A vehicle-mounted high-voltage connector and its processing method

Abstract

The present invention discloses a vehicle-mounted high-voltage connector and its processing method, including forming a preset microtrace pattern on the terminal contact surface of a sample to obtain a microtrace impedance gradient structure with preset non-linear resistance characteristics; setting a temperature response channel network in the insulating housing according to the current distribution prediction mode of the microtrace impedance gradient structure; inputting an alternating current test signal to the connector, collecting impedance data, and generating a three-dimensional characteristic map of impedance-frequency-voltage; applying a pulsed current to the connector based on the key frequency points of the characteristic map, collecting temperature change data, and obtaining a temperature-time response curve; performing a sequential comparative analysis on the characteristic map and the response curve, calculating the correlation parameter, calibrating the hot spot position corresponding to the non-linear impedance change region, and generating a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch. The technical solution of the present invention can effectively identify and predict the non-linear impedance change of the connector and the local hot spot problem caused by it.

Description

Technical Field

[0001] The present invention relates to the technical field of on-vehicle high-voltage connector detection, and particularly to an on-vehicle high-voltage connector and a processing method thereof. Background Art

[0002] On-vehicle high-voltage connectors are key electrical components in the power systems of electric vehicles and hybrid electric vehicles. They are mainly used to connect high-voltage battery packs, inverters, motor controllers, and other high-voltage electrical components to ensure the safe and effective transmission of high-voltage current. Such connectors usually operate in a voltage environment of three hundred to one thousand volts and need to meet strict safety standards, insulation performance, and reliability requirements.

[0003] In the prior art, during the manufacturing and detection processes of on-vehicle high-voltage connectors, attention is mainly paid to static electrical performance indicators, such as the detection of parameters like insulation resistance, dielectric strength, and contact resistance. However, these static detection methods are difficult to evaluate the non-linear impedance change problems that occur during the actual operation of the connectors. When the connectors alternately carry high and low currents for a long time, non-linear impedance changes will occur on the metal contact surface due to oxidation processes, fretting wear, and electromigration effects. This change is not a simple linear degradation but forms an abnormal impedance characteristic curve at specific frequencies or current densities, which in turn causes local hot spots inside the connectors. Since these hot spots are shielded by the structure, the heat will be absorbed and dispersed during the outward heat conduction process, resulting in the inability of external temperature detection means to effectively identify them. And these hidden hot spots will accelerate the local aging of the insulating material and may ultimately lead to insulation failure, posing a safety hazard. Therefore, how to identify and predict this non-linear impedance change and the resulting difficult-to-detect local hot spot problems through reasonable detection means during the connector processing has become an urgent technical problem to be solved. Summary of the Invention

[0004] The main object of the present invention is to solve the technical problem that the existing on-vehicle high-voltage connector detection methods cannot effectively evaluate the non-linear impedance change during the actual operation and the resulting difficult-to-detect local hot spot problems.

[0005] In a first aspect of the present invention, a processing method of an on-vehicle high-voltage connector is provided. The processing method of the on-vehicle high-voltage connector includes:

[0006] Form a preset microtrace pattern on the terminal contact surface of the sample to obtain a microtrace impedance gradient structure with preset non-linear resistance characteristics;

[0007] According to the current distribution prediction mode of the microtrace impedance gradient structure, set a plurality of microchannels in the connector insulating housing of the sample, inject a conductive thermosensitive composite material into the microchannels and perform a curing treatment to form a temperature response channel network covering potential hot spot areas;

[0008] An AC test signal within a preset frequency range is input into the connector of the sample, impedance data of the connector at each frequency point and within a preset voltage range is collected, and a three-dimensional impedance-frequency-voltage characteristic map characterizing the impedance characteristics of the connector is generated by combining the geometric characteristics of the microtrace impedance gradient structure;

[0009] Based on the key frequency points of the three-dimensional impedance-frequency-voltage characteristic map, multiple groups of pulsed currents with preset amplitudes and durations are applied to the connector of the sample, and temperature change data of key points inside the connector is collected through the temperature response channel network to obtain a temperature-time response curve characterizing the thermal characteristics of the connector;

[0010] The three-dimensional impedance-frequency-voltage characteristic map and the temperature-time response curve are subjected to sequential comparative analysis, the correlation parameter between the impedance change and the temperature change of the connector is calculated, the hot spot position corresponding to the non-linear impedance change region in the connector is calibrated, and a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch is generated according to the impedance change characteristics and temperature response characteristics of the hot spot position.

[0011] Preferably, forming a preset microtrace pattern on the terminal contact surface of the sample to obtain a microtrace impedance gradient structure with preset non-linear resistance characteristics includes:

[0012] Determine the sample selection criteria according to batch process parameters and material characteristics, and extract sample connectors not less than 3% of the total batch from the in-vehicle high-voltage connectors of the same batch;

[0013] Remove the oxide layer on the surface of the copper alloy terminal matrix of the sample connector, measure the surface roughness of the terminal matrix surface, and obtain a clean terminal surface with a surface roughness within a preset range;

[0014] Preset the contact point positions on the clean terminal surface, and use an etching process to form a radial microtrace pattern centered on the contact point positions. Control the depth of the radial microtrace pattern to gradually decrease outward from the contact point positions according to a preset attenuation coefficient, and control the spacing of the radial microtrace pattern to gradually increase outward from the contact point positions according to a preset growth coefficient;

[0015] Measure the depth distribution and lateral topography of the radial microtrace pattern, calculate the depth range, spacing range and lateral distribution uniformity of the microtraces based on the results of the depth distribution measurement and the lateral topography measurement, and obtain a microtrace impedance gradient structure that meets the preset uniformity requirements.

[0016] Preferably, on the surface of the clean terminal, a contact point position is preset, and an etching process is used to form a radial micro-scar pattern centered on the contact point position. The depth of the radial micro-scar pattern is controlled to gradually decrease outward from the contact point position according to a preset attenuation coefficient, and the spacing of the radial micro-scar pattern is controlled to gradually increase outward from the contact point position according to a preset growth coefficient, including:

[0017] Measure the current density distribution on the surface of the clean terminal, and determine the point with the maximum current density as the contact point position;

[0018] Divide multiple annular regions around the contact point position, and calculate the radius of each annular region according to a preset growth coefficient;

[0019] Adjust the etching current density, etching solution concentration, and etching time to form a radial micro-scar pattern with a depth decreasing according to a preset attenuation coefficient in the annular region, and at the same time form a radial micro-scar pattern with a spacing increasing according to the preset growth coefficient.

[0020] Preferably, according to the current distribution prediction mode of the micro-scar impedance gradient structure, a plurality of micro-channels are arranged in the connector insulating housing of the sample, and a conductive thermosensitive composite material is injected into the micro-channels and cured to form a temperature response channel network covering potential hot spot regions, including:

[0021] Collect impedance distribution data of the micro-scar impedance gradient structure under different current densities, and determine the current density gradient change region according to the impedance distribution data;

[0022] Set a multi-level micro-channel network in the connector insulating housing of the sample according to the current density gradient change region. The multi-level micro-channel network includes main channels and branch channels, and the cross-sectional area of the branch channels gradually decreases along the extension direction;

[0023] Prepare a conductive thermosensitive composite material including a conductive polymer matrix and nano-scale thermosensitive materials according to the distribution characteristics of the multi-level micro-channel network. By adjusting the mass ratio of the conductive polymer matrix to the nano-scale thermosensitive materials, the resistance temperature coefficient of the conductive thermosensitive composite material is matched with the current density gradient change region;

[0024] Perform a vacuum treatment on the multi-level micro-channel network under a first preset vacuum degree, and inject the conductive thermosensitive composite material into the multi-level micro-channel network under a second preset vacuum degree to form an initial channel network covering the current density gradient change region;

[0025] Perform a step - temperature curing process on the initial channel network, measure the change rate of the resistance value of the conductive thermosensitive composite material at each temperature step. When the change rate of the resistance value stabilizes within a preset range, enter the next temperature step to obtain a temperature - responsive channel network.

[0026] Preferably, a multi - level micro - channel network is arranged in the connector insulating housing of the sample according to the current density gradient change region. The multi - level micro - channel network includes a main channel and branch channels, and the cross - sectional area of the branch channels decreases gradually along the stretching direction, including:

[0027] Perform a zonal analysis on the current density gradient change region, mark the region where the change rate of the current density exceeds the third guiding value as the strong - change region, and the region where the change rate of the current density is lower than the third guiding value as the weak - change region;

[0028] According to the distribution of the strong - change region and the weak - change region, set the main channel in the strong - change region and the branch channels in the weak - change region;

[0029] Calculate the cross - sectional area decreasing coefficient of the branch channels according to the spatial distribution law of the current density gradient change region, so that the cross - sectional area of the branch channels decreases gradually from the connection with the main channel to the end to form the multi - level micro - channel network.

[0030] Preferably, an alternating - current test signal within a preset frequency range is input to the connector of the sample, impedance data of the connector at each frequency point and within a preset voltage range is collected, and combined with the geometric characteristics of the micro - trace impedance gradient structure, an impedance - frequency - voltage three - dimensional characteristic map representing the impedance characteristics of the connector is generated, including:

[0031] According to the micro - trace depth distribution of the micro - trace impedance gradient structure, determine the frequency - response characteristic points corresponding to different depth regions, apply multiple groups of alternating - current test signals to the connector of the sample, and collect impedance data at each frequency - response characteristic point to obtain the mapping relationship between the micro - trace depth and the frequency response;

[0032] Apply an alternating - current test signal with an amplitude increasing gradually within a preset voltage range to the connector of the sample, measure the impedance change trend of the frequency - response characteristic points at each voltage amplitude to obtain a set of response curves representing the non - linear impedance characteristics;

[0033] Analyze the change rate of the set of response curves, identify the points where the impedance change rate exceeds a predetermined threshold as impedance mutation points, increase the sampling frequency and voltage density near the impedance mutation points, and perform a local fine scan on the connector of the sample to obtain high - resolution impedance anomaly characteristic data;

[0034] Based on the mapping relationship between the microtrace depth and the frequency response, spatial localization analysis is performed on the high-resolution impedance anomaly characteristic data, the corresponding relationship between the impedance anomaly and the microtrace structure is established, and a three-dimensional characteristic map of impedance-frequency-voltage representing the impedance characteristics of the connector is generated.

[0035] Preferably, based on the key frequency points of the three-dimensional characteristic map of impedance-frequency-voltage, multiple groups of pulsed currents with preset amplitudes and durations are applied to the connector of the sample, and the temperature change data of key points inside the connector are collected through the temperature response channel network, and a temperature-time response curve representing the thermal characteristics of the connector is obtained, including:

[0036] Based on the key frequency points in the three-dimensional characteristic map of impedance-frequency-voltage, a pulsed current excitation sequence including a single amplitude increasing sequence, an alternating high and low amplitude sequence, and a random amplitude sequence is generated, and the amplitude range of the pulsed current excitation sequence covers 20% to 120% of the rated current of the connector;

[0037] According to the spatial distribution of the temperature response channel network, a temperature acquisition coordinate of the key points inside the connector is established, and the temperature response data of each temperature acquisition coordinate in the temperature response channel network are collected during the application of the pulsed current excitation;

[0038] The temperature response data is analyzed in real time. When it is detected that the temperature rising rate exceeds the first preset threshold, the temperature sampling frequency is increased. When it is detected that the temperature falling rate exceeds the second preset threshold, the initial sampling frequency is restored, and a temperature response data set containing temperature mutation characteristics is obtained;

[0039] According to the temperature response data set, the temperature response delay time and temperature decay coefficient of each key point inside the connector are calculated, a temperature propagation path map of the connector is established, and a temperature-time response curve representing the thermal characteristics of the connector is generated.

[0040] Preferably, the three-dimensional characteristic map of impedance-frequency-voltage and the temperature-time response curve are subjected to time-series comparative analysis, the correlation parameter between the impedance change and the temperature change of the connector is calculated, the hot spot position corresponding to the non-linear impedance change region in the connector is calibrated, and a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch is generated according to the impedance change characteristics and temperature response characteristics of the hot spot position, including:

[0041] Perform time-domain mapping on the three-dimensional characteristic map of impedance-frequency-voltage, and based on the spatial distribution of the microtrace impedance gradient structure, construct a multi-dimensional impedance response matrix reflecting the time-series characteristics of impedance changes in different regions;

[0042] According to the topological structure of the temperature response channel network, spatially analyze the temperature-time response curve, establish a propagation path map of temperature changes, and extract the temperature gradients and propagation time delays on each propagation path;

[0043] Perform spatial registration on the multi-dimensional impedance response matrix and the temperature propagation path map, identify the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determine the key regions where impedance changes induce temperature responses;

[0044] Perform impedance-temperature response feature decomposition on the key regions, extract impedance mutation features, temperature response delay features, and temperature cumulative effect features, and establish a multi-dimensional feature space for non-linear impedance anomalies;

[0045] Based on the multi-dimensional feature space, construct a feature fingerprint mapping function, map the combination of the impedance mutation feature, temperature response delay feature, and temperature cumulative effect feature into a quantifiable sequence of feature parameters, and generate a feature fingerprint for detecting non-linear impedance anomalies in connectors of the same batch.

[0046] Preferably, the performing spatial registration on the multi-dimensional impedance response matrix and the temperature propagation path map, identifying the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determining the key regions where impedance changes induce temperature responses includes:

[0047] Convert the spatial distribution data of the multi-dimensional impedance response matrix into impedance gradient distribution data;

[0048] Calculate the temperature propagation rate distribution data according to the temperature propagation path map;

[0049] Perform spatial coordinate mapping on the impedance gradient distribution data and the temperature propagation rate distribution data, and calculate their spatial overlap degree and temporal correlation degree;

[0050] Calculate the coupling coefficient according to the spatial overlap degree and the temporal correlation degree, and based on the coupling coefficient, identify the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determine the key regions where impedance changes induce temperature responses.

[0051] The second aspect of the present invention provides a vehicle-mounted high-voltage connector, and the processing process of the vehicle-mounted high-voltage connector adopts the above-mentioned processing method of the vehicle-mounted high-voltage connector.

[0052] The technical solution provided by the embodiments of the present application first forms a preset microtrace pattern on the contact surface of the sample terminal to create a microtrace impedance gradient structure with predictable non-linear resistance characteristics. This microtrace structure transforms the problem of uncontrollable resistance characteristics of the connector into predictable characteristics, providing a basic condition for subsequent detection. When the connector bears different current densities during actual operation, this preset microtrace structure makes the current distribution controllable and the resistance change trend predictable. By forming radial microtraces with both depth and spacing varying in a gradient on the terminal surface, the current distribution follows a specific path when diffusing from the center to the outside, so that the non-linear change of the impedance characteristics occurs in the expected area rather than randomly distributed.

[0053] Based on the current distribution prediction mode of the microtrace impedance gradient structure, the solution sets multiple microchannels in the insulating housing of the connector and injects a conductive thermosensitive composite material to form a temperature response channel network covering potential hot spot areas. This temperature response channel network endows the connector with the "self-sensing" ability, enabling the internal temperature change to be monitored. The resistance value of the conductive thermosensitive composite material changes with temperature. When hot spots are generated inside the connector due to non-linear impedance changes, the resistance change of the thermosensitive material can indicate the location of the hot spots and the temperature change trend. The microchannel network covers the key areas where hot spots may be generated through current distribution prediction, enabling those hot spots that are shielded by the connector structure and difficult to be identified by external temperature detection means to be "internally sensed".

[0054] The solution inputs an alternating current test signal within a preset frequency range to the sample connector, collects impedance data at each frequency point and within a preset voltage range, and generates a three-dimensional characteristic map of impedance-frequency-voltage. This multi-frequency point test method breaks through the limitations of traditional single-frequency testing and can comprehensively capture the impedance characteristics of the connector at different frequencies. Non-linear impedance changes often manifest as abnormal impedance responses at specific frequency points or specific voltages, and these hidden problems cannot be discovered by traditional single-condition testing. By means of scanning testing and combining with the geometric characteristics of the microtrace structure, the corresponding relationship between impedance anomalies and physical structures can be established to determine the accurate location of impedance changes. This three-dimensional characteristic map of impedance-frequency-voltage contains rich impedance change information, providing a data basis for subsequent non-linear impedance analysis.

[0055] Based on the key frequency points of the impedance characteristic map, the solution applies multiple sets of pulsed currents with preset amplitudes and durations to the sample connector, collects the temperature change data of the internal key points through the temperature response channel network, and obtains the temperature-time response curve. This step simulates the dynamic current fluctuation situation faced by the connector in the actual working environment, and can induce potential non-linear impedance changes and the resulting hot spot problems. By using various pulse sequences (such as a single amplitude increasing sequence, an alternating high and low amplitude sequence, and a random amplitude sequence), the thermal response characteristics of the connector under various working scenarios can be comprehensively evaluated. The temperature change data monitored in real time by the temperature response channel network directly reflects the thermal state inside the connector, especially those hot spot areas shielded by the structure. Parameters such as the temperature rise rate, peak temperature, and temperature decay characteristics in the temperature-time response curve can indicate the formation process and propagation path of the hot spots.

[0056] The solution conducts a sequential comparative analysis of the impedance characteristic map and the temperature response curve, calculates the correlation parameters between the impedance change and the temperature change of the connector, and calibrates the hot spot positions corresponding to the non-linear impedance change regions. Through the comparison in the time series, the causal relationship between the impedance change and the temperature change can be determined, especially identifying the regions where the impedance change precedes the temperature change, which are usually the sources of non-linear impedance changes. The impedance-thermal correlation analysis establishes the mapping relationship between the two physical quantities, enabling the prediction of the formation trend of hot spots through the impedance characteristics. For the calibrated hot spot positions, extract their impedance change characteristics and temperature response characteristics, and generate feature fingerprints for detecting non-linear impedance anomalies in connectors of the same batch. Such feature fingerprints contain multi-dimensional information such as impedance mutation characteristics, temperature response delay characteristics, and temperature cumulative effect characteristics, providing an effective tool for quality control in mass production. Description of the Drawings

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0058] Figure 1 It is a schematic diagram of an embodiment of the processing method of the in-vehicle high-voltage connector in the embodiment of the present invention.

[0059] The realization, functional characteristics, and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the drawings. Detailed Embodiments

[0060] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0061] It should be noted that if there are directional indications (such as up, down, left, right, front, back,...) involved in the embodiments of the present invention, then the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0062] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, "and / or" throughout the text includes three scenarios. Taking A and / or B as an example, it includes the technical solution of A, the technical solution of B, and the technical solution that A and B are satisfied simultaneously. In addition, the technical solutions between the various embodiments can be combined with each other, which must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention.

[0063] An embodiment of the present application provides a processing method for an in-vehicle high-voltage connector. Figure 1 It is a flowchart of a processing method for an in-vehicle high-voltage connector provided by an embodiment of the present application. In this embodiment, the method includes:

[0064] Please refer to Figure 1 , forming a preset microtrace pattern on the terminal contact surface of the sample to obtain a microtrace impedance gradient structure with preset non-linear resistance characteristics;

[0065] In an embodiment of the present invention, the forming a preset microtrace pattern on the terminal contact surface of the sample to obtain a microtrace impedance gradient structure with preset non-linear resistance characteristics includes:

[0066] Determining the sample selection criteria according to the batch process parameters and material characteristics, and extracting sample connectors not less than 3% of the total batch quantity from the in-vehicle high-voltage connectors of the same batch;

[0067] Removing the oxide layer on the surface of the copper alloy terminal matrix of the sample connector, measuring the surface roughness of the terminal matrix surface, and obtaining a clean terminal surface with a surface roughness within a preset range;

[0068] Preset contact point positions on the surface of the cleaned terminals, and use an etching process to form a radial microtrace pattern centered on the contact point positions. Control the depth of the radial microtrace pattern to gradually decrease outward from the contact point positions according to a preset attenuation coefficient, and control the spacing of the radial microtrace pattern to gradually increase outward from the contact point positions according to a preset growth coefficient;

[0069] Perform depth distribution measurement and lateral topography measurement on the radial microtrace pattern, calculate the depth range, spacing range, and lateral distribution uniformity of the microtraces based on the results of the depth distribution measurement and the results of the lateral topography measurement, and obtain a microtrace impedance gradient structure that meets the preset uniformity requirements.

[0070] The following specifically describes the steps involved in the above embodiments:

[0071] Determine the sample selection criteria according to batch process parameters and material characteristics. When extracting sample connectors that are not less than 3% of the total batch quantity from in-vehicle high-voltage connectors of the same batch, it is first necessary to analyze the process stability data of the batch, including the fluctuation range of raw material element content (such as the standard deviation of copper content in copper alloy), manufacturing environment parameters (temperature, humidity changes), and process parameters (such as welding temperature, pressure, etc.). Calculate the process capability index (Process Capability Index, abbreviated as Cpk value) based on these data. When the Cpk value is greater than 1.33, it indicates that the process is stable and a lower sampling ratio can be adopted; when the Cpk value is between 1.0 - 1.33, the sampling ratio needs to be increased to 5%. The sample extraction follows the principle of stratified random sampling to ensure that the samples cover different periods of batch production (such as the first piece, middle piece, and last piece). For a specific batch, such as a batch of 1000 connectors, at least 30 samples need to be extracted, marked with the batch number and sample serial number respectively, and a traceable sample management system is established. For example, for a production batch of 5000 pieces, if the standard deviation of the copper alloy material uniformity test shows less than 0.5%, 150 pieces (3% of the total) can be extracted as test samples; if fluctuations are found in the raw material batch, the sampling ratio should be increased to 4 - 5%, that is, 200 - 250 pieces.

[0072] The process of removing the oxide layer on the surface of the copper alloy terminal substrate of the sample connector, measuring the surface roughness of the terminal substrate, and obtaining a clean terminal surface with a surface roughness within a preset range specifically includes: First, adopt a chemical cleaning method, immerse the sample in a 5-10% citric acid solution to remove the surface oxide layer, control the soaking time to be 5-8 minutes, and keep the solution temperature at 40±2°C. Subsequently, rinse the terminal surface with deionized water and dry it with nitrogen. After drying, use a surface roughness measuring instrument to measure the surface roughness of the terminal. Measure 5 lines along different directions (0°, 45°, 90°, 135°) to obtain the arithmetic mean roughness value (abbreviated as Ra value) and the maximum height of profile (abbreviated as Rz value). The roughness parameters of the terminal surface need to meet the preset range: the Ra value is controlled between 0.2-0.5 microns, and the Rz value does not exceed 2.5 microns. For example, after the cleaning treatment of a certain batch of samples, the measured average Ra value is 0.32 microns, the standard deviation is 0.04 microns, and the average Rz value is 1.85 microns, indicating that the surface roughness is within the ideal range and suitable for subsequent microtrace preparation. The setting of the roughness range of the surface treatment takes into account the precision requirements of microtrace processing and the stability requirements of electrical contact. Too low roughness will lead to a decrease in the contact area, and too high will affect the precise formation of microtraces.

[0073] During the process of presetting the contact point position on the clean terminal surface and forming a radial microtrace pattern centered on the contact point position by using an etching process, first determine the contact point position through current density analysis. The specific operation is as follows: Apply a rated current (such as 350 amperes) to the terminal, use an infrared thermal imager to monitor the temperature distribution on the terminal surface, and identify the highest temperature point as the point with the maximum current density, that is, the contact point position. After determining the contact point, divide multiple annular regions around it, and the radii of the annular regions increase according to a geometric progression. Subsequently, adopt an electrochemical etching technique, use a platinum electrode and an electrolyte containing 5-8% copper sulfate, and control the etching current density to change according to an exponential decay law in different annular regions. By precisely controlling the etching time of each region (30-45 seconds for the inner layer region, gradually decreasing to 10-15 seconds for the outer layer region), a radial microtrace pattern with a depth gradually decreasing from the inside to the outside is formed. For example, for a certain sample, the microtrace depth in the central region is designed to be 8 microns, the radius is 50 microns, the growth coefficient is selected as 0.2, and the decay coefficient is 0.25. Then the radius of the third annular region is approximately 86.4 microns, the microtrace depth is approximately 3.7 microns, and the microtrace spacing is approximately 21.6 microns. The selection of the etching parameters in this step is based on the current distribution characteristics of the connector. The central region bears the maximum current density and requires deeper microtraces to provide controllable impedance changes; while the current density in the edge region is smaller, and the microtrace depth is correspondingly reduced to maintain the overall conductivity.

[0074] When performing depth distribution measurement and lateral topography measurement on the radial micro-scar pattern, a confocal laser scanning microscope is used for three-dimensional surface scanning, and the scanning resolution is set to 0.1 μm (XY plane) and 0.01 μm (Z-axis direction). Eight measurement lines are taken at equal angular intervals along the radial direction, and 100 - 200 measurement points are obtained for each line. Based on the measurement data, the depth range, spacing range, and distribution uniformity of the micro-scars are calculated. The lateral distribution uniformity is evaluated by calculating the coefficient of variation (abbreviated as CV value) of the corresponding position parameters on the eight measurement lines. It is required that the CV value of the depth distribution is less than 10%, and the CV value of the spacing distribution is less than 15%. For example, after measurement of a certain sample, the depth distribution gradually decreases from 7.8 μm at the center to 2.1 μm at the edge, the spacing increases from 15.2 μm at the center to 28.6 μm at the edge, the CV of the depth distribution is 8.2%, and the CV of the spacing distribution is 12.5%, meeting the preset uniformity requirements. The design parameters of the micro-scar gradient structure are selected based on the current density distribution law and the hot spot formation mechanism. A depth range of 2 - 10 μm ensures sufficient contact surface change without affecting the basic electrical conductivity, and a spacing of 15 - 30 μm balances the number of contact points and the requirements of heat diffusion efficiency. The precise control of such micro-scar geometric parameters is crucial for achieving the expected non-linear impedance characteristics. Excessive parameter deviation will cause the actual current distribution to deviate from the prediction model, affecting the accuracy of subsequent hot spot detection.

[0075] In an embodiment of the present invention, the contact point positions are preset on the clean terminal surface, and an etching process is used to form a radial micro-scar pattern centered on the contact point positions. The depth of the radial micro-scar pattern is controlled to gradually decrease outward from the contact point positions according to a preset attenuation coefficient, and the spacing of the radial micro-scar pattern is controlled to gradually increase outward from the contact point positions according to a preset growth coefficient, including:

[0076] Perform current density distribution measurement on the clean terminal surface, and determine the point with the maximum current density as the contact point position;

[0077] Divide multiple annular regions around the contact point positions, and calculate the radius of each annular region according to a preset growth coefficient;

[0078] Adjust the etching current density, etching solution concentration, and etching time to form a radial micro-scar pattern with a depth decreasing according to a preset attenuation coefficient within the annular regions, and at the same time form a radial micro-scar pattern with a spacing increasing according to the preset growth coefficient.

[0079] The following specifically describes the steps involved in the above embodiment:

[0080] The process of measuring the current density distribution on the clean terminal surface and determining the position of the contact point by identifying the point with the maximum current density uses an electrical-thermal infrared combined measurement method. First, the terminal is fixed on a special fixture, and a rated current (350 amperes) is applied to the terminal through a high-precision DC power supply. At the same time, a thermocouple is used to monitor the overall temperature of the terminal to prevent overheating. An infrared thermal imager (spatial resolution 0.1 mm, temperature accuracy ±0.5 °C) is used to collect the temperature distribution image of the terminal surface in real time, record the temperature changes within 10 - 15 seconds, and then the temperature distribution data is obtained through processing with thermal analysis software. Since there is a positive correlation between the current density and the local temperature rise, the point with the highest temperature corresponds to the point with the maximum current density. For example, when measuring a certain in-vehicle high-voltage connector terminal, after applying 300 amperes of current for 5 seconds, an obvious temperature gradient appears on the terminal surface. The temperature in the central area reaches 48.3 °C, and the temperature in the edge area is 36.7 °C. The position of the contact point is determined by accurately locating the temperature peak position (X = 3.78 mm, Y = 2.15 mm). This measurement method avoids the complexity of direct measurement of traditional current density and accurately reflects the current distribution characteristics under the actual working conditions.

[0081] Multiple annular regions are divided around the position of the contact point, and the radius of each annular region is calculated in a geometric increasing pattern according to a preset growth factor. Taking the determined contact point as the center, a rectangular coordinate system is established on the plane, and then the radius sequence of the annular regions is designed. The radius of the first annular region (inner ring) is set to = 50 μm, which is used as a reference value. The radii of the subsequent annular regions are calculated according to the geometric increasing relationship: = × , where λ is the preset growth factor, and its value range is 0.15 - 0.25, and n is the serial number of the annular region (n = 1, 2, 3...). For the case of λ = 0.2, it is calculated that = 60 μm, = 72 μm, = 86.4 μm, etc. In actual operation, computer-aided design software is used to generate the precise contour of the annular regions and output it to the subsequent etching control system. The reason for using geometric increasing rather than arithmetic increasing for the division of annular regions is that the current density decays non-linearly from the contact point outward, and the geometrically increasing region division can better match the change gradient of the current density, making the subsequent formed microtrace structure adapt to the actual current distribution law.

[0082] The process of adjusting the etching current density, etching solution concentration, and etching time to form a radial microtrace pattern with preset characteristics in the annular region uses precision electrochemical etching technology. The etching equipment includes a constant current source, a platinum electrode, an etching tank, and a precision displacement platform. The etching solution is a 5-8% copper sulfate solution with a pH value adjusted to 2.8-3.2. The etching process is carried out in regions, and different etching parameters are set for each annular region. In the central region (near the contact point), a higher current density (80-100 mA / cm²) and a longer etching time (40-50 s) are used to form microtraces with a depth of 8-10 μm. The etching current density of each annular region expanding outward gradually decreases according to a preset attenuation coefficient β (with a value of 0.2-0.3), and the calculation formula is = × where is the current density in the central region, is the current density in the nth annular region. At the same time, the etching mask patterns of each region are adjusted so that the microtrace spacing gradually increases from the center outward according to the same growth coefficient λ as the radius. For example, a certain connector terminal has 5 annular regions set from the center to the edge. The microtrace depth in the central region is 9.2 μm, and the spacing is 15 μm. The microtrace depth in the outermost annular region is 2.6 μm, and the spacing is 28.5 μm. This gradient microtrace structure design enables the connector to exhibit the expected non-linear impedance characteristics under different current densities, effectively changing the characteristic of uniform current distribution in traditional connectors and forming a predictable and controllable impedance change pattern.

[0083] Please continue to refer to Figure 1 , according to the current distribution prediction pattern of the microtrace impedance gradient structure, a plurality of microchannels are arranged in the connector insulating housing of the sample, and a conductive thermosensitive composite material is injected into the microchannels and cured to form a temperature response channel network covering potential hot spot regions;

[0084] In an embodiment of the present invention, the step of arranging a plurality of microchannels in the connector insulating housing of the sample according to the current distribution prediction pattern of the microtrace impedance gradient structure, injecting a conductive thermosensitive composite material into the microchannels and curing to form a temperature response channel network covering potential hot spot regions includes:

[0085] Collect impedance distribution data of the microtrace impedance gradient structure under different current densities, and determine the current density gradient change region according to the impedance distribution data;

[0086] Arrange a multi-level microchannel network in the connector insulating housing of the sample according to the current density gradient change region. The multi-level microchannel network includes main channels and branch channels, and the cross-sectional area of the branch channels gradually decreases along the extension direction;

[0087] Prepare a conductive thermosensitive composite material including a conductive polymer matrix and a nanoscale thermosensitive material according to the distribution characteristics of the multi-level microchannel network. By adjusting the mass ratio of the conductive polymer matrix to the nanoscale thermosensitive material, make the temperature coefficient of resistance of the conductive thermosensitive composite material match the current density gradient change region;

[0088] Under a first preset vacuum degree, evacuate the multi-level microchannel network, and inject the conductive thermosensitive composite material into the multi-level microchannel network under a second preset vacuum degree to form an initial channel network covering the current density gradient change region;

[0089] Perform a stepwise temperature increase curing process on the initial channel network, measure the change rate of the resistance value of the conductive thermosensitive composite material at each temperature step, and enter the next temperature step when the change rate of the resistance value is stable within a preset range to obtain a temperature-responsive channel network.

[0090] The following specifically describes the steps involved in the above embodiments:

[0091] Collect impedance distribution data of the microtrace impedance gradient structure at different current densities. The process of determining the current density gradient change region according to the impedance distribution data adopts a method combining multi-point testing and differential analysis. Specifically, during implementation, first install the sample terminals on the test fixture, and sequentially apply different intensities of current (gradually increasing from 20% to 120% of the rated current, with an interval of 10%) through a high-precision programmable DC power supply. At each current intensity, scan the entire surface of the microtrace impedance gradient structure using a micro-ohmmeter and a micro-region electrode array (composed of platinum electrodes with a diameter of 0.1 mm and an arrangement spacing of 0.5 mm) to measure the local resistance value. Obtain 5 readings at each measurement point and take the average value to form an impedance distribution data matrix. Subsequently, use data processing software to calculate the impedance gradient (the change rate of impedance between adjacent measurement points) and draw an impedance gradient contour map. The region where the impedance gradient change rate exceeds 30% is marked as the "current density gradient change region". For example, in a certain sample under the condition of 80% of the rated current, the impedance value in the central region is 0.2 mΩ, and the impedance value increases to 0.5 mΩ at a distance of 5 mm outward. The calculated impedance gradient change rate in this region is 42%, exceeding the threshold, and is determined as the key area of concern. This differential analysis method can accurately identify the regions in the connector where the impedance changes violently, and these regions are most likely to generate non-linear impedance changes and hidden hot spots during actual operation.

[0092] The process of setting up a multi-level microchannel network in the connector insulating housing of the sample according to the region of the current density gradient change adopts a method combining precise three-dimensional modeling and microfabrication. First, the insulating housing is fixed on a five-axis numerically controlled microfabrication platform, and an end mill with a diameter of 0.3 - 0.5 mm is used to machine the main channels according to the preset path. The diameter of the main channels is 0.5 mm and they are arranged in the region where the current density gradient change rate exceeds 40% (strong change region). Subsequently, a micro drill with a diameter of 0.1 - 0.2 mm is used to machine the branch channels in the extending direction of the main channels. The starting diameter of the branch channels is 0.3 mm, and the diameter decreases by 0.05 mm every 5 mm of extension, with the minimum diameter controlled at 0.2 mm. They are arranged in the region where the current density gradient change rate is 20% - 40% (weak change region). During the machining process, the tool rotation speed is controlled at 15000 - 20000 revolutions per minute, and the feed rate is controlled at 0.1 - 0.2 mm per second to ensure the machining accuracy and surface quality. For example, in a certain connector sample, 3 main channels and 12 branch channels are machined in the insulating housing. The total length of the main channels is 28.5 mm, and the total length of the branch channels is 63.2 mm, forming a three-dimensional network structure covering all regions of the current density gradient change. This multi-level microchannel network design ensures precise coverage of different hot spot hazard level regions by arranging main channels in the strong change region and branch channels in the weak change region. At the same time, the gradually decreasing design of the cross-sectional area of the microchannels matches the heat conduction characteristics, optimizing the sensitivity distribution of the temperature response channels.

[0093] The process of formulating a conductive thermosensitive composite material according to the distribution characteristics of the multi-level microchannel network includes three stages: matrix material preparation, nano-filler treatment, and mixing and blending. The matrix material is selected as the conductive polymer polyaniline (abbreviated as PANI), and the nano-scale thermosensitive material is selected as modified vanadium dioxide ( nanoparticles (particle size 30 - 50 nm). First, PANI is dissolved in an N-methylpyrrolidone solution, and the concentration is controlled at 15 - 20 wt%. It is ultrasonically dispersed for 30 minutes. Then, the surface of the nanoparticles is modified with a silane coupling agent to improve its compatibility with the polymer matrix. According to the positions of the microchannels in different hot spot regions, the mass ratio of PANI to is adjusted: for the composite material used in the strong change region (main channels), the mass ratio of PANI: is 65:35; for the composite material used in the weak change region (branch channels), the mass ratio of PANI: The mass ratio is 75:25. By adjusting the mass ratio, the resistance temperature coefficient (RTC) of the composite material is matched with the thermal sensitivity requirements of the current density gradient change region. The RTC value in the strong change region is 0.5 - 0.6% / °C, and the RTC value in the weak change region is 0.3 - 0.4% / °C. For example, in a batch of prepared composite materials, the material used for the main channel, PANI: = 67:33, and the measured RTC value is 0.55% / °C; the material used for the branch channel, PANI: = 73:27, and the measured RTC value is 0.37% / °C. This customized conductive thermosensitive composite material formula design for different regions realizes the sensitivity control of the temperature response channel network in different regions, and solves the problem that traditional single materials cannot meet the differentiated monitoring requirements of complex hot spot regions.

[0094] The multi-level microchannel network is evacuated under the first preset vacuum degree, and the process of injecting the conductive thermosensitive composite material into the multi-level microchannel network under the second preset vacuum degree adopts the precise vacuum-assisted injection technology. First, the connector sample is placed in the sealed chamber of the vacuum injection device, and the chamber is evacuated to the first preset vacuum degree (1 - 5 Pa) by a vacuum pump, and this vacuum degree is maintained for 15 - 20 minutes to fully discharge the air inside the microchannel network. Subsequently, the prepared conductive thermosensitive composite material is placed in the feed chamber and heated to 65 - 75 °C to reduce its viscosity to a suitable injection range (500 - 1000 cP). The feed valve is opened, and the composite material begins to flow into the microchannel network under the action of the pressure difference. At this time, the vacuum degree is adjusted to the second preset vacuum degree (10 - 20 Pa), and the injection rate is controlled at 0.2 - 0.5 ml / min to ensure that the material flows fully from the main channel to the branch channel and avoid generating bubbles. The entire injection process lasts for 40 - 60 minutes until all channels are completely filled. For example, after a certain sample is pretreated at a vacuum degree of 3 Pa for 18 minutes, the composite material at 70 °C is injected at a vacuum degree of 15 Pa, and the injection rate is 0.3 ml / min, and it takes 52 minutes to complete the filling of all channels. This vacuum-assisted injection process solves the problems of easy bubble generation and uneven filling in traditional filling methods, and the two-stage vacuum degree control strategy ensures the complete filling of the complex microchannel network.

[0095] The process of stepwise temperature rise curing for the initial channel network adopts a method combining precise temperature control and real-time monitoring. The sample after injection is placed in a programmable temperature-controlled heating furnace, and a stepwise temperature rise program is set: the starting temperature is 40°C, with a 5°C rise for each step, and a total of 8 temperature steps are set (40°C, 45°C, 50°C, 55°C, 60°C, 65°C, 70°C, 75°C). At each temperature step, the holding time is 30 - 45 minutes, and at the same time, the resistance value of the conductive thermosensitive composite material is measured in real time through the microelectrodes inserted into the conductive thermosensitive composite material. The calculation formula for the resistance value change rate is: change rate = (current resistance value - resistance value 10 minutes ago) / resistance value 10 minutes ago × 100%. When the resistance value change rate remains stable within the range of ±0.5% for 5 consecutive minutes, it is determined that the curing of the current temperature step is completed, and the next temperature step is entered. The total duration of the entire curing process is 4 - 6 hours. Finally, it is cooled to room temperature, and the reference resistance value and resistance temperature coefficient of the temperature-responsive channel network are measured again to confirm that the design requirements are met. For example, for a certain sample at the 55°C temperature step, the resistance value change rate stabilizes within the range of ±0.3% after 35 minutes, and then it enters the 60°C step; the entire curing process lasts for 5 hours and 20 minutes, and finally, the resistance temperature coefficient of the main channel is measured to be 0.53% / °C, and that of the branch channel is 0.36% / °C, meeting the design requirements. This stepwise temperature rise curing process avoids the problems of internal stress accumulation and performance instability in the material caused by traditional one-time curing. Through real-time monitoring of the resistance value change rate, it ensures the full completion of the curing reaction in each temperature stage, and improves the long-term stability and detection accuracy of the temperature-responsive channel network.

[0096] In an embodiment of the present invention, a multi-level microchannel network is arranged in the connector insulating housing of the sample according to the current density gradient change region. The multi-level microchannel network includes a main channel and branch channels, and the cross-sectional area of the branch channels gradually decreases along the extension direction, including:

[0097] The current density gradient change region is analyzed by partitioning, and the region where the current density change rate exceeds the third guiding value is marked as the strong change region, and the region where the current density change rate is lower than the third guiding value is marked as the weak change region;

[0098] According to the distribution of the strong change region and the weak change region, a main channel is arranged in the strong change region, and branch channels are arranged in the weak change region;

[0099] The cross-sectional area decreasing coefficient of the branch channels is calculated according to the spatial distribution law of the current density gradient change region, so that the cross-sectional area of the branch channels gradually decreases from the connection with the main channel to the end, forming the multi-level microchannel network.

[0100] The following specifically describes the steps involved in the above embodiments:

[0101] The process of partitioning and analyzing the region with changing current density gradient and marking the region where the current density change rate exceeds the third guiding value as the strong change region and the region where the current density change rate is lower than the third guiding value as the weak change region adopts the quantitative partitioning method. First, according to the current density gradient distribution data obtained in the previous step, use data processing software to draw a gradient contour map. Then, set the third guiding value to 35% / mm, that is, the region where the change rate exceeds 35% when the current density changes by 1 mm is marked as the strong change region, and the region below this value is marked as the weak change region. In specific operations, divide the surface of the connector sample into grid-like regions, with each grid cell size of 0.5 mm × 0.5 mm, calculate the current density gradient value within each grid region, and perform partitioning and marking after comparing with the third guiding value. For example, the analysis result of a certain connector sample shows that the current density gradient value within 2 mm around the contact point is 52% / mm and is marked as the strong change region; the current density gradient value in the region 2 - 6 mm away from the contact point is 18 - 32% / mm and is marked as the weak change region. The setting of the third guiding value is based on a large amount of experimental data analysis. 35% / mm is the critical threshold for the formation of local hot spots caused by the change of current density. The non-linear impedance change in the region above this threshold is significant and requires key monitoring.

[0102] According to the distribution of the strong change region and the weak change region, the implementation of setting the main channel in the strong change region and the branch channel in the weak change region adopts the selective layout method. Using 3D modeling software, first draw the path of the main channel in the strong change region. The diameter of the main channel is set to 0.5 mm and is arranged along the central axis of the strong change region to ensure coverage of all key hot spot regions. Then, draw the branch channels in the extending direction of the main channel. The branch channels extend from the main channel to the weak change region, and the layout density corresponds to the spatial distribution of the current density gradient. Specifically, when laying out, in the region where the current density gradient value is 25 - 35% / mm, the spacing between the branch channels is set to 5 mm; in the region where the current density gradient value is 15 - 25% / mm, the spacing between the branch channels is set to 8 mm. For example, the area of the strong change region of a certain connector sample is about 28 square millimeters, and 3 main channels with a total length of 32 mm are arranged; the area of the weak change region is about 120 square millimeters, and 15 branch channels with a total length of 85 mm are arranged. This differential layout strategy realizes the optimal allocation of monitoring resources, conducts intensive monitoring on high-risk regions, and at the same time ensures effective coverage of low-risk regions.

[0103] Calculate the cross-sectional area decreasing coefficient of the branch channels according to the spatial distribution law of the current density gradient change region, and adopt a gradient configuration method for the process of gradually decreasing the cross-sectional area of the branch channels from the connection with the main channel to the end. First, determine the cross-sectional area decreasing coefficient γ by analyzing the attenuation curve of the current density gradient along the extension direction of the branch channels. When the change rate of the current density gradient shows linear attenuation, γ is set to 0.05 - 0.08; when it shows exponential attenuation, γ is set to 0.10 - 0.15. The starting cross-sectional area of the branch channels (the connection with the main channel) is set to 0.3 square millimeters, and then every 5 millimeters of extension, the cross-sectional area is reduced to (1 - γ) times that of the previous section. Taking γ = 0.12 as an example, the cross-sectional area at the starting point of the branch channels is 0.3 square millimeters, which is reduced to 0.264 square millimeters after the first 5 millimeters, and to 0.232 square millimeters after the second section, and so on. For example, the current density gradient in the weak change region of a connector sample shows exponential attenuation, γ = 0.13 is selected, and a certain branch channel is 15 millimeters long. The cross-sectional areas from the starting point to the end are 0.3, 0.261, and 0.227 square millimeters in sequence. This design of gradually decreasing cross-sectional area takes into account the heat response signal conduction characteristics. As the distance from the hot spot increases, the required signal conduction ability decreases. By optimizing the cross-sectional area distribution, the material utilization efficiency and the channel network sensitivity are improved, while ensuring the consistency of signal acquisition in each region.

[0104] Please continue to refer to Figure 1 , input an AC test signal within a preset frequency range to the connector of the sample, collect the impedance data of the connector at each frequency point and within a preset voltage range, and combine the geometric characteristics of the microtrace impedance gradient structure to generate a three-dimensional impedance-frequency-voltage characteristic map representing the impedance characteristics of the connector;

[0105] In an embodiment of the present invention, the inputting an AC test signal within a preset frequency range to the connector of the sample, collecting the impedance data of the connector at each frequency point and within a preset voltage range, and combining the geometric characteristics of the microtrace impedance gradient structure to generate a three-dimensional impedance-frequency-voltage characteristic map representing the impedance characteristics of the connector includes:

[0106] According to the microtrace depth distribution of the microtrace impedance gradient structure, determine the frequency response characteristic points corresponding to different depth regions, apply multiple groups of AC test signals to the connector of the sample, collect the impedance data at each frequency response characteristic point, and obtain the mapping relationship between the microtrace depth and the frequency response;

[0107] Apply AC test signals with amplitudes gradually increasing within a preset voltage range to the connector of the sample, measure the impedance change trend of the frequency response characteristic points at each voltage amplitude, and obtain a set of response curves representing the non-linear impedance characteristics;

[0108] Analyze the change rate of the response curve group, identify the points where the impedance change rate exceeds a predetermined threshold as impedance mutation points, increase the sampling frequency and voltage density near the impedance mutation points, and perform local fine scanning on the connector of the sample to obtain high-resolution impedance anomaly characteristic data;

[0109] Based on the mapping relationship between the microtrace depth and the frequency response, perform spatial positioning analysis on the high-resolution impedance anomaly characteristic data, establish the corresponding relationship between the impedance anomaly and the microtrace structure, and generate a three-dimensional characteristic map of impedance-frequency-voltage characterizing the impedance characteristics of the connector.

[0110] The following specifically describes the steps involved in the above embodiments:

[0111] The process of determining the frequency response characteristic points according to the microtrace depth distribution of the microtrace impedance gradient structure adopts the frequency response characteristic analysis method. First, divide the microtrace depth into several intervals based on the microtrace depth distribution data obtained through the foregoing steps: 8 - 10 microns, 6 - 8 microns, 4 - 6 microns, 2 - 4 microns. For each depth interval, calculate the corresponding frequency response characteristic points according to the theory of the frequency response characteristics of the metal microscopic contact surface. The calculation basis is the matching relationship between the surface microstructure and the electromagnetic field penetration depth. The frequency range corresponding to the area with a depth of 8 - 10 microns is 10 - 100 Hz, 6 - 8 microns corresponds to 100 - 1000 Hz, 4 - 6 microns corresponds to 1 - 10 kHz, and 2 - 4 microns corresponds to 10 - 100 kHz. Install the sample connector in the test fixture of an impedance analyzer (such as Agilent E4990A), set the four-wire measurement mode to eliminate the influence of lead impedance, apply an AC test signal with an amplitude of 0.5 volts, scan the frequency from 10 Hz to 100 kHz, and set 10 equally distributed measurement points within the frequency range of each depth interval. Collect impedance amplitude and phase angle data at each measurement point, and repeat the measurement 3 times and take the average value to improve the accuracy. For example, the test results of a certain connector sample show that the impedance amplitude at the 8.5 - micron microtrace depth region is 0.25 mΩ and the phase angle is 15 degrees at a frequency of 50 Hz; while the impedance amplitude at the 3.2 - micron microtrace depth region is 0.58 mΩ and the phase angle is 42 degrees at a frequency of 50 kHz. Establish a mapping relationship model between the microtrace depth and the frequency response parameters through data fitting. This frequency response characteristic analysis method utilizes the unique response characteristics of microstructures with different depths to currents of different frequencies, and realizes the precise correlation between the microtrace structure and the electrical characteristics.

[0112] An AC test signal with an amplitude gradually increasing within a preset voltage range is applied to the sample connector, and the process of measuring the impedance change trend of the frequency response characteristic points adopts the multi-voltage step scanning method. The connector sample is fixed on the test fixture, and a programmable AC signal source is used to output a test signal whose frequency matches the frequency response characteristic points determined in the previous step. The amplitude of the test signal starts from 0.1 volts and increases in steps of 0.2 volts up to 2.1 volts, with a total of 11 voltage levels, covering the low-voltage to high-voltage operating conditions of the connector in actual work. At each voltage level, the impedance data of all frequency response characteristic points are measured in sequence, including impedance amplitude, phase angle, and equivalent circuit parameters (such as equivalent resistance, inductance, and capacitance). Each measurement point is collected 5 times, and the median value is taken to eliminate the influence of random fluctuations. The obtained data are grouped and sorted according to the frequency response characteristic points to obtain the impedance change curves of each characteristic point at different voltages, forming a set of response curves characterizing the non-linear impedance characteristics. For example, the test results of a certain connector at the 50 Hz frequency point show that when the signal amplitude increases from 0.1 volts to 2.1 volts, the impedance amplitude increases from 0.23 mΩ to 0.42 mΩ, with a change rate of 82.6%; while at the 50 kHz frequency point, the same voltage change results in the impedance amplitude increasing from 0.55 mΩ to 0.65 mΩ, with a change rate of only 18.2%. This differential impedance-voltage response characteristic reflects the non-linear electrical behavior of different micro-scar regions under different operating conditions, which is beyond the description range of the traditional linear impedance model.

[0113] The process of analyzing the change rate of the set of response curves and identifying the impedance mutation points adopts a method combining inflection point detection and local fine scanning. First, calculate the impedance change rate between adjacent measurement points for each impedance-voltage response curve. The change rate is calculated as ( - ) / ×100% / ( - ), where 、 are adjacent voltages 、 The impedance value below. Set a predetermined threshold of 25% / V, that is, the point where the impedance changes by more than 25% per 1 V change in voltage is marked as an impedance mutation point. For the identified impedance mutation points, reduce their voltage range to 1 / 5 of the original, and add 20 evenly distributed voltage measurement points within this range; at the same time, add 3 frequency measurement points before and after the frequency response characteristic points to which they belong to form a local encrypted grid. Use a precision impedance analyzer to perform high-precision measurements at these encrypted grid points, with the precision set to ±0.01%, and extend the sampling time to 500 ms / point to obtain high-resolution impedance anomaly characteristic data. For example, a certain connector detects an impedance change rate of 32% / V at 1.5 V and 5 kHz, exceeding the predetermined threshold, and is marked as an impedance mutation point. Subsequently, 20 voltage measurement points are added in the range of 1.4 - 1.6 V, and 6 frequency measurement points are added in the range of 4.7 - 5.3 kHz to form 120 fine scan points, obtaining impedance anomaly characteristic data with a 10-fold increased resolution. This adaptive fine scan method significantly improves the capture ability of the impedance anomaly characteristics at key points, avoiding the problems of resource waste and key information loss in the traditional uniform scan method.

[0114] Based on the mapping relationship between microtrace depth and frequency response, the process of spatial location analysis of high-resolution impedance anomaly characteristic data uses reverse inference and 3D visualization techniques. First, combine the impedance anomaly characteristic data obtained in the previous step with the microtrace depth - frequency response mapping model, and determine the microtrace structure position corresponding to each impedance anomaly point through reverse calculation. The specific operation is as follows: for each impedance anomaly characteristic point, query the mapping model according to its frequency response characteristics to determine the microtrace depth interval to which the point belongs; then, combine the spatial distribution data of the microtrace structure to accurately locate the coordinate position of the impedance anomaly point on the connector surface. Use a spatial interpolation algorithm to fill the area between the measurement points to generate a continuous impedance distribution function. Use 3D visualization software to construct a 3D characteristic map of impedance - frequency - voltage, with the horizontal axis being frequency (logarithmic scale, 10 Hz to 100 kHz), the vertical axis being voltage (linear scale, 0.1 to 2.1 V), and the color or height representing the impedance amplitude. At the same time, add the microtrace structure contour line as a reference layer to intuitively display the correspondence between impedance anomalies and microtrace structures. For example, the 3D characteristic map of a certain connector sample shows that there is an obvious impedance mutation in the voltage range of 1.6 - 1.8 V in the microtrace depth area of 7.5 μm (corresponding to a frequency point of about 80 Hz), and the impedance value suddenly rises from 0.38 mΩ to 0.65 mΩ; while the impedance in the microtrace depth area of 3.0 μm (corresponding to a frequency point of about 60 kHz) changes smoothly throughout the voltage range. This 3D characteristic map of impedance - frequency - voltage provides a comprehensive portrait of the impedance characteristics of the connector, realizes the precise correlation between electrical parameters and physical structures, and reveals complex impedance non-linear characteristics that cannot be discovered by traditional single-parameter tests.

[0115] Please continue to refer to Figure 1 Based on the key frequency points of the impedance-frequency-voltage three-dimensional characteristic map, apply multiple groups of pulsed currents with preset amplitudes and durations to the connector of the sample, and collect the temperature change data of the key points inside the connector through the temperature response channel network to obtain a temperature-time response curve characterizing the thermal characteristics of the connector;

[0116] In an embodiment of the present invention, the step of applying multiple groups of pulsed currents with preset amplitudes and durations to the connector of the sample based on the key frequency points of the impedance-frequency-voltage three-dimensional characteristic map and collecting the temperature change data of the key points inside the connector through the temperature response channel network to obtain a temperature-time response curve characterizing the thermal characteristics of the connector includes:

[0117] Based on the key frequency points in the impedance-frequency-voltage three-dimensional characteristic map, generate a pulsed current excitation sequence including a single amplitude increasing sequence, an alternating high and low amplitude sequence, and a random amplitude sequence, and the amplitude range of the pulsed current excitation sequence covers 20% to 120% of the rated current of the connector;

[0118] According to the spatial distribution of the temperature response channel network, establish a temperature acquisition coordinate for the key points inside the connector, and collect the temperature response data of each temperature acquisition coordinate in the temperature response channel network during the application of the pulsed current excitation;

[0119] Perform real-time analysis on the temperature response data. When it is detected that the temperature rising rate exceeds the first preset threshold, increase the temperature sampling frequency. When it is detected that the temperature falling rate exceeds the second preset threshold, restore the initial sampling frequency to obtain a temperature response data set including temperature mutation characteristics;

[0120] According to the temperature response data set, calculate the temperature response delay time and temperature decay coefficient of each key point inside the connector, establish a temperature propagation path map of the connector, and generate a temperature-time response curve characterizing the thermal characteristics of the connector.

[0121] The following specifically describes the steps involved in the above embodiments:

[0122] The process of generating a pulsed current excitation sequence based on the key frequency points in the three-dimensional impedance-frequency-voltage characteristic spectrum adopts a multi-mode pulse synthesis technique. First, the frequency points with the most significant impedance anomalies are extracted from the three-dimensional characteristic spectrum. Usually, the top 5 frequency points with the highest impedance change rate are selected as the key frequency points. Then, according to the characteristics of these key frequency points, three different types of pulse sequences are designed: The single amplitude increasing sequence starts from 20% of the connector's rated current, increases by 10% every 5 seconds until it reaches 120% of the rated current, and the pulse width is set to 100 milliseconds; The alternating high and low amplitude sequence alternates between 40% and 90% of the rated current with a time interval of 3 seconds and a pulse width of 80 milliseconds; The random amplitude sequence changes within the range of 20% - 120% according to a preset pseudo-random number list, and the pulse width is randomly distributed between 50 - 150 milliseconds. A programmable DC power supply is used to output these three sequences in turn. Each sequence lasts for 60 seconds, and there is a 30-second interval between sequences to eliminate the thermal accumulation effect. For example, for a connector with a rated current of 350 amperes, the pulsed current amplitude range is 70 - 420 amperes. The single increasing sequence starts from 70 amperes and increases by 35 amperes every 5 seconds; The alternating sequence switches between 140 amperes and 315 amperes; The random sequence changes randomly within the above range. This multi-mode pulse design comprehensively simulates various current change situations faced by in-vehicle high-voltage connectors during actual operation, including stable loading, working condition switching, and random load fluctuations, and can effectively stimulate potential non-linear impedance changes.

[0123] The process of establishing the temperature acquisition coordinates of the internal key points of the connector based on the spatial distribution of the temperature response channel network adopts a method combining three-dimensional mapping and data acquisition. First, based on the three-dimensional layout data of the temperature response channel network in the previous steps, a temperature acquisition point distribution map in a rectangular coordinate system is established. A temperature acquisition point is set every 3 millimeters on the main channel, and a temperature acquisition point is set every 5 millimeters on the branch channel. Additional acquisition points are added at the channel intersection points and end points. Each acquisition point is assigned a unique three-dimensional coordinate (x, y, z) and an identification code to form a temperature acquisition coordinate table. A multi-channel temperature data acquisition module (sampling rate 10 Hz, accuracy ±0.1 °C) is connected to the lead-out end of the temperature response channel network, and the temperature changes of each acquisition point are monitored in real time through a resistance-temperature conversion circuit. During the application of the pulsed current excitation, the system synchronously records the time stamp, current amplitude, and temperature data of each temperature acquisition point to form a three-dimensional correlation data set of time-temperature-position. For example, a certain connector sample is set with 32 temperature acquisition points, including 12 points on the main channel and 20 points on the branch channel. After applying a 350-ampere pulse, the temperature at the center point of the main channel rises from 23.5 °C to 38.7 °C within 1.2 seconds, while the temperature at the position of the most distal branch channel starts to rise significantly after 2.5 seconds. This precise spatial temperature acquisition strategy realizes the comprehensive monitoring of the internal temperature field of the connector and captures the internal temperature distribution and dynamic change process that cannot be obtained by traditional external temperature measurement methods.

[0124] Adaptive sampling technology is used for real-time analysis of temperature response data. The key lies in dynamically adjusting the sampling frequency to capture the temperature mutation characteristics. During specific implementation, the initial temperature sampling frequency is set to 10 Hz, the first preset threshold (temperature rise rate threshold) is 2 °C / s, and the second preset threshold (temperature fall rate threshold) is 1 °C / s. The sliding window algorithm is used to calculate the temperature change rate of each temperature acquisition point in real time, and the window width is 0.5 s. When it is detected that the temperature rise rate of any acquisition point exceeds the first preset threshold, the system automatically increases the sampling frequency of this point and its surrounding points to 50 Hz to capture the rapid temperature change process; when the temperature fall rate exceeds the second preset threshold, it is considered that the temperature change enters the stable stage, and the sampling frequency is restored to the initial value of 10 Hz to save system resources. All temperature data is stored together with the sampling frequency change mark to form a temperature response data group containing temperature mutation characteristics. For example, in a certain test, after the current jumps from 140 amperes to 315 amperes at the acquisition point with the ID of T15, the temperature rise rate reaches 2.8 °C / s, triggering the high-frequency sampling mode and successfully capturing the transient process of the temperature rising by 4.2 °C within 0.3 s; then the temperature rise slows down, and the system restores the conventional sampling frequency. This adaptive sampling technology solves the dilemma of traditional fixed-frequency sampling in capturing temperature mutation events, namely "too high sampling frequency leads to data redundancy" or "too low sampling frequency leads to loss of key information".

[0125] The temperature response characteristic parameters of each key point inside the connector are calculated based on the temperature response data set using the heat propagation analysis method. First, for each temperature acquisition point, its temperature-time curve is extracted, and key characteristic points are determined, including the time point when the temperature starts to rise, the time point when it reaches the peak, the time point when it starts to decline, etc. Calculate the temperature response delay time, that is, the time difference from the application of the pulsed current to the obvious rise of the temperature (a 0.5 °C rise); calculate the temperature decay coefficient, that is, the reciprocal of the time required for the temperature to drop from the peak to 36.8% of the difference between the peak and the ambient temperature. Based on these parameters, use the heat propagation path tracking algorithm to analyze the propagation direction and speed of heat inside the connector, and construct a temperature propagation path map. This path map is in the form of a directed graph, where the nodes represent the temperature acquisition points, the edges represent the heat propagation direction, and the edge weights represent the heat propagation speed. Finally, integrate the temperature-time curves of all temperature acquisition points, and combine with the spatial position information to generate a family of temperature-time response curves characterizing the thermal characteristics of the connector. For example, for a certain connector under the action of a 300-ampere pulse, the response delay time of the temperature acquisition point near the contact point is 0.3 seconds, and the temperature decay coefficient is 0.25 / second; while the response delay time of the acquisition point 8 millimeters away from the heat source is extended to 1.2 seconds, and the temperature decay coefficient drops to 0.12 / second. Through this thermal characteristic analysis, the heat conduction mechanism and temperature distribution law inside the connector are accurately revealed, providing strong evidence for identifying hot spots caused by non-linear impedance changes.

[0126] Please continue to refer to Figure 1 , perform a time-series comparison analysis on the impedance-frequency-voltage three-dimensional characteristic map and the temperature-time response curve, calculate the correlation parameters of the impedance change and temperature change of the connector, calibrate the hot spot positions corresponding to the non-linear impedance change regions in the connector, and generate a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch according to the impedance change characteristics and temperature response characteristics of the hot spot positions.

[0127] In an embodiment of the present invention, the performing a time-series comparison analysis on the impedance-frequency-voltage three-dimensional characteristic map and the temperature-time response curve, calculating the correlation parameters of the impedance change and temperature change of the connector, calibrating the hot spot positions corresponding to the non-linear impedance change regions in the connector, and generating a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch according to the impedance change characteristics and temperature response characteristics of the hot spot positions includes:

[0128] Perform a time-domain mapping on the impedance-frequency-voltage three-dimensional characteristic map, and based on the spatial distribution of the microtrace impedance gradient structure, construct a multi-dimensional impedance response matrix reflecting the time-series characteristics of impedance changes in different regions;

[0129] According to the topological structure of the temperature response channel network, spatially analyze the temperature-time response curve, establish a propagation path map of temperature changes, and extract the temperature gradient and propagation delay on each propagation path;

[0130] Perform spatial registration on the multi-dimensional impedance response matrix and the temperature propagation path map, identify the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determine the key regions where impedance changes induce temperature responses;

[0131] Perform impedance-temperature response feature decomposition on the key regions, extract impedance mutation features, temperature response delay features, and temperature cumulative effect features, and establish a multi-dimensional feature space for non-linear impedance anomalies;

[0132] Based on the multi-dimensional feature space, construct a feature fingerprint mapping function, map the combination of the impedance mutation feature, temperature response delay feature, and temperature cumulative effect feature into a quantifiable feature parameter sequence, and generate a feature fingerprint for detecting non-linear impedance anomalies in connectors of the same batch.

[0133] The following is a specific description of the steps involved in the above embodiments:

[0134] The process of performing time-domain mapping on the impedance-frequency-voltage three-dimensional feature spectrum adopts a method combining frequency-time transformation and spatial correspondence technology. First, convert the frequency-dimensional data in the three-dimensional feature spectrum into a time-domain representation. Using the inverse discrete Fourier transform algorithm, transform the impedance data Z(f, V) at frequency points to into the impedance response function Z(t, V) at time points to Then, based on the spatial distribution information of the microtrace impedance gradient structure, establish a coordinate mapping relationship, and associate each microtrace depth region with the corresponding spatial coordinates (x, y). For each spatial coordinate point, extract its time-domain impedance response characteristics at different voltages, including parameters such as rise time, peak time, and steady time, to form a time-domain response feature vector R(x, y, V) describing the spatial point (x, y) at voltage V. Combine the feature vectors of all spatial points into a multi-dimensional impedance response matrix M. For example, for a certain connector sample, the feature vector at the microtrace center region (x = 2mm, y = 3mm) contains the following parameters at a voltage of 1.5V: impedance rise time 0.5ms, peak time 1.2ms, steady time 2.8ms, and peak-to-steady ratio 1.35. This time-domain mapping method realizes the conversion of frequency-domain electrical characteristics to time-domain response characteristics, making it possible to compare the impedance change characteristics and temperature change characteristics (essentially time-domain characteristics) on the same time scale.

[0135] The process of spatially analyzing the temperature-time response curve according to the topological structure of the temperature response channel network uses the heat propagation path tracking technique. First, the three-dimensional layout of the temperature response channel network is converted into a topological graph, where nodes represent temperature acquisition points and edges represent channel connection relationships. For each node, its corresponding temperature-time response curve T(t) is associated, and key characteristic parameters are extracted: the starting time of temperature response (the moment when the temperature rises by 0.5 °C), the temperature rising rate, the peak temperature, the time when the peak appears, etc. Based on these parameters, the temperature propagation time delay (the difference in the starting times of the responses of two nodes) and the temperature gradient (the difference in the peak temperatures of two nodes divided by the spatial distance) between adjacent nodes are calculated. The temperature propagation path map is drawn using graphic visualization software, with arrows indicating the heat propagation direction, the color shade representing the magnitude of the temperature gradient, and the line width representing the propagation speed. For example, the temperature propagation path map of a certain connector shows that starting from the acquisition point P1 near the contact point, the temperature propagation diffuses outward along the main channel, the time delay to reach the branch point P5 is 0.8 seconds, and the temperature gradient is 2.5 °C / mm; while the time delay from P5 to the branch end P12 is 1.2 seconds, and the temperature gradient drops to 1.1 °C / mm. This spatial analysis method intuitively reveals the dynamic process of hot spot formation and heat propagation, providing key information for identifying the location of the hot spot source.

[0136] The process of spatially registering the multi-dimensional impedance response matrix with the temperature propagation path map uses a method combining coordinate transformation and correlation analysis. First, a unified coordinate system is established to align the node coordinates in the temperature propagation path map with the spatial coordinates in the multi-dimensional impedance response matrix. The spatial interpolation algorithm is used to expand the discrete temperature acquisition points into a continuous temperature field function T(x, y, t). The spatio-temporal correlation coefficient between the impedance change and the temperature change is calculated, and the formula is the correlation between the impedance change rate and the temperature change rate after a lag time τ. The correlation coefficient threshold is set to 0.85, and for the regions where the correlation coefficient exceeds the threshold, they are marked as regions with an obvious coupling relationship between the impedance change and the temperature change. Further analyze the regions where the impedance change precedes the temperature change, and determine them as the key regions where the impedance change induces the temperature response. For example, in a circular region with a microtrace depth of 6 - 8 μm of a certain connector, the correlation coefficient between the impedance change and the temperature change with a lag of 0.5 seconds reaches 0.92, exceeding the threshold, and the impedance change time is on average 0.5 seconds earlier than the temperature change, so it is determined as a key region. This spatial registration method solves the technical problem of the correlation between electrical characteristics and thermal characteristics in the spatio-temporal dimension, and realizes the precise positioning of hot spots caused by non-linear impedance changes.

[0137] The process of decomposing the impedance-temperature response characteristics of key regions uses multi-parameter feature extraction techniques. First, for the identified key regions, impedance mutation characteristics are extracted from the multi-dimensional impedance response matrix, including the peak value of the impedance change rate, the change duration, and the change curve shape parameters (such as steepness, curvature), etc.; temperature response delay characteristics are extracted from the temperature propagation path map, including the time delay from impedance change to temperature response, the temperature rise rate, and the response curve shape parameters, etc.; by continuously monitoring the temperature change process, temperature cumulative effect characteristics are extracted, including the heat accumulation rate, the heat dissipation rate, and the thermal cycle stability parameters, etc. The principal component analysis (PCA) method is used to reduce the dimension of these characteristics, and the principal components with an explained variance ratio exceeding 95% are retained to form a multi-dimensional feature space of non-linear impedance anomalies. For example, the feature decomposition result of a key region of a connector contains 5 principal components: the first principal component reflects the amplitude and rate characteristics of impedance mutation, with a contribution rate of 45%; the second principal component reflects the rate and peak characteristics of temperature response, with a contribution rate of 28%; the third to fifth principal components respectively reflect heat accumulation, heat dissipation characteristics, and cycle stability, with a total contribution rate of 23%. This feature decomposition method realizes the structured expression of complex impedance-temperature coupling phenomena and lays a mathematical foundation for subsequent feature fingerprint generation.

[0138] The process of constructing a feature fingerprint mapping function based on the multi-dimensional feature space uses a method combining machine learning and feature encoding. First, a feature normalization function is designed to convert various feature parameters with different dimensions into the [0,1] interval. Then, a weight optimization algorithm is used to determine the weight coefficients of each feature, and the weight assignment principle is: features that contribute greatly to the identification of non-linear impedance anomalies are assigned higher weights, with typical values of 0.4 for impedance mutation characteristics, 0.35 for temperature response delay characteristics, and 0.25 for temperature cumulative effect characteristics. A mapping function is constructed to convert the normalized and weighted feature vector into a feature parameter sequence with a fixed length, using a 32-bit encoding scheme, including 8-bit impedance mutation feature codes, 8-bit temperature response delay feature codes, 8-bit temperature cumulative effect feature codes, and 8-bit comprehensive feature codes. Finally, the feature parameter sequence is associated with the sample ID to form a feature fingerprint for detecting non-linear impedance anomalies in connectors of the same batch. For example, the feature fingerprint of a connector sample is "3A-75-C2-8F", where "3A" encodes the impedance mutation characteristics, indicating a significant non-linear impedance change at a specific frequency; "75" encodes the temperature response delay characteristics, reflecting the dynamic process of hot spot formation; "C2" encodes the temperature cumulative effect characteristics, indicating the heat accumulation characteristics of the hot spot area; "8F" is the comprehensive feature code, reflecting the overall anomaly degree. This feature fingerprint mapping method compresses complex multi-dimensional feature information into a concise identifier, facilitating the rapid identification of connectors with similar non-linear impedance anomaly risks in mass production.

[0139] In one embodiment of the present invention, the spatial registration of the multi-dimensional impedance response matrix and the temperature propagation path map, the identification of the coupling relationship between impedance change and temperature change in the spatio-temporal dimension, and the determination of the key region where impedance change induces temperature response include:

[0140] Converting the spatial distribution data of the multi-dimensional impedance response matrix into impedance gradient distribution data;

[0141] Calculating the temperature propagation rate distribution data according to the temperature propagation path map;

[0142] Performing spatial coordinate mapping on the impedance gradient distribution data and the temperature propagation rate distribution data, and calculating the spatial overlap degree and the temporal correlation degree between the two;

[0143] Calculating the coupling coefficient according to the spatial overlap degree and the temporal correlation degree, identifying the coupling relationship between impedance change and temperature change in the spatio-temporal dimension based on the coupling coefficient, and determining the key region where impedance change induces temperature response.

[0144] The following specifically describes the steps involved in the above embodiment:

[0145] The process of converting the spatial distribution data of the multi-dimensional impedance response matrix into impedance gradient distribution data uses spatial differential technology. First, the spatial distribution data in the multi-dimensional impedance response matrix is resampled onto a uniform grid with a grid spacing set to 0.2 mm to ensure sufficient spatial resolution. Then, the central difference method is used to calculate the spatial gradient of the impedance value at each grid point, that is, to calculate the impedance change rate of this point in the X direction and the Y direction. In specific calculations, take the impedance values of the grid point (i,j) and its four adjacent points (i + 1,j), (i - 1,j), (i,j + 1), (i,j - 1), and calculate the X direction gradient as [the impedance value of the point (i + 1,j) minus the impedance value of the point (i - 1,j)] divided by [twice the distance between the two points]. The Y direction gradient is calculated similarly. Finally, calculate the modulus of the gradient, that is, take the square root of the sum of the squares of the X direction and Y direction gradients to obtain the impedance gradient value of this point. Repeat the above calculations for all grid points to form the complete impedance gradient distribution data. For example, the impedance value of a connector sample at the position (2.4 mm, 3.6 mm) is 0.35 mΩ, and the impedance values of its four adjacent points in the east, west, south, and north directions are 0.38, 0.31, 0.36, and 0.33 mΩ respectively. The calculated X direction gradient is 0.035 mΩ / mm, the Y direction gradient is 0.015 mΩ / mm, and the gradient modulus is 0.038 mΩ / mm. This spatial differential conversion changes the impedance distribution data from representing "numerical magnitude" to representing "degree of change intensity", more intuitively reflecting the spatial distribution characteristics of non-linear impedance changes, and providing a suitable data form for subsequent comparison with temperature propagation characteristics.

[0146] The process of calculating the temperature propagation rate distribution data based on the temperature propagation path diagram uses a spatio-temporal analysis method. First, the node coordinates of all heat propagation paths and the corresponding temperature response time data are extracted from the temperature propagation path diagram. For each propagation path, the spatial distance between adjacent nodes and the temperature response time difference are calculated, and the two are divided to obtain the temperature propagation rate of this section of the path. In order to obtain a continuous temperature propagation rate distribution, the radial basis function (RBF) interpolation algorithm is used to extend the discrete rate data to a uniform grid with the same distribution as the impedance gradient. During the interpolation process, a Gaussian radial basis function is selected, and the influence radius is set to 3 mm to ensure a smooth transition without losing local details. The finally obtained temperature propagation rate distribution data represents the speed of heat propagation at each point inside the connector, with the unit of millimeters per second. For example, on the temperature propagation path of a certain connector, the spatial distance from node A (1.5 mm, 2.0 mm) to node B (3.5 mm, 2.5 mm) is 2.06 mm, and the temperature response time difference is 0.85 s. The calculated propagation rate is 2.42 mm / s; after interpolation, the propagation rate at the position of (2.4 mm, 2.2 mm) is 2.38 mm / s. This rate distribution calculation method overcomes the limitations of traditional point-to-point measurements, realizes the full-space characterization of temperature propagation characteristics, makes the heat propagation law more clearly visible, and is convenient for accurate comparison with the impedance gradient distribution.

[0147] The process of performing spatial coordinate mapping on impedance gradient distribution data and temperature propagation rate distribution data and calculating their spatial overlap and temporal correlation uses data fusion and correlation analysis techniques. First, ensure that the two sets of data have the same spatial coordinate system and resolution. If they are different, adjust them to a unified format through interpolation. Then, calculate the spatial overlap. The specific method is as follows: normalize the impedance gradient values and temperature propagation rate values respectively so that the numerical range is 0 - 1; set the thresholds to 0.7 and 0.6 respectively. Mark the area where the impedance gradient value is greater than 0.7 as the "high impedance gradient area", and the area where the temperature propagation rate is less than 0.6 as the "low propagation rate area" (i.e., the area with slow heat conduction); calculate the ratio of the intersection area of the two areas to the area of their respective areas, and take the arithmetic mean as the spatial overlap. Next, calculate the temporal correlation. The method is: at each grid point in the overlapping area, extract the time series of impedance change and the time series of temperature change at that point; calculate the cross-correlation function of the two time series, determine the maximum cross-correlation value and its corresponding time delay; after spatial averaging, obtain the overall temporal correlation. For example, the analysis results of a certain connector show that: the area of the high impedance gradient region is 28 square millimeters, the area of the low propagation rate region is 32 square millimeters, and the intersection area is 22 square millimeters. The calculated spatial overlap is 0.73; in the overlapping area, the impedance change on average precedes the temperature change by 0.65 seconds, and the average maximum cross-correlation value is 0.82, indicating a strong temporal correlation. This spatial coordinate mapping method correlates electrical characteristics and thermal characteristics in both spatial and temporal dimensions, providing a quantitative basis for in-depth understanding of their coupling mechanism.

[0148] The process of calculating the coupling coefficient based on the spatial overlap degree and the temporal correlation degree, and then identifying the coupling relationship between impedance change and temperature change adopts a weighted comprehensive evaluation method. First, according to the results verified by experiments, the weight coefficients of the spatial overlap degree and the temporal correlation degree are determined to be 0.4 and 0.6 respectively, reflecting the relative importance of the temporal correlation in the coupling relationship. The calculation formula of the coupling coefficient is: the spatial overlap degree multiplied by its weight coefficient 0.4 plus the temporal correlation degree multiplied by its weight coefficient 0.6. The threshold of the coupling coefficient is set to 0.75. When the coupling coefficient of a certain area exceeds this threshold and the impedance change time is earlier than the temperature change time, it is determined that this area is the "key area where impedance change induces temperature response". In order to more accurately characterize the range of the key area, the maximum gradient method is used to determine the boundary, that is, along the normal direction of the coupling coefficient contour line, the position with the largest gradient of the coupling coefficient is found as the boundary point. For example, the spatial overlap degree obtained by analyzing a certain connector is 0.73, and the temporal correlation degree is 0.82. The calculated coupling coefficient is 0.73×0.4 + 0.82×0.6 = 0.784, which exceeds the threshold of 0.75. After the boundary is determined, an elliptical key area with an area of about 18 square millimeters is identified, and the center is located at a microtrace depth of 7.2 micrometers. This coupling coefficient calculation method integrates the information in both the spatial and temporal aspects, realizes the quantitative evaluation of the impedance-temperature coupling relationship, and provides a reliable mathematical tool for accurately identifying the source of non-linear impedance anomalies.

[0149] Another embodiment of the present invention proposes a vehicle-mounted high-voltage connector. The processing process of this vehicle-mounted high-voltage connector adopts the processing method of the vehicle-mounted high-voltage connector in the above embodiment. Therefore, it has all the beneficial effects of the above embodiment and will not be described in detail here.

[0150] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. All equivalent structural transformations made under the inventive concept of the present invention by using the content of the specification and drawings of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A processing method for a vehicle-mounted high-voltage connector, characterized in that, Comprising: Forming a preset micro-scar pattern on the terminal contact surface of the sample to obtain a micro-scar impedance gradient structure with preset non-linear resistance characteristics; According to the current distribution prediction pattern of the micro-scar impedance gradient structure, arranging a plurality of micro-channels in the connector insulating housing of the sample, injecting a conductive thermosensitive composite material into the micro-channels and performing a curing treatment to form a temperature response channel network covering potential hot spot areas; Inputting an alternating current test signal within a preset frequency range to the connector of the sample, collecting impedance data of the connector at each frequency point and within a preset voltage range, and combining with the geometric characteristics of the micro-scar impedance gradient structure to generate a three-dimensional impedance-frequency-voltage characteristic map characterizing the impedance characteristics of the connector; Based on the key frequency points of the three-dimensional impedance-frequency-voltage characteristic map, applying multiple groups of pulsed currents with preset amplitudes and durations to the connector of the sample, and collecting temperature change data of key points inside the connector through the temperature response channel network to obtain a temperature-time response curve characterizing the thermal characteristics of the connector; Performing a sequential comparison and analysis on the three-dimensional impedance-frequency-voltage characteristic map and the temperature-time response curve, calculating the correlation parameter between the impedance change and the temperature change of the connector, calibrating the hot spot position corresponding to the non-linear impedance change area in the connector, and generating a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch according to the impedance change characteristics and temperature response characteristics of the hot spot position.

2. The processing method of the in-vehicle high-voltage connector according to claim 1, characterized in that, The forming a preset micro-scar pattern on the terminal contact surface of the sample to obtain a micro-scar impedance gradient structure with preset non-linear resistance characteristics comprises: Determining a sample selection criterion according to batch process parameters and material characteristics, and extracting sample connectors not less than 3% of the total batch quantity from in-vehicle high-voltage connectors of the same batch; Removing the oxide layer on the surface of the copper alloy terminal substrate of the sample connector, measuring the surface roughness of the terminal substrate surface to obtain a clean terminal surface with a surface roughness within a preset range; Presetting contact point positions on the clean terminal surface, and using an etching process to form a radial micro-scar pattern centered on the contact point positions, controlling the depth of the radial micro-scar pattern to gradually decrease outward from the contact point positions according to a preset attenuation coefficient, and controlling the spacing of the radial micro-scar pattern to gradually increase outward from the contact point positions according to a preset growth coefficient; Performing a depth distribution measurement and a lateral topography measurement on the radial micro-scar pattern, and calculating the depth range, spacing range and lateral distribution uniformity of the micro-scars based on the results of the depth distribution measurement and the lateral topography measurement to obtain a micro-scar impedance gradient structure meeting the preset uniformity requirements.

3. The processing method of the in-vehicle high-voltage connector according to claim 2, wherein, The presetting contact point positions on the clean terminal surface, and using an etching process to form a radial micro-scar pattern centered on the contact point positions, controlling the depth of the radial micro-scar pattern to gradually decrease outward from the contact point positions according to a preset attenuation coefficient, and controlling the spacing of the radial micro-scar pattern to gradually increase outward from the contact point positions according to a preset growth coefficient comprises: Measure the current density distribution on the cleaned terminal surface, and determine the point with the maximum current density as the position of the contact point; Divide multiple annular regions around the position of the contact point, and calculate the radius of each annular region according to a preset growth coefficient; Adjust the etching current density, the concentration of the etching solution, and the etching time to form a radial microtrace pattern with a depth decreasing according to a preset attenuation coefficient and a radial microtrace pattern with a spacing increasing according to the preset growth coefficient within the annular region.

4. The processing method of the in-vehicle high-voltage connector according to claim 1, characterized in that, According to the current distribution prediction mode of the microtrace impedance gradient structure, set multiple microchannels in the connector insulating housing of the sample, inject a conductive thermosensitive composite material into the microchannels and perform a curing process to form a temperature response channel network covering potential hot spot regions, including: Collect the impedance distribution data of the microtrace impedance gradient structure under different current densities, and determine the region of current density gradient change according to the impedance distribution data; Set a multi-level microchannel network in the connector insulating housing of the sample according to the region of current density gradient change. The multi-level microchannel network includes a main channel and branch channels, and the cross-sectional area of the branch channels gradually decreases along the extension direction; Prepare a conductive thermosensitive composite material including a conductive polymer matrix and a nano-scale thermosensitive material according to the distribution characteristics of the multi-level microchannel network. By adjusting the mass ratio of the conductive polymer matrix to the nano-scale thermosensitive material, make the resistance temperature coefficient of the conductive thermosensitive composite material match the region of current density gradient change; Perform a vacuum pumping process on the multi-level microchannel network under a first preset vacuum degree, and inject the conductive thermosensitive composite material into the multi-level microchannel network under a second preset vacuum degree to form an initial channel network covering the region of current density gradient change; Perform a stepwise temperature increase curing process on the initial channel network, measure the change rate of the resistance value of the conductive thermosensitive composite material at each temperature step, and enter the next temperature step when the change rate of the resistance value stabilizes within a preset range to obtain a temperature response channel network.

5. The processing method of the in-vehicle high-voltage connector according to claim 4, characterized in that, Set a multi-level microchannel network in the connector insulating housing of the sample according to the region of current density gradient change. The multi-level microchannel network includes a main channel and branch channels, and the cross-sectional area of the branch channels gradually decreases along the extension direction, including: Perform a zonal analysis on the region of current density gradient change, and mark the region where the current density change rate exceeds a third guiding value as the strong change region, and the region where the current density change rate is lower than the third guiding value as the weak change region; According to the distribution of the strong change region and the weak change region, set a main channel in the strong change region and set branch channels in the weak change region; Calculate the cross-sectional area decreasing coefficient of the branch channels according to the spatial distribution law of the region of current density gradient change, so that the cross-sectional area of the branch channels gradually decreases from the connection with the main channel to the end to form the multi-level microchannel network.

6. The processing method of the in-vehicle high-voltage connector according to claim 1, characterized in that, Input an AC test signal within a preset frequency range to the connector of the sample, collect impedance data of the connector at each frequency point and within a preset voltage range, and generate a three-dimensional impedance-frequency-voltage characteristic map representing the impedance characteristics of the connector, including: Determine the frequency response characteristic points corresponding to different depth regions according to the microtrace depth distribution of the microtrace impedance gradient structure, apply multiple sets of AC test signals to the connector of the sample, collect impedance data at each frequency response characteristic point, and obtain the mapping relationship between the microtrace depth and the frequency response; Apply an AC test signal with an amplitude gradually increasing within a preset voltage range to the connector of the sample, measure the impedance change trend of the frequency response characteristic points at each voltage amplitude, and obtain a set of response curves representing the non-linear impedance characteristics; Analyze the change rate of the set of response curves, identify the points where the impedance change rate exceeds a predetermined threshold as impedance mutation points, increase the sampling frequency and voltage density near the impedance mutation points, and perform local fine scanning on the connector of the sample to obtain high-resolution impedance anomaly characteristic data; Based on the mapping relationship between the microtrace depth and the frequency response, perform spatial positioning analysis on the high-resolution impedance anomaly characteristic data, establish the corresponding relationship between the impedance anomaly and the microtrace structure, and generate a three-dimensional impedance-frequency-voltage characteristic map representing the impedance characteristics of the connector.

7. The processing method of the in-vehicle high-voltage connector according to claim 1, characterized in that Based on the key frequency points of the three-dimensional impedance-frequency-voltage characteristic map, apply multiple sets of pulsed currents with preset amplitudes and durations to the connector of the sample, collect the temperature change data of the key points inside the connector through the temperature response channel network, and obtain a temperature-time response curve representing the thermal characteristics of the connector, including: Based on the key frequency points in the three-dimensional impedance-frequency-voltage characteristic map, generate a pulsed current excitation sequence including a single amplitude increasing sequence, an alternating high and low amplitude sequence, and a random amplitude sequence, and the amplitude range of the pulsed current excitation sequence covers 20% to 120% of the rated current of the connector; According to the spatial distribution of the temperature response channel network, establish the temperature acquisition coordinates of the key points inside the connector, and collect the temperature response data of each temperature acquisition coordinate in the temperature response channel network during the application of the pulsed current excitation; Perform real-time analysis on the temperature response data, increase the temperature sampling frequency when it is detected that the temperature rising rate exceeds the first preset threshold, and restore the initial sampling frequency when it is detected that the temperature falling rate exceeds the second preset threshold, and obtain a set of temperature response data including temperature mutation characteristics; According to the set of temperature response data, calculate the temperature response delay time and temperature decay coefficient of each key point inside the connector, establish the temperature propagation path map of the connector, and generate a temperature-time response curve representing the thermal characteristics of the connector.

8. The processing method of the in-vehicle high-voltage connector according to claim 1, characterized in that, Performing a sequential comparison and analysis of the impedance-frequency-voltage three-dimensional characteristic map and the temperature-time response curve, calculating the correlation parameter between the impedance change and the temperature change of the connector, calibrating the hot spot position corresponding to the non-linear impedance change region in the connector, and generating a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch, including: Performing a time-domain mapping of the impedance-frequency-voltage three-dimensional characteristic map, and constructing a multi-dimensional impedance response matrix reflecting the sequential characteristics of impedance changes in different regions based on the spatial distribution of the microtrace impedance gradient structure; Performing a spatial analysis of the temperature-time response curve according to the topological structure of the temperature response channel network, establishing a propagation path map of temperature changes, and extracting the temperature gradient and propagation delay on each propagation path; Performing a spatial registration of the multi-dimensional impedance response matrix and the temperature propagation path map, identifying the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determining the key region where impedance changes induce temperature responses; Performing a decomposition of the impedance-temperature response characteristics of the key region, extracting the impedance mutation characteristics, temperature response delay characteristics, and temperature cumulative effect characteristics, and establishing a multi-dimensional characteristic space for non-linear impedance anomalies; Constructing a characteristic fingerprint mapping function based on the multi-dimensional characteristic space, mapping the combination of the impedance mutation characteristics, temperature response delay characteristics, and temperature cumulative effect characteristics into a quantifiable sequence of characteristic parameters, and generating a characteristic fingerprint for detecting non-linear impedance anomalies in connectors of the same batch.

9. The processing method of the in-vehicle high-voltage connector according to claim 8, wherein The performing a spatial registration of the multi-dimensional impedance response matrix and the temperature propagation path map, identifying the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension, and determining the key region where impedance changes induce temperature responses, includes: Converting the spatial distribution data of the multi-dimensional impedance response matrix into impedance gradient distribution data; Calculating the temperature propagation rate distribution data according to the temperature propagation path map; Performing a spatial coordinate mapping of the impedance gradient distribution data and the temperature propagation rate distribution data, and calculating the spatial overlap degree and sequential correlation degree between the two; Calculating a coupling coefficient according to the spatial overlap degree and the sequential correlation degree, identifying the coupling relationship between impedance changes and temperature changes in the spatio-temporal dimension based on the coupling coefficient, and determining the key region where impedance changes induce temperature responses.

10. A vehicle-mounted high-voltage connector, characterized in that, The processing process of the in-vehicle high-voltage connector adopts the processing method of the in-vehicle high-voltage connector according to any one of claims 1 to 9.

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