Modular quick-change wireless charging port safety regulation test method and system

Abstract

The present application relates to the wireless charging technical field, especially modular quick change formula wireless charging mouth safety regulation test method and system, this method includes the following steps: first, through the synchronous acquisition of contact current, contact voltage, output voltage, leakage current, effective PD event and temperature field image and so on in the test process, multiple physical field parameters are constructed Contact quality, module health degree and insulation stability three independent evaluation indexes, then, through the three index system, the module health degree is introduced to correct the insulation stability, finally, according to the contact quality, the module health degree and the insulation stability carry out fault diagnosis. The present application can locate the fault type to contact bad, test equipment performance fluctuation or charging port itself insulation defect, solves the problem that the traditional test method can only give general unqualified signal, cannot decouple fault type, thereby leading to misjudgment and missing.

Description

Technical Field

[0001] This invention relates to the field of wireless charging technology, and in particular to a modular quick-change wireless charging port safety testing method and system. Background Technology

[0002] As a key component of new energy vehicles, the insulation performance and electrical safety of wireless charging ports are directly related to the overall vehicle quality and user safety. Therefore, it is essential to conduct rigorous safety testing on them during the production line stage.

[0003] In existing safety testing of wireless charging ports, when an anomaly is detected, the testing system can usually only provide a general failure signal, unable to accurately distinguish whether the root cause of the fault is an insulation defect in the charging port of the vehicle under test, poor contact between the test probe and the vehicle, or fluctuations in the performance of the testing equipment itself. This ambiguity in fault diagnosis often requires manual intervention to troubleshoot step by step, which is time-consuming, leading to production line interruptions and affecting production efficiency and testing reliability.

[0004] In existing technologies, diagnostic models are typically constructed using single indicators or partially fused composite indicators. For example, the instantaneous values ​​or statistical characteristics of key parameters such as voltage, current, partial discharge, or temperature during the testing process are monitored and compared with preset fixed thresholds to determine whether the test results are qualified. However, this method based on simple threshold judgment or preliminary fusion of indicators has limitations: in complex scenarios such as wireless charging port testing where multiple physical fields are coupled, the signal characteristics caused by different fault types, such as poor contact, module performance degradation, and vehicle insulation defects, are often intertwined and highly similar. A single physical quantity or a simple combination of indicators is difficult to effectively decouple these intertwined signal characteristics caused by different fault types, making it impossible to accurately identify fault modes, resulting in a high rate of false positives and false negatives in the diagnostic results. Summary of the Invention

[0005] To address the technical problem in the aforementioned wireless charging port safety testing where fault signals are intertwined due to multi-physical field coupling, and where single or partially fused index diagnostic methods cannot decouple and locate faults, resulting in a high false positive and false negative rate, this invention provides solutions in the following aspects.

[0006] In a first aspect, the present invention provides a modular quick-swap wireless charging port safety testing method, the method being executed by a testing system including a high-voltage generation module, comprising the following steps: dividing the testing process into three sequentially performed stages, acquiring multi-physics parameters for each stage, including: contact voltage timing data and contact current timing data for the first stage, output voltage timing data of the high-voltage generation module for the second stage, leakage current timing data for the third stage, effective PD events, and a temperature field image of the heat dissipation surface of the high-voltage generation module at the end of the third stage; calculating contact resistance timing data using the contact voltage timing data and contact current timing data, and determining contact quality by combining the relative fluctuation of the contact resistance timing data and the harmonic proportion of the contact current timing data; evaluating the module health of the high-voltage generation module using the temperature distribution uniformity of the temperature field image and the deviation of the output voltage timing data from a preset target voltage; obtaining the insulation stability of the charging port insulation system based on the occurrence frequency of the effective PD events, the dynamic instability of the leakage current timing data, and the module health; and performing fault diagnosis based on the contact quality, the module health, and the insulation stability.

[0007] This invention acquires multiple physical field parameters, including contact voltage, contact current, leakage current, effective PD events, and temperature field images, and constructs three targeted evaluation indicators: contact quality, module health, and insulation stability. This enables a comprehensive, multi-dimensional assessment of the safety performance of wireless charging ports. Compared to traditional single-parameter testing methods, this invention overcomes the limitations of focusing only on insulation or contact, simultaneously covering the three key risk points of "contact reliability, device health, and insulation safety" during testing. It also addresses the pain point of existing technologies that can only provide general non-compliance signals and cannot distinguish the root cause of the fault. Furthermore, this invention introduces module health as a correction factor into the insulation stability calculation, effectively eliminating misjudgments of the tested device due to problems with the testing equipment itself. This avoids the high misjudgment rate caused by the interweaving of fault signals in existing technologies, improving the accuracy, reliability, and diagnostic efficiency of safety testing, and providing a clear basis for subsequent fault investigation.

[0008] Preferably, obtaining the harmonic proportion of the contact current time series data includes: performing a Fourier transform on the contact current time series data to obtain the fundamental component and multiple harmonic components; calculating the sum of squares of the amplitudes of the multiple harmonic components, taking the square root of the sum of squares, and then dividing it by the amplitude of the fundamental component to obtain the harmonic proportion.

[0009] This invention obtains the fundamental and harmonic components by performing a Fourier transform on the contact current time-series data, and calculates the harmonic proportion by the ratio of the square root of the sum of squares of the harmonic component amplitudes to the fundamental amplitude. This method can accurately assess the degree of current waveform distortion caused by poor contact. Compared with simple summation of harmonic amplitudes, the square root calculation better highlights the impact of higher-order harmonics on waveform quality, providing a highly sensitive waveform stability dimension for contact quality assessment and enhancing the ability to detect non-steady-state contact faults, such as intermittent impedance changes caused by loose contact.

[0010] Preferably, obtaining the relative fluctuation of the contact resistance time series data includes: calculating the ratio of the standard deviation to the average value of the contact resistance time series data.

[0011] Preferably, the acquisition of the deviation between the output voltage timing data and the preset target voltage includes: acquiring the difference between the voltage value at each sampling time in the second stage output voltage timing data and the voltage value at the corresponding time of the preset target voltage, calculating the sum of squares of all differences, taking the square root of the sum of squares, and dividing it by the maximum value of the preset target voltage.

[0012] This invention evaluates the deviation of the output voltage by calculating the normalized root mean square error. This method evaluates the dynamic tracking performance throughout the voltage ramp-up phase, and by normalizing the maximum value, the evaluation results are not affected by the test voltage level. This allows for a more comprehensive reflection of the dynamic response capability and control accuracy of the high voltage generation module, thereby more accurately assessing its module health.

[0013] Preferably, obtaining the temperature distribution uniformity of the temperature field image includes: obtaining the temperature values ​​of all pixels in the temperature field image, and calculating the ratio of the standard deviation to the average value of all temperature values.

[0014] Preferably, the acquisition of the dynamic instability of the leakage current time series data includes: dividing the third stage into a time-continuous first half and a second half; integrating the square of the leakage current time series data over the corresponding time period of the first half, dividing by the duration of the first half to obtain the average energy of the first half; integrating the square of the leakage current time series data over the corresponding time period of the second half, dividing by the duration of the second half to obtain the average energy of the second half; calculating the ratio of the average energy of the second half to the average energy of the first half, adding a preset small value to the absolute difference between the ratio and 1, and taking the reciprocal to obtain the dynamic instability of the leakage current.

[0015] This invention divides the voltage holding phase into two halves, calculates the average energy of the square integral of the leakage current in each half, and compares the results to assess the dynamic instability of the leakage current. Compared with directly monitoring the changes in leakage current values, the energy-based assessment can better reflect the cumulative effect of leakage current, effectively capture the deterioration trend of insulation performance over time, and thus identify insulation defects in the early failure stage earlier, enhancing the early warning capability of insulation stability.

[0016] Preferably, obtaining the occurrence frequency of the effective PD events includes: counting the total number of effective PD events in the third stage and the time interval between every two adjacent effective PD events; calculating the average of the time intervals of all adjacent effective PD events; and dividing the total duration of the third stage by the average of the time intervals of all adjacent effective PD events to obtain the occurrence frequency of the effective PD events.

[0017] Preferably, the fault diagnosis based on the contact quality, module health, and insulation stability includes: comparing the contact quality, module health, and insulation stability with their respective preset thresholds; determining that the test passes when all three are greater than their respective thresholds; determining that the test fails when at least one of the contact quality, module health, and insulation stability is less than its threshold, and identifying the fault type associated with one or more indicators below the threshold, wherein the fault type includes poor contact, high-voltage module performance fluctuation, or charging port insulation defect.

[0018] This invention compares three indicators—contact quality, module health, and insulation stability—with their respective preset thresholds. It can not only clearly determine that the test has passed when all three are greater than or equal to the threshold, but also attribute the problem to specific fault types such as poor contact, high-voltage module performance fluctuations, or charging port insulation defects when at least one indicator is less than the threshold. This provides a clear process, definite results, and direct guidance for fault diagnosis in production line safety testing, effectively reducing the time cost of fault location after testing and improving the overall efficiency of testing and subsequent maintenance.

[0019] Preferably, the location of fault types associated with one or more indicators below a threshold includes: when two or more indicators are below the threshold and correspond to multiple fault types, diagnostic output is performed in the priority order of poor contact, high voltage generation module performance fluctuation, and charging port insulation defect.

[0020] In a second aspect, the present invention provides a modular quick-switch wireless charging port safety testing system, the modular quick-switch wireless charging port safety testing system including a memory and a processor, the memory storing computer program instructions, and when the computer program instructions are executed by the processor, implementing the modular quick-switch wireless charging port safety testing method of the first aspect of the present invention.

[0021] By adopting the above technical solution, a computer program for the modular quick-change wireless charging port safety testing method of the first aspect of the present invention is generated and stored in a memory so that it can be loaded and executed by a processor, thereby making a terminal device based on the memory and the processor for convenient use.

[0022] The beneficial effects of this invention are as follows: By simultaneously collecting multi-physical field data such as contact voltage, contact current, output voltage, leakage current, effective PD events, and temperature field images during the safety testing of wireless charging ports, this invention overcomes the limitations of traditional single-parameter testing and constructs three decoupled evaluation indicators: contact quality, module health, and insulation stability. Contact quality focuses on the contact reliability between the probe and the charging port; module health focuses on the operational stability of the high-voltage generation module; and insulation stability directly addresses the insulation safety of the charging port itself. These three indicators correspond to the three core stages of the entire testing process: contact establishment, equipment operation, and insulation protection, forming a complete indicator system covering test risk points. This system not only enables the basic determination of whether safety performance is qualified or unqualified, but also helps to pinpoint the fault direction through the correlation between indicators and faults, effectively alleviating the problems of intertwined fault signals and difficulty in fault location in traditional testing. At the same time, the decoupling characteristics of the three indicators prevent misjudging the overall fault due to a single indicator anomaly, improving testing accuracy and diagnostic efficiency, and providing a standardized and efficient solution for production line batch testing and after-sales maintenance of modular quick-change wireless charging ports. Attached Figure Description

[0023] Figure 1 A flowchart of a modular quick-swap wireless charging port safety testing method provided in an embodiment of the present invention;

[0024] Figure 2 The changes in output voltage and their corresponding stages are provided for embodiments of the present invention.

[0025] Figure 3 This is a structural block diagram of a modular quick-change wireless charging port safety testing system provided in an embodiment of the present invention. Detailed Implementation

[0026] The first aspect of this invention provides a safety testing method for a modular quick-swap wireless charging port, such as... Figure 1 As shown, the method includes steps S100-S300:

[0027] Step S100: Divide the testing process into three stages to be carried out sequentially, and obtain the multiphysics parameters of each stage.

[0028] It should be noted that in actual safety testing of wireless charging ports, the causes of faults are diverse and often interdependent. Measuring only a single electrical parameter is insufficient to accurately distinguish between different types of potential faults, such as poor contact, charging module degradation, and insulation defects in the charging port. This can easily lead to the lumping of abnormal phenomena observed during testing attributing them indiscriminately to the device under test, resulting in vague fault diagnosis results and a high misjudgment rate, failing to meet the requirements for fault localization in safety testing. This step involves deploying multi-physics sensors to synchronously collect feature data directly related to various fault types at different stages of testing. This provides data support for subsequently constructing independent fault identification indicators and achieving accurate fault diagnosis in wireless charging port safety testing. Therefore, real-time acquisition of multi-physics parameters is necessary.

[0029] This step of multiphysics parameter acquisition follows the procedure for wireless charging port safety testing, and can be divided into three stages based on the output voltage: contact establishment stage, voltage ramp-up stage, and voltage hold-up stage. The specific divisions are as follows: Figure 2 As shown in the figure, the horizontal axis represents time, and the vertical axis represents the output voltage. During this time period, the contact establishment phase is underway. During this phase, the output voltage remains at a low level to prepare for subsequent testing. During this period, the voltage ramp-up phase begins, with the output voltage trending upwards, gradually reaching the high voltage level required for the test; from From then on, that is The time period is the voltage holding phase, during which the output voltage remains stable in order to conduct relevant safety tests.

[0030] The differences between the test states in each stage are as follows: The contact establishment stage is the initial stage of the test, which mainly completes the physical contact and connection verification between the wireless charging port and the modular quick-change test device (hereinafter referred to as the test device); the voltage ramp-up stage starts after the contact stabilizes, and the output voltage of the test device increases linearly from 0V to the preset safety test target voltage, which is determined according to the rated insulation class of the wireless charging port or the corresponding safety standard; the voltage holding stage is the stable test stage after the voltage reaches the target value, which lasts until the end of the safety test cycle.

[0031] Specifically, the sensors deployed at each stage and the data collected are as follows:

[0032] Contact Establishment Phase A high-frequency voltage sensor and a high-frequency current sensor are deployed, both installed at the contact interface between the wireless charging port and the testing device, and fixed on opposite sides of the contact point. The high-frequency voltage sensor operates at a preset fixed frequency. Real-time acquisition of contact voltage at both ends of the wireless charging port contact point to generate contact voltage timing data. ,in, The exemplary value is 10kHz, but it can also be set according to requirements; the high-frequency current sensor synchronously collects the contact current flowing through the contact point at the same frequency to form contact current time sequence data. At the same time, the background noise amplitude is measured simultaneously during this stage. These two types of data are used to reflect the connection quality of the contact interface and provide a basis for judging whether there are potential contact problems.

[0033] Voltage ramp-up phase A high-voltage sensor is deployed in the output circuit of the charging module. The high-voltage generation module is the core unit of the charging module. The testing device starts after confirming stable contact. The criteria for determining stable contact are: the standard deviation of the contact voltage timing data is less than 0.1V for three consecutive sampling periods, and there is no amplitude jump in the contact current timing data. The jump threshold can be set to the current average value. Subsequently, the high-voltage generation module begins to output voltage. During the linear rise of the voltage from 0V to the target test voltage, the high-voltage sensor operates at a preset fixed frequency. Real-time acquisition of the output voltage of the charging module yields the timing data of the output voltage of the high-voltage generator module. It is used to monitor the output stability of the charging module during dynamic voltage changes, and to help determine whether the module is at risk of degradation.

[0034] Voltage holding phase A micro-current sensor is connected in series to the grounding loop of the wireless charging port. An ultra-high frequency (UHF) antenna array is arranged in the test space around the wireless charging port, and an infrared thermal imager is aimed at the heat dissipation surface of the charging module. The micro-current sensor operates at a preset fixed frequency. Real-time acquisition of leakage current from the wireless charging port to generate leakage current timing data. This reflects the insulation performance of the charging port insulation system; the UHF antenna array monitors high-frequency pulse signals in space in real time. When the pulse amplitude exceeds three times the background noise amplitude measured synchronously during the contact establishment phase, it is determined to be an effective partial discharge (PD) event. The frequency and amplitude of partial discharge events can reflect the degree of aging or defects in the insulation system, and the time of event occurrence is recorded. ,in, The total number of valid PD events during this phase further verifies the stability of the insulation system; before the end of the voltage holding phase test, an infrared thermal imager captures the temperature field image of the heat dissipation surface of the high-voltage generator module. By analyzing temperature distribution characteristics, it can be determined whether there is localized overheating in the module, thus providing a supplementary assessment of the module's health status.

[0035] This completes the three-stage data collection process.

[0036] Step S200: Calculate contact resistance timing data using the contact voltage timing data and contact current timing data; determine contact quality by combining the relative fluctuation of the contact resistance timing data and the harmonic proportion of the contact current timing data; evaluate the module health of the high-voltage generation module by using the temperature distribution uniformity of the temperature field image and the deviation of the output voltage timing data from the preset target voltage; obtain the insulation stability of the charging port insulation system based on the occurrence frequency of the effective PD events, the dynamic instability of the leakage current timing data, and the module health.

[0037] It should be noted that although the collected data contains rich information, it still has discreteness and multi-dimensional characteristics, making it difficult to use directly for fault location. This step constructs three evaluation feature indicators that are strongly correlated with and independent of specific physical fault sources, namely contact interface, test module, and vehicle itself, by mathematical modeling and fusion of these raw data. These are contact quality, module health, and insulation stability. This process realizes dimensionality reduction and information extraction from multi-dimensional raw data to low-dimensional feature indicators.

[0038] Specifically, this step includes steps S210-S230:

[0039] Step S210: Calculate the contact quality between the wireless charging port and the test device during the contact establishment phase.

[0040] It should be noted that the vehicle charging pad is the core contact component of the wireless charging port. Abnormal conditions at the contact interface between the test probe and the vehicle charging pad are a common cause of test failure. This abnormality will directly affect the stability of the contact resistance and the waveform quality of the contact current. When there is an oxide layer, impurities, or unstable contact pressure at the contact interface, the contact resistance will experience instantaneous jumps, leading to an increased relative fluctuation. At the same time, unstable contact will cause interruptions or impedance changes in the current transmission path, resulting in current waveform distortion, manifested as a significant increase in harmonic components other than the fundamental frequency in the current signal.

[0041] Considering that Fourier transform has the ability to decompose current time-series signals in the time domain into fundamental and harmonic components in the frequency domain, and can accurately separate and extract harmonic information reflecting waveform distortion, this invention integrates two types of features to construct contact quality by first calculating the degree of contact resistance fluctuation and then using Fourier transform to extract the harmonic proportion, in order to determine whether the fault originates from the contact interface between the test probe and the vehicle body charging plate.

[0042] Specifically, the contact resistance array during the contact establishment phase is first calculated. According to Ohm's law, the contact voltage timing data and contact current timing data at the same sampling time are divided point by point to obtain the contact resistance timing array. ,in, It is the first The contact resistance at the sampling time is measured; then, the contact current time series data is processed by Fast Fourier Transform to obtain the fundamental component. With each harmonic component ,in, It is the highest order of harmonic analysis. Based on the operating frequency and safety testing standards of the wireless charging port, in one feasible implementation, if the operating frequency of the wireless charging port is 150kHz, m=10th order is set according to twice the operating frequency to cover the main harmonic components. The implementer can set it according to the requirements; finally, the contact quality is calculated based on the above data.

[0043] Based on the above logic, the contact quality satisfies the following relationship:

[0044] ;

[0045] in, It refers to the contact quality between the wireless charging port and the testing device; It is a timing array of contact resistances; It is the standard deviation of the contact resistance timing array; It is the average value of the contact resistance timing array; It is the amplitude of the fundamental component of the contact current time series data; It represents the amplitude of each harmonic component of the contact current timing data; It is a natural exponential function.

[0046] In this relation, Used to assess the relative fluctuation of contact resistance, when oxidation, impurities, or unstable contact pressure are present on the contact surface, the contact resistance will fluctuate drastically, causing its standard deviation to increase significantly relative to the average value. This ratio subsequently rises, ultimately affecting the contact quality. The contact resistance decreases; conversely, under ideal contact conditions, the contact resistance is stable, and this ratio approaches zero. The ratio of the square root of the sum of the squares of the amplitudes of all harmonic components to the amplitude of the fundamental component, also known as the harmonic proportion, is used to assess the degree of distortion in the current waveform. When the probe oxidizes or the contact is interrupted, current transmission is hindered, and the waveform is no longer an ideal sine wave, generating a large number of harmonic components, which increases the total harmonic amplitude. Consequently, this ratio increases, ultimately affecting the contact quality. The ratio decreases; conversely, when the contact is good and the current waveform is close to a pure sine wave, the ratio approaches zero. Used to map the superposition value of resistance fluctuation and harmonic proportion to The range makes the assessment of contact quality more intuitive.

[0047] At this point, the contact quality between the wireless charging port and the test device during the contact establishment phase was obtained.

[0048] Step S220: Calculate the module health of the high voltage generating module.

[0049] It should be noted that the stability of the high-voltage generation module, as the high-voltage source of the testing device, is crucial to ensuring the validity of the test benchmark. Deterioration in the performance of the high-voltage generation module typically manifests in two ways: first, abnormal heat dissipation systems, such as blocked heat dissipation channels or aging power chips, can lead to localized hot spots on the surface of the high-voltage generation module, resulting in uneven overall temperature distribution; second, abnormal output control circuits, such as circuit parameter drift or power device response delays, can cause the actual output voltage to deviate from the preset ideal linear ramp-up trajectory. Therefore, this invention constructs a module health score by integrating the coefficient of variation of the final temperature field of the high-voltage generation module's heat dissipation surface and the normalized root mean square error during the voltage ramp-up process, which is used to determine whether a fault originates from a performance problem within the high-voltage generation module itself.

[0050] Specifically, after the voltage holding phase ends, based on the collected final temperature field data of the heat dissipation surface and the output voltage timing data of the voltage ramp-up phase, the health of the high-voltage generation module is calculated using the following formula, wherein the health satisfies the following formula:

[0051] ;

[0052] in, It refers to the health status of the high-voltage generating module; These are pixels in the temperature field image of the heat dissipation surface of the high-voltage generator module. Temperature field data; It is the standard deviation of the temperature field data of all pixels in the temperature field image of the heat dissipation surface; It is the average value of the temperature field data of all pixels in the temperature field image of the heat dissipation surface; This represents the total number of voltage samples during the voltage ramp-up phase. For the first The output voltage of the high-voltage generation module at the sampling time; For the first The preset target output voltage of the high voltage generation module at the sampling time is the preset linear voltage trajectory during the voltage ramp-up phase, that is, the theoretical value of linearly rising from 0V to the target test voltage. It is a maximum value function used to obtain the maximum value of the preset target output voltage of the high voltage generating module; It is a natural exponential function.

[0053] In this formula, the first term This is the coefficient of variation of the final temperature field, used to reflect the relative uniformity of temperature distribution. When the high-voltage generator module has blocked heat dissipation channels or chip aging, local overheating will occur on the heat dissipation surface, leading to increased temperature differences at different locations, higher standard deviation, and consequently, an increase in this ratio, thus reducing the module's health. (Second item) It is the normalized voltage output error. The L2 norm, essentially the normalized root mean square error, characterizes the degree of deviation between the actual output voltage and the target linear trajectory. When the parameters of the voltage regulation circuit within the module drift or the power device response is delayed, the actual output voltage... It will be unable to accurately match the preset target output voltage. This leads to an increase in the sum of squared errors, which in turn increases the value of this item, ultimately resulting in a decrease in the module's health.

[0054] Different fault types of the tested charging port, such as poor contact, high-voltage performance fluctuations, and insulation defects, will have unique effects on its equivalent electrical load characteristics. When the test system of this invention applies high voltage to the tested charging port, the output voltage or current waveform of the high-voltage generation module built into the test system will deviate from its reference waveform under ideal load due to the different load characteristics of the tested charging port. Therefore, by analyzing the degree of this deviation, the specific fault state of the tested charging port can be inferred. In this application scenario, the module health is not used to assess whether the test equipment itself is damaged, but rather serves as an indirect, highly sensitive diagnostic indicator to reflect the performance status of the tested object.

[0055] At this point, the health status of the high-voltage generating module has been obtained.

[0056] Step S230: Calculate the insulation stability of the vehicle charging port insulation system.

[0057] It should be noted that the insulation performance of the vehicle charging port is the core of safety testing. Insulation defects are usually exposed through two phenomena: first, the frequency of partial discharge events (PD events) becomes more frequent when the charging port has insulation damage or conductive impurities on its surface; second, the dynamic characteristics of leakage current. In a healthy insulation system, the leakage current may fluctuate slightly in the initial stage and then tend to stabilize, while in a defective system, the leakage current may continue to leak, resulting in little difference in the average energy before and after the test. Furthermore, the health of the high-voltage generation module directly affects the quality of the test signal. An unhealthy high-voltage generation module may output high voltage with noise, thus interfering with the measurement of leakage current and PD events. Therefore, this invention constructs a comprehensive charging port insulation stability by integrating evaluation indicators characterizing the above two phenomena and introducing module health as a correction factor.

[0058] Specifically, the calculation process first constructs measures to characterize the severity of partial discharge and the instability of leakage current, and then merges them to obtain the insulation stability of the charging port insulation system.

[0059] First, to assess the density of partial discharge events, this invention establishes the occurrence frequency of effective PD events during the voltage holding phase. Considering that within a fixed test time, the more dense the effective PD events, the shorter their average time interval, the occurrence frequency of effective PD events satisfies the following relationship:

[0060] ;

[0061] in, It is the frequency of occurrence of effective PD events during the voltage holding phase; Effective during the voltage holding phase The total number of events; It is the first The and the first One valid The time interval between events; This represents the total duration of the voltage holding phase.

[0062] In this formula, the numerator is the total duration of the voltage holding phase, and the denominator is the average time interval between all adjacent valid PD events. The ratio of the two is a multiple of the total test duration to the average interval of valid PD events. For example, if... The average time interval is ,but This indicates that the total duration is equal to the average interval. Times, occurring per unit time Number of valid PD events; if the average time interval is ,but The frequency of effective PD events per unit time has increased to Secondly, it intuitively demonstrates that the larger the multiplier, the more effective PD events there are per unit time, and the higher the density. Therefore, the more concentrated the effective PD events, the higher the density. A higher value indicates problems such as insulation damage or conductive impurities on the surface of the charging port insulation system, resulting in more frequent partial discharges; conversely, a lower value indicates better insulation of the charging port and sparser effective PD events. The smaller the value, the higher the stability of the insulation system.

[0063] It should be noted that when no valid PD event is detected during the voltage holding phase, that is... At this time, it indicates that there are no partial discharge-related defects in the charging port insulation system, and at this time, it can be set When only one valid PD event is detected during the voltage holding phase, because This renders the denominator meaningless, and since single events are usually sporadic interferences rather than caused by insulation defects, a setting can be made. It can also be adjusted according to safety regulations and standards. In this case, it is neither judged as good insulation nor as defective, leaving reasonable room for judgment in case of occasional events and avoiding misjudgment.

[0064] Secondly, to evaluate the dynamic instability characteristics of leakage current, this invention constructs a leakage current instability model. Considering that the leakage current of a healthy insulator tends to decay and stabilize, while the leakage current of a defective insulator will persist or even increase, a voltage holding phase is included. Further subdivided into the first half With the second half The dividing point between the two segments It is the midpoint of the total duration of the voltage holding phase, that is... ,and , Under healthy insulation conditions, the average energy difference between the first and second halves of the leakage current is significant, with the ratio deviating from 1. When insulation defects exist, the ratio of the average energy of the leakage current between the first and second halves of the voltage holding phase will approach 1. Based on the above logic, the leakage current instability satisfies the following relationship:

[0065] ;

[0066] in, It is leakage current instability during the voltage holding phase; , These are the start and end times of the voltage holding phase; This is the total duration of the voltage holding phase. ; It is the middle moment of the voltage holding phase; This is the leakage current timing data during the voltage holding phase; This is a preset microvalue used to prevent the denominator from being zero; it can be set to... It can also be configured according to needs.

[0067] In this relation, This refers to the total energy of the leakage current during the latter part of the voltage holding phase, divided by [the specified value]. This refers to the average energy of the leakage current in the latter part of the voltage holding phase. It refers to the average energy of leakage current during the first period of the voltage holding phase; the leakage current energy of a healthy insulation system changes with time, showing slight fluctuations in the early stage and stabilization in the later stage, and the ratio of the energy before and after the stage will deviate from 1; when the insulation is defective, the leakage current energy will continue to leak, the difference between the energy before and after the stage is small, and the ratio of the energy before and after the stage will be close to 1.

[0068] Finally, the two metrics mentioned above are merged, normalized using an exponential function, and then the calculated module health score is introduced. As a correction factor, the final insulation stability of the insulation system is obtained, and the insulation stability of the insulation system satisfies the following relationship:

[0069] ;

[0070] in, It refers to the insulation stability of the charging port insulation system; It refers to the module health status of the high-voltage generating module; It is leakage current instability during the voltage holding phase; It is the frequency of occurrence of effective PD events during the voltage holding phase; It is a natural exponential function.

[0071] In this relation, the natural exponential function... and The summation term represents the overall degree of insulation degradation; any increase in the frequency of effective PD events or the degree of leakage current instability will lead to an increase in this summation term, thus significantly reducing the evaluation result through the effect of the negative natural exponential function; correction factor This reflects the reliability of the test benchmark, when the module health... A low value indicates a problem with the test source itself, which will directly lower the final insulation stability assessment result. This effectively distinguishes between problems with the testing equipment and insulation issues with the vehicle's charging port itself, avoiding misjudgments.

[0072] Thus, the insulation stability of the vehicle charging port insulation system was obtained.

[0073] Step S300: Perform fault diagnosis based on the contact quality, module health, and insulation stability.

[0074] It should be noted that after calculating the three independent characteristic indicators of contact quality, module health, and insulation stability, this step establishes a clear decision-making logic. By comparing these indicators with their respective thresholds, a specific and actionable fault diagnosis conclusion is finally output.

[0075] Specifically, it is necessary to determine the judgment thresholds for three indicators. , , .

[0076] These thresholds can be collected by performing multiple fault-free tests on the same model or batch of vehicles. , , The distribution of indicators is set using the lower confidence limit of the statistical distribution, such as the mean minus three standard deviations, to ensure the reliability of the diagnosis. If there is insufficient fault-free test data for the same model or batch, industry standards or threshold data for similar models can be referenced and determined after calibration in combination with the actual test scenario.

[0077] Then, the fault type is determined according to the following logic:

[0078] Fault-free scenario: If all indicators meet the conditions , and If the result is positive, the test is considered passed, and the output conclusion is "normal".

[0079] Single failure scenario: If only the contact quality fails to meet the conditions, i.e. ,and and If the fault type is determined to be "probe-vehicle charging pad poor contact", the corresponding fault information will be output; if only the module health condition is not met, i.e. ,and ,and If the value is too low, the fault type is determined to be "fluctuation in the performance of the high-voltage generator module itself". In this case, due to the insulation stability... The calculation was affected by unhealthy The correction of the value may result in an underestimation and distortion. Therefore, instead of directly determining an insulation defect, a module fault will be reported first, and a suggestion will be made to repair the high-voltage generating module and retest. If the contact quality and module health are both normal, i.e. and However, the insulation stability does not meet the requirements, i.e. If the fault type is determined to be "charging port insulation defect", the corresponding fault information will be output.

[0080] Complex fault scenarios: If two or more indicators are below their corresponding thresholds, diagnosis will be performed according to a preset troubleshooting priority. This priority is determined based on the flow of test signals and the chain of influence: a good contact interface is a prerequisite for all subsequent signal acquisition; the high-voltage generator module, as the test source, is the source of signal generation; and the vehicle charging port insulation system is the final test object. Therefore, the priority is set as contact interface → high-voltage generator module → insulation system. For example, if... and The system will first report a "probe-car body charging pad poor contact" fault, as contact problems are the most fundamental cause affecting all subsequent measurements; if and The system will first report a fault indicating "performance fluctuation of the high-voltage generator module," prompting the user to repair the module and retest. If... and First report the "probe-car body charging board poor contact" fault, and then check the module fault after ruling out contact problems.

[0081] The second aspect of this embodiment provides a modular quick-swap wireless charging port safety testing system, such as... Figure 3 As shown, the modular quick-switch wireless charging port safety testing system includes a memory and a processor. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the first aspect of the present invention, a modular quick-switch wireless charging port safety testing method, is implemented.

[0082] The modular quick-change wireless charging port safety testing system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces. Their setup and functions are known in the art and will not be described in detail here.

[0083] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (DRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (DRAM), high-bandwidth memory, hybrid memory cube, etc., or any other medium that can be used to store desired information and can be accessed by an application, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device.

[0084] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A modular quick-switch wireless charging port safety testing method, the method being executed by a testing system, the testing system including a high-voltage generation module, characterized in that, Including the following steps: The testing process was divided into three phases performed sequentially, and multiphysics parameters for each phase were obtained, including: contact voltage timing data and contact current timing data in the first phase, output voltage timing data of the high voltage generation module in the second phase, leakage current timing data, effective PD events, and temperature field images of the heat dissipation surface of the high voltage generation module at the end of the third phase. Contact resistance time-series data is calculated using the contact voltage and contact current time-series data. Contact quality is determined by combining the relative fluctuation of the contact resistance time-series data with the harmonic proportion of the contact current time-series data. The module health of the high-voltage generation module is evaluated using the temperature distribution uniformity of the temperature field image and the deviation of the output voltage time-series data from the preset target voltage. The insulation stability of the charging port insulation system is obtained based on the occurrence frequency of effective PD events, the dynamic instability of the leakage current time-series data, and the module health. Fault diagnosis is performed based on the contact quality, module health, and insulation stability.

2. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the harmonic proportion of the contact current timing data includes: Perform a Fourier transform on the contact current time series data to obtain the fundamental component and multiple harmonic components; Calculate the sum of squares of the amplitudes of the multiple harmonic components, take the square root of the sum, and then divide it by the amplitude of the fundamental component to obtain the harmonic proportion.

3. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the relative fluctuation of the contact resistance timing data includes: Calculate the ratio of the standard deviation to the mean of the contact resistance time series data.

4. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the deviation between the output voltage timing data and the preset target voltage includes: Obtain the difference between the voltage value at each sampling time in the second stage output voltage timing data and the voltage value at the corresponding time of the preset target voltage, calculate the sum of squares of all differences, take the square root of the sum of squares, and divide it by the maximum value of the preset target voltage.

5. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the temperature distribution uniformity of the temperature field image includes: Obtain the temperature values ​​of all pixels in the temperature field image, and calculate the ratio of the standard deviation to the mean of all temperature values.

6. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the dynamic instability of the leakage current timing data includes: The third stage is divided into a first half and a second half that are consecutive in time; Integrate the square of the leakage current time series data over the corresponding time period in the first half, and divide by the duration of the first half to obtain the average energy of the first half; integrate the square of the leakage current time series data over the corresponding time period in the second half, and divide by the duration of the second half to obtain the average energy of the second half. Calculate the ratio of the average energy of the second half to the average energy of the first half, add a preset small value to the absolute difference between the ratio and 1, and take the reciprocal to obtain the dynamic instability of the leakage current.

7. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The acquisition of the occurrence frequency of the effective PD events includes: Count the total number of valid PD events in the third phase, and the time interval between any two adjacent valid PD events; Calculate the average time interval of all adjacent valid PD events; The frequency of occurrence of effective PD events is obtained by dividing the total duration of the third stage by the average time interval of all adjacent effective PD events.

8. The modular quick-change wireless charging port safety testing method according to claim 1, characterized in that, The fault diagnosis based on the contact quality, the module health, and the insulation stability includes: The contact quality, module health, and insulation stability are compared with their respective preset thresholds; when all three are greater than their respective thresholds, the test is deemed to have passed. When at least one of the contact quality, module health, and insulation stability is less than its threshold, the test is deemed to have failed, and the fault type associated with one or more indicators below the threshold is identified, wherein the fault type includes poor contact, high voltage module performance fluctuation, or charging port insulation defect.

9. The modular quick-change wireless charging port safety testing method according to claim 8, characterized in that, The location is associated with one or more fault types that are below a threshold, including: When two or more indicators are below the threshold, corresponding to multiple fault types, diagnostic outputs are performed in the order of priority: poor contact, high voltage generation module performance fluctuation, and charging port insulation defect.

10. A modular quick-change wireless charging port safety testing system, characterized in that, The modular quick-switch wireless charging port safety testing system includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a modular quick-switch wireless charging port safety testing method according to any one of claims 1-9.

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