Method, device and system for detecting ac-dc charging pile

Abstract

The present application relates to the technical field of charging pile detection, and discloses an alternating current and direct current charging pile detection method, device and system, the method comprising the following steps: S1, applying a preliminary wideband disturbance signal to a charging pile to be detected; S2, generating an optimized composite disturbance signal according to sensitive frequency band characteristics; S3, synchronously applying the optimized composite disturbance signal to the charging pile to be detected; S4, performing Fourier transform on the output response; S5, constructing a dynamic response signature matrix based on a transfer function; S6, after detection, calculating the difference between the dynamic response signature matrix and stored reference data; and S7, when it is determined that the charging pile to be detected is unqualified, performing structured deviation analysis on the difference. The present application identifies the sensitive frequency band of the system through a preliminary wideband disturbance, and then generates an optimized composite disturbance signal, thereby concentrating energy in the sensitive frequency band to accurately excite. The present application improves the detection speed and signal-to-noise ratio, and achieves the technical effect of fast and efficient testing.

Description

Technical Field

[0001] This invention relates to the field of charging pile testing technology, and in particular to AC / DC charging pile testing methods, devices and systems. Background Technology

[0002] In the current field of charging pile testing, broadband scanning technology is commonly used to evaluate the dynamic characteristics of charging piles. While this method can cover a wide frequency range, the test step size is usually large, resulting in excessively long test times. This is clearly unsuitable for large production lines that require rapid testing. Especially when facing fierce market competition, lengthy testing significantly limits production efficiency.

[0003] Existing technologies often focus on independent testing in the electrical or communication control domains. This single-dimensional testing approach cannot fully reflect the complex situations that charging piles may encounter in real-world environments. Multi-domain coupling characteristics are a crucial factor affecting charging pile performance; however, traditional methods frequently overlook this, resulting in potential performance defects being missed and ultimately impacting product reliability and safety.

[0004] Even after detecting defective products, traditional methods often only provide a simple judgment of whether they pass or fail. This superficial result greatly limits subsequent troubleshooting. Technicians need to rely on experience to locate the fault, and experience itself contains uncertainty. This approach not only leads to low detection efficiency but also increases maintenance costs. Summary of the Invention

[0005] The purpose of this invention is to provide a method, device and system for testing AC / DC charging piles, which solves the problems of long testing time, inability to fully evaluate multi-domain coupling characteristics and unclear fault location in existing charging pile testing technologies.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an AC / DC charging pile detection method, comprising the following steps:

[0007] S1. By applying a preliminary broadband disturbance signal to the charging pile under test, its response data is obtained in order to identify the sensitive frequency band of the system;

[0008] S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band to excite the charging pile.

[0009] S3. Simultaneously apply the optimized composite disturbance signal to the charging pile under test to obtain its output response;

[0010] S4. Calculate the transfer functions of the input and output signals by performing a Fourier transform on the output response;

[0011] S5. Construct a dynamic response signature matrix based on the transfer function and store the matrix as baseline data;

[0012] S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the qualification of the charging pile and generate a test report.

[0013] S7. When a non-compliance is determined, a structured deviation analysis is performed on the difference to achieve in-depth diagnosis of potential faults and generate a fault report.

[0014] Preferably, the response data in step S1 includes the output voltage and output current of the charging pile, and the sensitive frequency band is determined by performing spectrum analysis on the response data.

[0015] Preferably, the step of generating the optimized composite disturbance signal in step S2 specifically involves superimposing multiple sine wave signals to form the optimized composite disturbance signal, wherein the frequencies of the multiple sine wave signals are all set within the sensitive frequency band.

[0016] Preferably, the step of simultaneously applying the optimized composite disturbance signal to the charging pile under test in step S3 specifically involves: superimposing one component of the optimized composite disturbance signal onto the AC input voltage of the charging pile under test via a programmable AC power supply, and simultaneously superimposing another component of the optimized composite disturbance signal onto the charging command sent to the charging pile under test via a controller local area network communication device.

[0017] Preferably, in step S4, the Fourier transform uses the Fast Fourier Transform algorithm to process the output response and the input signal to obtain a frequency domain representation.

[0018] Preferably, the step of constructing the dynamic response signature matrix in step S5 specifically involves arranging the values ​​of the transfer function at multiple preset frequency points in frequency order to form a multi-row, multi-column matrix to represent the dynamic response characteristics of the charging pile at different frequencies.

[0019] Preferably, the step of calculating the difference in step S6 specifically involves: obtaining a quantitative difference value to characterize the overall degree of difference by calculating the Frobenius norm of the difference between the dynamic response signature matrix and the benchmark data.

[0020] Preferably, the structured deviation analysis in step S7 includes:

[0021] The difference between the dynamic response signature matrix and the baseline data is decomposed into amplitude difference and phase difference, and corresponding fault feature vectors are established for each.

[0022] The fault feature vector is matched with a preset fault mode database to determine the fault type and the corresponding fault component.

[0023] An AC / DC charging pile testing device includes a protective box; a display screen is fixedly connected to the outer surface of the protective box, a charging gun connector is fixedly connected to the inside of the protective box, one end of the charging gun connector is electrically connected to a data acquisition device, the outer wall of the data acquisition device is fixedly connected to the inside of the protective box, one end of the data acquisition device is electrically connected to a storage battery, the outer wall of the storage battery is fixedly connected to the inner wall of the protective box, one end of the data acquisition device is electrically connected to a processing controller, the outer wall of the processing controller is fixedly connected to the inner wall of the protective box, and one end of the processing controller is electrically connected to a signal generation module, the outer wall of the signal generation module is fixedly connected to the inner wall of the protective box.

[0024] AC / DC charging pile testing system, including;

[0025] The signal generation module is used to generate preliminary broadband disturbance signals and optimized composite disturbance signals, and simultaneously apply them to the AC input terminal and communication control terminal of the charging pile under test.

[0026] The data acquisition module is used to acquire the response data of the output voltage and output current of the charging pile under test;

[0027] The processing control module is used to perform spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis.

[0028] The report generation module is used to generate inspection reports and fault reports.

[0029] In summary, the present invention has at least one of the following beneficial technical effects:

[0030] 1. This invention identifies the sensitive frequency band of a system through preliminary broadband perturbation, and then generates an optimized composite perturbation signal to concentrate energy on the sensitive frequency band for precise excitation. This approach significantly improves detection speed and signal-to-noise ratio, achieving rapid and efficient testing. Compared to existing technologies that typically involve a complete scan of the entire frequency band, this invention overcomes the shortcomings of long testing times, low efficiency, and inability to meet the fast-paced testing requirements of mass production lines.

[0031] 2. This invention applies optimized disturbance signals synchronously to the electrical domain and communication control domain of the charging pile's power grid, and constructs a multi-dimensional dynamic response signature matrix. This approach comprehensively and systematically characterizes the dynamic characteristics of the charging pile under real-world combined operating conditions, achieving more accurate and comprehensive detection results. Unlike existing technologies that test from only a single dimension, this invention solves the problems of ineffectively evaluating cross-domain coupling characteristics and easily missing potential stability and performance defects caused by multi-domain interactions.

[0032] 3. By quantitatively analyzing the differences between the measured matrix and the benchmark matrix and matching them with the fault database, automatic fault location is directly achieved. Compared with existing technologies that simply provide a pass or fail conclusion, this invention solves the shortcomings of failing to identify the root cause of the fault and relying heavily on manual experience for subsequent maintenance, greatly improving the efficiency and accuracy of fault diagnosis. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0034] Figure 2 This is a schematic diagram illustrating the application of the initial broadband perturbation signal according to the present invention;

[0035] Figure 3 This is a schematic diagram illustrating the optimized composite disturbance signal generation of the present invention;

[0036] Figure 4 This is a schematic diagram of the dynamic response signature matrix structure of the present invention;

[0037] Figure 5 This is a schematic diagram of the system framework of the present invention;

[0038] Figure 6 This is a perspective view of the device of the present invention;

[0039] Figure 7 This is a cross-sectional view of the protective box of the present invention.

[0040] The components include: 1. Protective box; 2. Display screen; 3. Charging gun connector; 4. Data acquisition unit; 5. Storage battery; 6. Processing controller; and 7. Signal generation module. Detailed Implementation

[0041] The following is in conjunction with the appendix Figure 1 -Appendix Figure 4 The present invention will be further described in detail below.

[0042] This invention provides a method for testing AC / DC charging piles, including:

[0043] S1. By applying a preliminary broadband disturbance signal to the charging pile under test, its response data is obtained to identify the sensitive frequency band of the system. Specifically, in step S1 of this embodiment, a preliminary broadband disturbance signal is applied to the charging pile under test, and its response data is obtained to identify the sensitive frequency band of the system. This step is the foundation of the entire detection method, and the accuracy of its identification result directly determines the effectiveness of subsequent tests.

[0044] First, a preset initial broadband perturbation signal is applied to the charging pile under test. The purpose of this signal is to uniformly excite the charging pile under test over a wide frequency range in order to fully stimulate its potential dynamic characteristics.

[0045] For example, the initial broadband perturbation signal can be a chirp signal, whose frequency is linearly or logarithmically swept from low frequency (e.g., 1 Hz) to high frequency (e.g., 10 kHz) over a preset time period. Alternatively, the signal can also be a pseudo-random binary sequence (PRBS), whose spectrum approximates white noise below the Nyquist frequency, enabling simultaneous excitation of all frequency points in a short period of time.

[0046] The initial broadband disturbance signal is synchronously applied to multiple input ports of the charging pile under test through the test system to simulate a real composite operating environment. Specifically, one component of the signal is superimposed on the AC input voltage of the charging pile, while another component is modulated into its communication control command.

[0047] Throughout the application of the disturbance signal, a high-precision, highly synchronized data acquisition module is used to collect the output response data of the charging pile under test in real time. To ensure the accuracy of subsequent analysis, the synchronization of data acquisition is crucial, guaranteeing that the causal and phase relationships between the input disturbance and the output response are recorded without distortion.

[0048] The response data specifically includes the time-domain signal V of the DC output voltage of the charging pile under test. out (t) and the DC output current time-domain signal I out (t).

[0049] After acquiring the time-domain response data, the processing and control module performs spectral analysis on it to determine the system's sensitive frequency bands. This spectral analysis process is preferably implemented using the Fast Fourier Transform (FFT) algorithm, which can efficiently convert the time-domain signal to the frequency domain for analysis.

[0050] This transformation process can be represented by the following formula:

[0051]

[0052] In the formula, X[k] represents the frequency domain representation of the Discrete Fourier Transform (DFT) result, x[n] represents the discrete-time signal sequence, represents the value of the signal at discrete time n, N represents the total number of sampling points, and k represents the frequency index in the frequency domain. The part representing the complex exponent, j represents the imaginary unit.

[0053] By calculating the spectrum V out (f) and I out (f) Analysis was conducted to identify frequency bands with significant energy responses. These frequency bands were defined as the sensitive frequency bands Ω. critical Its characteristics include resonance peaks present in the spectrum, or regions where the amplitude or phase of the system transfer function (preliminary estimate) changes drastically.

[0054] The resonance peak typically corresponds to the internal electrical resonance point of the system and is key to evaluating system stability. Regions of abrupt gain or phase changes are often related to the bandwidth of the system's control loop, reflecting the boundaries of control performance.

[0055] S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band to excite the charging pile.

[0056] Specifically, in step S2 of this embodiment, an optimized composite disturbance signal is generated based on the characteristics of the sensitive frequency band to accurately excite the charging pile under test.

[0057] The purpose of this step is to concentrate the test energy on the frequency range that has the most significant impact on the dynamic characteristics of the system, thereby replacing the traditional broadband, low-efficiency scanning, in order to achieve shorter test time and higher response signal-to-noise ratio.

[0058] Specifically, this step is performed by a signal generation module. This signal generation module first receives the sensitive frequency band Ω determined in step S1 from the processing control module. critical This frequency band information is the core basis for generating the optimized composite perturbation signal.

[0059] According to a further embodiment of the present invention, the optimized composite perturbation signal is generated by linearly superimposing multiple sinusoidal signals whose frequencies fall within the sensitive frequency band. This method can accurately construct the desired energy distribution in the frequency domain.

[0060] The mathematical model of the optimized composite perturbation signal in the time domain can be expressed by the following equation:

[0061]

[0062] In the formula, Δx OCPS (t) represents the time-domain waveform of the final optimized composite anti-disturbance signal, N represents the total number of sine waves constituting the composite signal, k represents the index of the sine wave component, and f represents the k-th sine wave component in the signal. k The frequency f represents the frequency of the k-th sine wave component. k Selected in the sensitivity band Ω critical Within a defined range, A k This represents the amplitude of the k-th sine wave component. The initial phase of the k-th sine wave component is represented by t, and the time variable is represented by t.

[0063] The peak value of the composite signal is optimized by setting the phase of each component to ensure the optimal distribution of the excitation energy of the signal and avoid over-response or shock of the system.

[0064] The optimized composite perturbation signal generated in this way has its energy precisely confined in the frequency domain to a pre-identified sensitive frequency band. The advantage of this technique is that it significantly improves the signal-to-noise ratio at the target frequency in subsequent response signal analysis, thereby enabling the use of perturbation signals with smaller amplitudes to obtain a clear system response.

[0065] S3. Simultaneously apply the optimized composite disturbance signal to the charging pile under test to obtain its output response;

[0066] Specifically, in step S3 of this embodiment, the optimized composite disturbance signal is synchronously applied to the charging pile under test to obtain its output response under composite excitation.

[0067] The core of this step is to simulate the disturbances that charging piles may encounter in actual operation, which come from both the electrical domain and the communication control domain of the power grid, thereby enabling the stimulation and observation of dynamic characteristics caused by multi-domain coupling effects.

[0068] Specifically, this step is executed collaboratively by a synchronization controller. This synchronization controller ensures that the optimized composite disturbance signal Δx generated in step S2 is performed effectively. OCPS (t), under the same time reference, is decomposed and synchronously applied to two different input ports of the charging pile under test.

[0069] According to a further definition of another embodiment of the present invention, the specific implementation process of the synchronous application includes the following aspects.

[0070] First, a component of the optimized composite disturbance signal, namely the voltage disturbance component, is superimposed on the nominal AC input voltage supplied to the charging pile under test through a programmable AC power supply.

[0071] The mathematical model of this process can be represented as:

[0072] V in,AC (t)=V nom,AC (t)+ΔV OCPS (t);

[0073] In the formula, V in,AC (t) represents the total voltage actually applied to the AC input terminal of the charging pile, V. nom,AC (t) represents the nominal AC voltage required for the charging pile to operate normally, ΔV OCPS (t) represents the voltage disturbance component.

[0074] At the same time, through a Controller Area Network (CAN) communication device, another component of the optimized composite disturbance signal, namely the command disturbance component, is superimposed on the charging command sent to the charging pile under test.

[0075] For example, the communication device modulates the charging current request value in real time within a standard charging control message. This process can be represented as:

[0076] I cmd,pert (t)=I cmd,nom +ΔI OCPS (t);

[0077] In the formula, I cmd,pert (t) represents the actual charging current command value sent to the charging pile after the disturbance is superimposed, I cmd,nom The nominal charging current command value set under the current operating conditions, ΔI OCPS (t) represents the command perturbation component, whose waveform and amplitude are also determined by the optimized composite perturbation signal Δx. OCPS (t) is determined.

[0078] Throughout the entire process of performing the above synchronous application, the data acquisition module works continuously to acquire and record the output response of the charging pile under test in real time. The response data includes at least the time-domain waveforms of its DC output voltage and DC output current.

[0079] S4. Calculate the transfer functions of the input and output signals by performing a Fourier transform on the output response; specifically, in this embodiment, step S4 involves calculating the transfer functions of the input and output signals by performing a Fourier transform on the output response.

[0080] This step is performed by a processing control module, which first receives the output response data from the data acquisition module, as well as the input disturbance signal actually applied in step S3, recorded by the synchronization controller.

[0081] The input disturbance signal includes a voltage disturbance component ΔV applied to the AC input terminal. OCPS (t), and the command disturbance component ΔI applied to the communication control terminal. OCPS (t). The output response data includes the DC output voltage time-domain signal V of the charging pile. out (t) and DC output current time-domain signal I out (t).

[0082] To obtain a frequency domain representation, the processing control module employs an efficient spectrum analysis algorithm. According to a further embodiment of the present invention, the Fourier transform specifically employs a Fast Fourier Transform (FFT) algorithm to process the output response and the input signal.

[0083] The algorithm was applied to the input perturbation signal and the output response signal respectively to calculate their respective discrete frequency points f contained in the optimized composite perturbation signal.k The complex spectrum on the x-axis. The general mathematical model of this transformation process can be expressed as:

[0084] In the formula, x(t) represents any time-domain signal. Represents the Fourier transform operator; X(f k ) represents the time-domain signal x(t) at a specific frequency f. k The complex spectral value on the spectrum contains amplitude and phase information.

[0085] After obtaining the frequency domain representations of all relevant signals, the processing control module further calculates the transfer function between the input and output signals. The transfer function H(f) k ) is defined as at a specific frequency f k The complex spectrum of the output signal is the ratio of the complex spectrum of the input signal to the complex spectrum of the output signal.

[0086] The calculation formula is as follows:

[0087]

[0088] In the formula, H Y←X (f k () represents the transition from input X to output Y at frequency f k The transfer function value on, Y(f) k X(f) is the complex spectrum of the output signal. k ) represents the complex spectrum of the input signal.

[0089] This step calculates at least the following four core transfer functions to fully characterize the dynamic characteristics of the charging pile as a dual-input, dual-output system:

[0090] This step calculates at least the following four core transfer functions to fully characterize the dynamic characteristics of the charging pile as a dual-input, dual-output system:

[0091] Transfer function from grid voltage to output voltage:

[0092] Transfer function from grid voltage to output current:

[0093] Transfer function from CAN command to output voltage: Transfer function from CAN command to output current:

[0094] S5. Construct a dynamic response signature matrix based on the transfer function and store the matrix as baseline data;

[0095] Specifically, in step S5 of this embodiment, a structured dynamic response signature matrix is ​​constructed based on the transfer function, and the matrix is ​​stored as the reference data for subsequent comparison.

[0096] The purpose of this step is to integrate the discrete transfer function data obtained in the previous step, which is distributed across multiple frequency points, into a standardized, multi-dimensional mathematical entity. This entity can comprehensively and compactly represent the complete dynamic characteristics of the charging pile under test under specific operating conditions, forming its unique "dynamic fingerprint," thereby facilitating subsequent quantitative analysis and comparison.

[0097] The transfer function values ​​calculated in step S4 are used as input. These values ​​are at N preset discrete frequency points f1, f2, ..., f N Above, the transfer function from different input ports to different output ports, where each frequency point is located in a previously determined sensitive frequency band Ω. critical Inside

[0098] According to a further definition of another embodiment of the present invention, the step of constructing the dynamic response signature matrix specifically involves arranging the values ​​of the transfer function at multiple preset frequency points according to a predefined row and column rule to form a multi-row, multi-column matrix that can represent the dynamic response characteristics of the charging pile at different frequencies.

[0099] The structure of this dynamic response signature matrix is ​​a deterministic mapping, and its exemplary structure is as follows:

[0100]

[0101] In the formula, DRSM is the constructed dynamic response signature matrix; each column of the matrix is ​​identified by the column index k = 1, ..., N, corresponding to a specific preset frequency point f. k Each row of the matrix is ​​identified by its row index and corresponds to a specific input-output transmission path;

[0102] For frequency f k Above, the transfer function value from the grid voltage input to the output voltage;

[0103] For frequency f k Above, the transfer function value from the grid voltage input to the output current;

[0104] For frequency f k Above, the transfer function value from CAN command input to output voltage;

[0105] For frequency f kAbove, the transfer function value from CAN command input to output current.

[0106] Each element of this matrix is ​​a complex number, which contains information about both the amplitude gain and phase delay of the system response at a specific frequency and along a specific transmission path. Therefore, this matrix provides a complete quantitative description of the multi-dimensional, cross-domain dynamic characteristics of the charging pile.

[0107] During the initialization or calibration phase of this method, benchmark data needs to be established. This process involves selecting a benchmark charging station whose performance indicators fully comply with the design specifications and have undergone comprehensive verification, and executing steps S1 to S5 on it to obtain its corresponding dynamic response signature matrix.

[0108] The matrix generated by the reference charging station was subsequently designated as the reference data DRSM. ref The processing control module will use this reference matrix DRSM ref It is stored in a storage module of the test system.

[0109] S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the qualification of the charging pile and generate a test report.

[0110] Specifically, in step S6 of this embodiment, the difference between the dynamic response signature matrix and the pre-stored benchmark data is calculated to determine the performance of the charging pile and finally generate a test report.

[0111] First, obtain the dynamic response signature matrix of the charging pile under test from step S5, denoted as DRSM. UUT It retrieves the pre-stored baseline data from the storage module, denoted as DRSM. ref .

[0112] Subsequently, the processing control module calculates the difference matrix ΔDRSM between the two matrices. This calculation is performed by subtracting corresponding elements of the two matrices:

[0113] ΔDRSM=DRSM UUT -DRSM ref ;

[0114] Each element δ of the difference matrix ΔDRSM ij These all represent the complex deviations of the charging pile under test from the reference state at a specific frequency point and on a specific transmission path.

[0115] According to a further definition of another embodiment of the present invention, the step of calculating the difference specifically involves calculating the Frobenius norm of the difference matrix ΔDRSM to obtain a quantitative difference value for characterizing the overall degree of difference.

[0116] The formula for calculating the quantitative difference value D is as follows:

[0117]

[0118] In the formula:

[0119] D represents the final obtained quantity difference value, indicating the magnitude of the quantity difference value, which is used to measure the degree of difference in the data matrix.

[0120] ||·|| F denoted as the Frobenius norm, which is the square root of the sum of the squares of the matrix elements;

[0121] m and n represent the number of rows and columns of matrix ΔDRSM, respectively;

[0122] δ ij Let be the element in the i-th row and j-th column of the matrix ΔDRSM;

[0123] |δ ij | represents the complex element δ ij The model.

[0124] This quantitative difference value D compresses the deviation information of the entire matrix into a single scalar, intuitively reflecting the overall distance between the dynamic characteristics of the charging pile under test and its ideal reference state.

[0125] The processing control module compares the calculated quantitative difference value D with a preset quality control threshold T. QC Compare the threshold T. QC It is a value that is pre-set based on product design tolerances, production process statistics, or aging test data and stored in the testing system.

[0126] The determination logic is as follows: if the calculated quantitative difference value D is less than or equal to the quality control threshold T... QC If D is greater than T, the processing control module determines that the charging pile under test is a qualified product. Conversely, if D is greater than T, the charging pile under test is qualified. QC If the result is not met, the product is deemed defective. Finally, based on this determination, the system automatically generates a structured inspection report. This report includes at least the following information: the unique product identifier of the charging pile under test, the date and time of the inspection, the calculated quantitative difference value D, and the set quality control threshold T. QC And the final decision on whether it is qualified or unqualified.

[0127] S7. When a non-conformity is determined, a structured deviation analysis is performed on the discrepancy to achieve in-depth diagnosis of potential faults and generate a fault report:

[0128] Specifically, in step S7 of this embodiment, a structured deviation analysis is performed on the aforementioned calculated differences to achieve in-depth diagnosis of potential faults and generate corresponding fault reports.

[0129] The purpose of this step is to go beyond a simple "qualified / unqualified" binary judgment, and to provide precise, data-driven guidance for locating the root cause of the fault by deeply mining the structured information in the dynamic response signature matrix.

[0130] Specifically, upon receiving a non-conformance determination instruction, the processing control module will initiate the structured deviation analysis process. This process first obtains the calculated difference matrix ΔDRSM from step S6 as the initial input for the analysis.

[0131] According to a further definition of another embodiment of the present invention, the first stage of the structured deviation analysis includes decomposing the complex difference matrix ΔDRSM into amplitude differences and phase differences to reveal deviations in system performance from different physical dimensions. Exemplarily, this decomposition process involves processing the reference matrix DRSM... ref With the matrix to be tested DRSM UUT Each corresponding element in the matrix is ​​processed separately to establish an independent amplitude difference matrix ΔM and phase difference matrix ΔΦ.

[0132] This process can be represented by the following formula:

[0133] ΔM ij =|H UUT,ij |-|H ref,ij |;

[0134] ΔΦ ij =∠H UUT,ij -∠H ref,ij ;

[0135] In the formula;

[0136] ΔM ij Represents matrix element H UUT and H ref The difference in magnitude between the elements in the i-th row and j-th column;

[0137] ΔΦ ij Represents matrix element H UUT and H ref The phase difference of the element in the i-th row and j-th column;

[0138] |H UUT,ij | represents matrix H UUT The magnitude of the element in the i-th row and j-th column;

[0139] |H ref,ij | represents matrix H ref The magnitude of the element in the i-th row and j-th column;

[0140] ∠H UUT,ij Representation matrix H UUT The phase (angle) of the element in the i-th row and j-th column;

[0141] ∠H ref,ij Representation matrix H ref The phase (angle) of the element in the i-th row and j-th column.

[0142] After obtaining the difference matrices in both amplitude and phase dimensions, the analysis process continues to extract standardized fault feature vectors from these matrices. These fault feature vectors map the original matrix deviation data to a low-dimensional space strongly correlated with a specific physical subsystem or fault mode.

[0143] The next stage of the analysis process involves matching the extracted fault feature vectors with a pre-established fault mode database. This database is a collection that stores the mapping relationships between various typical faults and their corresponding fault feature vectors.

[0144] The database was established through extensive fault injection experiments and system simulations of charging piles.

[0145] The matching process is achieved by calculating the similarity or distance between the fault feature vector of the charging pile under test and the feature vectors of each fault mode stored in the database. The fault type corresponding to the database entry with the highest similarity is identified as the most likely fault of the charging pile under test.

[0146] Ultimately, based on the matching results, the processing control module determined the specific type of fault and the faulty components that might be causing the problem.

[0147] The AC / DC charging pile testing system described below can be referred to in correspondence with the AC / DC charging pile testing method described above.

[0148] Please see the appendix Figure 5 The present invention also provides an AC / DC charging pile detection system, comprising:

[0149] The signal generation module is used to generate preliminary broadband disturbance signals and optimized composite disturbance signals, and simultaneously apply them to the AC input terminal and communication control terminal of the charging pile under test.

[0150] The data acquisition module is used to acquire the response data of the output voltage and output current of the charging pile under test;

[0151] The processing control module is used to perform spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis.

[0152] The report generation module is used to generate inspection reports and fault reports.

[0153] The system in this embodiment can be used to execute the above method embodiments, and its principle and technical effect are similar, so they will not be described again here.

[0154] Please see the appendix Figure 6-7 The present invention also provides an AC / DC charging pile detection device, including a protective box 1; a display screen 2 is fixedly connected to the outer surface of the protective box 1, a charging gun connector 3 is fixedly connected to the inside of the protective box 1, one end of the charging gun connector 3 is electrically connected to a data collector 4, the outer wall of the data collector 4 is fixedly connected to the inside of the protective box 1, one end of the data collector 4 is electrically connected to a storage battery 5, the outer wall of the storage battery 5 is fixedly connected to the inner wall of the protective box 1, one end of the data collector 4 is electrically connected to a processing controller 6, the outer wall of the processing controller 6 is fixedly connected to the inner wall of the protective box 1, one end of the processing controller 6 is electrically connected to a signal generation module 7, and the outer wall of the signal generation module 7 is fixedly connected to the inner wall of the protective box 1.

[0155] Specifically, by inserting the charging gun into the charging gun connector 3 and applying a preliminary broadband disturbance signal to the charging pile under test through the signal generation module 7, the system obtains its response data to identify the sensitive frequency bands of the system. The charging pile output response is then acquired through the acquisition unit 4 and stored in the storage battery 5. The acquired data is then sent to the processing controller 6 to perform spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis.

[0156] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for testing AC / DC charging piles, characterized in that, Includes the following steps: S1. By applying a preliminary broadband disturbance signal to the charging pile under test, its response data is obtained in order to identify the sensitive frequency band of the system; S2. Generate an optimized composite disturbance signal based on the characteristics of the sensitive frequency band. This signal concentrates energy in the sensitive frequency band to excite the charging pile. S3. Simultaneously apply the optimized composite disturbance signal to the charging pile under test to obtain its output response; The step of simultaneously applying the optimized composite disturbance signal to the charging pile under test in step S3 is as follows: one component of the optimized composite disturbance signal is superimposed on the AC input voltage of the charging pile under test through a programmable AC power supply, and the other component of the optimized composite disturbance signal is superimposed on the charging command sent to the charging pile under test through a controller local area network communication device. S4. Calculate the transfer functions of the input and output signals by performing a Fourier transform on the output response; S5. Construct a dynamic response signature matrix based on the transfer function and store the matrix as baseline data; The step of constructing the dynamic response signature matrix in step S5 is as follows: the values ​​of the transfer function at multiple preset frequency points are arranged in frequency order to form a multi-row, multi-column matrix to represent the dynamic response characteristics of the charging pile at different frequencies. S6. After the test, calculate the difference between the dynamic response signature matrix and the stored benchmark data to determine the qualification of the charging pile and generate a test report. S7. When a non-conformity is determined, a structured deviation analysis is performed on the difference to achieve in-depth diagnosis of potential faults and generate a fault report. The structured deviation analysis in step S7 includes: The difference between the dynamic response signature matrix and the baseline data is decomposed into amplitude difference and phase difference, and corresponding fault feature vectors are established for each. The fault feature vector is matched with a preset fault mode database to determine the fault type and the corresponding fault component.

2. The AC / DC charging pile testing method according to claim 1, characterized in that, The response data in step S1 includes the output voltage and output current of the charging pile, and the sensitive frequency band is determined by performing spectrum analysis on the response data.

3. The AC / DC charging pile testing method according to claim 1, characterized in that, The step of generating the optimized composite disturbance signal in step S2 is as follows: multiple sine wave signals are superimposed to form the optimized composite disturbance signal, wherein the frequencies of the multiple sine wave signals are all set within the sensitive frequency band.

4. The AC / DC charging pile testing method according to claim 1, characterized in that, In step S4, the Fast Fourier Transform algorithm is used to process the output response and the input signal to obtain a frequency domain representation.

5. The AC / DC charging pile testing method according to claim 1, characterized in that, The specific steps for calculating the difference in step S6 are as follows: by calculating the Frobenius norm of the difference between the dynamic response signature matrix and the benchmark data, a quantitative difference value is obtained to characterize the overall degree of difference.

6. An AC / DC charging pile testing device, applied to the AC / DC charging pile testing method as described in any one of claims 1-5, characterized in that, The device includes a protective box (1); a display screen (2) is fixedly connected to the outer surface of the protective box (1); a charging gun connector (3) is fixedly connected to the inside of the protective box (1); a collector (4) is electrically connected to one end of the charging gun connector (3); the outer wall of the collector (4) is fixedly connected to the inside of the protective box (1); a storage battery (5) is electrically connected to one end of the collector (4); the outer wall of the storage battery (5) is fixedly connected to the inner wall of the protective box (1); a processing controller (6) is electrically connected to one end of the collector (4); the outer wall of the processing controller (6) is fixedly connected to the inner wall of the protective box (1); a signal generation module (7) is electrically connected to one end of the processing controller (6); the outer wall of the signal generation module (7) is fixedly connected to the inner wall of the protective box (1).

7. An AC / DC charging pile testing system, applied to the AC / DC charging pile testing method as described in any one of claims 1-5, characterized in that, include; The signal generation module is used to generate preliminary broadband disturbance signals and optimized composite disturbance signals, and simultaneously apply them to the AC input terminal and communication control terminal of the charging pile under test. The data acquisition module is used to acquire the response data of the output voltage and output current of the charging pile under test; The processing control module is used to perform spectrum analysis, transfer function calculation, dynamic response signature matrix construction, difference value calculation, and structured deviation analysis. The report generation module is used to generate inspection reports and fault reports.

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