IGBT (Insulated Gate Bipolar Translator) module consistency classification method and device and electronic equipment

Abstract

The invention relates to the technical field of IGBT module performance detection, and provides an IGBT module consistency classification method and device and electronic equipment, and the method comprises the steps: obtaining the identity information of a to-be-detected IGBT module, obtaining the test setting parameter information of the IGBT module, and generating a control drive signal applied to the IGBT module; collecting input and output signals of a collector-emitter of the IGBT module, and generating original waveform data to be analyzed; analyzing the original waveform data, and intercepting an effective waveform data segment corresponding to the identity identification information; obtaining turn-on time T1 and turn-off time T2 of the IGBT module by adopting a time parameter differencing algorithm based on the effective waveform data segment, and generating a switching time feature point P; and then a grouping decision algorithm is adopted to generate a grouping mapping table comprising multiple pieces of group information, and IGBT modules are classified based on the group information. By adopting the method, an objective basis is provided for classification; efficient and accurate consistency grouping is achieved, and the reliability of parallel application of the IGBT modules is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of IGBT module performance testing, and particularly to an IGBT module consistency classification method and device and electronic equipment. BACKGROUND

[0002] Insulated Gate Bipolar Transistor (IGBT) modules are widely used in high-power applications due to their excellent performance. In order to meet the growing current capacity requirements, multiple IGBT modules are commonly used in parallel in the design. However, this parallel application faces serious consistency problems. Due to the dispersion of the manufacturing process, even IGBT modules of the same batch have inevitable differences in the turn-on time and turn-off time of the dynamic switching parameters. This mismatch in characteristics can easily lead to an ideal current sharing of the modules in parallel during operation. Modules that turn on too quickly or turn off too slowly will be subjected to an impact far exceeding their design margin, causing local overheating, performance degradation, and even instantaneous burning, which seriously threatens the reliability and safety of the entire system.

[0003] Therefore, the industry urgently needs a technical solution that can automatically, accurately and efficiently test and classify the dynamic switching characteristics of IGBT modules to solve the above problems. SUMMARY

[0004] The present application provides an IGBT module consistency classification method, device and electronic equipment to solve the problems raised in the background art.

[0005] In a first aspect, the present application provides an IGBT module consistency classification method, comprising: Obtaining the identity information of the IGBT module to be tested, and generating a test record processing library based on the identity information; wherein the test record processing library corresponds to the IGBT module one by one; Obtaining the test setting parameter information of the IGBT module, and generating a control driving signal applied to the IGBT module based on the test setting parameter information; Collecting the input and output signals of the collector-emitter of the IGBT module, generating raw waveform data for analysis, and uploading the raw waveform data to the test record processing library; Analyzing the raw waveform data and intercepting the effective waveform data segment corresponding to the identity information; Based on the effective waveform data segment, the test setting parameter information of the IGBT module and a plurality of preset threshold values, a time parameter difference algorithm is used to obtain the turn-on time T1 and the turn-off time T2 of the IGBT module; Generate a switch time feature point P = (T1, T2) recording the identity information based on the turn-on time T1, the turn-off time T2 and the identity information; Based on the switch time feature point P, a grouping mapping table including a plurality of group information is generated by using a grouping decision algorithm, wherein the group information stores the identity information; and the IGBT module is classified based on the group information.

[0006] In an implementation manner, the analyzing the original waveform data and intercepting an effective waveform data segment corresponding to the identity information comprises: Performing wavelet transform denoising processing on the original waveform data to obtain denoised waveform data; According to the denoised waveform data, the starting point and the ending point of the rising edge and the falling edge of the waveform are extracted by using a difference threshold method; According to the starting point and the ending point, the denoised waveform data is segmented and intercepted to obtain a plurality of candidate waveform segments; According to the identity information, a corresponding standard waveform template is called from the test record processing library; The correlation coefficients of each candidate waveform segment and the standard waveform template are calculated, and the candidate waveform segment with the largest correlation coefficient is selected as the effective waveform data segment.

[0007] In an implementation manner, the calculating the correlation coefficients of each candidate waveform segment and the standard waveform template, and selecting the candidate waveform segment with the largest correlation coefficient as the effective waveform data segment comprises: Performing resampling processing on the standard waveform template based on linear interpolation to make the length of the time axis consistent with the current candidate waveform segment, to obtain a resampled standard waveform template; Performing amplitude alignment processing based on mean shift on the resampled standard waveform template and the candidate waveform segment to adjust the direct current components of the two waveforms to zero mean, to obtain a zero-mean standard waveform and a zero-mean candidate waveform; Performing correlation coefficient calculation processing based on Pearson product-moment formula on the zero-mean standard waveform and the zero-mean candidate waveform to obtain a correlation coefficient value p; and selecting the candidate waveform segment with the largest correlation coefficient as the effective waveform data segment from the plurality of correlation coefficient values p.

[0008] In an implementation manner, the obtaining the turn-on time T1 and the turn-off time T2 of the IGBT module by using a time parameter difference algorithm based on the effective waveform data segment, the test setting parameter information of the IGBT module and a plurality of preset threshold values comprises: The effective waveform data section includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as the time starting point to, and the 50% point of the falling edge of the turn-off process voltage waveform data is located as the time starting point tf; With the time starting point to as the reference point, reverse search processing is performed on the voltage waveform to find the time point t1 at which the voltage value first crosses the first preset threshold value, and forward search processing is performed to find the time t2 at which the voltage value first stably reaches the second preset threshold value; According to the time point t1 and the time point t2, time difference calculation processing is performed to obtain the turn-on time T1 = t2 - t1; With the time starting point tf as the reference point, reverse search processing is performed on the voltage waveform data to find the time point t3 at which the voltage value first stably reaches the third preset threshold value, and forward search processing is performed to find the time point t4 at which the voltage value first crosses the fourth preset threshold value; According to the time point t4 and the time point t3, time difference calculation processing is performed to obtain the turn-off time T2 = t4 - t3.

[0009] In an implementation manner, the effective waveform data section includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as the time starting point to, and the 50% point of the falling edge of the turn-off process voltage waveform data is located as the time starting point tf includes: The rising edge interval and the falling edge interval in the voltage waveform data are extracted to obtain a rising edge data sequence and a falling edge data sequence, respectively; The rising edge data sequence is sorted to obtain an ordered sequence arranged in ascending order of voltage values, and the median voltage value of the rising edge of the ordered sequence is calculated; A plurality of data points in the rising edge data sequence whose voltage values are closest to the median voltage value of the rising edge are searched, and the median of the time coordinates of the data points is calculated to obtain the time starting point to; The falling edge data sequence is sorted to obtain an ordered sequence arranged in descending order of voltage values, and the median voltage value of the falling edge of the ordered sequence is calculated; A plurality of data points in the falling edge data sequence whose voltage values are closest to the median voltage value of the falling edge are searched, and the median of the time coordinates of the data points is calculated to obtain the time starting point tf.

[0010] In an implementation manner, the generating, based on the turn-on time T1, the turn-off time T2, and the identity information, of a switch time feature point recording the identity information includes: The on-time T1 and the off-time T2 are subjected to dimension unification and precision standardization processing to obtain a standardized on-time T1 and a standardized off-time T2; The standardized on-time T1 is taken as the abscissa, and the standardized off-time T2 is taken as the ordinate to perform two-dimensional feature space coordinate construction processing to obtain a switch time feature point P = (T1, T2); The switch characteristic feature point P is data-bonded with the identity identification information.

[0011] In an implementation manner, a grouping decision algorithm is adopted to generate a grouping mapping table including a plurality of group information based on the switch time feature point P, wherein the group information stores the identity identification information; and the IGBT module is classified based on the group information, including: A uniform grid array of N x M is constructed according to a preset grid starting point coordinate (T1s, T2s), a grid width ΔT1 and a grid length ΔT2, wherein N is the number of grid in the on-time T1 direction, and M is the number of grid in the off-time T2 direction; A unique group number G ij is allocated to each grid unit, wherein i is a row index, and 0≤i<N; j is a column index, and 0≤j<M; and a mapping relationship table of grid coordinates and group numbers is established; The switch time feature point P (T1, T2) of the IGBT module to be classified is acquired, and the grid coordinates (i, j) thereof are calculated, wherein: i = floor((T1 - T1s) / ΔT1), j = floor((T2 - T2s) / ΔT2); The corresponding group number G ij is queried from the mapping relationship table according to the grid coordinates (i, j); The identity identification information and the group number G ij are associatedly stored into the grouping mapping table; and the group number G ij corresponding to the identity identification information is displayed to a test record processing library, thereby completing the consistency classification of the IGBT module.

[0012] In a second aspect, an embodiment of the present application provides an IGBT module consistency classification device, including: A first acquisition module is configured to acquire identity identification information of an IGBT module to be tested, and generate a test record processing library based on the identity identification information; wherein the test record processing library is in one-to-one correspondence with the IGBT module; A second acquisition module is configured to acquire test setting parameter information of the IGBT module, and generate a control driving signal applied to the IGBT module based on the test setting parameter information; The collection module is configured to collect input and output signals of the collector-emitter of the IGBT module, generate original waveform data to be analyzed, and upload the original waveform data to a test record processing library; The analysis module is configured to analyze the original waveform data, and intercept an effective waveform data segment corresponding to the identity information. The processing module is configured to obtain the turn-on time T1 and the turn-off time T2 of the IGBT module by using a time parameter difference algorithm based on the effective waveform data segment, test setting parameter information of the IGBT module, and a plurality of preset threshold values. The first generation module is configured to generate a switching time feature point P = (T1, T2) having the identity information recorded therein based on the turn-on time T1, the turn-off time T2, and the identity information. The second generation module is configured to generate a grouping mapping table including a plurality of group information based on the switching time feature point P by using a grouping decision algorithm, wherein the group information stores the identity information, and classify the IGBT module based on the group information.

[0013] In a third aspect, the present application provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein the computer program is executed by the processor to implement any one of the IGBT module consistency classification methods described above.

[0014] The present application provides an IGBT module consistency classification method, device and electronic device, wherein the method includes obtaining identity information of an IGBT module to be tested, obtaining test setting parameter information of the IGBT module, and generating a control driving signal applied to the IGBT module; collecting input and output signals of the collector-emitter of the IGBT module, and generating original waveform data to be analyzed; analyzing the original waveform data, and intercepting an effective waveform data segment corresponding to the identity information; obtaining the turn-on time T1 and the turn-off time T2 of the IGBT module by using a time parameter difference algorithm based on the effective waveform data segment, and generating a switching time feature point P; then generating a grouping mapping table including a plurality of group information by using a grouping decision algorithm, and classifying the IGBT module based on the group information. This method creates an independent test library through identity information, ensures full-process automation and data traceability; applies a driving signal based on unified test parameters, ensures consistency of test conditions and comparability of results; accurately extracts the turn-on and turn-off times by analyzing waveform data, forms a quantitative switching time feature point, and provides an objective basis for classification; finally, automatically completes module classification by using a grouping decision algorithm, realizes efficient and accurate consistency grouping, and significantly improves the reliability of IGBT module parallel application. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0016] Figure 1 A flowchart of the IGBT module consistency classification method provided by the embodiments of the present application is shown in the figure. Figure 2 A voltage waveform diagram of the IGBT module provided by the embodiments of the present application is shown in the figure. Figure 3 A structural schematic block diagram of the IGBT module consistency classification method device provided by the embodiments of the present application is shown in the figure. Figure 4 A structural schematic block diagram of the electronic device provided by the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort belong to the scope of protection of the present application.

[0018] The flowchart shown in the drawings is only an example and does not necessarily include all the contents and operations / steps, nor does it have to be executed in the order described. For example, some operations / steps can be decomposed, combined or partially merged, so the actual execution order can be changed according to the actual situation.

[0019] It should also be understood that the terms used in this specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application and the appended claims, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0020] It should be further understood that the term "and / or" used in the specification of the present application and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0021] Insulated Gate Bipolar Transistor (IGBT) modules are widely used in high-power applications due to their excellent performance. In order to meet the increasing demand for current capacity, it is common in design to use multiple IGBT modules in parallel. However, this parallel application faces serious consistency problems. Due to the dispersion of the manufacturing process, even IGBT modules of the same batch have inevitable differences in the turn-on time and turn-off time of the dynamic switching parameters. This mismatch in characteristics can easily lead to an ideal current sharing of the modules in parallel during operation. Modules that turn on too quickly or turn off too slowly will be subjected to an impact far beyond their design margin, causing local overheating, performance degradation, and even instantaneous burning, which seriously threatens the reliability and safety of the entire system.

[0022] Therefore, the industry urgently needs a technical solution that can automatically, accurately and efficiently test and classify the dynamic switching characteristics of IGBT modules to solve the above problems.

[0023] To this end, the embodiments of the present application provide an IGBT module consistency classification method, device, electronic equipment and storage medium to realize the consistency classification of IGBT modules and improve the reliability of parallel application of IGBT modules.

[0024] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the case of no conflict, the following examples and features in the examples can be combined with each other.

[0025] Please refer to Figure 1 , Figure 1 The flowchart of the IGBT module consistency classification method provided by the embodiments of the present application is shown in Figure 1 The IGBT module consistency classification method provided by the embodiments of the present application includes steps S10 to S70.

[0026] Step S10, obtaining the identity information of the IGBT module to be tested, generating a test record processing library based on the identity information; wherein the test record processing library corresponds to the IGBT module one by one; It can be understood that obtaining the identity information of the IGBT module to be tested can be reading the unique code on the surface of the IGBT module shell by using a two-dimensional code scanner, and generating a data table containing code information, test time, original waveform storage address, feature parameter storage address, etc. On this basis, a data index association is established, so that all test data can be quickly retrieved through the code.

[0027] Step S20, obtaining the test setting parameter information of the IGBT module, generating a control driving signal applied to the IGBT module based on the test setting parameter information; Specifically, the test setting parameter information includes gate drive voltage, collector test voltage, load current, junction temperature, etc. of the IGBT module, and DC bus voltage Vdc output by the DC power supply.

[0028] Optionally, the control drive signal can be a double-pulse drive signal, and can also be a high-performance function signal. It can also be understood that the control drive signal can be executed once, twice or three times.

[0029] Step S30, collecting the input and output signals of the collector-emitter of the IGBT module, generating raw waveform data to be analyzed, and uploading the raw waveform data to a test record processing library; Optionally, a high-voltage differential probe is used to measure the voltage waveform data of the collector-emitter.

[0030] Optionally, a Rogowski coil is used to collect the waveform data of the collector current.

[0031] Step S40, analyzing the raw waveform data, and intercepting an effective waveform data segment corresponding to the identity information; The raw waveform data is subjected to denoising processing, and the effective waveform data segment is extracted by a differential threshold method.

[0032] Step S50, based on the effective waveform data segment, the test setting parameter information of the IGBT module, and a plurality of preset threshold values, using a time parameter difference algorithm to obtain the turn-on time T1 and the turn-off time T2 of the IGBT module; Specifically, the turn-on time T1 and the turn-off time T2 can be directly obtained by the voltage waveform data segment, or a threshold voltage can be introduced for accurate calculation.

[0033] It should be further pointed out that the specific method of obtaining the turn-on time T1 and the turn-off time T2 of the IGBT module by using the time parameter difference algorithm is described in detail below, and will not be repeated here.

[0034] Step S60, based on the turn-on time T1, the turn-off time T2 and the identity information, generating a switching time feature point P = (T1, T2) recording the identity information. Preferably, after generating the switching time feature point P, the P value is subjected to decimal place unification and unit normalization processing.

[0035] For example, the unit is unified to nanoseconds, and the decimal places are unified to three decimal places.

[0036] Step S70, based on the switching time characteristic point P, a grouping decision algorithm is used to generate a grouping mapping table including a plurality of group information, wherein the group information stores the identity information; and the IGBT modules are classified based on the group information.

[0037] Optionally, the P value is mapped into a two-dimensional space with T1 and T2 of the switching time characteristic point P as two dimensions, and according to a preset consistency tolerance range, such as an allowable deviation of T1 and T2 of ±10 ns, points with similar distances are automatically merged into the same group code. The identity information of each module is assigned a group code. The output of this step is a grouping mapping table which clearly defines which identity information belongs to which group code. It clearly shows which identity information corresponds to the IGBT modules that meet the consistency requirements.

[0038] It can be understood that, by using the method of the embodiment, a group code can be obtained for each IGBT module after testing, thereby realizing the consistency classification of the IGBT module, and the IGBT modules in the same group are used in parallel, thereby improving the reliability of the parallel module switching.

[0039] Optionally, the grouping decision algorithm can be a preset consistency tolerance algorithm, a Gaussian classification algorithm that unifies all P values, or a clustering algorithm.

[0040] It should be noted that, when the IGBT module is used as a test object, the IGBT module is an IGBT with a driving small plate.

[0041] In some embodiments, the analysis of the original waveform data, and the interception of the effective waveform data segment corresponding to the identity information, includes the following steps: Wavelet transform denoising processing is performed on the original waveform data to obtain denoised waveform data; According to the denoised waveform data, the starting point and the ending point of the rising edge and the falling edge of the waveform are extracted by the difference threshold method; According to the starting point and the ending point, the denoised waveform data is segmented and intercepted to obtain a plurality of candidate waveform segments; According to the identity information, the corresponding standard waveform template is retrieved from the test record processing library; The correlation coefficients of each candidate waveform segment and the standard waveform template are calculated, and the candidate waveform segment with the largest correlation coefficient is selected as the effective waveform data segment.

[0042] It can be understood that the above steps are the core link of the original waveform data processing, and play a key role in removing false information. Specifically, the wavelet transform denoising and the correlation coefficient matching of the template are used to accurately extract the effective waveform segment which can best represent the switching characteristics of the test device itself from the original data which may contain noise and interference, thereby laying a solid foundation for accurately calculating the key parameters in the next step.

[0043] It should be further pointed out that the specific method of calculating the correlation coefficient of each candidate waveform segment and the standard waveform template and selecting the candidate waveform segment with the largest correlation coefficient as the effective waveform data segment is described in detail below, and will not be repeated here.

[0044] It should be further pointed out that the starting point and the ending point of the rising edge and the falling edge of the waveform are extracted by the difference threshold method according to the denoised waveform data; the current waveform data can be obtained in combination with the voltage waveform data, and the current waveform data is used to verify the reliability of the starting point and the ending point data. Among them, the candidate waveform segment is mainly the voltage waveform candidate segment.

[0045] In some embodiments, the calculation of the correlation coefficient of each candidate waveform segment and the standard waveform template, and the selection of the candidate waveform segment with the largest correlation coefficient as the effective waveform data segment, includes the following steps: Resampling processing based on linear interpolation is performed on the standard waveform template to make the time axis length consistent with the current candidate waveform segment, and a resampled standard waveform template is obtained; The resampled standard waveform template and the candidate waveform segment are subjected to amplitude alignment processing based on mean shift, and the direct current components of the two waveforms are adjusted to zero mean value, and a zero mean standard waveform and a zero mean candidate waveform are obtained; The zero mean standard waveform and the zero mean candidate waveform are subjected to correlation coefficient calculation processing based on Pearson product moment formula, and a correlation coefficient value ρ is obtained; among a plurality of correlation coefficient values ρ, the candidate waveform segment with the largest correlation coefficient is selected as the effective waveform data segment.

[0046] Please refer to Figure 2 , Figure 2 The voltage waveform schematic diagram of the IGBT module provided by the embodiment of the present application, in some embodiments, based on the effective waveform data segment, the test setting parameter information of the IGBT module and a plurality of preset threshold values, the time parameter difference algorithm is used to obtain the turn-on time T1 and the turn-off time T2 of the IGBT module, including the following steps: The effective waveform data segment includes the waveform data of the collector-emitter voltage changing with time, and the 50% point of the rising edge of the voltage waveform data in the on process is located as the time starting point to, and the 50% point of the falling edge of the voltage waveform data in the off process is located as the time starting point tf; Taking the time point to as a reference point, the voltage waveform is reversely searched to find a time point t1 at which the voltage value first crosses a first preset threshold value, and is forwardly searched to find a time t2 at which the voltage value first stably reaches a second preset threshold value; According to the time point t1 and the time point t2, a time difference calculation process is performed to obtain a turn-on time T1 = t2 - t1; Taking the time point tf as a reference point, the voltage waveform data is reversely searched to find a time point t3 at which the voltage value first stably reaches a third preset threshold value, and is forwardly searched to find a time point t4 at which the voltage value first crosses a fourth preset threshold value; According to the time point t4 and the time point t3, a time difference calculation process is performed to obtain a turn-off time T2 = t4 - t3.

[0047] It should be noted that the effective waveform data segment includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as the time point to, and the 50% point of the falling edge of the voltage waveform data in the turn-off process is located as the time point tf. The specific method will be described in detail below, and will not be described here.

[0048] The reverse search refers to reverse search along the time axis, and the forward search refers to forward search along the time axis. Specifically, in the time point t1 of the first preset threshold value, the first preset threshold value is Vce = k1 x Vdc, wherein 0≤k1≤10%; in the time point t2 of the second preset threshold value, the second preset threshold value is Vce = k2 x Vdc, wherein 90%≤k2≤100%.

[0049] In the time point t3 of the third preset threshold value, the third preset threshold value is Vce = k3 x Vdc, wherein 90%≤k3≤100%; in the time point t4 of the fourth preset threshold value, the fourth preset threshold value is Vce = k4 x Vdc, wherein 0≤k4≤10%.

[0050] Optionally, k1 is 5%, k2 is 90%, k3 is 95%, and k4 is 10%. It can be understood that the setting of the plurality of preset threshold values can clearly and consistently define the turn-on and turn-off processes, avoid errors caused by data fluctuations, and ensure the repeatability and stability of the test results.

[0051] In some embodiments, the effective waveform data segment includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as the time point to, and the 50% point of the falling edge of the voltage waveform data in the turn-off process is located as the time point tf, including the following steps: extracting a rising edge interval and a falling edge interval in the voltage waveform data, and obtaining a rising edge data sequence and a falling edge data sequence respectively; sorting the rising edge data sequence to obtain an ordered sequence arranged in ascending order of voltage values, and calculating a rising edge median voltage value of the ordered sequence; finding a plurality of data points in the rising edge data sequence whose voltage values are closest to the rising edge median voltage value, calculating a median of time coordinates of the data points, and obtaining a time start point to; sorting the falling edge data sequence to obtain an ordered sequence arranged in descending order of voltage values, and calculating a falling edge median voltage value of the ordered sequence; finding a plurality of data points in the falling edge data sequence whose voltage values are closest to the falling edge median voltage value, calculating a median of time coordinates of the data points, and obtaining a time start point tf.

[0052] It can be understood that the above method steps clarify the calculation of the time start point to and the time start point tf, improve the consistency and repeatability of the test process, and ensure the high uniformity of the measurement standards between different modules and different tests.

[0053] In some embodiments, the generating, based on the turn-on time T1, the turn-off time T2, and the identity information, a switch time feature point recorded with the identity information, includes the following steps: performing dimension unification and precision standardization processing on the turn-on time T1 and the turn-off time T2 to obtain a standardized turn-on time T1 and a standardized turn-off time T2; performing two-dimensional feature space coordinate construction processing with the standardized turn-on time T1 as the horizontal coordinate and the standardized turn-off time T2 as the vertical coordinate to obtain a switch time feature point P = (T1, T2); data binding the switch characteristic feature point P with the identity information.

[0054] It can be understood that the above method steps complete the two-dimensional space construction of the switch time feature point P, and prepare for subsequent consistency grouping for the P point.

[0055] In some embodiments, the generating, based on the switch time feature point P, a grouping mapping table including a plurality of group information by using a grouping decision algorithm, wherein the group information stores the identity information; and classifying the IGBT module based on the group information includes the following steps: According to preset grid starting coordinates (T1s, T2s), grid width ΔT1 and grid length ΔT2, a uniform grid array of N×M is constructed, where N is the number of grids in the on-time T1 direction, and M is the number of grids in the off-time T2 direction; A unique group number Gij is assigned to each grid unit, where i is a row index, and 0≤i<N; j is a column index, and 0≤j<M; a mapping relationship table of grid coordinates and group numbers is established; The switching time feature points P(T1, T2) of the IGBT module to be classified are obtained, and the grid coordinates (i, j) thereof are calculated, where: i = floor((T1 - T1s) / ΔT1), j = floor((T2 - T2s) / ΔT2); The corresponding group number Gij is queried from the mapping relationship table according to the grid coordinates (i, j); The identity information and the group number Gij are associated and stored in a grouping mapping table, and the group number Gij corresponding to the identity information is displayed to a test record processing library, thereby completing the consistency classification of the IGBT module.

[0056] It can be understood that in the embodiment, i and j are integers obtained by rounding down. Alternatively, the preset grid starting coordinates (T1s, T2s) can be (0, 0), or the minimum value of T1 and the minimum value of T2 obtained according to empirical values and rounded down.

[0057] It can also be understood that in the embodiment, the classification standard is objectively defined as grid parameters (T1s, T2s, ΔT1, ΔT2) in advance. Which group each module belongs to is completely determined by its own parameters and the fixed grid rule, thereby completely eliminating the problem of inconsistent classification standards caused by experience and subjective judgment differences of different operators. Regardless of who operates, the same module will be classified into the same group, thereby ensuring the absolute objectivity and repeatability of the classification result, and being conducive to large-scale industrial application.

[0058] Please refer to Figure 3 , Figure 3 The structure of an IGBT module consistency classification device 100 provided in the embodiment is shown in a schematic block diagram as Figure 3 The IGBT module consistency classification device 100 includes: A first obtaining module 110 is configured to obtain identity information of an IGBT module to be tested, and generate a test record processing library based on the identity information; the test record processing library is in one-to-one correspondence with the IGBT module. The second acquisition module 120 is configured to acquire test setting parameter information of the IGBT module, and generate a control driving signal applied to the IGBT module based on the test setting parameter information. The collection module 130 is configured to collect input and output signals of the collector-emitter of the IGBT module, generate raw waveform data to be analyzed, and upload the raw waveform data to a test record processing library. The analysis module 140 is configured to analyze the raw waveform data, and intercept an effective waveform data segment corresponding to the identity information. The processing module 150 is configured to obtain turn-on time T1 and turn-off time T2 of the IGBT module by using a time parameter difference algorithm based on the effective waveform data segment, the test setting parameter information of the IGBT module, and a plurality of preset threshold values. The first generation module 160 is configured to generate a switching time feature point P = (T1, T2) having the identity information recorded therein based on the turn-on time T1, the turn-off time T2, and the identity information. The second generation module 170 is configured to generate a grouping mapping table including a plurality of group information by using a grouping decision algorithm based on the switching time feature point P, wherein the group information stores the identity information; and classify the IGBT module based on the group information.

[0059] It should be noted that, for the convenience and brevity of description, the specific working processes of the above-described device and each module can refer to the corresponding processes in the foregoing embodiment of the IGBT module consistency classification method, which will not be described herein.

[0060] The IGBT module consistency classification device 100 provided in the foregoing embodiment can be implemented in the form of a computer program, which can run on an electronic device 200 as shown in the specification. Figure 3 The electronic device 200 provided in the embodiment of the present application is shown in the form of a structural schematic block diagram of an electronic device 200, which includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected through a system bus 203. The memory 202 can include a non-volatile storage medium and an internal memory.

[0061] Please refer to Figure 4 , Figure 4 The electronic device 200 provided in the embodiment of the present application is shown in the form of a structural schematic block diagram of an electronic device 200, which includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected through a system bus 203. The memory 202 can include a non-volatile storage medium and an internal memory.

[0062] The non-volatile storage medium can store a computer program. The computer program includes program instructions, which, when executed by the processor 201, can cause the processor 201 to perform any of the above-mentioned IGBT module consistency classification methods.

[0063] The processor 201 is configured to provide computing and control capabilities to support the operation of the entire electronic device 200.

[0064] The internal memory provides an environment for the running of a computer program in a non-volatile storage medium, which, when executed by the processor 201, can cause the processor 201 to perform any of the above IGBT module consistency classification methods.

[0065] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the electronic device 200 involved in the scheme of the present application. The specific electronic device 200 can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0066] It should be understood that the processor 201 can be a central processing unit (CPU), and the processor 201 can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0067] In some embodiments, the processor 201 is configured to run a computer program stored in the memory to implement the following steps: Obtain the identity information of the IGBT module to be tested, and generate a test record processing library based on the identity information; wherein the test record processing library corresponds to the IGBT module one by one; Obtain the test setting parameter information of the IGBT module, and generate a control driving signal applied to the IGBT module based on the test setting parameter information; Collect the input and output signals of the collector-emitter of the IGBT module, generate raw waveform data to be analyzed, and upload the raw waveform data to the test record processing library; Analyze the raw waveform data, and intercept the effective waveform data segment corresponding to the identity information; Based on the effective waveform data segment, the test setting parameter information of the IGBT module and a plurality of preset threshold values, a time parameter difference algorithm is used to obtain turn-on time T1 and turn-off time T2 of the IGBT module; Based on the turn-on time T1, the turn-off time T2 and the identity information, a switch time characteristic point P = (T1, T2) recording the identity information is generated; Based on the switch time characteristic point P, a grouping mapping table including a plurality of group information is generated by using a grouping decision algorithm, wherein the group information stores the identity information; and the IGBT module is classified based on the group information.

[0068] It should be noted that, for the convenience and brevity of description, the specific working process of the electronic device 200 described above can refer to the corresponding process of the IGBT module consistency classification method, which will not be described here.

[0069] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An IGBT module uniformity classification method, characterized by, The method comprises the following steps: acquiring identity information of an IGBT module to be tested, and generating a test record processing library based on the identity information; the test record processing library corresponds to the IGBT module one by one; acquiring test setting parameter information of the IGBT module, and generating a control driving signal applied to the IGBT module based on the test setting parameter information; collecting input and output signals of a collector-emitter of the IGBT module, generating original waveform data to be analyzed, and uploading the original waveform data to the test record processing library; analyzing the original waveform data, and intercepting an effective waveform data segment corresponding to the identity information; based on the effective waveform data segment, the test setting parameter information of the IGBT module, and a plurality of preset threshold values, obtaining turn-on time T1 and turn-off time T2 of the IGBT module by using a time parameter difference algorithm; based on the turn-on time T1, the turn-off time T2, and the identity information, generating a switching time feature point P = (T1, T2) having the identity information recorded; based on the switching time feature point P, generating a grouping mapping table including a plurality of group information by using a grouping decision algorithm, wherein the group information stores the identity information; and classifying the IGBT module based on the group information.

2. The IGBT module uniformity classification method of claim 1, wherein, The analysis of the original waveform data and the interception of the effective waveform data segment corresponding to the identity information comprise the following steps: performing wavelet transform denoising processing on the original waveform data to obtain denoised waveform data; extracting starting points and ending points of rising edges and falling edges of the waveform by using a difference threshold method according to the denoised waveform data; segmenting and intercepting the denoised waveform data according to the starting points and the ending points to obtain a plurality of candidate waveform segments; calling a corresponding standard waveform template from the test record processing library according to the identity information; calculating correlation coefficients of each candidate waveform segment and the standard waveform template, and selecting a candidate waveform segment with the largest correlation coefficient as the effective waveform data segment.

3. The IGBT module uniformity classification method according to claim 2, characterized by, The calculation of the correlation coefficients of each candidate waveform segment and the standard waveform template, and the selection of the candidate waveform segment with the largest correlation coefficient as the effective waveform data segment comprise the following steps: performing resampling processing on the standard waveform template based on linear interpolation to make the length of the time axis consistent with that of the current candidate waveform segment, to obtain a resampled standard waveform template; performing amplitude alignment processing based on mean translation on the resampled standard waveform template and the candidate waveform segment, adjusting the direct current components of the two waveforms to zero mean, to obtain a zero-mean standard waveform and a zero-mean candidate waveform; performing correlation coefficient calculation processing based on the Pearson product-moment formula on the zero-mean standard waveform and the zero-mean candidate waveform, to obtain a correlation coefficient value ρ; and selecting a candidate waveform segment with the largest correlation coefficient from a plurality of correlation coefficient values ρ as the effective waveform data segment.

4. The IGBT module uniformity classification method of claim 1, wherein The obtaining of the turn-on time T1 and the turn-off time T2 of the IGBT module based on the effective waveform data segment, the test setting parameter information of the IGBT module, and a plurality of preset threshold values by using a time parameter difference algorithm comprises the following steps: The effective waveform data section includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as a time starting point to, and the 50% point of the falling edge of the turn-off process voltage waveform data is located as a time starting point tf; With the time starting point to as a reference point, the voltage waveform is processed in reverse search to find a time point t1 at which the voltage value first crosses a first preset threshold value, and is processed in forward search to find a time t2 at which the voltage value first stably reaches a second preset threshold value; According to the time point t1 and the time point t2, time difference calculation processing is performed to obtain a turn-on time T1 = t2 - t1; With the time starting point tf as a reference point, the voltage waveform data is processed in reverse search to find a time point t3 at which the voltage value first stably reaches a third preset threshold value, and is processed in forward search to find a time point t4 at which the voltage value first crosses a fourth preset threshold value; According to the time point t4 and the time point t3, time difference calculation processing is performed to obtain a turn-off time T2 = t4 - t3.

5. The IGBT module uniformity classification method according to claim 4, characterized by, The effective waveform data section includes collector-emitter voltage waveform data changing with time, and the 50% point of the rising edge of the turn-on process voltage waveform data is located as a time starting point to, and the 50% point of the falling edge of the turn-off process voltage waveform data is located as a time starting point tf includes: The rising edge interval and the falling edge interval in the voltage waveform data are extracted to obtain a rising edge data sequence and a falling edge data sequence, respectively; The rising edge data sequence is sorted to obtain an ordered sequence arranged in ascending order of voltage values, and a median voltage value of the rising edge of the ordered sequence is calculated; A plurality of data points in the rising edge data sequence whose voltage values are closest to the median voltage value of the rising edge are found, and a median of the time coordinates of these data points is calculated to obtain the time starting point to; The falling edge data sequence is sorted to obtain an ordered sequence arranged in descending order of voltage values, and a median voltage value of the falling edge of the ordered sequence is calculated; A plurality of data points in the falling edge data sequence whose voltage values are closest to the median voltage value of the falling edge are found, and a median of the time coordinates of these data points is calculated to obtain the time starting point tf.

6. The IGBT module consistency classification method of claim 1, wherein, The switch time feature point based on the turn-on time T1, the turn-off time T2, and the identity information includes: The turn-on time T1 and the turn-off time T2 are processed for dimension unification and precision standardization to obtain a standardized turn-on time T1 and a standardized turn-off time T2; The standardized turn-on time T1 is taken as the horizontal coordinate, and the standardized turn-off time T2 is taken as the vertical coordinate, and two-dimensional feature space coordinate construction processing is performed to obtain a switch time feature point P = (T1, T2); The switch characteristic feature point P is data bound with the identity information.

7. The IGBT module consistency classification method of claim 1, wherein, The grouping decision algorithm is used to generate a grouping mapping table including a plurality of group information based on the switching time feature point P, wherein the group information stores the identity information; and the IGBT module is classified based on the group information, including: According to a preset grid starting point coordinate (T1s, T2s), a grid width ΔT1 and a grid length ΔT2, an N×M uniform grid array is constructed, wherein N is the number of grid in the turn-on time T1 direction, and M is the number of grid in the turn-off time T2 direction; A unique group number G ij is assigned to each grid unit, wherein i is a row index, and 0≤i<N; j is a column index, and 0≤j<M; a mapping relationship table of grid coordinates and group numbers is established; The switching time feature point P (T1, T2) of the IGBT module to be classified is obtained, and the grid coordinates (i, j) thereof are calculated, wherein: i = floor((T1 - T1s) / ΔT1), j = floor((T2 - T2s) / ΔT2); The corresponding group number G ij is queried from the mapping relationship table according to the grid coordinates (i, j); The identity information and the group number G ij are stored in the grouping mapping table in association, and the group number G ij corresponding to the identity information is displayed to the test record processing library, thereby completing the consistency classification of the IGBT module.

8. An IGBT module uniformity classification apparatus characterized by comprising: Including: A first acquisition module is configured to acquire identity information of an IGBT module to be tested, and generate a test record processing library based on the identity information; wherein the test record processing library corresponds to the IGBT module one by one; A second acquisition module is configured to acquire test setting parameter information of the IGBT module, and generate a control driving signal applied to the IGBT module based on the test setting parameter information; An acquisition module is configured to acquire input and output signals of a collector-emitter of the IGBT module, generate original waveform data to be analyzed, and upload the original waveform data to the test record processing library; An analysis module is configured to analyze the original waveform data, and intercept an effective waveform data segment corresponding to the identity information; A processing module is configured to obtain turn-on time T1 and turn-off time T2 of the IGBT module by using a time parameter difference algorithm based on the effective waveform data segment, the test setting parameter information of the IGBT module and a plurality of preset threshold values; A first generation module is configured to generate a switching time feature point P = (T1, T2) recording the identity information based on the turn-on time T1, the turn-off time T2 and the identity information; A second generation module is configured to generate a grouping mapping table including a plurality of group information by using a grouping decision algorithm based on the switching time feature point P, wherein the group information stores the identity information; and the IGBT module is classified based on the group information.

9. An electronic device, comprising: The electronic device comprises a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program, when executed by the processor, implements the IGBT module consistency classification method according to any one of claims 1 to 7.

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