Multifunctional power electronic equipment testing method, system, equipment and medium
By constructing a unified test interface and simulating power grid operating conditions, and combining digital twins and hardware-in-the-loop real-time simulation, the problems of inconsistent interfaces and low intelligence in the testing of power electronic equipment have been solved, achieving efficient and accurate equipment performance evaluation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-24
- Publication Date
- 2026-03-20
AI Technical Summary
Existing power electronic equipment testing methods lack unified testing interfaces and protocol standards, cannot simulate complex power grid conditions, have low levels of intelligence, resulting in low testing efficiency and high costs, and cannot effectively support new equipment such as energy storage converters and electric vehicle charging piles.
By constructing a unified test interface, system state modeling and interface adaptation are performed to simulate power grid operating conditions. Combining digital twins and hardware-in-the-loop real-time simulation, the real-time simulation step size and synchronization accuracy are optimized. Multi-sensor data is integrated for anomaly detection to achieve equipment performance testing and report generation.
It improves the versatility and accuracy of testing, reduces costs, enhances testing efficiency and equipment utilization, and ensures the reliability and consistency of test results.
Smart Images
Figure CN121703525A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of power electronic device testing, and in particular to a multifunctional power electronic device testing method, system, device and medium. BACKGROUND
[0002] With the rapid advancement of new power system construction and large-scale access of distributed power sources, the types of power electronic devices on the distribution network side are increasing, and the complexity of their functions is continuously improving, which puts higher requirements on device performance testing and quality inspection.
[0003] However, the traditional power electronic device testing method mainly uses a single device-specific testing platform, which lacks universality and compatibility, and has obvious shortcomings in terms of testing efficiency and cost control. The existing testing equipment lacks unified testing interfaces and protocol standards, and different types of devices from different manufacturers need to be configured with special testing devices, which is costly and has low equipment utilization. The traditional testing platform lacks the ability to simulate real complex grid conditions, and cannot effectively verify the performance and adaptability of the device in actual operating environment. The existing testing method lacks intelligent monitoring and remote control functions, and the testing process requires a lot of manual intervention, making it difficult to ensure testing efficiency and consistency. The traditional testing device lacks effective support for new power electronic devices such as energy storage converters and electric vehicle charging piles, and the testing capability lags behind the needs of technological development. SUMMARY
[0004] In view of the above existing problems, the present application is proposed.
[0005] Therefore, the present application provides a multifunctional power electronic device testing method and system to solve the technical problems of non-uniform interfaces, unrealistic simulation of testing environment, low degree of intelligence, poor compatibility, etc. in the current power electronic device testing.
[0006] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a multifunctional power electronic device testing method, comprising: Obtaining system state parameters of the electronic device and performing system state modeling to obtain a system state vector and generate a device compatibility matrix; According to the interface state and the compatibility matrix, identifying the interface type and communication protocol of the device under test, performing interface adaptation conversion and optimizing communication efficiency; According to the test parameters in the system state parameters and the interface adaptation result, allocating hardware resources and configuring a reconfigurable hardware platform; According to the environment simulation state in the system state parameters and the interface adaptation result, simulating grid conditions and analyzing power quality; Based on the simulation of power grid operating conditions and hardware resources, the real-time simulation step is optimized, the hardware and simulation time are synchronized, and the fidelity of the simulation output is evaluated; Fusion of multi-sensor monitoring data, detection of abnormal state and optimization of remote control response; Combined with digital twin and hardware-in-the-loop real-time simulation, a virtual model of the device under test is constructed, the simulation step is optimized, and the synchronization accuracy is optimized for dynamic synchronization verification of the physical system and the virtual model; After updating, perform device performance test, calculate device performance, determine whether the device meets the technical requirements, and combine adaptive test strategy to optimize test sequence; comprehensive analysis of all test data to generate test report.
[0007] As a preferred scheme of the multifunctional power electronic device test method, according to the interface state and compatibility matrix, the interface type and communication protocol of the device under test are identified, interface adaptation conversion is performed, and communication efficiency is optimized, including: The interface adaptation conversion is realized by mapping the source interface parameters of the device under test to the target interface parameters; The optimization of communication efficiency is realized by comparing the ratio of effective data volume to total data volume and the ratio of standard transmission time to actual transmission time, and comprehensively evaluating the data transmission quality and speed of the test device interface.
[0008] As a preferred scheme of the multifunctional power electronic device test method, according to the test parameters in the system state parameters and the interface adaptation results, the hardware resources are allocated and the reconfigurable hardware platform is configured, including: The hardware resource allocation is dynamically allocated according to the demand of each test task, the total resource amount and the task priority, the allocation process is based on the proportion of task demand to total demand, and combined with the deviation of task priority and average priority, an adjustment coefficient is used to adjust the allocation; The hardware reconfiguration time includes configuration analysis time, resource mapping time, configuration loading time and verification time, the sum of each time period is predicted, which is used to formulate the reconfiguration strategy; And by evaluating the system flexibility, the adaptability to different devices is verified.
[0009] As a preferred scheme of the multifunctional power electronic device test method, wherein the simulated power grid operating conditions and power quality analysis include: According to the set reference power, combined with the deviation between the reference frequency and the actual frequency, the active output power is dynamically adjusted by combining proportional control and integral control, to simulate the load change in the power grid; According to the set reference reactive power, combined with the deviation between the reference voltage and the actual voltage, the output reactive power is dynamically adjusted by the proportional control and the differential control, so as to simulate the voltage fluctuation and the reactive power compensation scene in the power grid. According to the fundamental angular frequency, combined with the amplitude and phase of each harmonic, a synthesized voltage waveform from the fundamental to the specified highest harmonic order is generated, which is used to simulate the harmonic interference and power quality problems in the power grid.
[0010] The beneficial effects of the preferred technical scheme are: the output active power is mainly realized through the control of the reference power and the frequency deviation, ensuring that the test environment can accurately reflect the actual working condition. The output reactive power is realized through the adjustment of the reference reactive power and the voltage deviation, so as to ensure the precise control of the voltage and power factor of the test environment. The harmonic voltage is generated by superimposing multiple harmonic components, which is used to simulate the harmonic interference and power quality problems in the power grid, thereby providing complex power grid environment test conditions for the measured device.
[0011] As a preferred scheme of the multifunctional power electronic device test method, based on the simulated power grid working condition and the hardware resource, the real-time simulation step is optimized, the hardware and the simulation time are synchronized, and the fidelity of the simulation output is evaluated, including: The optimization of the real-time simulation step is realized by balancing the simulation error, the calculation time and the system stability; The control of the hardware and the simulation time synchronization is completed by minimizing the difference between the hardware time step and the simulation time step; The evaluation of the fidelity of the simulation output is realized by comparing the relative deviation of the actual output of the multiple sensors.
[0012] As a preferred scheme of the multifunctional power electronic device test method, the multi-sensor monitoring data is fused, the abnormal state is detected, and the remote control response is optimized, including: The fusion is realized by weighting and summing the weight and the reliability coefficient of each sensor data; The mean and the standard deviation of the normal state data are dynamically set, and the confidence coefficient is set for abnormal state detection; The response optimization is realized by minimizing the network transmission, processing, execution and feedback time.
[0013] As a preferred scheme of the multifunctional power electronic device test method, the virtual model of the measured device is constructed by combining the digital twin and the hardware-in-the-loop real-time simulation, the simulation step and the synchronization accuracy are optimized, and the dynamic synchronization verification of the physical system and the virtual model is realized, including: The test accuracy is calculated by comparing the ratio of the absolute difference between the measured value and the true value to the true value; A repeatability index is derived by calculating the ratio of the standard deviation to the measurement mean and converting to a percentage; Based on the physical characteristics and operating parameters of the measured device, a digital twin model is constructed to simulate the dynamic behavior of the device under different operating conditions. Through data-driven and physics-driven model updating strategies, the twin model is dynamically adjusted by combining update weights to ensure consistency with the physical system, and the model accuracy is evaluated by comparing the deviation between the twin model output and the physical system output. In a second aspect, the present application provides a multifunctional power electronic device test system, comprising: In a third aspect, the present application provides a computer device, comprising: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, which realize the steps of the multifunctional power electronic device test method when the computer executable instructions are executed by the processor.
[0014] In a fourth aspect, the present application provides a computer readable storage medium storing computer executable instructions, which realize the steps of the multifunctional power electronic device test method when the computer executable instructions are executed by the processor.
[0015] Compared with the prior art, the present application has the following advantages: the present application provides a reliable data basis and seamless connection for the test process by constructing a unified test interface, ensuring the universality and safety of the test. Through dynamic resource allocation and real power grid operating condition simulation, the present application provides efficient hardware support and realistic test environment for the test, improving the authenticity and comprehensiveness of the test. Combined with real-time simulation optimization, hardware synchronization and digital twin model construction, the present application ensures the high precision and consistency of the test, and enhances the credibility of the results. Through data fusion and anomaly detection, the present application improves the data quality and test safety, and provides reliable input for performance evaluation; the present application can significantly improve the test efficiency and test precision, and provides a complete technical solution for the standardized test of power electronic devices. BRIEF DESCRIPTION OF DRAWINGS
[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.
[0017] Figure 1 The overall flowchart of a multifunctional power electronic device test method according to an embodiment of the present application. DETAILED DESCRIPTION
[0018] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.
[0019] Embodiment 1, refer to Figure 1 For an embodiment of the present application, a multifunctional power electronic device test method is provided, comprising: S100: Obtain system state parameters of the electronic device, and perform system state modeling to obtain a system state vector and generate a device compatibility matrix; S200: According to the interface state and the compatibility matrix, identify the interface type and communication protocol of the device under test, perform interface adaptation conversion and optimize communication efficiency; S300: According to the test parameters in the system state parameters and the interface adaptation result, allocate hardware resources and configure a reconfigurable hardware platform; S400: According to the environmental simulation state in the system state parameters and the interface adaptation result, simulate power grid conditions and analyze power quality; S500: Based on the simulated power grid conditions and hardware resources, optimize the real-time simulation step, control the hardware and simulation time synchronization, and evaluate the fidelity of the simulation output; S600: Fusion of multi-sensor monitoring data, detection of abnormal state and optimization of remote control response; S700: Combined with digital twin and hardware-in-the-loop real-time simulation, a virtual model of the device under test is constructed, the simulation step and synchronization accuracy are optimized, and the dynamic synchronization verification of the physical system and the virtual model is used; S800: After updating, perform device performance test, perform device performance calculation, determine whether the device meets the technical requirements, and combine adaptive test strategy to optimize the test sequence; comprehensively analyze all test data to generate a test report.
[0020] It should be noted that steps S100-S800 are based on power electronics, digital twin theory, real-time simulation technology and intelligent control algorithm, and through unified interface design, modular hardware architecture, integrated simulation of load power supply and intelligent monitoring, etc. Key technologies, a multifunctional power electronic device test platform is constructed. The system adopts hardware-in-the-loop test architecture, combined with real-time simulation and physical test, to realize comprehensive performance verification of various power electronic devices.
[0021] Embodiment 2, refer to Figure 1As an embodiment of the present invention, a multifunctional power electronic equipment testing method is provided based on the above embodiment.
[0022] In this embodiment of the application, in step S100, the system state parameters of the electronic device are obtained, and system state modeling is performed to obtain the system state vector and generate the device compatibility matrix. Specifically, system status parameters include: device interfaces, test parameters, environmental simulation, and control command information; For example, based on the specific parameters mentioned above, the system state vector can be represented as: In the formula, For the first The system state vector at each moment The interface status of the device under test. Configure test parameters, This is a simulated environmental state. To control the state of the command, To monitor the status of the data.
[0023] It should be noted that, Directly used for interface adaptation and communication optimization of S200; This provides parameter constraints for the hardware resource allocation of S300 and the power grid operating condition simulation of S400, and provides parameter constraints for simulation step size optimization to ensure that the simulation and test objectives are consistent. The initial states of the power grid operating conditions, such as voltage, frequency, and harmonics, are defined to provide reference conditions for the real-time simulation in subsequent step S400. For example, simulation error (Esimulation) and stability index (Sstability) need to be defined. To determine the boundary conditions of the simulation environment. and This provides a reference for real-time simulation and data fusion of S500 and S600.
[0024] Specifically, the test equipment compatibility matrix: In the formula, For device compatibility matrix, For the first Type of test function and the first The compatibility coefficient of this type of equipment To test the number of features, To support a certain number of device types.
[0025] It should be noted that the device compatibility matrix S200 can be used to identify the interface type and communication protocol of the device, and ensure the adaptability of the test device and the device under test.
[0026] System dynamic response characteristics: In the formula, is the system output response, is the transfer function matrix, is the test excitation signal, is the external interference signal.
[0027] In an optional embodiment, an overload protection threshold can also be set in the configuration stage to establish a security protection mechanism; specifically, the overload protection algorithm can be represented as: In the formula, is the protection action signal, is the measured current, is the protection threshold, is the delay time.
[0028] It should be noted that S100 is the starting point of the test process, which provides a basic system state description and compatibility evaluation, and lays a foundation for subsequent interface adaptation, hardware allocation and environment simulation.
[0029] In the embodiments of the present application, in step S200, the interface type and communication protocol of the device under test are identified according to the interface state and compatibility matrix, interface adaptation conversion is performed, and communication efficiency is optimized, including: A1: The interface adaptation conversion is realized by mapping the source interface parameters of the device under test to the target interface parameters; Specifically, according to the interface state and compatibility matrix provided by S100, the interface type and communication protocol are identified, interface adaptation conversion and compatibility evaluation are performed, wherein the interface adaptation conversion can be represented as: In the formula, is the target interface parameter, is the interface adaptation matrix, is the source interface parameter, is the interface offset vector.
[0030] It should be noted that, The interface consistency between the device under test and the test system can be ensured, and the adapted interface parameters are provided for the hardware resource allocation of S300 and the power grid working condition simulation of S400.
[0031] In an alternative embodiment, based on the interface adaptation conversion in the above embodiment, interface compatibility evaluation can also be performed, which can be expressed as: wherein, is the interface compatibility index, is the compatibility of the th feature, is the feature weight coefficient, is the total number of features.
[0032] It should be noted that, A1 is used to verify the reliability of interface adaptation, which indirectly affects the priority of S300 hardware resource allocation; at the same time, A1 is mainly for interface adaptation and compatibility evaluation in the initial configuration stage.
[0033] A2: The optimization of communication efficiency is to evaluate the data transmission quality and speed of the test device interface by comparing the ratio of effective data volume to total data volume and the ratio of standard transmission time to actual transmission time; Specifically, the interface recognition program is started to automatically detect the interface type and communication protocol of the device under test; and the interface communication efficiency is calculated to optimize the data transmission performance, and the interface communication efficiency can be expressed as: wherein, is the communication efficiency, is the effective data volume, is the total data volume, is the standard transmission time, is the actual transmission time.
[0034] It should be noted that, A2 provides a reference for the data transmission performance of the real-time simulation of S500 and the remote control response optimization of S600, ensuring the efficiency of the simulation and control process.
[0035] In the embodiments of the present application, the hardware resources are allocated and the reconfigurable hardware platform is configured in step S300 according to the test parameters in the system state parameters and the interface adaptation results, including: B1: The hardware resource allocation is dynamically allocated according to the demand of each test task, the total resource amount and the task priority, and the allocation process is based on the proportion of the task demand amount to the total demand amount, and combined with the deviation of the task priority from the average priority, the allocation is adjusted by adjusting the coefficient; Specifically, the hardware resource allocation can be expressed as: wherein, is the resource allocation of the th test task, is the task demand amount, is the total resource amount, is the task priority, is the average priority, is the adjustment coefficient.
[0036] It should be noted that, can be directly used for real-time simulation of S500, ensuring that the hardware resources meet the test task demand; through B1, it can be ensured that high-priority tasks obtain more resources, thereby optimizing the test efficiency and resource utilization.
[0037] B2: The hardware reconstruction time includes configuration analysis time, resource mapping time, configuration loading time and verification time, and the sum of each time period is predicted to formulate a reconstruction strategy; Specifically, the hardware reconstruction time can be represented as: In the formula, is the hardware reconstruction time, is the configuration analysis time, is the resource mapping time, is the configuration loading time, is the verification time.
[0038] It should be noted that, provides time prediction for the hardware and simulation time synchronization of S500, ensuring the continuity of real-time simulation. By estimating the total time required to complete hardware reconstruction, the system estimates the total time required to complete hardware reconstruction, thereby formulating an efficient reconstruction strategy, reducing test interruption time and improving the continuity of the test process.
[0039] B3: And by evaluating the system flexibility, the adaptability to different devices is verified.
[0040] Specifically, the system flexibility is evaluated by two ratios: one is the ratio of the number of supported device types to the total number of devices to be tested, reflecting the system's coverage ability for different device types; the second is the ratio of the reconfigurable ability to the total configuration ability, measuring the system's adaptability in hardware configuration; Specifically, the flexibility index can be represented as: In the formula, is the system flexibility index, is the number of supported device types, is the total number of devices to be tested, is the reconfigurable ability, is the total configuration ability.
[0041] It should be noted that, The digital twin model construction of S700 can be referenced to verify the support capability of the system for multiple device types. The flexibility index is generated by combining the two in the above formula, which is mainly used to verify the adaptive capability of the system to the test requirements of multiple power electronic devices.
[0042] In the embodiment of the present application, according to the environment simulation state in the system state parameter and the interface adaptation result in step S400, the simulation of power grid working condition and the analysis of power quality include: C1: According to the set reference power, combined with the deviation between the reference frequency and the actual frequency, the active output power is dynamically adjusted by the combination of proportional control and integral control, to simulate the load change of power grid; Specifically, the active power control equation is expressed as: In the formula, is the output active power, is the reference power, is the reference frequency, is the actual frequency, and are proportional and integral control parameters respectively.
[0043] C2: According to the set reference reactive power, combined with the deviation between the reference voltage and the actual voltage, the output reactive power is dynamically adjusted by the combination of proportional control and differential control, to simulate the voltage fluctuation and reactive compensation scene in power grid; Specifically, the reactive power regulation strategy is expressed as: In the formula, is the output reactive power, is the reference reactive power, is the reference voltage, is the actual voltage, and are proportional and differential control parameters respectively.
[0044] C3: According to the fundamental angular frequency, combined with the amplitude and phase of each harmonic, the synthesized voltage waveform from the fundamental to the specified highest harmonic order is generated, which is used to simulate the harmonic interference in power grid and monitor the power quality problem; Specifically, the harmonic voltage generation algorithm is expressed as: In the formula, is the harmonic voltage, is the amplitude of the nth harmonic, is the fundamental angular frequency, is the phase of the nth harmonic, is the amplitude of the nth harmonic, Second harmonic phase This is the highest harmonic order.
[0045] It should be noted that the simulated power grid operating conditions , , It can provide a testing environment for real-time simulation of S500, ensuring that the simulation can reflect the actual power grid operating conditions.
[0046] Specifically, power quality issues are monitored by calculating voltage imbalance, measuring power factor, and total harmonic distortion. Voltage imbalance can be expressed as: In the formula, For voltage imbalance, It is a negative sequence voltage component. This represents the positive sequence voltage component.
[0047] The power factor can be expressed as: In the formula, For power factor, Active power This refers to reactive power.
[0048] The total harmonic distortion rate can be expressed as: In the formula, The total harmonic distortion of voltage. For the first RMS value of subharmonic voltage This represents the effective value of the fundamental voltage.
[0049] It should be noted that power quality indicators can provide a reference for the abnormal state detection of S600 and the equipment performance testing of S800, and can be used to evaluate the performance of equipment in complex power grid environments.
[0050] The aforementioned output active power is primarily achieved through the control of reference power and frequency deviation, ensuring that the test environment accurately reflects actual operating conditions. Output reactive power is achieved through the adjustment of reference reactive power and voltage deviation, ensuring precise control of voltage and power factor in the test environment. Harmonic voltage is generated by superimposing multiple harmonic components to simulate harmonic interference and power quality issues in the power grid, thus providing the device under test with complex power grid environment test conditions. Overall, a test environment capable of realistically simulating power grid load changes, voltage fluctuations, and power quality disturbances is constructed, ensuring that the test equipment can comprehensively verify the performance of power electronic equipment under complex power grid conditions.
[0051] In the embodiments of the present application, in step S500, the real-time simulation step length is optimized based on the simulated power grid operating condition and hardware resources, the hardware and simulation time are synchronized, and the fidelity of the simulation output is evaluated, including: D1: the optimization of the real-time simulation step length is achieved by balancing the simulation error, calculation time and system stability; Specifically, the optimization of the real-time simulation step length can be represented as: In the formula, is the optimal simulation step length, is the simulation error, is the calculation time, is the stability index, is the weight coefficient.
[0052] It should be noted that the balance is achieved by the weight coefficient, the optimal simulation time step is calculated, and the best balance between accuracy, efficiency and stability is ensured in the simulation process.
[0053] D2: the synchronization of the hardware and simulation time is achieved by minimizing the difference between the hardware time step and the simulation time step; Specifically, the hardware-in-the-loop synchronization accuracy can be represented as: In the formula, is the synchronization accuracy, is the hardware time step, is the simulation time step, is the reference time step.
[0054] It should be noted that the synchronization accuracy index is calculated, which can reflect the synchronization degree of the hardware and the simulation system, and the higher the accuracy indicates the more consistent the time step lengths of the two.
[0055] D3: the evaluation of the fidelity of the simulation output is achieved by comparing the relative deviation of the actual outputs of multiple sensors; Specifically, the simulation fidelity evaluation can be represented as: In the formula, is the simulation fidelity, is the i-th simulation output, is the i-th actual output. It should be noted that the simulation fidelity is calculated, that is, the degree of agreement between the simulation result and the actual system behavior is evaluated, and the higher the fidelity indicates that the simulation is closer to the reality.
[0056] It should be noted that the simulation fidelity is calculated, that is, the degree of agreement between the simulation result and the actual system behavior is evaluated, and the higher the fidelity indicates that the simulation is closer to the reality.
[0057] Overall, the S500 can build efficient and accurate real-time simulation and hardware-in-the-loop testing systems, ensuring accurate simulation of the behavior of power electronic devices and high consistency with actual hardware. The monitoring data from the S100 and the simulation output from the S500 provide input for the data fusion and anomaly detection of the S600.
[0058] In this embodiment of the application, step S600, which integrates multi-sensor monitoring data to detect abnormal states and optimize remote control response, includes: E1: The data from each sensor is fused by weighting and summing the data based on weights and reliability coefficients assigned to each sensor. Specifically, the monitoring data fusion algorithm can be expressed as: In the formula, For the merged data, For the first Sensor data, These are the weighting coefficients. This represents the reliability coefficient.
[0059] It should be noted that E1 generates high-precision fused data by weighted summation of data from multiple sensors, combining the weights and reliability coefficients of each sensor data, thereby improving the accuracy and reliability of test data monitoring.
[0060] E2: Dynamically set the mean and standard deviation based on normal state data, and set the confidence coefficient to detect abnormal states; Specifically, the anomaly detection threshold can be expressed as: In the formula, This is the anomaly detection threshold. This represents the mean value under normal conditions. The standard deviation of the normal state. , is the confidence coefficient For safety margin.
[0061] It should be noted that E2 can further ensure test security and stability by calculating anomaly detection thresholds and identifying abnormal states in real time during the testing process.
[0062] E3: Optimizes response by minimizing network transmission, processing, execution, and feedback time.
[0063] Specifically, the remote control response time can be expressed as: In the formula, For the total response time of remote control, For network transmission time, For processing time, For execution time, For feedback time.
[0064] It should be noted that E3 can ensure fast response to instructions by calculating the remote control total response time, meeting the real-time monitoring and control requirements.
[0065] In the embodiments of the present application, in step S700, a virtual model of the device under test is constructed by combining digital twinning and hardware-in-the-loop real-time simulation, the simulation step and synchronization accuracy are optimized, and dynamic synchronization verification of the physical system and the virtual model is realized, including: F1: Calculate the test accuracy by comparing the ratio of the absolute difference between the measured value and the true value to the true value; Specifically, the measurement accuracy calculation can be expressed as: In the formula, is the measurement accuracy, is the measured value, is the true value.
[0066] In an optional embodiment, the system uncertainty can also be calculated for evaluation. For example, the system uncertainty can be expressed as: In the formula, is the total system uncertainty, is the type A uncertainty, is the type B uncertainty, is the environmental uncertainty.
[0067] F2: Obtain the repeatability index by calculating the ratio of the standard deviation to the measurement average value and converting it to a percentage; Specifically, the test repeatability index is: In the formula, is the repeatability index, s is the standard deviation, is the measurement average value.
[0068] F3: Based on the physical characteristics and operating parameters of the device under test, a digital twin model is constructed to simulate the dynamic behavior of the device under different working conditions; Specifically, the twinning model accuracy can be expressed as: In the formula, is the twinning model accuracy, is the output of the i-th twinning model, is the output of the i-th physical system.
[0069] F4: Through the model updating strategy driven by data and physics, the twin model is dynamically adjusted by combining the updating weight, the consistency with the physical system is ensured, and the model accuracy is evaluated by comparing the deviation of the twin model output and the physical system output; Specifically, the model updating strategy is represented as: In the formula, is the updated model, is the current model, is the data-driven update amount, is the physics-driven update amount, and is the updating weight.
[0070] The twin synchronization delay is represented as: In the formula, is the synchronization delay, is the physical system time, is the twin model time.
[0071] In the embodiments of the present application, after the update in step S800, the device performance test is performed, the device performance is calculated, it is determined whether the device meets the technical requirements, and the test sequence is optimized in combination with the adaptive test strategy; comprehensive analysis is performed on all test data, and a test report is generated, including: G1: Perform device performance test, calculate device comprehensive performance index, efficiency and device reliability; Specifically, the comprehensive performance index is represented as: In the formula, is the comprehensive performance index, is the efficiency index, is the reliability index, is the quality index.
[0072] The efficiency evaluation is represented as: In the formula, is the device efficiency, is the output power, is the input power, is the effective working time, is the total test time.
[0073] The reliability evaluation is represented as: In the formula, is a device reliability function, is a failure rate function; reliability evaluation is used to analyze long-term operation capability of the device.
[0074] G2: determine whether the device performance parameter meets the technical requirements by setting a qualified threshold; Specifically, the test result evaluation is expressed as: In the formula, is the test result, is the test parameter, and are the lower limit and the upper limit, respectively.
[0075] In an alternative embodiment, the test data can also be filtered during the test process to eliminate noise interference; Specifically, the data filtering algorithm is expressed as: In the formula, is the filtered signal, is the filter impulse response, is the input signal, is the filter order.
[0076] In another alternative embodiment, fault isolation and safety evaluation can also be implemented after obtaining the test evaluation result to ensure the safety of the subsequent test process; Specifically, the fault isolation strategy can be expressed as: In the formula, is the optimal isolation strategy, is the number of affected devices, is the operating cost.
[0077] The safety evaluation index can be expressed as: In the formula, is the system safety, is the subsystem safety, is the dangerous state time.
[0078] G3: start the adaptive test strategy and automatically adjust the test parameters; Specifically, the test parameter self-adjustment is expressed as: In the formula, is the updated parameter, is the current parameter, is the learning rate, is the target function gradient, is the momentum coefficient, is the previous parameter change amount.
[0079] G4: By optimizing the test sequence, considering test time, cost and coverage, the optimal test scheme is generated to improve efficiency; Specifically, the test sequence optimization is expressed as: In the formula, is the optimal test sequence, is the time of the test item, is the cost of the test item, is the coverage weight, is the test coverage.
[0080] G5: By comparing the deviation of performance before and after learning with the target performance, the optimization effect of the adaptive strategy is evaluated to ensure the reliability and consistency of the test results; Specifically, the optimization effect of the adaptive strategy is expressed as: In the formula, is the adaptive learning effect, is the performance after learning, is the performance before learning, is the target performance.
[0081] G7: Comprehensive analysis is made on all test data to generate a test report; Specifically, the system comprehensive evaluation index can be expressed as: In the formula, is the system comprehensive evaluation, is the accuracy index, is the efficiency index, is the flexibility index, is the safety index.
[0082] The test report can include device performance parameters, test result analysis and improvement suggestions.
[0083] In an optional implementation, data compression can also be performed in the adaptive optimization learning stage to optimize data storage and transmission efficiency; according to historical test data and device characteristics, the test strategy and parameter configuration are continuously optimized; Specifically, the data compression efficiency can be expressed as: wherein, is the compression efficiency, is the original data size, is the compressed size, is the recovery quality, is the original quality.
[0084] In another optional embodiment, based on the above-mentioned embodiments, after generating the report, a test database can be established to record the test history and performance change trend of various types of equipment. Technical support and improvement suggestions are provided for equipment manufacturers and users, the test process is completed and the system is reset to prepare for the next test.
[0085] Example 3, based on the above-mentioned embodiments, this embodiment provides a simulation verification of a multifunctional power electronic equipment test method to prove the effectiveness and practicality of the method.
[0086] The test environment includes low-voltage grid-connected inverters, reactive power compensation devices, power active filters, energy storage converters, and electric vehicle charging piles, covering different power levels and technical types. The experimental time span is 18 months, and more than 3000 equipment tests and verifications have been completed.
[0087] The experimental results show the test performance of the system under different equipment types, as shown in Tables 1-3: Table 1: Comparison of test performance of different equipment types
[0088] Table 2: Test results of system performance indicators
[0089] Table 3: Analysis of economic benefits and technical effects
[0090] Through Tables 1-3, the experimental results show that the system has significantly improved in test accuracy, compatibility, and automation. The test accuracy reaches 99.3%, the compatibility reaches 98.2%, and the equipment utilization rate increases by 143%. The system supports unified testing of various power electronic equipment, reduces test cost by 60%, shortens test cycle by 70%, and provides a complete technical solution for standardized testing of power electronic equipment.
[0091] Embodiment 4, the above is a schematic solution of a multifunctional power electronic device test method. It should be noted that the technical solution of the multifunctional power electronic device test system and the technical solution of the multifunctional power electronic device test method described above belong to the same concept. The technical solution of the multifunctional power electronic device test system in this embodiment is not described in detail. The details can be seen from the description of the technical solution of the multifunctional power electronic device test method.
[0092] The embodiment also provides another multifunctional power electronic device test system, which comprises: The acquisition module is configured to acquire system state parameters of the electronic device, perform system state modeling, obtain a system state vector, and generate a device compatibility matrix. The interface optimization module is configured to identify an interface type and a communication protocol of the device under test according to the interface state and the compatibility matrix, perform interface adaptation conversion, and optimize communication efficiency. The hardware allocation module is configured to allocate hardware resources and configure a reconfigurable hardware platform according to test parameters in the system state parameters and the interface adaptation result. The working condition simulation module is configured to simulate power grid working conditions and analyze power quality according to environmental simulation states in the system state parameters and the interface adaptation result. The simulation optimization module is configured to optimize a real-time simulation step length, control synchronization of hardware and simulation time, and evaluate fidelity of simulation output based on the simulated power grid working conditions and the hardware resources. The fusion optimization module is configured to fuse multi-sensor monitoring data, detect abnormal states, and optimize remote control responses. The twin model updating module is configured to combine digital twinning and hardware-in-the-loop real-time simulation, construct a virtual model of the device under test, optimize simulation step length and synchronization accuracy, and realize dynamic synchronization verification of the physical system and the virtual model. The adaptive optimization module is configured to perform device performance testing, perform device performance calculation, determine whether the device meets technical requirements, optimize test sequences in combination with an adaptive test strategy, and generate a test report by comprehensively analyzing all test data.
[0093] The embodiment also provides a computer device suitable for a multifunctional power electronic device test, which comprises a memory and a processor. The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions to implement the multifunctional power electronic device test method proposed in the above embodiment.
[0094] The embodiment also provides a storage medium having a computer program stored thereon. The program is executed by a processor to implement the multifunctional power electronic device test method proposed in the above embodiment.
[0095] The storage medium proposed in the embodiment belongs to the same inventive concept as the method for testing a multifunctional power electronic device proposed in the above embodiment. The technical details not described in the embodiment can be seen from the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.
[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by means of software and necessary universal hardware. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH, a hard disk, or an optical disc, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.
[0097] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and all of them should be covered in the scope of the claims of the present application.
Claims
1. A test method for multifunctional power electronic equipment, characterized in that, include: Obtain the system state parameters of the electronic device, perform system state modeling, obtain the system state vector, and generate the device compatibility matrix; Based on the interface status and compatibility matrix, identify the interface type and communication protocol of the device under test, perform interface adaptation conversion, and optimize communication efficiency. Based on the test parameters and interface adaptation results in the system status parameters, allocate hardware resources and configure a reconfigurable hardware platform. Based on the environmental simulation status and interface adaptation results in the system status parameters, simulate the power grid operating conditions and analyze the power quality. Based on simulated power grid operating conditions and hardware resources, the real-time simulation step size is optimized, the hardware is synchronized with the simulation time, and the fidelity of the simulation output is evaluated. By integrating monitoring data from multiple sensors, abnormal conditions can be detected and remote control responses can be optimized. By combining digital twins and hardware-in-the-loop real-time simulation, a virtual model of the device under test is constructed, and the simulation step size and synchronization accuracy are optimized for dynamic synchronization verification between the physical system and the virtual model. After the update, perform equipment performance tests, calculate equipment performance, determine whether the equipment meets the technical requirements, and optimize the test sequence in conjunction with an adaptive testing strategy. A comprehensive analysis of all test data is performed to generate a test report.
2. The multifunctional power electronic equipment testing method as described in claim 1, characterized in that, Based on the interface status and compatibility matrix, identify the interface type and communication protocol of the device under test, perform interface adaptation and conversion, and optimize communication efficiency, including: The interface adaptation and conversion is achieved by mapping the source interface parameters of the device under test to the target interface parameters; The optimization of communication efficiency is achieved by comparing the ratio of effective data volume to total data volume and the ratio of standard transmission time to actual transmission time, thereby comprehensively evaluating the data transmission quality and speed of the test device interface.
3. The multifunctional power electronic equipment testing method as described in claim 2, characterized in that, Based on the test parameters and interface adaptation results in the system status parameters, allocate hardware resources and configure a reconfigurable hardware platform, including: Hardware resource allocation is dynamically performed based on the demand of each test task, the total amount of resources, and the task priority. The allocation process is based on the proportion of the task demand to the total demand, and takes into account the deviation of the task priority from the average priority, and adjusts the allocation through an adjustment coefficient. Hardware refactoring time includes configuration analysis time, resource mapping time, configuration loading time, and verification time. The sum of these time periods is predicted and used to formulate a refactoring strategy. And by evaluating the system's flexibility, we can verify its adaptability to different devices.
4. The multifunctional power electronic equipment testing method as described in claim 3, characterized in that, The simulated power grid operating conditions and power quality analysis include: Based on the set reference power and the deviation between the reference frequency and the actual frequency, the output power is dynamically adjusted through a combination of proportional control and integral control to simulate load changes in the power grid. Based on the set reference reactive power and the deviation between the reference voltage and the actual voltage, the output reactive power is dynamically adjusted by combining proportional control and derivative control to simulate voltage fluctuations and reactive power compensation scenarios in the power grid. Based on the fundamental angular frequency, and combined with the amplitude and phase of each harmonic, a synthetic voltage waveform from the fundamental frequency to the specified highest harmonic order is generated to simulate harmonic interference and power quality problems in the power grid.
5. The multifunctional power electronic equipment testing method as described in claim 4, characterized in that, Based on simulated power grid operating conditions and hardware resources, the real-time simulation step size is optimized, hardware synchronization with simulation time is controlled, and the fidelity of the simulation output is evaluated, including: The optimized real-time simulation step size is achieved by balancing simulation error, computation time, and system stability. The control hardware is synchronized with the simulation time by minimizing the difference between the hardware time step and the simulation time step; The fidelity of the simulation output is evaluated by comparing the relative deviations of the actual outputs from multiple sensors.
6. The multifunctional power electronic equipment testing method as described in claim 5, characterized in that, By integrating monitoring data from multiple sensors, abnormal states can be detected and remote control responses optimized, including: The data from each sensor is fused by weighting and summing the data based on weights and reliability coefficients. The mean and standard deviation of normal state data are dynamically set, and a confidence coefficient is set to detect abnormal states. Response optimization is achieved by minimizing network transmission, processing, execution, and feedback times.
7. The multifunctional power electronic equipment testing method as described in claim 6, characterized in that, By combining digital twins and hardware-in-the-loop real-time simulation, a virtual model of the device under test is constructed, and the simulation step size and synchronization accuracy are optimized to achieve dynamic synchronous verification between the physical system and the virtual model, including: The accuracy of the test is calculated by comparing the ratio of the absolute difference between the measured value and the true value to the true value. The repeatability index is derived by calculating the ratio of the standard deviation to the measurement mean and converting it to a percentage. Based on the physical characteristics and operating parameters of the equipment under test, a digital twin model is constructed to simulate the dynamic behavior of the equipment under different operating conditions. By employing data-driven and physics-driven model update strategies, and dynamically adjusting the twin model with update weights, consistency with the physical system is ensured. The model accuracy is evaluated by comparing the deviation between the twin model output and the physical system output.
8. A multifunctional power electronic equipment testing system, using the method described in any one of claims 1-7, characterized in that, include: The acquisition module is used to acquire system state parameters of electronic devices, perform system state modeling, obtain system state vectors, and generate device compatibility matrices. The interface optimization module is used to identify the interface type and communication protocol of the device under test based on the interface status and compatibility matrix, perform interface adaptation conversion, and optimize communication efficiency. The hardware allocation module is used to allocate hardware resources and configure a reconfigurable hardware platform based on the test parameters and interface adaptation results in the system status parameters. The operating condition simulation module is used to simulate power grid operating conditions and analyze power quality based on the environmental simulation state and interface adaptation results in the system state parameters; The simulation optimization module is used to optimize the real-time simulation step size, control the synchronization of hardware and simulation time, and evaluate the fidelity of simulation output based on simulated power grid operating conditions and hardware resources. The fusion optimization module is used to fuse monitoring data from multiple sensors, detect abnormal states, and optimize remote control responses. The twin model update module is used to combine digital twins and hardware-in-the-loop real-time simulation to build a virtual model of the device under test, optimize the simulation step size and synchronization accuracy, and realize dynamic synchronous verification between the physical system and the virtual model. The adaptive optimization module is used to perform equipment performance tests after the update, calculate equipment performance, determine whether the equipment meets the technical requirements, and optimize the test sequence in conjunction with the adaptive testing strategy. A comprehensive analysis of all test data is performed to generate a test report.
9. A computer device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the multifunctional power electronic device testing method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions, which, when executed by a processor, implement the steps of the test method for a multifunctional power electronic device as described in any one of claims 1 to 7.