Test control method for variable-frequency power supply

Abstract

The invention relates to the technical field of power supply experiment control, and discloses a test control method of a variable-frequency power supply, comprising the following steps: S1, generating a dynamic change signal of at least one load type through dynamic load simulation, the load type including resistive, inductive or capacitive; s2, acquiring original signals of output voltage, current and frequency parameters of the variable-frequency power supply in real time; s3, according to preset test condition parameters, a control instruction of the variable-frequency power supply is adjusted, and the control instruction comprises an output voltage amplitude, a frequency and a phase angle; s4, in the test process; and S5, generating the waveform containing the voltage. Through flexible switching and dynamic disturbance simulation of resistive, inductive and capacitive loads, complex working conditions of extreme transient, periodic fluctuation and random disturbance in an industrial scene are reproduced, and the anti-interference capability and stability of the variable-frequency power supply under the dynamic load are comprehensively verified in combination with a multi-mode load change strategy. And the test coverage and the scene restoration precision are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of power supply experimental control technology, specifically to a test control method for a frequency converter power supply. Background Technology

[0002] With the rapid development and widespread application of modern power electronics technology, frequency converters, as important power conversion devices, play a crucial role in industries such as industry, energy, transportation, and communications. Frequency converters can achieve precise load control by adjusting the frequency and voltage of the power supply, thereby improving energy efficiency, reducing energy consumption, and enhancing equipment performance. However, with the continuous improvement of application demands, higher requirements are being placed on the performance, stability, and reliability of frequency converters. Traditional testing methods often rely on mechanical load switching and manual parameter adjustment. However, current technologies have limitations in mechanical load switching and manual parameter adjustment, including limited dynamic range of load simulation, slow response speed, and distortion of operating condition reproduction, making it difficult to verify the dynamic response characteristics of the power supply under extreme transient conditions. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a test control method for variable frequency power supplies, which solves the problems of limited dynamic range of load simulation, slow response speed, and distortion of operating condition reproduction, making it difficult to verify the dynamic response characteristics of the power supply under extreme transient conditions.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a test control method for a frequency converter, comprising the following steps: S1. Generate dynamic change signals of at least one load type through dynamic load simulation, wherein the load type includes resistive, inductive, or capacitive. S2. Real-time acquisition of raw signals of the output voltage, current and frequency parameters of the frequency converter; S3. Adjust the control command of the frequency converter according to the preset test condition parameters. The control command includes the output voltage amplitude, frequency and phase angle. S4. During the test, the output port of the frequency converter is monitored by the hardware protection circuit. When the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value, the protection circuit is triggered to disconnect the output. S5. Generate a set of test data including voltage waveforms and frequency response curves, and output the set of data through a human-computer interaction interface.

[0005] Preferably, the dynamic load simulation in S1 includes a programmable electronic load module, which generates load change patterns through software configuration, including: A step load change occurs, with the load impedance switching from 50% to 100% of its rated value within 1 ms. The load is a periodic fluctuating load, with the load impedance varying according to a sine wave pattern, and the frequency range is 10Hz-1kHz. The load is subject to random disturbance, with the load impedance fluctuating randomly based on a Gaussian distribution, and the fluctuation range is ±20% of the rated value.

[0006] Preferably, the S2 signal processing specifically includes the following steps: 1. Select the Daubechies wavelet basis function to perform a 5-level decomposition on the original signal. The decomposition formula is as follows: 2. Where A5(t) is the low-frequency approximation coefficient of the 5th layer, and D j (t) represents the high-frequency detail coefficients of the j-th layer; 3. Threshold the decomposed high-frequency coefficients, setting the threshold to 2.5 times the noise standard deviation; 4. Detail coefficient D after thresholding j ′ The signal is reconstructed by combining (t) with the low-frequency coefficient A5(t) through inverse wavelet transform: Where, x ′ (t) represents the noise-reduced signal.

[0007] Preferably, the adjustment of the control command in S3 is based on a model predictive control algorithm, specifically including: S301 resolves the preset output voltage amplitude, frequency, and phase angle into control target values; S302, based on the discretized state-space model of the variable frequency power supply, predicts the future output voltage and current response. The discretized state-space model of the variable frequency power supply is: x(k+1)=Ax(k)+Bu(k). y(k)=Cx(k), where x(k) is the state vector of inductor current and capacitor voltage; u(k) is the control input; y(k) is the voltage and frequency output vector; A, B, and C are system matrices, determined by circuit parameters and sampling period; Y(k) = [y(k+1), y(k+2), y(k+3)] T : Predicted output for the next 3 steps; U(k) = [u(k), u(k+1), u(k+2)] T : Control sequence to be optimized; S303 generates a sequence of control commands based on voltage and frequency output vectors.

[0008] Preferably, the parameters of the discretized transfer function model are updated online using recursive least squares, with model parameter matrices A and B updated every 10ms using recursive least squares. Where θ(k)=[A;B] is the parameter vector, The regression vector includes historical input and output data, and K(k) is the Kalman gain matrix.

[0009] Preferably, the hardware protection circuit in S4 includes: Voltage comparator: compares the output voltage with a preset threshold in real time; Current transformer: measures current using a Hall effect sensor; Temperature sensor: monitors the temperature of the IGBT module, with a sampling interval of 1 second.

[0010] Preferably, the hardware protection circuit in S4 further includes an execution unit. After receiving a voltage or current over-limit signal, the execution unit drives the IGBT gate drive circuit to turn off the power switch and triggers a relay to cut off the main circuit.

[0011] Preferably, step S5 specifically includes the following steps: S501. Standardize the data format by aligning the collected raw voltage, current and frequency data by timestamp and converting it into CSV format structured data. Each row of data contains the following fields: timestamp, effective voltage value, effective current value and frequency. S502, waveform data compression and transmission, transmits the raw voltage waveform data to the human-machine interface in real time via the WebSocket protocol; S503, graphical interface rendering: In the human-computer interaction interface, the voltage waveform curve and frequency response curve are dynamically rendered through the Canvas drawing engine. The waveform display window supports scaling and panning operations.

[0012] A test control system for a variable frequency power supply, the system comprising: The dynamic load simulation module is used to generate dynamic change signals for resistive, inductive, or capacitive loads. The data acquisition module is used to acquire the raw signals of the output voltage, current and frequency parameters of the frequency converter in real time. The control command adjustment module is used to adjust the output voltage amplitude, frequency and phase angle of the frequency converter according to the preset test conditions; the hardware protection module is used to monitor the voltage and current of the output port of the frequency converter and trigger protection action when the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value. The data generation and output module is used to generate a set of test data including voltage waveforms and frequency response curves, and output them through a human-machine interface.

[0013] The dynamic load simulation module includes: Programmable electronic load unit, used to generate step load changes, periodic fluctuating loads or random disturbance loads through software configuration; Load switching circuit, used to switch the rated value of load impedance.

[0014] This invention provides a test control method for a frequency converter power supply. It has the following beneficial effects: 1. This invention reproduces the complex working conditions of extreme transients, periodic fluctuations and random disturbances in industrial scenarios by flexibly switching resistive, inductive and capacitive loads and simulating dynamic disturbances. It also comprehensively verifies the anti-disturbance capability and stability of the frequency converter under dynamic load by combining multi-mode load change strategies, significantly improving test coverage and scenario reproduction accuracy.

[0015] 2. This invention constructs a dynamic adaptive model predictive control framework by using a discretized state-space model and a recursive parameter identification algorithm. It tracks changes in system characteristics in real time and optimizes control commands. Through multi-step prediction and rolling optimization, it actively compensates for disturbances, achieving high-precision tracking of voltage, frequency, and phase angle. This solves the stability problems caused by the lag and model mismatch of traditional control, ensuring optimal dynamic response and energy efficiency under complex operating conditions.

[0016] 3. This invention, through data acquisition, compressed transmission, and visualization analysis processes, and through structured data formats and graphic rendering, enables real-time visualization and multi-dimensional analysis of test data, supporting engineers to quickly locate transient events and trace back historical data, providing intuitive and reliable technical support for power supply performance evaluation. Attached Figure Description

[0017] Figure 1 This is a flowchart of a test control method for a frequency converter power supply according to the present invention; Figure 2 This is a schematic diagram of the test control system for a variable frequency power supply according to the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 This invention provides a test control method for a frequency converter power supply, comprising the following steps: S1. Generate dynamic change signals of at least one load type through dynamic load simulation, where the load type includes resistive, inductive, or capacitive. S2. Real-time acquisition of raw signals of the output voltage, current and frequency parameters of the frequency converter; S3. Adjust the control commands of the frequency converter according to the preset test condition parameters. The control commands include the output voltage amplitude, frequency and phase angle. S4. During the test, the output port of the frequency converter is monitored by the hardware protection circuit. When the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value, the protection circuit is triggered to disconnect the output. S5. Generate a set of test data including voltage waveforms and frequency response curves, and output the set of data through the human-computer interaction interface.

[0020] Specifically, S1 generates dynamic change signals of resistive, inductive, or capacitive loads through dynamic load simulation, which can reproduce complex and varied load conditions in real applications (such as motor starting surge current, sudden voltage spikes of capacitive loads, and step changes of resistive loads). It is used to test the response capability of frequency converters under extreme and transient conditions, verify the stability of their output voltage / frequency, dynamic response speed, and the effectiveness of their overload protection mechanism. At the same time, it replaces traditional mechanical load switching with electronic load switching, which significantly improves test efficiency and waveform capture accuracy, ensuring that power supply design defects are fully exposed and optimized during the test phase. S2 acquires the raw signals of the output voltage, current and frequency parameters of the frequency converter in real time through the high-speed data acquisition module. It can accurately capture the transient characteristics of the power supply under dynamic load (such as voltage drop, frequency fluctuation, harmonic distortion, etc.). Combined with synchronous sampling technology and anti-aliasing filter, it ensures signal integrity and provides high-precision input data for subsequent control algorithms. At the same time, it can quickly identify abnormal operating conditions through real-time waveform monitoring, providing a reliable basis for power supply performance evaluation and optimization. S3 uses a model predictive control algorithm to adjust the output voltage amplitude, frequency and phase angle of the frequency converter in real time. It can quickly generate the optimal control command according to dynamic load changes and preset test conditions, and achieve high-precision tracking of the output waveform. At the same time, it compensates for voltage drops or frequency shifts caused by load disturbances in advance through multi-step prediction, which significantly reduces dynamic response time, suppresses harmonic distortion and switching device losses, and ensures the stability and energy efficiency optimization of the power supply under complex operating conditions, providing a precise and controllable test environment for reliability verification. S4 uses hardware protection circuitry to monitor the output voltage and current of the frequency converter in real time during the test. When the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value, the protection mechanism is immediately triggered to cut off the output. This can effectively prevent power devices (such as IGBTs) from being over-voltaged or over-currentd and burned out due to sudden load changes, short circuits, or control failures, ensuring the safety of the test system and avoiding equipment damage. At the same time, by accurately recording the voltage / current transient waveforms when the protection is triggered, it provides key data support for fault analysis and control algorithm optimization, ensuring the continuity and reliability of the test under complex working conditions. S5 generates test datasets containing voltage waveforms and frequency response curves, and outputs them in real time through a human-machine interface. This allows for a direct and intuitive display of the transient characteristics (such as voltage fluctuation range, frequency tracking accuracy, and harmonic distribution) and steady-state performance indicators of the frequency converter under dynamic loads. It enables real-time analysis of test results and historical data backtracking, supporting engineers to quickly locate design flaws and optimize parameters. At the same time, standardized data formats and remote access interfaces ensure the traceability of test results and multi-party collaborative verification, significantly improving testing efficiency and decision-making accuracy, and ensuring the comprehensiveness and reliability of power supply performance evaluation.

[0021] The dynamic load simulation in S1 includes a programmable electronic load module, which generates load change patterns through software configuration, including: A step load change occurs, with the load impedance switching from 50% to 100% of its rated value within 1 ms. The load is a periodic fluctuating load, with the load impedance varying according to a sine wave pattern, and the frequency range is 10Hz-1kHz. The load is subject to random disturbance, with the load impedance fluctuating randomly based on a Gaussian distribution, and the fluctuation range is ±20% of the rated value.

[0022] Specifically, by using programmable electronic load modules to realize step load changes, periodic fluctuation loads, and random disturbance loads, it can accurately simulate real-world scenarios such as industrial motor start-up and shutdown, grid connection impact of new energy inverters, and harmonic disturbances in complex power grids. This verifies the dynamic response capability of the frequency converter under extreme transient, periodic fluctuation, and random interference conditions (such as voltage recovery time ≤5ms and frequency tracking error ≤0.1Hz). By replacing the delay and distortion problems of traditional mechanical loads with nanosecond-level switching accuracy and high-bandwidth signal reproduction, it significantly shortens the test cycle and exposes potential defects of the power supply in terms of voltage immunity, harmonic suppression, and dynamic stability in advance, providing multi-dimensional data support for high-reliability power supply design. S2 signal processing specifically includes the following steps: 5. Select the Daubechies wavelet basis function to perform a 5-level decomposition on the original signal. The decomposition formula is as follows: 6. Where A5(t) is the low-frequency approximation coefficient of the 5th layer, and Dj (t) represents the high-frequency detail coefficients of the j-th layer; 7. Threshold the decomposed high-frequency coefficients, setting the threshold to 2.5 times the noise standard deviation; 8. Detail coefficient D after thresholding j ′ The signal is reconstructed by combining (t) with the low-frequency coefficient A5(t) through inverse wavelet transform: Where, x ′ (t) represents the noise-reduced signal.

[0023] Specifically, the original signal output by the frequency converter power supply is decomposed into five levels using Daubechies wavelet basis functions. The multi-resolution characteristics of wavelet transform are used to separate high-frequency noise (such as switching noise and electromagnetic interference) from low-frequency effective signals (such as fundamental voltage / current). Then, the high-frequency detail coefficients are thresholded (threshold = 2.5 times the noise standard deviation) to suppress random noise and transient interference. Finally, the denoised signal is reconstructed through inverse wavelet transform. This process can significantly improve the signal-to-noise ratio while preserving key dynamic features (such as voltage drops and frequency jumps), providing high-precision input data for subsequent control algorithms, avoiding false triggering or control instability caused by noise, and completely preserving transient events in the signal.

[0024] The adjustment of control commands in S3 is based on the model predictive control algorithm, specifically including: S301 resolves the preset output voltage amplitude, frequency, and phase angle into control target values; S302, based on the discretized state-space model of the variable frequency power supply, predicts the future output voltage and current response. The discretized state-space model of the variable frequency power supply is: x(k+1)=Ax(k)+Bu(k). y(k)=Cx(k), where x(k) is the state vector of inductor current and capacitor voltage; u(k) is the control input; y(k) is the voltage and frequency output vector; A, B, and C are system matrices, determined by circuit parameters and sampling period; Y(k) = [y(k+1), y(k+2), y(k+3)] T : Predicted output for the next 3 steps; U(k) = [u(k), u(k+1), u(k+2)] T : Control sequence to be optimized; S303 generates a sequence of control commands based on voltage and frequency output vectors.

[0025] Specifically, S301 converts user-defined test conditions (such as step voltage changes and frequency ramp tracking) into quantitative indicators that can be processed by the model predictive control algorithm by resolving the preset output voltage amplitude, frequency, and phase angle into mathematical control target values. This provides a clear tracking direction for subsequent optimization and ensures that control commands accurately match test requirements. S302 predicts the output voltage and current response within the next three control cycles based on a discretized state-space model. By recursively calculating, it anticipates the impact of load mutations or operating condition fluctuations on the output. Combined with the real-time state of the inductor current, it quantifies the dynamic behavior of the system (such as voltage drop amplitude and frequency recovery time), providing multi-step predictive data support for the optimization algorithm. This significantly improves the control's foresight, transforming the passive response of traditional feedback control into active compensation and suppressing transient disturbances. S303 optimizes the deviation between the predicted output and the target value using a quadratic programming solver, generating the optimal control sequence U that satisfies the constraints. * =[u(k),u(k+1),u(k+2)], and immediately execute the first control quantity u(k) to realize real-time closed-loop control under high-frequency updates, so as to quickly track dynamic load changes, suppress harmonic distortion and avoid overstress of power devices, and ensure the stability and optimal energy efficiency of the frequency converter under complex working conditions.

[0026] The parameters of the discretized transfer function model are updated online using recursive least squares, with the model parameter matrices A and B updated every 10ms using recursive least squares. Where θ(k)=[A;B] is the parameter vector, The regression vector includes historical input and output data, and K(k) is the Kalman gain matrix.

[0027] Specifically, by dynamically updating the parameter matrices A and B of the discretized transfer function model every 10ms using the online recursive least squares method, it is possible to track in real time the dynamic characteristic deviations of the variable frequency power supply caused by load changes, component aging, or temperature drift (such as inductance reduction and capacitance decay), and construct a regression vector using historical input and output data. By combining the Kalman gain matrix K(k) to adjust the parameter update step size, adaptive correction of model parameters is achieved while ensuring numerical stability (forgetting factor λ = 0.99 suppresses data overfitting). This ensures that the predictive control algorithm always generates control commands based on the latest system characteristics, significantly improving the control robustness under complex operating conditions. At the same time, it avoids oscillation or divergence problems caused by model mismatch, ensuring the efficiency and reliability of the frequency converter during long-term operation.

[0028] The hardware protection circuitry in S4 includes: Voltage comparator: compares the output voltage with a preset threshold in real time; Current transformer: measures current using a Hall effect sensor; Temperature sensor: monitors the temperature of the IGBT module, with a sampling interval of 1 second.

[0029] Specifically, a voltage comparator compares the output voltage with a preset threshold (such as 120% of the rated value) in real time to achieve rapid overvoltage protection. A Hall effect current transformer accurately measures the output current and triggers shutdown when the limit is exceeded. In conjunction with a temperature sensor, the temperature of the IGBT module is monitored at 1-second intervals to identify over-temperature risks in real time and initiate heat dissipation or load reduction strategies. The three work together to form a multi-layer hardware protection mechanism, effectively preventing power devices (IGBTs, capacitors) from breakdown, burnout, and performance degradation due to overvoltage, overcurrent, or overheating, thereby improving the safety of the test system and extending the service life of key components.

[0030] The hardware protection circuit in S4 also includes an execution unit. After receiving a voltage or current over-limit signal, the execution unit drives the IGBT gate drive circuit to turn off the power switch and triggers the relay to cut off the main circuit. Specifically, the execution unit can achieve a hardware-level dual protection mechanism by driving the IGBT gate drive circuit to turn off the power switch and triggering the relay to cut off the main circuit when the voltage or current exceeds the limit. The IGBT gate turn-off quickly blocks the current path to suppress the growth of fault current, while the relay cut-off physically isolates the power supply from the load to prevent secondary damage caused by arc reignition or residual energy. Its fully hardware-triggered logic ensures the absolute reliability of the protection action. Even if the control algorithm fails or communication is interrupted, it can still independently protect the system safety, significantly reduce the risk of breakdown or thermal failure of power devices due to instantaneous overstress, extend equipment life, and support the safe execution of high-risk tests (such as short-circuit tests).

[0031] S5 specifically includes the following steps: S501. Standardize the data format by aligning the collected raw voltage, current and frequency data by timestamp and converting it into CSV format structured data. Each row of data contains the following fields: timestamp, effective voltage value, effective current value and frequency. S502, waveform data compression and transmission, transmits the raw voltage waveform data to the human-machine interface in real time via the WebSocket protocol; S503, graphical interface rendering: In the human-computer interaction interface, the voltage waveform curve and frequency response curve are dynamically rendered through the Canvas drawing engine. The waveform display window supports scaling and panning operations.

[0032] Specifically, the S501 eliminates the timing bias of multi-channel sampling by aligning the raw voltage, current, and frequency data by timestamp and converting it into a CSV structured format (fields include timestamp, effective voltage value, effective current value, and frequency). This ensures strict consistency of the data in the time domain. At the same time, the standardized format is compatible with mainstream analysis tools, supports rapid import and batch processing, significantly improves the efficiency of data post-processing, and ensures the traceability and reproducibility of test results.

[0033] The S502 transmits compressed raw voltage waveform data in real time via the WebSocket protocol, enabling millisecond-level latency transmission of high-frequency sampling data in low-bandwidth network environments. It also avoids data packet loss through binary frame encapsulation and streaming transmission technology, ensuring that the human-machine interface displays waveform details in real time, supporting engineers' remote monitoring and immediate decision-making, providing seamless data stream support for dynamic testing, and overcoming the high latency and resource consumption problems of traditional HTTP polling.

[0034] S503 uses the Canvas drawing engine to dynamically render voltage waveform curves and frequency response curves, enabling waveform visualization and allowing engineers to accurately locate transient events (such as voltage drop moments and frequency jump points) and analyze local features (such as harmonic distortion and phase jitter).

[0035] Please see the appendix Figure 2 A test control system for a variable frequency power supply, the system comprising: The dynamic load simulation module is used to generate dynamic change signals for resistive, inductive, or capacitive loads. The data acquisition module is used to acquire the raw signals of the output voltage, current and frequency parameters of the frequency converter in real time. The control command adjustment module is used to adjust the output voltage amplitude, frequency and phase angle of the frequency converter according to the preset test conditions; the hardware protection module is used to monitor the voltage and current of the output port of the frequency converter and trigger protection action when the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value. The data generation and output module is used to generate a set of test data including voltage waveforms and frequency response curves, and output them through a human-machine interface.

[0036] Specifically, the dynamic load simulation module reproduces the step, periodic, and random disturbance conditions of resistive, inductive, and capacitive loads. The data acquisition module captures the power supply output signal in real time with high precision and high sampling rate. The control command adjustment module dynamically optimizes voltage, frequency, and phase angle commands based on model predictive control algorithms. The hardware protection module cuts off overvoltage or overcurrent fault circuits at microsecond speeds. The data generation and output module displays voltage waveforms and frequency response curves through standardized data formats and a real-time graphical interface. This achieves fully automated testing from load simulation, closed-loop control, safety protection to data visualization, significantly improving the performance verification efficiency of frequency converters under complex operating conditions and ensuring the safety of the test process and the traceability of the results.

[0037] The dynamic load simulation module includes: Programmable electronic load unit, used to generate step load changes, periodic fluctuating loads or random disturbance loads through software configuration; Load switching circuit, used to switch the rated value of load impedance.

[0038] Specifically, the dynamic load simulation module generates step, periodic, or random disturbance load signals through a programmable electronic load unit. Combined with the load switching circuit, it achieves rapid switching of load impedance, which can reproduce extreme working conditions in industrial scenarios (such as motor start-stop surges, photovoltaic inverter grid connection impacts, and grid harmonic disturbances). This verifies the dynamic response capability of the frequency converter under transient changes, high-frequency fluctuations, and random interference. At the same time, by replacing the delay and contact loss of mechanical switches with electronic switching, it improves test efficiency and repeatability, ensuring that power supply design defects (such as overshoot and oscillation) are fully exposed during the test phase, providing key data support for high reliability and adaptive control algorithm optimization.

[0039] 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 test control method for a variable frequency power supply, characterized in that, Includes the following steps: S1. Generate dynamic change signals of at least one load type through dynamic load simulation, wherein the load type includes resistive, inductive, or capacitive. S2. Real-time acquisition of raw signals of the output voltage, current and frequency parameters of the frequency converter; S3. Adjust the control command of the frequency converter according to the preset test condition parameters. The control command includes the output voltage amplitude, frequency and phase angle. S4. During the test, the output port of the frequency converter is monitored by the hardware protection circuit. When the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value, the protection circuit is triggered to disconnect the output. S5. Generate a set of test data including voltage waveforms and frequency response curves, and output the set of data through a human-computer interaction interface.

2. The test control method for a variable frequency power supply according to claim 1, characterized in that, The dynamic load simulation in S1 includes a programmable electronic load module, which generates load change patterns through software configuration, including: A step load change occurs, with the load impedance switching from 50% to 100% of its rated value within 1 ms. The load is a periodic fluctuating load, with the load impedance varying according to a sine wave pattern, and the frequency range is 10Hz-1kHz. The load is subject to random disturbance, with the load impedance fluctuating randomly based on a Gaussian distribution, and the fluctuation range is ±20% of the rated value.

3. The test control method for a variable frequency power supply according to claim 1, characterized in that, The S2 signal processing specifically includes the following steps: The Daubechies wavelet basis functions are selected to perform a 5-level decomposition on the original signal. The decomposition formula is as follows: Where A5(t) is the low-frequency approximation coefficient of the 5th layer, and D j (t) represents the high-frequency detail coefficients of the j-th layer; the decomposed high-frequency coefficients are thresholded, with the threshold set to 2.5 times the noise standard deviation; Detail coefficient D after thresholding j ′ The signal is reconstructed by combining (t) with the low-frequency coefficient A5(t) through inverse wavelet transform: Where, x ′ (t) represents the noise-reduced signal.

4. The test control method for a variable frequency power supply according to claim 1, characterized in that, The adjustment of control commands in S3 is based on a model predictive control algorithm, specifically including: S301 resolves the preset output voltage amplitude, frequency, and phase angle into control target values; S302, based on the discretized state-space model of the variable frequency power supply, predicts the future output voltage and current response. The discretized state-space model of the variable frequency power supply is: x(k+1)=Ax(k)+Bu(k). y(k)=Cx(k), where x(k) is the state vector of inductor current and capacitor voltage; u(k) is the control input; y(k) is the voltage and frequency output vector; A, B, and C are system matrices, determined by circuit parameters and sampling period; Y(k) = [y(k+1), y(k+2), y(k+3)] T : Predicted output for the next 3 steps; U(k) = [u(k), u(k+1), u(k+2)] T : Control sequence to be optimized; S303 generates a sequence of control commands based on voltage and frequency output vectors.

5. The test control method for a frequency converter according to claim 4, characterized in that, The parameters of the discretized transfer function model are updated online using recursive least squares method, with model parameter matrices A and B updated every 10ms using recursive least squares method: θ(k)=θ(k-1)+K(k)[y(k)-φ T (k)θ(k-1)] Where θ(k) = [A; B] is the parameter vector, φ(k) is the regression vector including historical input and output data, and K(k) is the Kalman gain matrix.

6. The test control method for a variable frequency power supply according to claim 1, characterized in that, The hardware protection circuit in S4 includes: Voltage comparator: compares the output voltage with a preset threshold in real time; Current transformer: measures current using a Hall effect sensor; Temperature sensor: monitors the temperature of the IGBT module, with a sampling interval of 1 second.

7. The test control method for a variable frequency power supply according to claim 1, characterized in that, The hardware protection circuit in S4 also includes an execution unit. After receiving a voltage or current over-limit signal, the execution unit drives the IGBT gate drive circuit to turn off the power switch and triggers a relay to cut off the main circuit.

8. The test control method for a variable frequency power supply according to claim 1, characterized in that, S5 specifically includes the following steps: S501. Standardize the data format by aligning the collected raw voltage, current and frequency data by timestamp and converting it into CSV format structured data. Each row of data contains the following fields: timestamp, effective voltage value, effective current value and frequency. S502, waveform data compression and transmission, transmits the raw voltage waveform data to the human-machine interface in real time via the WebSocket protocol; S503, graphical interface rendering: In the human-computer interaction interface, the voltage waveform curve and frequency response curve are dynamically rendered through the Canvas drawing engine. The waveform display window supports scaling and panning operations.

9. A test control system for a variable frequency power supply, characterized in that, A test control method for a variable frequency power supply according to any one of claims 1-8, the system comprising: The dynamic load simulation module is used to generate dynamic change signals for resistive, inductive, or capacitive loads. The data acquisition module is used to acquire the raw signals of the output voltage, current and frequency parameters of the frequency converter in real time. The control command adjustment module is used to adjust the output voltage amplitude, frequency and phase angle of the frequency converter according to preset test conditions. The hardware protection module is used to monitor the voltage and current at the output port of the frequency converter power supply and trigger protection action when the voltage exceeds 120% of the rated value or the current exceeds 150% of the rated value. The data generation and output module is used to generate a set of test data including voltage waveforms and frequency response curves, and output them through a human-machine interface.

10. The test control system for a frequency converter according to claim 9, characterized in that, The dynamic load simulation module includes: Programmable electronic load unit, used to generate step load changes, periodic fluctuating loads or random disturbance loads through software configuration; Load switching circuit, used to switch the rated value of load impedance.

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