenance decisions more scientific and operational. In summary, the present application scheme realizes all-round fault monitoring and reliability evaluation of gallium nitride power devices under high-frequency switching conditions by establishing safe operating parameters, collecting state response characteristics, constructing a fault evidence matrix, and calculating the fault state factor, thereby improving the accuracy of fault warning and the safety of device operation.

[0044] In the second embodiment, the present application provides a fault detection system for a gallium nitride power device, referring to Figure 4 As shown, this figure is a schematic diagram of a gallium nitride power device fault detection system according to this embodiment of the present application. The gallium nitride power device fault detection system includes: An acquisition module 100 is configured to determine safe operating parameters of the GaN power device under preset operating conditions based on rated electrical parameters, chip structure parameters, and packaging characteristics of the GaN power device; A feature processing module 200 is configured to extract a state response feature of the GaN power device under the preset operating conditions; The feature processing module 200 is further configured to construct a fault evidence matrix of the gallium nitride power device under a preset working condition based on the safety operation parameter and the state response feature. The execution module 300 is configured to perform fault state evaluation on the gallium nitride power device according to the fault evidence matrix, to obtain a fault state factor of the gallium nitride power device, and to determine a fault probability of the gallium nitride power device from gate degradation based on the fault state factor.

[0045] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The functions specified in one flow or multiple flows and / or blocks

[0046] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage, a magnetic tape storage, or any other medium capable of carrying or storing data which can be read by a computer.

[0047] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without further restriction, exclude the existence of additional elements of the process, method, article, or apparatus that comprises the element.

Claims

1. A gallium nitride power device fault detection method, characterized in that: The steps include: determining safe operating parameters of the GaN power device under preset operating conditions based on rated electrical parameters, chip structure parameters, and packaging characteristics of the GaN power device, wherein the preset operating conditions include a high-frequency switching state, and the safe operating parameters include a transient voltage threshold and a high-frequency loss threshold; Extracting state response characteristics of the gallium nitride power device under the preset operating conditions, wherein the state response characteristics include switching transient voltage fluctuation, drain current fluctuation, and on-resistance change; Constructing a fault evidence matrix of the gallium nitride power device under a preset operating condition based on the safe operating parameters and the state response characteristics; A fault state assessment is performed on the gallium nitride power device according to the fault evidence matrix to obtain a fault state factor of the gallium nitride power device, and then a fault probability of gate degradation occurring in the gallium nitride power device is determined based on the fault state factor.

2. The method according to claim 1, wherein Determining the safe operating parameters of the GaN power device under preset operating conditions based on the rated electrical parameters, chip structure parameters, and packaging characteristics of the GaN power device specifically includes: Obtaining rated electrical parameters, chip structural parameters, and packaging characteristics of the gallium nitride power device, wherein the rated electrical parameters include rated voltage and rated current, the chip structural parameters include gate length and epitaxial layer thickness, and the packaging characteristics include parasitic inductance and heat dissipation coefficient; Substituting the rated electrical parameters, the chip structural parameters, and the packaging characteristics into a device simulation model, thereby determining a transient voltage threshold and a high-frequency loss threshold under a preset operating condition; The transient voltage threshold and the high-frequency loss threshold are integrated to obtain safe operating parameters of the gallium nitride power device under preset operating conditions.

3. The method according to claim 1, wherein The transient voltage threshold refers to the maximum voltage spike critical value that the GaN power device can withstand during the switching process.

4. The method according to claim 1, wherein The high-frequency loss threshold refers to the maximum energy loss critical value allowed by the GaN power device when it operates at a continuous high frequency.

5. The method according to claim 1, wherein Extracting the state response characteristics of the gallium nitride power device under the preset working condition specifically includes: Build a high-frequency switching state simulation test environment, connect the GaN power device to the environment and make it operate under the preset high-frequency switching conditions; The voltage and drain current signals of the GaN power device during the switching process are collected in real time through the voltage sensor and current sensor, and the resistance signal of the GaN power device when it is turned on is collected through the resistance test module; Extract the voltage fluctuation data of the switching transient stage from the collected voltage signal and calculate the switching transient voltage fluctuation amount; extract the current fluctuation data from the drain current signal and calculate the drain current fluctuation amount; extract the on-resistance change data from the resistance signal and calculate the on-resistance change amount; The switching transient voltage fluctuation, the drain current fluctuation, and the on-resistance change are used as state response characteristics of the gallium nitride power device under the preset working condition.

6. The method according to claim 1, wherein Constructing a fault evidence matrix of the GaN power device under a preset operating condition based on the safe operating parameters and the state response characteristics specifically includes: Taking the safe operation parameters and the parameters in the state response characteristics as fuzzy variables; For each fuzzy variable, three fuzzy subsets, namely normal, slightly deviated and seriously deviated, are defined, and the membership function of each fuzzy subset is set respectively; Calculate the membership of each fuzzy variable to its fuzzy subset according to the membership function; Establishing a fuzzy reasoning rule base, wherein the rule base includes a corresponding relationship between a fuzzy state combination of fuzzy variables and a strength of fault evidence; Performing fuzzy reasoning based on the membership degree of each fuzzy variable and the fuzzy reasoning rule base to obtain the fault evidence strength corresponding to each fuzzy variable; The fuzzy variables are used as columns, the evidence categories related to gate degradation faults are used as rows, and the fault evidence strengths are arranged according to the corresponding relationship between rows and columns to obtain the fault evidence matrix of the gallium nitride power device.

7. The method according to claim 1, wherein Performing a fault state assessment on the GaN power device according to the fault evidence matrix to obtain a fault state factor of the GaN power device specifically includes: Preset key indicators for fault status assessment; Standardize the elements in the fault evidence matrix so that the strength values ​​of different types of evidence are in the same numerical range; Assign corresponding weights to each key indicator based on its importance in gate degradation fault assessment; The standardized matrix elements are classified according to key indicators, and the weighted sum of each type of indicator is calculated to obtain the evaluation value of each key indicator; The evaluation values ​​of the key indicators are comprehensively calculated to obtain a comprehensive value that can reflect the overall fault state of the gallium nitride power device, and the comprehensive value is used as the fault state factor.

8. The method according to claim 7, wherein The key indicators include voltage stability indicator, current consistency indicator and resistance change rate indicator.

9. The method according to claim 1, wherein Determining the failure probability of gate degradation of the gallium nitride power device based on the failure state factor specifically includes: Collect historical data of GaN power devices under different fault conditions; Performing statistical analysis on the historical data, establishing a corresponding relationship model between the fault state factor and the gate degradation failure probability, and dividing different intervals of the fault state factor and their corresponding gate degradation failure probability ranges; Substituting the currently obtained fault state factor into the corresponding relationship model, and then determining the interval in which the fault state factor is located; The failure probability of gate degradation occurring in the gallium nitride power device is calculated based on the failure probability range corresponding to the interval and the probability distribution characteristics within the interval.

10. A gallium nitride power device fault detection system, characterized in that: include: an acquisition module, configured to determine safe operating parameters of the GaN power device under preset operating conditions based on the rated electrical parameters, chip structure parameters, and packaging characteristics of the GaN power device; a feature processing module, configured to extract a state response feature of the gallium nitride power device under the preset operating conditions; The feature processing module is further configured to construct a fault evidence matrix of the gallium nitride power device under a preset operating condition based on the safe operation parameters and the state response characteristics; An execution module is configured to perform a fault state assessment on the GaN power device according to the fault evidence matrix to obtain a fault state factor of the GaN power device, and further determine a fault probability of gate degradation occurring in the GaN power device based on the fault state factor.

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