A method for automatically detecting charging gun faults

Abstract

The present invention relates to the technical field of electric vehicle charging equipment, and specifically to a method for automatic detection of charging gun faults, which aims to solve the problem in the prior art that when combining resistance measurement values ​​to judge cable break faults, such hidden faults cannot be accurately located. The present invention can accurately identify non-breakage poor contact faults such as oxidation and false connection of the charging gun interface, and effectively distinguish between physical breaks and abnormal contact impedance. It can stably detect weak fault characteristics in complex electromagnetic environments, improve the accuracy of locating multiple fault points, and avoid maintenance delays caused by misjudgment of a single parameter. The method achieves coordinated optimization of fault diagnosis accuracy and environmental adaptability through composite signal separation and processing technology.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging equipment, and in particular to a method for automatically detecting faults of a charging gun. Background Art

[0002] Existing charging gun fault detection solutions suffer from weak anti-interference capabilities, insufficient multi-fault point resolution, and flawed reference library management. Specifically, existing technologies primarily detect the transmission time difference between the sending and receiving signals at the charging station port, reflecting the physical length of the cable, and combine this with resistance measurements to identify cable breakage faults.

[0003] However, this method cannot accurately locate hidden faults caused by non-disconnection failures, such as those caused by interface oxidation or loose connections, which result in an abnormal increase in resistance but no change in physical length. This is because the transmission time difference in this case still shows normal values, and relying solely on resistance measurements may lead to misjudgments of "no fault" or "unclear fault." Furthermore, existing solutions lack detection reliability in complex interference environments, have limited ability to identify and locate multiple fault points, and lack a robust baseline data management and update mechanism. Summary of the Invention

[0004] (1) Technical issues to be resolved

[0005] To solve the above problems, the present invention proposes a method for automatically detecting charging gun faults, which aims to solve the problem in the prior art that when combining resistance measurement values ​​to judge cable breakage faults, such hidden faults cannot be accurately located.

[0006] (2) Technical solution

[0007] The present invention provides a method for automatically detecting faults of a charging gun, and the technical solution is as follows:

[0008] include:

[0009] A composite detection signal is injected into the positive and negative ports of the charging gun. The composite detection signal is formed by coupling the time domain pulse component and the frequency domain swept frequency component of the linear frequency modulation;

[0010] Synchronously collect the reflected signal of the port and separate and process the reflected signal to obtain the pulse reflection sub-signal and the swept frequency reflection sub-signal;

[0011] Perform time domain analysis on the pulse reflection sub-signal and calculate the pulse transmission time difference to evaluate the cable physical length anomaly;

[0012] Performing time-frequency transformation on the swept frequency reflection sub-signal to generate a time-frequency matrix, and extracting frequency domain characteristic parameters from the time-frequency matrix. The frequency domain characteristic parameters include resonance peak characteristics, fundamental frequency impedance amplitude, and resonance point phase jump;

[0013] When the pulse transmission time difference does not trigger a physical fracture alarm, frequency domain verification is performed based on the frequency domain characteristic parameters: the frequency domain verification includes at least two verification conditions. If the verification conditions are met at the same time, it is determined that a non-fracture poor contact fault exists.

[0014] Furthermore, this application also proposes that the verification conditions include:

[0015] The first condition is that the resonance peak quality factor value is greater than the threshold;

[0016] The second condition is that the growth rate of the fundamental frequency impedance amplitude relative to the historical benchmark value is greater than the threshold;

[0017] The third condition is that the phase jump angle of the resonance point is greater than the threshold;

[0018] If the first condition, the second condition, and the third condition are met at the same time, it is determined that a non-disconnection poor contact fault exists.

[0019] Furthermore, the present application also proposes:

[0020] Based on the center frequency of the resonance peak characteristics and the dynamically updated wave velocity parameters, the location distance of the poor contact fault point is calculated through the wave velocity adaptive model;

[0021] After each successful charge, the current impedance characteristic vector is stored in the benchmark library according to vehicle type classification, and the historical benchmark value is updated through the aging factor weighted algorithm.

[0022] Furthermore, the present application also proposes that the generation of the composite detection signal includes:

[0023] The driving circuit of the multiplexing charging pile power device generates a time domain pulse component;

[0024] Generate frequency domain swept frequency component of linear frequency modulation through programmable waveform generator;

[0025] The signal injection is transmitted to the charging gun port using differential coupling.

[0026] Furthermore, the present application also proposes that when synchronously collecting the reflected signal:

[0027] Use high-precision ADC analog-to-digital converter for signal acquisition;

[0028] The sampling clock is equipped with a temperature compensation mechanism to maintain time base stability.

[0029] Furthermore, the present application also proposes that performing time-frequency transformation on the swept frequency reflection sub-signal includes:

[0030] Perform windowing and segmentation processing on the signal stream;

[0031] Perform Fourier transform in each time window to generate a time-frequency matrix;

[0032] Coherent averaging is performed on the swept frequency components to improve the signal-to-noise ratio.

[0033] Furthermore, the present application also proposes that the threshold condition for the frequency domain triple verification is a predetermined numerical range and satisfies:

[0034] The resonance peak quality factor value exceeds a first threshold;

[0035] The relative rate of change of the fundamental frequency impedance amplitude exceeds a second threshold;

[0036] The phase jump angle of the resonance point exceeds a third threshold;

[0037] The wave velocity adaptive model includes an impedance correction term, which is obtained by fitting the difference between the measured data and the transmission line model.

[0038] Furthermore, the present application also proposes that the benchmark library includes:

[0039] The current impedance characteristic vector is stored by vehicle type classification;

[0040] The historical data is updated weightedly through the time decay function.

[0041] Furthermore, the present application also proposes an electronic device, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the above-mentioned charging gun fault automatic detection method is implemented.

[0042] Furthermore, the present application also proposes a computer-readable storage medium having computer instructions stored thereon, which implements the above-mentioned charging gun fault automatic detection method when the instructions are executed.

[0043] (3) Beneficial effects

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) The present invention uses a composite detection signal injection and reflection signal separation process, combined with a dual detection mechanism of time domain analysis and frequency domain verification, to effectively identify non-disruptive poor contact faults, improve detection accuracy and anti-interference capability, and has the advantages of improving the detection accuracy of non-disruptive poor contact faults, enhancing anti-interference capability, and realizing dynamic benchmark management.

[0046] (2) The present invention can accurately identify non-fracture poor contact faults such as oxidation and false connection of the charging gun interface, and effectively distinguish between physical fracture and abnormal contact impedance. It can stably detect weak fault characteristics in complex electromagnetic environments, improve the accuracy of locating multiple fault points, and avoid maintenance delays caused by misjudgment of a single parameter. This method achieves the coordinated optimization of fault diagnosis accuracy and environmental adaptability through composite signal separation and processing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is a schematic diagram of the overall logical structure of the automatic detection method for charging gun faults;

[0049] Figure 2 Schematic diagram of the waveform of the composite detection signal;

[0050] Figure 3 Schematic diagram of the comparison waveform of the reflected signal in normal state and poor contact fault state;

[0051] Figure 4 It is a schematic diagram of the analysis curve of the rate of change of the fundamental frequency impedance amplitude;

[0052] Figure 5 Schematic diagram of the framework structure of the execution equipment.

[0053] 1. Processor, 2. Memory, 3. Communication interface, 4. Communication bus. DETAILED DESCRIPTION

[0054] Charging gun fault detection primarily relies on transmission time difference and resistance measurement to identify cable breaks. This method has significant drawbacks when detecting non-breakage contact defects, such as interface oxidation or loose connections. Because the physical length remains unchanged, the transmission time difference indicates a normal value, and relying solely on resistance measurement can easily lead to misjudgment. Traditional solutions lack anti-interference capabilities in complex electromagnetic environments, are unable to effectively identify the locations of multiple fault points, and have a lag in the baseline data update mechanism.

[0055] The inventors discovered that non-fracture faults can cause changes in the impedance spectrum characteristics, which existing technologies fail to effectively capture. By analyzing the resonance peak shift and phase mutation caused by poor contact, they proposed combining time-domain reflectometry with frequency-domain impedance analysis. To address signal coupling interference, they employed composite signal separation and processing techniques to establish a hierarchical diagnostic mechanism. To address the challenge of locating multiple fault points, they introduced a time-frequency matrix analysis method to improve spatial resolution.

[0056] Example 1

[0057] like Figure 1-Figure 4 The method for automatically detecting a charging gun fault shown in the figure specifically includes the following steps:

[0058] S100, injecting a composite detection signal into the positive and negative ports of the charging gun, where the composite detection signal is formed by coupling a time domain pulse component and a frequency domain sweep component of linear frequency modulation;

[0059] S200, synchronously collecting the reflection signal of the port, and separating and processing the reflection signal to obtain a pulse reflection sub-signal and a swept frequency reflection sub-signal;

[0060] The S300 performs time-domain analysis on the pulse reflection sub-signal and calculates the pulse transmission time difference to assess cable physical length anomalies;

[0061] S400, performing time-frequency transformation on the swept frequency reflection sub-signal to generate a time-frequency matrix, and extracting frequency domain characteristic parameters from the time-frequency matrix, where the frequency domain characteristic parameters include resonance peak characteristics, fundamental frequency impedance amplitude, and resonance point phase jump;

[0062] S500. When the pulse transmission time difference does not trigger a physical fracture alarm, perform frequency domain verification based on frequency domain characteristic parameters: the frequency domain verification includes at least two verification conditions. If the verification conditions are met at the same time, it is determined that a non-fracture poor contact fault exists.

[0063] Specifically, a composite detection signal is a mixed signal consisting of both time-domain pulse and frequency-domain swept components. This can be achieved by coupling the pulse component generated by an IGBT drive circuit with the swept component generated by a programmable waveform generator. This signal design enables simultaneous acquisition of the cable's physical state and contact impedance characteristics. Synchronous acquisition of reflected signals utilizes multi-channel synchronous sampling technology, specifically through a high-precision ADC coupled with a temperature-compensated clock. This ensures time alignment between the time-domain and frequency-domain signals.

[0064] Separation processing involves decomposing the mixed reflection signal into pulse and swept-frequency components. Specifically, a matched filter is used to extract the pulse sub-signals, and a bandpass filter is used to separate the swept-frequency sub-signals. This step eliminates cross-interference between the signals. Time-frequency transformation converts the swept-frequency reflection signal into a joint distribution in the time and frequency domains. Specifically, a short-time Fourier transform is used to segment the signal and generate a time-frequency matrix. This method can capture the dynamic response of impedance characteristics as they change with frequency.

[0065] After injecting a composite signal into the charging gun port, a physical breakage fault will change the transmission path length of the pulse signal. Cable integrity is determined by calculating the time difference between the transmitted and reflected pulses. If no physical length anomaly is detected, time-frequency analysis is performed on the swept reflection signal. The resonance peak characteristics are extracted to reflect the parasitic capacitance formed by the oxide layer on the contact surface. Changes in the fundamental frequency impedance amplitude indicate increased contact resistance, and phase jumps indicate arcing at the contact point. By simultaneously meeting the resonance peak quality factor threshold, impedance growth rate, and phase jump angle threshold, hidden contact failures that are undetectable by traditional methods can be accurately identified.

[0066] Traditional solutions rely on a single signal type, resulting in incomplete coverage of fault signatures. This method utilizes composite signal injection to achieve multi-dimensional fault signature acquisition. Existing technologies use fixed-frequency impedance measurement, which is susceptible to environmental interference. This method utilizes linear frequency modulation to obtain a wideband impedance spectrum, improving interference resistance. Traditional methods cannot distinguish between physical breaks and poor contact. This solution establishes a hierarchical diagnosis mechanism, first eliminating physical breaks and then verifying contact characteristics, significantly reducing the rate of false positives.

[0067] This method accurately identifies non-fracture contact faults, such as oxidation and loose connections on charging gun interfaces, and effectively distinguishes between physical fractures and abnormal contact impedance. It stably detects subtle fault signatures in complex electromagnetic environments, improving the accuracy of locating multiple fault points and avoiding maintenance delays caused by misjudgment of a single parameter. This method utilizes composite signal separation and processing technology to achieve a coordinated optimization of fault diagnosis accuracy and environmental adaptability.

[0068] This application further proposes verification conditions, including first, second, and third conditions. If all three conditions are met simultaneously, a non-rupture poor contact fault is determined to exist. The first condition is that the resonance peak quality factor is greater than a threshold; the second condition is that the growth rate of the fundamental frequency impedance amplitude relative to the historical baseline value is greater than a threshold; and the third condition is that the phase jump angle at the resonance point is greater than a threshold.

[0069] Resonance peak quality factor The value refers to a quantitative indicator of the degree of energy concentration of the resonance peak. Specifically, it can be achieved by calculating the ratio of the resonance peak half-power bandwidth to the center frequency through spectrum analysis of the swept-frequency reflection sub-signal. This parameter is used to characterize the capacitance effect caused by contact surface oxidation.

[0070] The growth rate of the fundamental frequency impedance amplitude relative to the historical baseline value refers to the impedance change between the current measurement and the dynamically updated baseline value. This can be achieved by using an aging factor weighted algorithm to attenuate and update historical data before calculating the relative rate of change. This parameter is used to distinguish normal aging from sudden contact failure. The resonant point phase jump angle refers to the phase mutation value of the swept frequency signal at the resonant frequency. This can be achieved by detecting the phase difference between adjacent frequency points in the time-frequency matrix. This parameter is used to identify nonlinear distortion caused by microgap discharge on the contact surface.

[0071] When the charging gun port is oxidized or poorly connected, the insulating layer formed on the contact surface will change the equivalent capacitance parameters, causing the resonance peak quality factor to The value exceeds the preset threshold. At the same time, an abnormal increase in contact resistance will cause the fundamental frequency impedance amplitude to increase significantly relative to the dynamically updated historical baseline value, while the impedance changes during normal aging are automatically absorbed by the baseline library update mechanism.

[0072] Furthermore, the micro-gap of the contact surface generates arc discharge under the excitation of high-frequency signals, causing a steep jump in the phase characteristics of the resonance point. The three conditions must be met at the same time to trigger the fault judgment, among which The value threshold is used to eliminate occasional resonance caused by environmental noise, the impedance growth rate threshold prevents material fatigue from being misjudged as a fault, and the phase jump threshold filters out phase fluctuations caused by temperature drift.

[0073] Traditional solutions rely solely on transmission time differences and resistance measurements, failing to detect impedance anomalies caused by oxide layer formation or loose connections. For example, patent CN119310379A uses a single impedance amplitude measurement, which can misinterpret poor contact as normal in salt spray pollution scenarios. However, this solution combines analysis of resonance characteristics, dynamic impedance changes, and phase jumps to accurately identify multiple non-fracture faults, including oxidation, loose connections, and contamination.

[0074] This application can effectively detect hidden faults caused by oxidation of the charging gun contact surface, avoiding missed detections due to unchanged physical length. Furthermore, it can distinguish between abnormal increases in contact resistance and natural equipment aging, preventing false alarms caused by material degradation. Phase jump detection can also be used to identify micron-level contact gaps, improving the accuracy of locating false connection faults.

[0075] This application further proposes a center frequency based on the resonance peak characteristics and a dynamically updated wave velocity parameter, and calculates the location distance of the poor contact fault point through a wave velocity adaptive model; after each successful charging, the current impedance characteristic vector is stored in the benchmark library according to the vehicle type classification, and the historical benchmark value is updated through an aging factor weighted algorithm.

[0076] The wave velocity adaptive model refers to a calculation model that dynamically adjusts the electromagnetic wave propagation speed according to the cable material characteristics and environmental factors. Specifically, it can be implemented by fitting the difference between the measured data and the transmission line model using the iterative least squares method to compensate for the nonlinear distortion during high-frequency signal transmission.

[0077] Storing impedance feature vectors by vehicle type classification means classifying impedance data according to the voltage level and interface characteristics of the vehicle's electrical platform. This can be achieved by extracting the fundamental frequency impedance and resonant peak characteristics through the principal component analysis algorithm to form a three-dimensional vector, which is used to eliminate the interference of differences in electrical parameters of different vehicle types on fault judgment.

[0078] The aging factor weighting algorithm refers to a calculation method that dynamically adjusts the weight of historical data based on the length of cable use. Specifically, it can be implemented by progressively updating the historical baseline value using an exponential decay function to track the slow changes in impedance characteristics caused by cable oxidation.

[0079] Specifically, the wave velocity adaptive model calculates a wave velocity correction coefficient based on real-time impedance changes. This coefficient, along with the center frequency of the resonant peak, contributes to the fault distance calculation, enabling the location results to automatically adapt to wave velocity changes caused by cable aging. During baseline data management, the impedance characteristics of the current charging cycle are automatically extracted after charging is complete and classified into the database partition corresponding to the vehicle model based on the vehicle identification code. At the same time, the weight of older data is reduced based on a time decay function to ensure that historical baseline values ​​always reflect the current true state of the cable.

[0080] This application further proposes a method for generating a composite detection signal, including multiplexing the driving circuit of the charging pile power device to generate a time domain pulse component, generating a frequency domain sweep component of linear frequency modulation through a programmable waveform generator, and transmitting the signal injection to the charging gun port using differential coupling.

[0081] Reusing the driving circuit of the charging pile power device to generate the time domain pulse component means using the existing power device driving circuit of the charging pile to generate a pulse signal. Specifically, it can be achieved by using the switching characteristics of the IGBT gate drive circuit. By intercepting the rising edge of the gate drive signal, a high-voltage pulse is generated, thereby avoiding the addition of an independent pulse circuit.

[0082] The frequency domain swept frequency component of linear frequency modulation refers to a signal whose frequency changes linearly with time. Specifically, the sweep frequency range and rate can be adjusted through a programmable waveform generator. For example, frequency modulation can be performed within the range of 1kHz to 1MHz to meet the detection requirements of different fault characteristics.

[0083] Among them, differential coupling transmission refers to injecting signals into the positive and negative ports in a symmetrical manner. Specifically, a coupling transformer can be used to achieve signal transmission, and the stability of signal transmission can be improved by offsetting common-mode interference.

[0084] During normal operation, the driver circuit of a charging pile's power device generates a rapidly switching gate control signal. The rising edge of this signal is intercepted and converted into a high-voltage pulse signal, which is directly used to generate the time domain component. A programmable waveform generator, integrated into the charging pile controller, generates a swept frequency signal by adjusting the carrier frequency of the PWM module, ensuring that the bandwidth of the frequency domain component covers the characteristic frequency band of poor contact faults.

[0085] The differential coupling method transmits the composite detection signal to the charging gun port through a symmetrical injection point. The core parameters of the coupling transformer match the inductance characteristics of the power cable, thereby suppressing the common-mode interference caused by the charging current.

[0086] Traditional solutions require the configuration of an independent pulse generator and an external sweep signal source, increasing hardware costs and reducing signal compatibility. This solution, however, reuses existing drive circuits and integrates a programmable waveform generator to generate composite detection signals without adding new hardware. Furthermore, differential coupling utilizes the symmetrical structure of the charging gun to offset interference, addressing the susceptibility of traditional single-ended coupling to noise.

[0087] Through the above technical solution, this application effectively reduces the cost of generating composite detection signals, avoids the hardware overhead caused by the addition of new circuits, and improves the anti-interference capability of signal transmission. The bandwidth and rate of the frequency sweep signal can be flexibly adjusted according to actual needs, enhancing the adaptability of fault detection. The differential coupling method ensures the accuracy of the reflected signal by suppressing common-mode interference, providing a reliable data foundation for subsequent fault analysis.

[0088] The present application further proposes using a high-precision ADC analog-to-digital converter for signal acquisition when synchronously acquiring the reflected signal, and the sampling clock is equipped with a temperature compensation mechanism to maintain time base stability.

[0089] A high-precision ADC (analog-to-digital converter) is a device that digitizes analog signals with high resolution, typically implemented as a 24-bit resolution conversion chip. It converts weak reflected signals into high-precision digital signals, thus avoiding signal distortion. A temperature compensation mechanism dynamically corrects the sampling clock frequency, typically implemented as a voltage-controlled crystal oscillator with a built-in temperature sensor. This mechanism monitors ambient temperature in real time and adjusts the oscillation frequency to eliminate clock drift caused by temperature changes.

[0090] Specifically, during the signal acquisition process, a high-precision ADC quantizes the reflected signal. Its high resolution accurately captures subtle changes in the signal, such as impedance fluctuations caused by poor contact. The sampling clock's temperature compensation mechanism continuously monitors the operating environment temperature and dynamically adjusts the clock circuit's oscillation parameters to ensure the stability of the timebase signal under varying temperature conditions. These two technical approaches work together to ensure that the signal acquisition process can both resist signal distortion caused by electromagnetic interference and avoid timing errors caused by temperature fluctuations, providing an accurate data foundation for subsequent fault analysis.

[0091] The present application further proposes a method for performing time-frequency transformation on the swept frequency reflection sub-signal, including windowing and segmenting the signal stream, performing Fourier transform in each time window to generate a time-frequency matrix, and performing coherent averaging on the swept frequency components to improve the signal-to-noise ratio.

[0092] Window segmentation processing refers to the truncation and segmentation of continuous signals using a specific window function. Specifically, it can be implemented using the Hanning window function. The main lobe width of this window function is 1.5 times that of the rectangular window, and the sidelobe attenuation reaches -31dB, which can effectively suppress spectrum leakage and improve frequency resolution.

[0093] Time-frequency matrix generation refers to converting the time domain signal into two-dimensional time-frequency domain data through short-time Fourier transform. Specifically, it can be implemented using an 8192-point FFT algorithm, with a frequency resolution of 61 Hz and a time resolution of 1.2 ms, which can capture the transient impedance change characteristics.

[0094] Coherent averaging refers to the phase alignment and superposition of multiple acquired swept frequency signals. It can be implemented using a 256-cycle accumulation algorithm. By pre-sampling background noise and a time-slice rotation acquisition mechanism, random noise can be suppressed while ensuring real-time performance.

[0095] During signal processing, the swept-frequency reflection signal is first segmented using a Hanning window to eliminate spurious frequency components caused by signal mutations. The signal within each time window undergoes a high-precision Fourier transform, forming a matrix containing three-dimensional information: time, frequency, and amplitude. This provides an accurate time-frequency distribution map for subsequent feature extraction. To address the unique periodicity of the swept-frequency component, multiple phase-synchronized signal superposition is employed to coherently enhance the effective signal components and cancel out noise components, significantly improving signal quality.

[0096] Compared with existing technologies, traditional solutions use rectangular windows for signal truncation, which results in severe spectral leakage, causing the resonant peak characteristics to be drowned out by switching noise from adjacent frequency bands. Simple arithmetic averaging in existing technologies can only improve the signal-to-noise ratio by 6dB. However, this solution, through phase-aligned coherent averaging, can achieve a 24dB improvement in signal-to-noise ratio with the same number of averaging times. Furthermore, the 512-point FFT algorithm used in existing technologies has insufficient frequency resolution of 488Hz, making it impossible to accurately identify the narrowband resonant peaks caused by poor contact failures.

[0097] This application accurately extracts the frequency-domain characteristic parameters of the swept-frequency reflection signal in strong electromagnetic interference environments, effectively distinguishing impedance anomalies caused by poor contact from background noise interference, and avoiding misidentifying non-fracture faults such as oxidation corrosion as normal conditions. This processing method significantly improves the detection accuracy of the resonant peak quality factor, fundamental frequency impedance amplitude, and phase jump angle, providing a reliable signal analysis basis for identifying hidden poor contact faults.

[0098] This application further proposes a technical solution for charging gun fault detection using a frequency domain triple verification mechanism and a wave velocity adaptive model. The threshold conditions for the frequency domain triple verification are set to a predetermined range of values, specifically including the resonance peak quality factor exceeding a first threshold, the relative rate of change of the fundamental frequency impedance amplitude exceeding a second threshold, and the resonance point phase jump angle exceeding a third threshold. The wave velocity adaptive model includes an impedance correction term obtained by differentially fitting the measured data with the transmission line model.

[0099] The resonant peak quality factor is the ratio of the resonant peak center frequency to the half-power bandwidth. This can be achieved using a fast Fourier transform combined with a peak detection algorithm. This parameter characterizes the capacitive effect of the oxide layer formed at the contact interface. The relative rate of change of the fundamental frequency impedance amplitude is the percentage difference between the current measurement and the historical baseline value. This parameter can be calculated using a sliding window average and is used to capture sudden changes in contact resistance.

[0100] The resonant point phase jump angle refers to the amplitude of the signal's phase change at the resonant frequency. Specifically, Hilbert transform can be used for phase demodulation. This parameter is used to detect impedance changes caused by microgap discharges. The impedance correction term in the wave velocity adaptive model is a compensation term based on a logarithmic function. Specifically, the difference between the measured scattering parameters and the theoretical model can be fitted using the iterative least squares method. This correction term is used to eliminate deviations in wave velocity calculations caused by cable aging.

[0101] Specifically, after injecting a composite detection signal into the charging gun port, the system extracts three key characteristic parameters through frequency domain analysis of the reflected signal. If the pulse transmission time difference detects that no physical fracture alarm has been triggered, the system automatically initiates a triple verification mechanism: a resonance peak quality factor exceeding the first threshold indicates that the contact surface oxidation area has reached a critical state; a relative change rate of the fundamental frequency impedance amplitude exceeding the second threshold indicates a sudden change in contact resistance; and a resonance point phase jump angle exceeding the third threshold indicates the presence of intermittent arcing.

[0102] The simultaneous satisfaction of these three conditions constitutes the basis for determining non-disconnection poor contact. Simultaneously, the wave velocity adaptive model analyzes the differences between real-time impedance data and the theoretical transmission line model, dynamically adjusting the impedance correction term in the wave velocity calculation to eliminate model errors caused by cable material aging or environmental factors.

[0103] In the frequency domain triple verification, the threshold range includes but is not limited to the resonant peak quality factor The value is greater than the range of 2.5 to 5, the relative change rate of the fundamental frequency impedance amplitude exceeds 30% to 50%, and the phase jump angle of the resonance point exceeds 25° to 35°.

[0104] Further quality factor The calculation formula is ,in Indicates the resonant center frequency in Hz. is the -3dB bandwidth in Hz. Value Threshold The preferred value of is 3, and its effective range is , which is used to quantify the capacitance effect strength of the oxide layer formed on the contact surface.

[0105] The expression for the relative rate of change of fundamental frequency impedance amplitude is: ,in is the current measured impedance in Ω, The historical baseline impedance is dynamically updated in Ω. The preferred value is 40%, and the effective range is , used to capture sudden changes in contact resistance.

[0106] The phase jump angle of the resonance point is defined as ,in is the frequency offset in Hz, Indicates the phase angle in degrees. The preferred value is 30°, and the effective range is , used to detect nonlinear distortion caused by microgap discharge.

[0107] For the impedance correction term in the wave velocity adaptive model , the fitting process can use any of the following algorithms or combinations:

[0108] Iterative Least Squares: Solving the Objective Function ,in is the measured scattering parameter, dimensionless, expressed at the frequency point The scattering parameter value actually measured at reflects the reflection / transmission characteristics of electromagnetic waves in the transmission line. is the transmission line model, is the propagation constant (complex number), is the imaginary unit, is the angular frequency, is the distribution parameter vector to be solved, is the resistance per unit length, in units of , represents the resistance loss per meter of conductor length, is the inductance per unit length, in units of , represents the magnetic energy storage capacity of the conductor per meter length, is the capacitance per unit length, in units of , which represents the electrical energy storage capacity per meter length between conductors, is the conductance per unit length, in units of , represents the conductivity loss of the medium per meter length, is the total number of frequency sampling points, For the The frequency of the sampling points is in Hz. It is updated iteratively through the Jacobian matrix Until convergence.

[0109] The present application further proposes that the benchmark library includes storing the current impedance characteristic vector by vehicle type classification, and performing weighted update on historical data through a time decay function.

[0110] Among them, storage by vehicle type classification refers to the partitioning management of impedance characteristics according to the voltage platform and cooling method of the vehicle electrical system. Specifically, this can be achieved by establishing a three-dimensional classification tree of vehicle type-voltage-cooling method. The fundamental frequency impedance data of different vehicle types are rigidly isolated through the voltage platform to avoid cross-interference of baseline data caused by differences in electrical characteristics.

[0111] The time decay function refers to a mathematical function that dynamically adjusts the weight of historical data based on the timeliness of the data. Specifically, it can be implemented by combining an exponential decay model with the copper cable oxidation rate parameter. The aging factor weighting algorithm is used to reduce the impact of outdated data on the benchmark value, allowing the benchmark library to continuously track material aging and environmental changes.

[0112] After each charge, the charging gun analyzes the collected impedance feature vector based on the vehicle identification code to determine the corresponding voltage platform and cooling method, which is then stored in the corresponding storage partition of the three-dimensional classification tree. To update the historical baseline value, an exponential decay model is used to calculate the weight ratio of new and old data. Newly collected impedance features contribute to the baseline value calculation with exponentially increasing weight, while the contribution of old data decays exponentially over time, ensuring that the baseline value always reflects the current cable status.

[0113] Existing solutions typically use unified storage or single-dimensional classification, resulting in mixed data for vehicles on different voltage platforms. Furthermore, baseline value updates rely on fixed-cycle replacements, making them incapable of adapting to cable aging rates. This solution uses a three-dimensional classification tree to isolate cross-platform data. Combined with a dynamic attenuation model based on oxidation kinetics, this solution enables baseline library management with both vehicle adaptability and time-based tracking capabilities.

[0114] This application solves the problem of impedance characteristic confusion caused by differences in vehicle models, effectively improves the accuracy of benchmark data matching, and at the same time suppresses the impact of outdated data on the benchmark value through a dynamic weight adjustment mechanism, ensuring that the basis for fault judgment is always synchronized with the current cable status, and significantly reducing the misjudgment rate of non-breakage poor contact faults.

[0115] Example 2

[0116] An embodiment of the present invention provides a computer-readable storage medium.

[0117] The computer-readable storage medium provided in the embodiment of the present invention stores a computer program, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods for automatically detecting faults of a charging gun can be implemented.

[0118] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0119] For an introduction to the computer-readable storage medium provided in an embodiment of the present invention, please refer to the above method embodiment, and the present invention will not elaborate on it here.

[0120] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0121] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0122] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. Example 3

[0123] An embodiment of the present invention provides an execution device.

[0124] Please refer to Figure 5 , Figure 5 This is a schematic diagram of the structure of an execution device provided by the present invention, which may include:

[0125] memory for storing computer programs;

[0126] The processor is configured to implement the steps of any of the above-mentioned methods for automatically detecting charging gun faults when executing a computer program.

[0127] like Figure 5 FIG2 is a schematic diagram of the structure of the execution device, which may include a processor 1, a memory 2, a communication interface 3, and a communication bus 4. The processor 1, the memory 2, and the communication interface 3 communicate with each other via the communication bus 4.

[0128] In the embodiment of the present invention, the processor 1 may be a central processing unit (CPU), an application specific integrated circuit, a digital signal processor, a field programmable gate array, or other programmable logic devices.

[0129] The processor 1 may call a program stored in the memory 2. Specifically, the processor 1 may execute the operations in the embodiment of the push button switch fault detection method.

[0130] The memory 2 is used to store one or more programs. The programs may include program codes, and the program codes include computer operating instructions. In the embodiment of the present invention, the memory 2 stores at least a program for implementing the following functions:

[0131] Injecting a composite detection signal into the positive and negative ports of the charging gun, wherein the composite detection signal is formed by coupling a time domain pulse component and a frequency domain swept frequency component of linear frequency modulation;

[0132] Synchronously collecting the reflected signal of the port, and separating and processing the reflected signal to obtain a pulse reflection sub-signal and a swept frequency reflection sub-signal;

[0133] Performing time domain analysis on the pulse reflection sub-signal to calculate the pulse transmission time difference to evaluate the abnormality of the cable physical length;

[0134] Performing a time-frequency transformation on the swept frequency reflection sub-signal to generate a time-frequency matrix, and extracting frequency domain characteristic parameters from the time-frequency matrix, wherein the frequency domain characteristic parameters include resonance peak characteristics, fundamental frequency impedance amplitude, and resonance point phase jump;

[0135] When the pulse transmission time difference does not trigger a physical break alarm, frequency domain verification is performed based on the frequency domain characteristic parameters: the frequency domain verification includes at least two verification conditions. If the verification conditions are met at the same time, it is determined that a non-break poor contact fault exists.

[0136] In one possible implementation, the memory 2 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function, etc.; the data storage area may store data created during use.

[0137] In addition, the memory 2 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device or other volatile solid-state storage device.

[0138] The communication interface 3 may be an interface of a communication module, used for connecting to other devices or systems.

[0139] Of course, it needs to be explained that Figure 5 The structure shown does not constitute a limitation on the execution device in the embodiment of the present invention. In actual applications, the execution device may include Figure 5 More or fewer components than shown, or combinations of certain components.

[0140] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Any modifications and improvements made to the technical solution of the present invention by a person of ordinary skill in the art without departing from the design concept of the present invention shall fall within the scope of protection of the present invention. The technical content for which protection is sought in the present invention is fully set forth in the claims.

[0141] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Any modifications and improvements made to the technical solution of the present invention by a person of ordinary skill in the art without departing from the design concept of the present invention shall fall within the scope of protection of the present invention. The technical content for which protection is sought in the present invention is fully set forth in the claims.

Claims

1. A method for automatically detecting charging gun faults, characterized in that: include: Injecting a composite detection signal into the positive and negative ports of the charging gun, wherein the composite detection signal is formed by coupling a time domain pulse component and a frequency domain swept frequency component of linear frequency modulation; Synchronously collecting the reflected signal of the port, and separating and processing the reflected signal to obtain a pulse reflection sub-signal and a swept frequency reflection sub-signal; Performing time domain analysis on the pulse reflection sub-signal to calculate the pulse transmission time difference to evaluate the abnormality of the cable physical length; Performing a time-frequency transformation on the swept frequency reflection sub-signal to generate a time-frequency matrix, and extracting frequency domain characteristic parameters from the time-frequency matrix, wherein the frequency domain characteristic parameters include resonance peak characteristics, fundamental frequency impedance amplitude, and resonance point phase jump; When the pulse transmission time difference does not trigger a physical fracture alarm, frequency domain verification is performed based on the frequency domain characteristic parameters: the frequency domain verification includes at least two verification conditions, and if the verification conditions are met at the same time, it is determined that a non-fracture poor contact fault exists; The verification conditions include: The first condition is that the resonance peak quality factor value is greater than the threshold; The second condition is that the growth rate of the fundamental frequency impedance amplitude relative to the historical benchmark value is greater than the threshold; The third condition is that the phase jump angle of the resonance point is greater than the threshold; If the first condition, the second condition, and the third condition are met at the same time, it is determined that a non-disconnection poor contact fault exists.

2. The automatic detection method for charging gun faults according to claim 1, characterized in that: Also includes: Based on the center frequency of the resonance peak characteristic and the dynamically updated wave velocity parameter, the location distance of the poor contact fault point is calculated through a wave velocity adaptive model; After each successful charge, the current impedance characteristic vector is stored in the benchmark library according to vehicle type classification, and the historical benchmark value is updated through the aging factor weighted algorithm.

3. The method for automatically detecting charging gun faults according to claim 1, wherein: The generation of the composite detection signal includes: The driving circuit of the multiplexing charging pile power device generates a time domain pulse component; Generate frequency domain swept frequency component of linear frequency modulation through programmable waveform generator; The signal injection is transmitted to the charging gun port using differential coupling.

4. The method for automatically detecting charging gun faults according to claim 1, wherein: When synchronously collecting the reflected signal of the port: Use high-precision ADC analog-to-digital converter for signal acquisition; The sampling clock is equipped with a temperature compensation mechanism to maintain time base stability.

5. The method for automatically detecting charging gun faults according to any one of claims 1 to 4, characterized in that: Performing time-frequency transformation on the swept frequency reflected sub-signal includes: Perform windowing and segmentation processing on the signal stream; Perform Fourier transform in each time window to generate a time-frequency matrix; Coherent averaging is performed on the swept frequency components to improve the signal-to-noise ratio.

6. The method for automatically detecting charging gun faults according to claim 2, characterized in that: The threshold condition for the frequency domain verification is a predetermined value range and satisfies: The resonance peak quality factor value exceeds a first threshold; The relative rate of change of the fundamental frequency impedance amplitude exceeds a second threshold; The phase jump angle of the resonance point exceeds a third threshold; The wave velocity adaptive model includes an impedance correction term, which is obtained by fitting the difference between measured data and the transmission line model.

7. The method for automatically detecting charging gun faults according to claim 2, characterized in that: The benchmark library includes: The current impedance characteristic vector is stored by vehicle type classification; The historical data is updated weightedly through the time decay function.

8. An electronic device comprising a processor and a memory, wherein the memory stores a computer program, wherein: When the computer program is executed by a processor, the method for automatically detecting faults of a charging gun according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed, the charging gun fault automatic detection method according to any one of claims 1 to 7 is implemented.

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