A method and system for determining the degree of aging of a power semiconductor device

Abstract

The application discloses a kind of power semiconductor device aging degree determination method and system, it is related to power semiconductor device monitoring technical field, comprising: constructing the health power semiconductor device data model under different working conditions;Actual working parameter of the measured power semiconductor device in actual working condition is obtained in power electronic equipment when running;According to actual working condition, the health power semiconductor device data model corresponding to the measured power semiconductor device is determined, and according to actual working parameter and the health power semiconductor device data model corresponding to the measured power semiconductor device, the predicted voltage rise time of the measured power semiconductor device is determined;According to actual voltage rise time and the predicted voltage rise time, the aging degree of the measured power semiconductor device is determined.The application can accurately determine the aging degree of power semiconductor device, improve the reliability of power electronic equipment.

Description

Technical Field

[0001] This invention relates to the field of power semiconductor device monitoring technology, and in particular to a method and system for determining the aging degree of power semiconductor devices. Background Technology

[0002] Due to their advantages such as high input impedance and low on-state voltage, insulated-gate bipolar transistors (IGBTs) have become the mainstream fully controllable power semiconductor devices, widely used in industrial fields such as renewable energy integration, aerospace, rail transportation, and electric vehicles, playing a significant role in promoting the efficient development of the global energy industry and energy conservation and environmental protection. As a core component of power electronic equipment, the reliability of power semiconductor devices has become a crucial factor related to the safe operation of power electronic equipment, and their health status is essential for the safety and effectiveness of power electronic equipment.

[0003] However, industry surveys show that power semiconductor devices are among the most vulnerable components in power electronic equipment. Failure types of power semiconductor devices can be categorized into sudden failure and aging failure. Sudden failure occurs when a power semiconductor device is suddenly subjected to stresses exceeding its rated voltage, current, and temperature limits; it is instantaneous and unpredictable. Aging failure occurs when a power semiconductor device, under normal operating conditions, is continuously subjected to electrothermal stresses, leading to gradual performance degradation. This type of failure is slow, cumulative, and inevitable. Failure to promptly detect and replace severely aged power semiconductor devices can result in catastrophic failures. During the operation of power electronic equipment, power fluctuations, environmental changes, and intermittent operation all accelerate the aging failure of power semiconductor devices, thereby reducing the reliability of the power electronic equipment. Therefore, monitoring the aging degree and health status of power semiconductor devices is of great significance. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for determining the aging degree of power semiconductor devices, which can accurately determine the aging degree of power semiconductor devices and improve the reliability of power electronic equipment.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] In a first aspect, the present invention provides a method for determining the aging degree of a power semiconductor device, comprising:

[0007] A data model of a healthy power semiconductor device under different operating conditions is constructed. The data model represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device under healthy conditions. The some operating parameters include the initial shutdown current, the shutdown end voltage, and the external temperature.

[0008] The actual operating parameters of the power semiconductor device under test in the power electronic equipment are obtained under actual operating conditions. The actual operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time. The actual operating conditions can be any operating condition.

[0009] The data model of the healthy power semiconductor device corresponding to the power semiconductor device under test is determined based on the actual operating conditions. The predicted voltage rise time of the power semiconductor device is determined based on the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the data model of the healthy power semiconductor device corresponding to the power semiconductor device under test.

[0010] The degree of aging of the power semiconductor device under test is determined based on the actual voltage rise time and the predicted voltage rise time.

[0011] Optionally, the construction of a data model for healthy power semiconductor devices under different operating conditions specifically includes:

[0012] Multiple historical sample datasets are obtained; each historical sample dataset corresponds to an operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample datasets represent the operating parameters of healthy power semiconductor devices in power electronic equipment under an operating condition.

[0013] The random sample consensus algorithm is used to preprocess all the historical sample datasets.

[0014] Based on all preprocessed historical sample datasets, a data model of healthy power semiconductor devices under different operating conditions is constructed.

[0015] Optionally, the voltage rise time is the time period during which the collector-emitter on-state voltage drop of the power semiconductor device changes from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device.

[0016] Optionally, the initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

[0017] Optionally, determining the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time specifically includes:

[0018] The absolute value of the difference between the actual voltage rise time and the predicted voltage rise time is determined as the relative deviation value;

[0019] When the relative deviation value is less than the first set threshold, the aging degree of the power semiconductor device under test is determined to be unaged.

[0020] When the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than the second set threshold, the aging degree of the power semiconductor device under test is determined to be slight aging.

[0021] When the relative deviation value is greater than or equal to the second set threshold, the aging degree of the power semiconductor device under test is determined to be severe aging.

[0022] In a second aspect, the present invention provides a system for determining the aging degree of a power semiconductor device, comprising:

[0023] A healthy power semiconductor device data model construction module is used to construct a healthy power semiconductor device data model under different operating conditions. The healthy power semiconductor device data model represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device in a healthy state. The some operating parameters include the initial shutdown current, the shutdown end voltage, and the external temperature.

[0024] The actual operating parameter acquisition module is used to acquire the actual operating parameters of the power semiconductor device under test in the power electronic equipment under actual operating conditions; the actual operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time; the actual operating conditions can be any operating condition.

[0025] The predicted voltage rise time determination module is used to determine the healthy power semiconductor device data model corresponding to the power semiconductor device under test based on the actual operating conditions, and to determine the predicted voltage rise time of the power semiconductor device under test based on the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature and the healthy power semiconductor device data model corresponding to the power semiconductor device under test.

[0026] An aging degree determination module is used to determine the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time.

[0027] Optionally, the healthy power semiconductor device data model construction module specifically includes:

[0028] A historical sample dataset acquisition unit is used to acquire multiple historical sample datasets; one historical sample dataset corresponds to one operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample dataset represents the operating parameters of a healthy power semiconductor device in a power electronic device under an operating condition.

[0029] The preprocessing unit is used to preprocess all the historical sample datasets using a random sample consensus algorithm;

[0030] The Healthy Power Semiconductor Device Data Model Building Unit is used to construct healthy power semiconductor device data models under different operating conditions based on all preprocessed historical sample datasets.

[0031] Optionally, the voltage rise time is the time period during which the collector-emitter on-state voltage drop of the power semiconductor device changes from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device.

[0032] Optionally, the initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

[0033] Optionally, the aging degree determination module specifically includes:

[0034] The relative deviation calculation unit is used to determine the absolute value of the difference between the actual voltage rise time and the predicted voltage rise time as the relative deviation value.

[0035] The aging degree determination unit is used for:

[0036] When the relative deviation value is less than the first set threshold, the aging degree of the power semiconductor device under test is determined to be unaged.

[0037] When the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than the second set threshold, the aging degree of the power semiconductor device under test is determined to be slight aging.

[0038] When the relative deviation value is greater than or equal to the second set threshold, the aging degree of the power semiconductor device under test is determined to be severe aging.

[0039] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0040] In establishing a healthy power semiconductor device data model, this invention directly uses the operating parameters of power semiconductor devices in power electronic equipment under actual operating conditions as the data source. This eliminates the discrepancies caused by accelerated aging experiments simulating the actual operating state of power semiconductor devices, and avoids the problem that the limited and incomplete data collected makes it difficult to effectively apply to monitoring under actual operating conditions. In other words, this invention determines the predicted voltage rise time of the power semiconductor device under test through the established healthy power semiconductor device data model, and then accurately determines the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time, thereby improving the reliability of power electronic equipment. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A flowchart illustrating the method for determining the aging degree of power semiconductor devices provided in an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of the structure of the power semiconductor device aging degree determination system provided in an embodiment of the present invention;

[0044] Figure 3 A flowchart illustrating the method for monitoring the aging degree of insulated gate bipolar transistors (IGBTs) based on electrical big data, provided in an embodiment of the present invention;

[0045] Figure 4 A schematic diagram of the structure of an insulated gate bipolar transistor (IGBT) aging monitoring system based on electrical big data provided in an embodiment of the present invention;

[0046] Figure 5 A schematic diagram of the turn-off process of an insulated gate bipolar transistor (IGBT) provided in an embodiment of the present invention;

[0047] Figure 6 A schematic diagram illustrating the construction process of the health IGBT device data model provided in this embodiment of the invention;

[0048] Figure 7 This is a schematic diagram illustrating the specific operation of the data processing step provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] The purpose of this invention is to provide a method and system for determining the aging degree of power semiconductor devices, which can accurately determine the aging degree of power semiconductor devices and improve the reliability of power electronic equipment.

[0051] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] Example 1

[0053] This embodiment provides a method for determining the aging degree of power semiconductor devices, such as... Figure 1 As shown, it includes:

[0054] Step 101: Construct a data model of a healthy power semiconductor device under different operating conditions; the data model of the healthy power semiconductor device represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device under healthy conditions; the some operating parameters include the initial shutdown current, the shutdown end voltage and the external temperature.

[0055] Step 102: Obtain the actual operating parameters of the power semiconductor device under test in the power electronic device under actual operating conditions; the actual operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time; the actual operating conditions can be any operating condition. This power electronic device can be a mining power electronic device.

[0056] Step 103: Determine the healthy power semiconductor device data model corresponding to the power semiconductor device under test based on the actual operating conditions, and determine the predicted voltage rise time of the power semiconductor device based on the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the healthy power semiconductor device data model corresponding to the power semiconductor device under test.

[0057] Step 104: Determine the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time.

[0058] In one example, the voltage rise time is the time interval during which the collector-emitter on-state voltage drop of the power semiconductor device increases from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device. The initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

[0059] Furthermore, step 101 specifically includes:

[0060] Multiple historical sample datasets are obtained; each historical sample dataset corresponds to an operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample datasets represent the operating parameters of healthy power semiconductor devices in power electronic equipment under an operating condition.

[0061] The random sample consensus algorithm is used to preprocess all the historical sample datasets.

[0062] Based on all preprocessed historical sample datasets, a data model of healthy power semiconductor devices under different operating conditions is constructed.

[0063] Furthermore, step 104 specifically includes:

[0064] The absolute value of the difference between the actual voltage rise time and the predicted voltage rise time is determined as the relative deviation value.

[0065] When the relative deviation value is less than the first set threshold, the aging degree of the power semiconductor device under test is determined to be unaged.

[0066] When the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than the second set threshold, the aging degree of the power semiconductor device under test is determined to be slight aging.

[0067] When the relative deviation value is greater than or equal to the second set threshold, the aging degree of the power semiconductor device under test is determined to be severe aging.

[0068] Example 2

[0069] To achieve the above objectives, this embodiment provides a system for determining the aging degree of power semiconductor devices, such as... Figure 2 As shown, it includes:

[0070] The healthy power semiconductor device data model construction module 201 is used to construct a healthy power semiconductor device data model under different operating conditions. The healthy power semiconductor device data model represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device in a healthy state. The some operating parameters include the initial shutdown current, the shutdown end voltage, and the external temperature.

[0071] The actual operating parameter acquisition module 202 is used to acquire the actual operating parameters of the power semiconductor device under test in the power electronic equipment under actual operating conditions; the actual operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time; the actual operating conditions can be any operating condition.

[0072] The predicted voltage rise time determination module 203 is used to determine the healthy power semiconductor device data model corresponding to the power semiconductor device under test based on the actual operating conditions, and to determine the predicted voltage rise time of the power semiconductor device under test based on the actual initial turn-off current, the actual end-turn-off voltage, the actual external temperature and the healthy power semiconductor device data model corresponding to the power semiconductor device under test.

[0073] The aging degree determination module 204 is used to determine the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time.

[0074] In one example, the voltage rise time is the time interval during which the collector-emitter on-state voltage drop of the power semiconductor device increases from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device. The initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

[0075] The healthy power semiconductor device data model construction module 201 specifically includes:

[0076] A historical sample dataset acquisition unit is used to acquire multiple historical sample datasets; one historical sample dataset corresponds to one operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample dataset represents the operating parameters of a healthy power semiconductor device in a power electronic device under an operating condition.

[0077] The preprocessing unit is used to preprocess all the historical sample datasets using a random sample consensus algorithm.

[0078] The Healthy Power Semiconductor Device Data Model Building Unit is used to construct healthy power semiconductor device data models under different operating conditions based on all preprocessed historical sample datasets.

[0079] The aging degree determination module 204 specifically includes:

[0080] The relative deviation calculation unit is used to determine the absolute value of the difference between the actual voltage rise time and the predicted voltage rise time as the relative deviation value.

[0081] The aging degree determination unit is used for:

[0082] When the relative deviation value is less than the first set threshold, the aging degree of the power semiconductor device under test is determined to be unaged.

[0083] When the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than the second set threshold, the aging degree of the power semiconductor device under test is determined to be slight aging.

[0084] When the relative deviation value is greater than or equal to the second set threshold, the aging degree of the power semiconductor device under test is determined to be severe aging.

[0085] Example 3

[0086] Aging monitoring of IGBT modules typically involves accelerated aging tests to obtain aging failure data and then constructing an IGBT module aging model. However, accelerated aging tests under full operating conditions are overly complex, and the experiments are conducted under known, defined, and structured operating conditions, resulting in limited and incomplete data that is difficult to apply effectively to IGBT module monitoring under real-world operating conditions. Therefore, how to perform accurate and efficient aging monitoring is a pressing technical problem that needs to be solved.

[0087] To address the aforementioned shortcomings in the existing technology, this embodiment provides a method for monitoring the aging status of insulated gate bipolar transistors (IGBTs) based on electrical big data, which monitors the aging status of IGBT modules in real time online.

[0088] like Figure 3 As shown in the figure, this embodiment provides a method for monitoring the aging degree of an insulated gate bipolar transistor (IGBT) based on electrical big data, which includes the following steps:

[0089] Step 301: Collect and process the operating parameters of healthy IGBTs in actual power electronic devices under different operating conditions, and construct a historical sample dataset based on the operating parameters; wherein, the operating parameters include the initial turn-off current I, the turn-off end voltage U, and the external temperature T.e and voltage rise time t rv .

[0090] Step 302: Construct a healthy IGBT data model based on the obtained historical sample dataset.

[0091] Step 303: Monitor and record the operating parameters of the IGBT under test in the actual power electronic equipment under the target operating condition in real time. Then, determine the predicted voltage rise time of the IGBT under test based on the operating parameters and the healthy IGBT data model. Next, determine the relative deviation value based on the predicted voltage rise time and the actual voltage rise time. The target operating condition is one of the above-mentioned operating conditions. The operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time.

[0092] Step 304: Determine the aging degree of the IGBT under test based on the magnitude of the obtained relative deviation value, so as to monitor the aging status and provide early warning of faults.

[0093] In one example, the voltage rise time t rv For the period of time when the collector-emitter on-state voltage drop of the IGBT changes from 10%U to 90%U, the voltage rise time t is used. rv To assess the correlation between IGBT health status and aging level, an IGBT health status assessment was conducted.

[0094] In one example, during the establishment of a healthy IGBT data model, the operating parameters of IGBTs in power electronic devices under actual operating conditions were directly used as the data source. This eliminated the differences brought about by accelerated aging experiments in simulating the actual operating state of power semiconductor devices, and avoided the problem that the limited and incomplete data collected could not be effectively applied to monitoring under actual operating conditions.

[0095] In one example, the historical sample dataset varies randomly within a certain range, exhibiting randomness in the short term and regularity in the long term; for example, using years as the monitoring time unit, it includes the impact of different environmental conditions in spring, summer, autumn and winter on IGBTs.

[0096] In one example, the initial turn-off current I is the collector current at the initial turn-off moment of the IGBT, the final turn-off voltage U is the collector-emitter voltage at the final turn-off moment of the IGBT, and the external temperature T is... e This refers to the operating ambient temperature or module temperature of the IGBT.

[0097] In one example, the Random Sample Consensus (RANSAC) algorithm is used to remove outliers from historical sample datasets to establish the voltage rise time t under healthy conditions. rv Mapping relationship t with different working conditions rv=f(I,U,T) e Based on the operating conditions of the IGBT under test in actual operation, the voltage rise time t of the IGBT under test in a healthy state is obtained. rvp .

[0098] In one example, the relative deviation value δ is determined based on the operating conditions of the IGBT under test, i.e., a specific I... certain U certain T e_certain The voltage rise time t predicted by the healthy IGBT data model is obtained. rvp The voltage rise time t obtained by actual measurement rva The relative deviation between them.

[0099] Furthermore, the aging degree of the tested IGBT is determined using, but not limited to, the following settings: when the relative deviation value δ < 5%, an indication of "healthy" is provided, i.e., no aging; when 5% ≤ relative deviation value δ < 10%, a warning of "Warning, mild aging" is issued; when the relative deviation value δ ≥ 10%, an alarm is issued and "Alarm, severe aging" is displayed. If the actual operating conditions exceed these states, the mapping relationship between the magnitude of the relative deviation value and the aging degree of the IGBT is redefined.

[0100] This embodiment is based on the operating data of IGBT modules under actual working conditions, which reduces the complexity of accelerated aging tests and avoids the errors caused by the accelerated aging test simulating actual working conditions. It uses voltage rise time to characterize the aging of IGBT modules and combines data-driven models to realize the aging monitoring of modules. It solves the problems of high data acquisition difficulty and low accuracy of existing monitoring methods, which has strong industrial applicability and is reliable and scalable.

[0101] Example 4

[0102] like Figure 4 As shown in this embodiment, the insulated gate bipolar transistor (IGBT) aging monitoring system based on electrical big data includes a power device health data model, a data processing stage, and an aging identification module. The power device health data model predicts the voltage rise time of the tested power device (IGBT) in a healthy state under a certain operating condition. The data processing stage calculates the relative deviation between the predicted and actual voltage rise times. The aging identification module determines the aging degree of the tested power device (IGBT) based on the relative deviation.

[0103] In this embodiment, the turn-off process of an insulated gate bipolar transistor (IGBT) can be illustrated as follows: Figure 5 As shown, the voltage rise time t rvFor the period of time when the collector-emitter on-state voltage drop of the IGBT changes from 10%U to 90%U, the voltage rise time t is used. rv To assess the correlation between IGBT health status and aging level, an IGBT health status assessment was conducted.

[0104] In this embodiment, during the establishment of the healthy IGBT data model, the operating parameters of the IGBT in the power electronic equipment under actual operating conditions are directly used as the data source. This eliminates the differences brought about by the accelerated aging experiment in simulating the actual operating state of power semiconductor devices, and avoids the problem that the collected data is limited and incomplete, making it difficult to effectively apply to the monitoring under actual operating conditions.

[0105] Historical sample datasets vary randomly within a certain range, exhibiting randomness in the short term and regularity in the long term; for example, using years as the monitoring time unit, they include the impact of different environmental conditions in spring, summer, autumn and winter on IGBTs.

[0106] The initial turn-off current I is the collector current at the initial turn-off moment of the IGBT, and the final turn-off voltage U is the collector-emitter voltage at the final turn-off moment of the IGBT. The external temperature T is... e This refers to the operating ambient temperature or module temperature of the IGBT.

[0107] In this embodiment of the invention, the process of establishing and predicting the healthy IGBT data model can be found in [reference needed]. Figure 6 The specific steps include:

[0108] S1: Input data.

[0109] S2: The Random Sample Consensus (RANSAC) algorithm is used to process the data, creating training and test datasets, i.e., removing outliers from historical sample data.

[0110] S2: Establish the voltage rise time t under healthy conditions rv Mapping relationship t with different working conditions rv =f(I,U,T) e ).

[0111] S3: Based on the operating conditions of the IGBT under test in actual operation, obtain the voltage rise time t of the IGBT under test in a healthy state. rv .

[0112] In this embodiment, a detailed operational diagram of the data processing stage can be found by referring to... Figure 7 The relative deviation value δ is determined based on the operating conditions of the IGBT being tested, i.e., a specific I... certain U certain T e_certain The voltage rise time t predicted by the healthy IGBT data model is obtained.rvp The voltage rise time t rvp The voltage rise time t obtained by actual measurement rva The relative deviation between them.

[0113] In this embodiment, the voltage rise time t in the initial healthy IGBT data model when there is no IGBT failure is... rv The data is defined as follows:

[0114] Based on voltage rise time t rv Different warnings are provided depending on the magnitude of the corresponding average relative deviation value, using, but not limited to, the following settings:

[0115] When the relative deviation value is <5%, an indication of "health" is provided; when 5% ≤ relative deviation value <10%, a warning of "Warning, mild aging" is issued; when the relative deviation value is ≥10%, an alarm is issued and "Alarm, severe aging" is displayed.

[0116] If the actual operating conditions exceed this type of operating state, redefine the voltage rise time t. rv The mapping relationship between the magnitude of the corresponding average relative deviation value and the degree of IGBT aging.

[0117] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0118] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for determining the aging degree of a power semiconductor device, characterized in that, include: A data model of a healthy power semiconductor device under different operating conditions is constructed. The data model represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device under healthy conditions. The some operating parameters include the initial shutdown current, the shutdown end voltage, and the external temperature. To obtain the actual operating parameters of the power semiconductor device under test in power electronic equipment under actual operating conditions; The actual operating parameters include the actual initial shutdown current, the actual shutdown end voltage, the actual external temperature, and the actual voltage rise time. The actual operating conditions refer to any operating condition. The data model of the healthy power semiconductor device corresponding to the power semiconductor device under test is determined based on the actual operating conditions. The predicted voltage rise time of the power semiconductor device under test is determined based on the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the data model of the healthy power semiconductor device corresponding to the power semiconductor device under test. The aging degree of the power semiconductor device under test is determined based on the actual voltage rise time and the predicted voltage rise time, specifically including: determining the absolute value of the difference between the actual voltage rise time and the predicted voltage rise time as the relative deviation value; When the relative deviation value is less than the first set threshold, the aging degree of the power semiconductor device under test is determined to be no aging; when the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than the second set threshold, the aging degree of the power semiconductor device under test is determined to be slight aging; when the relative deviation value is greater than or equal to the second set threshold, the aging degree of the power semiconductor device under test is determined to be severe aging.

2. The method for determining the aging degree of a power semiconductor device according to claim 1, characterized in that, The construction of a data model for healthy power semiconductor devices under different operating conditions specifically includes: Multiple historical sample datasets are obtained; each historical sample dataset corresponds to an operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample datasets represent the operating parameters of healthy power semiconductor devices in power electronic equipment under an operating condition. The random sample consensus algorithm is used to preprocess all the historical sample datasets. Based on all preprocessed historical sample datasets, a data model of healthy power semiconductor devices under different operating conditions is constructed.

3. The method for determining the aging degree of a power semiconductor device according to claim 1, characterized in that, The voltage rise time is the time period during which the collector-emitter on-state voltage drop of the power semiconductor device increases from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device.

4. The method for determining the aging degree of a power semiconductor device according to claim 1, characterized in that, The initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

5. A system for determining the aging degree of a power semiconductor device, characterized in that, include: A healthy power semiconductor device data model construction module is used to construct a healthy power semiconductor device data model under different operating conditions. The healthy power semiconductor device data model represents the mapping relationship between the voltage rise time of the power semiconductor device and some operating parameters of the power semiconductor device in a healthy state. The some operating parameters include the initial shutdown current, the shutdown end voltage, and the external temperature. The actual operating parameter acquisition module is used to acquire the actual operating parameters of the power semiconductor device under test in the power electronic equipment under actual operating conditions; the actual operating parameters include the actual initial turn-off current, the actual turn-off end voltage, the actual external temperature, and the actual voltage rise time. The actual operating conditions refer to any operating condition. The predicted voltage rise time determination module is used to determine the healthy power semiconductor device data model corresponding to the power semiconductor device under test based on the actual operating conditions, and to determine the predicted voltage rise time of the power semiconductor device under test based on the actual initial turn-off current, the actual end-turn-off voltage, the actual external temperature and the healthy power semiconductor device data model corresponding to the power semiconductor device under test. An aging degree determination module is used to determine the aging degree of the power semiconductor device under test based on the actual voltage rise time and the predicted voltage rise time. The aging degree determination module specifically includes: a relative deviation value calculation unit, used to determine the absolute value of the difference between the actual voltage rise time and the predicted voltage rise time as the relative deviation value; The aging degree determination unit is used to: determine that the aging degree of the power semiconductor device under test is not aged when the relative deviation value is less than a first set threshold; determine that the aging degree of the power semiconductor device under test is slightly aged when the relative deviation value is greater than or equal to the first set threshold and the relative deviation value is less than a second set threshold; and determine that the aging degree of the power semiconductor device under test is severely aged when the relative deviation value is greater than or equal to the second set threshold.

6. The system for determining the aging degree of a power semiconductor device according to claim 5, characterized in that, The healthy power semiconductor device data model construction module specifically includes: A historical sample dataset acquisition unit is used to acquire multiple historical sample datasets; one historical sample dataset corresponds to one operating condition, and different historical sample datasets correspond to different operating conditions; the historical sample dataset represents the operating parameters of a healthy power semiconductor device in a power electronic device under an operating condition. The preprocessing unit is used to preprocess all the historical sample datasets using a random sample consensus algorithm; The Healthy Power Semiconductor Device Data Model Building Unit is used to construct healthy power semiconductor device data models under different operating conditions based on all preprocessed historical sample datasets.

7. The system for determining the aging degree of a power semiconductor device according to claim 5, characterized in that, The voltage rise time is the time period during which the collector-emitter on-state voltage drop of the power semiconductor device increases from 10%U to 90%U; U represents the collector-emitter voltage of the power semiconductor device.

8. The system for determining the aging degree of a power semiconductor device according to claim 5, characterized in that, The initial turn-off current is the collector current at the initial turn-off moment of the power semiconductor device; the final turn-off voltage is the collector-emitter voltage at the final turn-off moment of the power semiconductor device; and the external temperature is the operating ambient temperature of the power semiconductor device or the temperature of the power electronic equipment in which the power semiconductor device is located.

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