Intelligent frequency converter test system

Abstract

The invention relates to the technical field of power electronics, and particularly discloses an intelligent frequency converter test system which comprises an upper computer system, a motor control PLC, a load control PLC, a current detection module, a voltage detection module, a test fixture, a motor module, an accompanying test assembly and an energy recovery system. The motor module and the accompanying test assembly can be controlled, motor matching and load loading can be automatically completed, traditional manual operation is replaced, the test efficiency is improved, and the current detection module can detect current and improve the energy recovery efficiency through the Hall current sensor and the first system control chip.

Description

Technical Field

[0001] This invention relates to the field of power electronics technology, and more specifically, to an intelligent frequency converter testing system. Background Technology

[0002] With the increasing demands for industrial automation and energy conservation and emission reduction, frequency converters (VDCs), as a crucial component of motor control, play a vital role in the operation of various machines and equipment. Performance testing of VDCs is a key step in ensuring their quality and reliability. Existing VDC testing systems typically rely on manual motor matching and load application. This method is not only inefficient but also susceptible to external environmental interference, leading to poor reliability of test results. Furthermore, traditional VDC testing systems mostly employ manual or algorithmic loading methods. However, manual loading cannot meet the demands of rapid and efficient testing in mass production. While algorithmic loading can automate the testing process to some extent, its algorithms are complex, require additional detection modules, and have poor anti-interference capabilities and interpretability. Therefore, existing testing systems are significantly inadequate in handling mass production, energy recovery, and efficient control of VDCs. In particular, residual energy generated during testing is often consumed through braking resistors or not recovered at all, resulting in significant energy waste. Summary of the Invention

[0003] To overcome the aforementioned deficiencies in the prior art, this invention provides an intelligent frequency converter testing system. This system utilizes a motor control PLC and a load control PLC working collaboratively to control the motor module and test components, automatically completing motor matching and load loading. The first system control chip in the current detection module dynamically adjusts the energy feedback amplitude based on a particle swarm optimization algorithm, improving energy recovery efficiency, thereby solving the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] An intelligent frequency converter testing system includes a host computer system, a motor control PLC, a load control PLC, a current detection module, a voltage detection module, a test fixture, a motor module, a test support component, and an energy recovery system.

[0006] The first system control chip in the current detection module dynamically adjusts the energy feedback, enabling the inverter test system to feed energy back to the grid under various operating conditions. This formalizes the energy recovery process of the inverter test system, maximizing energy recovery efficiency, defined as the ratio of the inverter's output power to the total input power in the system. Bus voltage and bus current are input parameters of the first system control chip, and their product is the bus power. The first system control chip collects bus voltage and bus current in real time, calculates the bus power, and calculates the inverter's output power based on a feedback control model. This model represents the inverter's output power as a product of proportional gain and bus power, minus the difference in grid load, plus integral gain, and finally multiplied by the integral of this difference. This allows for the regulation of the output power. The proportional gain adjusts the inverter's output power by amplifying the difference between the bus power and grid load, while the integral gain adjusts the inverter's output power by accumulating the integral of the difference between the bus power and grid load.

[0007] As a further aspect of the present invention, based on the aforementioned feedback control model and using a particle swarm optimization algorithm combined with real-time feedback information, the output power of the inverter is adjusted to maximize energy recovery efficiency. The specific steps of the dynamic optimization algorithm are as follows:

[0008] Step S1: Initialize each particle in the particle swarm. Initialization includes position initialization, velocity initialization, and objective function initialization. Position initialization assigns a random initial position to each particle, representing its starting point in the solution space. The position is represented as a control parameter vector, consisting of two elements: the first element represents the inverter output power at the i-th position, and the second element represents the power factor angle at the i-th position, thus defining the particle's starting point in the solution space. Velocity initialization assigns an initial velocity to each particle, initialized to zero. Objective function initialization evaluates the particle's fitness by calculating the objective function value for each particle.

[0009] Step S2: In each iteration, the particle swarm optimization algorithm calculates the fitness of each particle and updates it as follows based on the fitness: If the fitness of particle i at the current position is greater than the individual best fitness of particle i, then the current position is taken as the individual best position; If the fitness of particle i at the current position is greater than the fitness function corresponding to the global best position, then the global best position is updated: the global best position is equal to the control parameter vector.

[0010] Step S3, the particle velocity update is specifically as follows: First, the particle retains a portion of its current velocity in this iteration, and the influence of this portion of the current velocity on the updated new velocity is controlled by inertia weight; Second, the particle references the difference between its current position and its best position found so far, and the particle swarm optimization algorithm uses the parameters of the first learning factor and the first random number to adjust the influence of individual difference information on the velocity update, the value of which is between 0 and 1; Finally, the particle references the difference between its current position and the global best position found so far by the entire particle swarm, and the particle swarm optimization algorithm uses the parameters of the second learning factor and the second random number to adjust the influence of global difference information on the velocity update, the value of which is also between 0 and 1; The introduction of the first and second random numbers helps the particle swarm optimization algorithm avoid getting trapped in local optima and failing to find the global optimum; In summary, the new velocity of the particle in the (t+1)th iteration is obtained by the combined and weighted combination of its current velocity, the directional component guided by its best position, and the directional component guided by the global best position;

[0011] Step S4, the particle position update is specifically: the new position of the particle after the next iteration is calculated as the sum of the particle's current position at the current iteration and the particle's velocity after the next iteration, thereby realizing the adjustment of the particle's position in the solution space;

[0012] Step S5: The global optimal fitness is the maximum value of the objective function, which is the energy recovery efficiency obtained by dividing the inverter's output power by the total input power in the system. The fitness difference is obtained by calculating the absolute value of the difference between the global optimal fitness in the t-th iteration and the global optimal fitness in the (t-1)-th iteration. If the fitness difference is less than the preset convergence threshold, the particle swarm optimization algorithm has converged and outputs the global optimal position, which is the optimal control parameter that maximizes the energy recovery efficiency.

[0013] As a further aspect of this invention, the host computer system is used for data processing and control tasks, including the following specific components: The host computer system includes an industrial control panel, a core processor, and testing software. The industrial control panel serves as the user interface for interacting with the system, providing intuitive operation and monitoring functions, and displaying real-time data during the testing process. The core processor is an x64 processor, serving as the data processing and control unit of the host computer system, used to receive data from the PLC and the inverter under test, and perform real-time data processing and logical operations. The testing software is used to execute a series of functional and performance verification programs for the inverter under test, comprehensively evaluating the performance of the inverter under test in actual operation.

[0014] As a further aspect of the present invention, the motor control PLC adjusts the working state of the motor module according to the instructions of the host computer system, including the following specific contents: one end of the motor control PLC is electrically connected to the host computer system to receive instructions from the host computer system, and the other end is connected to the motor module to achieve matching between the tested frequency converter and the motor by controlling the motor module.

[0015] As a further aspect of the present invention, the load control PLC is used to receive data transmitted by the current detection module, including the following specific details: one end of the load control PLC is electrically connected to the host computer system, and the other end is electrically connected to the test component. The load control PLC receives the data transmitted by the current detection module, processes it, returns the information to the host computer system, and issues control commands to the test component according to the instructions of the host computer system.

[0016] As a further aspect of the present invention, the current detection module is used to detect the current output by the frequency converter under test and transmit the current data to the load control PLC. Specifically, the input terminal of the current detection module is connected to the test fixture, and the output terminal is electrically connected to the load control PLC. The main components of the current detection module are a Hall current sensor and a first system control chip. The Hall current sensor is used to detect the current signal and convert it into a voltage signal; the first system control chip is a DSP, which performs calculations and processing on the acquired current signal.

[0017] As a further aspect of the present invention, a voltage detection module is used to detect the voltage output by the frequency converter and transmit its data to a host computer system. This includes the following specific details: the voltage detection module typically uses a digital multimeter to provide real-time voltage information to the host computer system. The input terminal of the voltage detection module is electrically connected to a test fixture, and the output terminal is electrically connected to the host computer system.

[0018] As a further aspect of the present invention, the test fixture is used to ensure the stability and safety of the equipment during testing, and includes the following specific components: The test fixture includes a support housing, a push-pull mechanism, a terminal block, and a support rod. The support housing provides stable support and protection, ensuring reliable fixation and positioning of the inverter under test during testing; the push-pull mechanism is used for loading and unloading the inverter under test; the terminal block provides electrical connections between the host computer system, current detection module, voltage detection module, motor module, power system, and the inverter under test; the support rod connects the support housing and the terminal block, as well as the terminal block and the push-pull mechanism.

[0019] As a further aspect of the present invention, the motor module includes multiple motors with different power ranges to simulate different load conditions, including the following specific details: The motor module includes nine groups of asynchronous motors with different power ranges. Each group of motors includes two motors of the same power; one is electrically connected to the test fixture, and the other is electrically connected to the output terminal of the test inverter. The two motors are coaxially connected to simulate the load through a mutual dragging method.

[0020] As a further aspect of the present invention, the test assembly includes test inverters of different power ranges, specifically: the test assembly includes four test inverters of different power ranges, with power ratings of 5.5kW, 15kW, 37kW, and 75kW respectively. The power of each test inverter is greater than the power of the motor connected to its output, to avoid overload caused by motor starting or load changes. The input terminal of each test inverter is electrically connected to the power system, and the output terminal is electrically connected to the motor module. The four test inverters are electrically connected to the energy recovery system via a common bus.

[0021] As a further aspect of this invention, the energy recovery system feeds back the surplus energy generated during the testing process to the power grid, comprising the following specific components: The energy recovery system includes a bus voltage detection module, a second system control chip, and an inverter module. The second system control chip sets a bus voltage threshold for energy recovery. The bus voltage detection module monitors the bus voltage of the test inverter in real time. When the bus voltage of the test inverter exceeds the set bus voltage threshold, the inverter module converts DC power into AC power, feeding energy back to the power grid. The main component of the bus voltage detection module is a voltage sensor, which can convert high-voltage signals into low-voltage signals to meet the requirements of the second system control chip. The second system control chip is a DSP, which can perform calculations and processing on the acquired voltage signals and control the switching on and off of the inverter module. The inverter module consists of nine IGBT modules, grouped in sets of three as one phase, with each phase's IGBT modules connected in parallel.

[0022] As a further embodiment of the present invention, the host computer system exchanges data with the motor control PLC and the load control PLC through an interface, sends control commands, and receives status feedback; the host computer system acquires real-time test data through the voltage detection module and the current detection module; the host computer system is electrically connected to the test fixture; the output terminal of the motor control PLC is connected to the motor module, and the PLC controls the start / stop, speed, and output power of the motor; the load control PLC is connected to the test component; the load control PLC is connected to the current detection module to receive the bus current signal; the input terminal of the current detection module is connected to the inverter under test, and the output terminal is connected to the load control PLC; the input terminal of the voltage detection module is electrically connected to the test fixture; the inverter under test is connected to the motor module, and the motor module is connected to the test component; the test component is connected to the energy recovery system, and the energy recovery system is connected to the power system.

[0023] A method for automatically matching motors using an intelligent frequency converter testing system includes the following specific steps:

[0024] Step Z1: Push the push-pull mechanism to lift the terminal block, fix the inverter under test to the support housing, and pull the push-pull mechanism to lower the terminal block, so that the inverter under test is electrically connected to the host computer system, the current detection module and the voltage detection module.

[0025] Step Z2: Close QF1 to complete the electrical connection between the host computer system, motor control PLC, load control PLC and power system.

[0026] Step Z3: Open the host computer system and start the test software, select the program corresponding to the inverter under test and run it.

[0027] Step Z4: The software controls the voltage detection module to test the inverter under test, mainly including the main circuit short circuit test and the diode voltage drop test.

[0028] Step Z5: After completing the voltage detection, the system will determine whether there is a fault. If there is no fault, the program will continue to execute. If there is a fault, the system will exit the program and report the fault type.

[0029] In step Z6, the host computer system controls QF2 to close, thus electrically connecting the tested frequency converter to the power system.

[0030] Step Z7: The software controls the host computer system to establish communication with the frequency converter under test.

[0031] Step Z8: If communication is successfully established, the program continues to run; if a fault is reported, the program exits and reports a communication failure.

[0032] Step Z9: The software controls the host computer system to read the DSP data of the tested frequency converter.

[0033] In step Z10, based on the rated power data returned by the DSP, the host computer system sends a command to the motor control PLC to control QF18 or QF20 or QF22 or QF24 or QF26 or QF28 or QF30 or QF32 or QF34 to close, so that the output of the tested frequency converter is electrically connected to the motor module.

[0034] In step Z11, the software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system.

[0035] In step Z12, the software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the output of the test inverter is electrically connected to the motor module.

[0036] In step Z13, the software controls QF8, QF9 or QF10, QF11 or QF12, QF13 or QF14, QF15 to close, and QF16, QF17 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system.

[0037] In step Z14, the software controls QF7 to close, making the energy recovery system output electrically connected to the power system.

[0038] A method for implementing intelligent loading in an intelligent frequency converter testing system includes the following specific steps:

[0039] Step Y1: The software controls the test inverter to start running, reaching the set output frequency of the test inverter, and then proceeds to the next step after 1 minute.

[0040] In step Y2, the software controls the test inverter to apply reverse torque to the motor connected to the output of the test inverter until the output current of the tested inverter reaches the rated current.

[0041] A method for energy recovery in an intelligent frequency converter testing system includes the following specific steps: a bus voltage detection module detects the bus voltage of the frequency converter under test, processes the detected voltage signal, and sends it to the energy recovery system DSP. When the detected voltage signal is higher than the preset value of the energy recovery system DSP, the energy recovery system DSP sends a drive signal to control the inverter module IGBT to turn on and feed energy back to the grid; when the detected voltage signal is lower than the preset value of the energy recovery system DSP, the energy recovery system DSP outputs no signal.

[0042] The technical effects and advantages of this intelligent inverter testing system are as follows: The industrial control screen, core processor, and testing software of the host computer system work together to achieve efficient data processing and control, providing users with intuitive operation and comprehensive monitoring functions, and improving the visualization and operability of the testing process. The motor control PLC and load control PLC work in tandem to control the motor module and test components, automatically completing motor matching and load loading, replacing traditional manual operation, improving testing efficiency, and avoiding the problem of poor reliability of test results caused by external environmental interference during manual operation. The current detection module, through a Hall current sensor and the first system control chip, not only detects current but also dynamically adjusts the energy feedback amplitude based on a particle swarm optimization algorithm, improving energy recovery efficiency and solving the problem of energy waste in traditional systems. The voltage detection module provides real-time voltage information, providing data support for testing. The support housing, push-pull mechanism, terminal block, and support rod of the test fixture ensure the stability and safety of the testing process. The motor module and test components are equipped with devices of different power ranges, which can simulate various load conditions to meet the testing needs of different inverters. The energy recovery system will test the remaining energy and feed it back into the grid, further improving energy efficiency. Attached Figure Description

[0043] Figure 1 This is a structural diagram of an intelligent frequency converter testing system according to the present invention.

[0044] Figure 2 This is a wiring diagram of an intelligent frequency converter testing system according to the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below 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.

[0046] Example 1

[0047] See Figure 1 The structural diagram shown illustrates an intelligent frequency converter testing system provided in this embodiment of the invention. The system includes a host computer system, a motor control PLC, a load control PLC, a current detection module, a voltage detection module, a test fixture, a motor module, a test support component, and an energy recovery system.

[0048] Furthermore, the host computer system includes an industrial control panel, a core processor, and testing software. The industrial control panel serves as the user interface, providing intuitive operation and monitoring functions and displaying real-time data during the testing process. The core processor, an x64 processor, acts as the data processing and control unit of the host computer system, receiving data from the PLC and the inverter under test, and performing real-time data processing and logical operations. The testing software executes a series of functional and performance verification programs for the inverter under test, comprehensively evaluating its performance in actual operation.

[0049] Furthermore, one end of the motor control PLC is electrically connected to the host computer system to receive instructions from the host computer system, and the other end is connected to the motor module to achieve matching between the tested frequency converter and the motor by controlling the motor module.

[0050] Furthermore, one end of the load control PLC is electrically connected to the host computer system, and the other end is electrically connected to the test component. The load control PLC receives data transmitted by the current detection module, processes it, and returns the information to the host computer system. Based on the instructions from the host computer system, it issues control commands to the test component.

[0051] Furthermore, the input terminal of the current detection module is connected to the test fixture, and the output terminal is electrically connected to the load control PLC. The main components of the current detection module are a Hall current sensor and a first system control chip. The Hall current sensor is used to detect the current signal and convert it into a voltage signal; the first system control chip is a DSP, which performs calculations and processing on the acquired current signal.

[0052] The first system control chip dynamically adjusts the energy feedback, enabling the inverter test system to achieve optimal energy return to the grid under various operating conditions. This formalizes the energy recovery process of the inverter test system, maximizing energy recovery efficiency, which is defined as the ratio of the inverter's output power to the total input power in the system. Bus voltage and bus current are input parameters of the first system control chip, and their product is the bus power.

[0053] The first control chip collects the bus voltage and bus current in real time, calculates the bus power, and calculates the inverter's output power according to the feedback control model. The feedback control model expresses the inverter's output power as the product of the proportional gain and the bus power, minus the difference between the grid load and the proportional gain, plus the integral gain, and finally multiplies it by the integral of the difference, thereby achieving the regulation of the output power. The proportional gain adjusts the inverter's output power by amplifying the difference between the bus power and the grid load, and the integral gain adjusts the inverter's output power by accumulating the integral of the difference between the bus power and the grid load.

[0054] Based on the particle swarm optimization algorithm and combined with real-time feedback information, the output power of the inverter is adjusted to maximize energy recovery efficiency. The specific steps of the dynamic optimization algorithm are as follows:

[0055] Step S1: Initialize each particle in the particle swarm. Initialization includes position initialization, velocity initialization, and objective function initialization. Position initialization assigns a random initial position to each particle, representing its starting point in the solution space. The position is represented as a control parameter vector, consisting of two elements: the first element represents the inverter output power at the i-th position, and the second element represents the power factor angle at the i-th position, thus defining the particle's starting point in the solution space. Velocity initialization assigns an initial velocity to each particle, initialized to zero. Objective function initialization evaluates the particle's fitness by calculating the objective function value for each particle.

[0056] Step S2: In each iteration, the particle swarm optimization algorithm calculates the fitness of each particle and updates it as follows based on the fitness: If the fitness of particle i at the current position is greater than the individual best fitness of particle i, then the current position is taken as the individual best position; if the fitness of particle i at the current position is greater than the fitness function corresponding to the global best position, then the global best position is updated: the global best position is equal to the control parameter vector.

[0057] Step S3, the particle velocity update is specifically as follows: First, the particle retains a portion of its current velocity in this iteration, and the influence of this portion of the current velocity on the updated new velocity is controlled by inertia weight; Second, the particle references the difference between its current position and its best position found so far, and the particle swarm optimization algorithm uses the parameters of the first learning factor and the first random number to adjust the influence of individual difference information on the velocity update, the value of which is between 0 and 1; Finally, the particle references the difference between its current position and the global best position found so far by the entire particle swarm, and the particle swarm optimization algorithm uses the parameters of the second learning factor and the second random number to adjust the influence of global difference information on the velocity update, the value of which is also between 0 and 1; The introduction of the first and second random numbers helps the particle swarm optimization algorithm avoid getting trapped in local optima and failing to find the global optimum; In summary, the new velocity of the particle in the (t+1)th iteration is obtained by the weighted combination of its current velocity, the directional component guided by its best position, and the directional component guided by the global best position.

[0058] Step S4, the particle position update is specifically: the new position of the particle after the next iteration is calculated as the sum of the particle's current position in the current iteration and the particle's velocity after the next iteration, thereby realizing the adjustment of the particle's position in the solution space.

[0059] Step S5: The global optimal fitness is the maximum value of the objective function, which is the energy recovery efficiency obtained by dividing the inverter's output power by the total input power in the system. The fitness difference is obtained by calculating the absolute value of the difference between the global optimal fitness in the t-th iteration and the global optimal fitness in the (t-1)-th iteration. If the fitness difference is less than the preset convergence threshold, the particle swarm optimization algorithm has converged and outputs the global optimal position, which is the optimal control parameter that maximizes the energy recovery efficiency.

[0060] Furthermore, the voltage detection module typically employs a digital multimeter to provide real-time voltage information to the host computer system. The input terminal of the voltage detection module is electrically connected to the test fixture, and the output terminal is electrically connected to the host computer system.

[0061] Furthermore, the test fixture includes a support housing, a push-pull mechanism, a terminal block, and a support rod. The support housing provides stable support and protection, ensuring reliable fixation and positioning of the inverter under test during testing. The push-pull mechanism is used for loading and unloading the inverter under test. The terminal block provides electrical connections between the host computer system, current detection module, voltage detection module, motor module, power system, and the inverter under test. The support rod connects the support housing and the terminal block, as well as the terminal block and the push-pull mechanism.

[0062] Furthermore, the motor module includes nine sets of asynchronous motors with different power ranges. Each set of motors includes two motors of the same power; one is electrically connected to the test fixture, and the other is electrically connected to the output of the test inverter. The two motors are coaxially connected to simulate a load through a drag-to-load method.

[0063] Furthermore, the test setup includes four test inverters with different power ratings: 5.5kW, 15kW, 37kW, and 75kW. The power of each test inverter is greater than the power of the motor it powers, to avoid overload caused by motor startup or load changes. The input of each test inverter is electrically connected to the power system, and its output is electrically connected to the motor module. All four test inverters are electrically connected to the energy recovery system via a common busbar.

[0064] Furthermore, the energy recovery system includes a bus voltage detection module, a second system control chip, and an inverter module. The second system control chip sets the bus voltage threshold for energy recovery. The bus voltage detection module monitors the bus voltage of the test inverter in real time. When the bus voltage of the test inverter exceeds the set bus voltage threshold, the inverter module converts DC power into AC power to feed energy back to the grid. The main component of the bus voltage detection module is a voltage sensor, which can convert high-voltage signals into low-voltage signals to meet the requirements of the second system control chip. The second system control chip is a DSP, which can perform calculations and processing on the acquired voltage signals and control the switching on and off of the inverter module. The inverter module consists of nine IGBT modules, grouped in sets of three as one phase, with each phase's IGBT modules connected in parallel.

[0065] Furthermore, the host computer system exchanges data with the motor control PLC and the load control PLC through interfaces, sends control commands, and receives status feedback; the host computer system acquires real-time test data through voltage detection modules and current detection modules; the host computer system is electrically connected to the test fixture; the output terminal of the motor control PLC is connected to the motor module, and the PLC controls the motor's start / stop, speed, and output power; the load control PLC is connected to the test component; the load control PLC is connected to the current detection module to receive the bus current signal; the input terminal of the current detection module is connected to the inverter under test, and the output terminal is connected to the load control PLC; the input terminal of the voltage detection module is electrically connected to the test fixture; the inverter under test is connected to the motor module, and the motor module is connected to the test component; the test component is connected to the energy recovery system, and the energy recovery system is connected to the power system.

[0066] Example 2

[0067] See Figure 2 The wiring diagram shown illustrates a method for automatically matching motors in an intelligent frequency converter testing system, comprising the following specific steps:

[0068] Step Z1: Push the push-pull mechanism to lift the terminal block, fix the inverter under test to the support housing, and pull the push-pull mechanism to lower the terminal block, so that the inverter under test is electrically connected to the host computer system, the current detection module and the voltage detection module.

[0069] Step Z2: Close QF1 to complete the electrical connection between the host computer system, motor control PLC, load control PLC and power system.

[0070] Step Z3: Open the host computer system and start the test software, select the program corresponding to the inverter under test and run it.

[0071] Step Z4: The software controls the voltage detection module to test the inverter under test, mainly including the main circuit short circuit test and the diode voltage drop test.

[0072] Step Z5: After completing the voltage detection, the system will determine whether there is a fault. If there is no fault, the program will continue to execute. If there is a fault, the system will exit the program and report the fault type.

[0073] In step Z6, the host computer system controls QF2 to close, thus electrically connecting the tested frequency converter to the power system.

[0074] Step Z7: The software controls the host computer system to establish communication with the frequency converter under test. The communication method can be selected according to actual needs, such as RS-485 communication, CAN communication, Modbus TCP communication, etc.

[0075] Step Z8: If communication is successfully established, the program continues to run; if a fault is reported, the program exits and reports a communication failure.

[0076] Step Z9: The software controls the host computer system to read the DSP data of the tested frequency converter.

[0077] In step Z10, based on the rated power data returned by the DSP, the host computer system sends a command to the motor control PLC to control QF18 or QF20 or QF22 or QF24 or QF26 or QF28 or QF30 or QF32 or QF34 to close, so that the output of the tested frequency converter is electrically connected to the motor module.

[0078] In step Z11, the software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system.

[0079] In step Z12, the software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the output of the test inverter is electrically connected to the motor module.

[0080] In step Z13, the software controls QF8, QF9 or QF10, QF11 or QF12, QF13 or QF14, QF15 to close, and QF16, QF17 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system.

[0081] In step Z14, the software controls QF7 to close, making the energy recovery system output electrically connected to the power system.

[0082] In this embodiment, taking a 1.5kW frequency converter under test as an example, the host computer system sends a command to the motor control PLC to control QF18 to close, and the output of the frequency converter under test is electrically connected to the 1.5kW motor; according to the motor matched with the frequency converter under test, the software controls QF3 to close, and the input of the 5.5kW auxiliary frequency converter is electrically connected to the power system; the software controls QF19 to close, and the output of the auxiliary frequency converter is electrically connected to the 1.5kW motor; the software controls QF8, QF9, QF16, and QF17 to close, and the bus of the auxiliary frequency converter is electrically connected to the energy recovery system; the software controls QF7 to close, and the output of the energy recovery system is electrically connected to the power system.

[0083] Example 3

[0084] See Figure 2 The wiring diagram shown illustrates a method for intelligent loading in an intelligent frequency converter testing system, comprising the following specific steps:

[0085] Step Y1: The software controls the test inverter to start running, reaching the set output frequency of the test inverter, and then proceeds to the next step after 1 minute.

[0086] In step Y2, the software controls the test inverter to apply reverse torque to the motor connected to the output of the test inverter until the output current of the tested inverter reaches the rated current.

[0087] In this embodiment, step Y2 is specifically implemented in the following way: the current detection module sends the output current of the inverter under test to the load control PLC. The load control PLC processes the current data and sends it to the host computer system. The host computer system compares the detected current with the rated current of the inverter. If the detected current is less than the rated current of the inverter under test, the host computer system sends a command to the load control PLC to apply a reverse torque to the inverter under test. The magnitude of the reverse torque applied to the inverter under test should be set as follows: the output current of the inverter under test increases by 3% of its rated current each time.

[0088] Example 3

[0089] This invention provides a method for energy recovery in an intelligent frequency converter testing system, comprising the following specific steps: a bus voltage detection module detects the bus voltage of the frequency converter under test, processes the detected voltage signal, and sends it to the energy recovery system DSP. When the detected voltage signal is higher than a preset value of the energy recovery system DSP, the energy recovery system DSP sends a drive signal to control the inverter module IGBT to turn on and feed energy back to the grid; when the detected voltage signal is lower than the preset value of the energy recovery system DSP, the energy recovery system DSP outputs no signal.

[0090] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0091] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent frequency converter testing system, characterized in that, It includes a host computer system, a motor control PLC, a load control PLC, a current detection module, a voltage detection module, a test fixture, a motor module, a test support component, and an energy recovery system; The first system control chip in the current detection module dynamically adjusts the energy feedback, enabling the inverter test system to feed energy back to the grid. This formalizes the energy recovery process of the inverter test system, maximizing the energy recovery efficiency, defined as the ratio of the inverter's output power to the total input power in the system. Bus voltage and bus current are input parameters of the first system control chip, and their product is the bus power. The first system control chip collects bus voltage and bus current in real time, calculates the bus power, and calculates the inverter's output power based on a feedback control model. This model represents the inverter's output power as a product of proportional gain and bus power, minus the difference in grid load, plus integral gain, and finally multiplied by the integral of this difference. This allows for the regulation of the output power. The proportional gain adjusts the inverter's output power by amplifying the difference between the bus power and grid load, while the integral gain adjusts the inverter's output power by accumulating the integral of the difference between the bus power and grid load.

2. The intelligent frequency converter testing system according to claim 1, characterized in that... Based on the aforementioned feedback control model, and using the particle swarm optimization algorithm combined with real-time feedback information, the inverter's output power is adjusted to maximize energy recovery efficiency. The specific steps of the dynamic optimization algorithm are as follows: Step S1: Real-time collected bus voltage and bus current data are used as input to initialize each particle in the particle swarm. Initialization includes position initialization, velocity initialization, and objective function initialization. Position initialization assigns a random initial position to each particle, representing its starting point in the solution space. The position is represented as a control parameter vector, consisting of two elements: the first element represents the inverter output power at the i-th position, and the second element represents the power factor angle at the i-th position, thus defining the particle's starting point in the solution space. Velocity initialization assigns an initial velocity to each particle, initialized to zero. Objective function initialization evaluates the particle's fitness by calculating the objective function value for each particle. Step S2: In each iteration, the particle swarm optimization algorithm calculates the fitness of each particle and updates it as follows based on the fitness: If the fitness of particle i at the current position is greater than the individual best fitness of particle i, then the current position is taken as the individual best position; If the fitness of particle i at the current position is greater than the fitness function corresponding to the global best position, then the global best position is updated: the global best position is equal to the control parameter vector. Step S3, the particle velocity update is specifically as follows: First, the particle retains a portion of its current velocity in this iteration, and the influence of the portion of the current velocity on the updated new velocity is controlled by the inertial weight; Secondly, the particle references the difference between its current position and its best position found so far. The particle swarm optimization algorithm uses a first learning factor parameter and a first random number to adjust the influence of individual differences on velocity updates. The value of the random number is between 0 and 1. Finally, the particle references the difference between its current position and the global best position found so far by the entire particle swarm. The particle swarm optimization algorithm uses a second learning factor parameter and a second random number to adjust the influence of global differences on velocity updates. The value of the second random number is also between 0 and 1. Introducing the first and second random numbers helps the particle swarm optimization algorithm avoid getting trapped in local optima and failing to find the global optimum. In summary, the particle's new velocity at the (t+1)th iteration is obtained by a weighted combination of its current velocity, the directional component guided by its best individual position, and the directional component guided by the global best position. Step S4, the particle position update is specifically: the new position of the particle after the next iteration is calculated as the sum of the particle's current position at the current iteration and the particle's velocity after the next iteration, thereby realizing the adjustment of the particle's position in the solution space; Step S5: The global optimal fitness is the maximum value of the objective function, which is the energy recovery efficiency obtained by dividing the inverter's output power by the total input power in the system. The fitness difference is obtained by calculating the absolute value of the difference between the global optimal fitness in the t-th iteration and the global optimal fitness in the (t-1)-th iteration. If the fitness difference is less than the preset convergence threshold, the particle swarm optimization algorithm has converged and outputs the global optimal position, which is the optimal control parameter that maximizes the energy recovery efficiency.

3. The intelligent frequency converter testing system according to claim 1, characterized in that... The host computer system includes an industrial control screen, a core processor, and testing software. The industrial control screen serves as the user interface for interacting with the system, displaying real-time test data. The core processor is an x64 processor used to receive and process data and perform logical operations. The testing software is used to execute the function and performance verification program of the inverter under test. The motor control PLC is electrically connected to the host computer system at one end to receive instructions from the host computer system, and connected to the motor module at the other end to control the motor module to achieve matching between the inverter under test and the motor.

4. The intelligent frequency converter testing system according to claim 1, characterized in that, The load control PLC is electrically connected to the host computer system at one end and to the test component at the other end. It receives data transmitted by the current detection module, processes it, and returns it to the host computer system. It also issues control commands to the test component according to the instructions of the host computer system. The input end of the current detection module is electrically connected to the test fixture, and the output end is electrically connected to the load control PLC. Its main components are a Hall current sensor and a first system control chip. The Hall current sensor detects the current signal and converts it into a voltage signal. The first system control chip is a DSP used to perform calculations and processing on the acquired current signal.

5. The intelligent frequency converter testing system according to claim 1, characterized in that, The voltage detection module's input terminal is electrically connected to the test fixture, and its output terminal is electrically connected to the host computer system. A digital multimeter is used to detect the inverter's output voltage and transmit the data to the host computer system. The test fixture includes a support housing, a push-pull mechanism, a terminal block, and a support rod. The support housing is used to fix and position the inverter under test, the push-pull mechanism is used to load and unload the inverter under test, the terminal block is used to provide electrical connections between the components, and the support rod is used to connect the support housing, the terminal block, and the push-pull mechanism.

6. The intelligent frequency converter testing system according to claim 1, characterized in that, The motor module includes nine asynchronous motors with different power ranges. Each motor group includes two motors of the same power, which are coaxially connected to simulate a load in a counter-drive manner. One motor is electrically connected to the test fixture, and the other is electrically connected to the output of the test inverter. The test component includes four test inverters with different power ranges, namely 5.5kW, 15kW, 37kW, and 75kW. The power of each test inverter is greater than the power of the motor it drives. Its input is electrically connected to the power system, and its output is electrically connected to the motor module. All four test inverters are electrically connected to the energy recovery system via a common bus.

7. The intelligent frequency converter testing system according to claim 1, characterized in that, The energy recovery system includes a bus voltage detection module, a second system control chip, and an inverter module. The second system control chip sets the bus voltage threshold for energy recovery. The bus voltage detection module monitors the bus voltage of the test inverter in real time. When the bus voltage is higher than the threshold, the inverter module converts DC power into AC power to feed energy back to the grid. The main component of the bus detection module is a voltage sensor, and the second system control chip is a DSP. The inverter module consists of nine IGBT modules, arranged in groups of three as one phase, with each phase's IGBT modules connected in parallel.

8. A method for automatically matching motors using an intelligent frequency converter testing system, characterized in that, The intelligent frequency converter testing system according to any one of claims 1-7 includes the following steps: Step Z1: Push the push-pull mechanism to lift the terminal block, fix the inverter under test to the support housing, and pull the push-pull mechanism to lower the terminal block, so that the inverter under test is electrically connected to the host computer system, the current detection module and the voltage detection module. Step Z2: Close QF1 to complete the electrical connection between the host computer system, motor control PLC, load control PLC and power system; Step Z3: Open the host computer system and start the test software, select the program corresponding to the inverter under test and run it; Step Z4: The software controls the voltage detection module to test the inverter under test, including main circuit short circuit test and diode voltage drop test; Step Z5: After completing the voltage detection, if there is no fault, the program continues to execute; if a fault exists, the system will exit the program and report the fault type. Step Z6: The host computer system controls QF2 to close, so that the frequency converter under test is electrically connected to the power system. Step Z7: The software controls the host computer system to establish communication with the tested frequency converter; Step Z8: If communication is successfully established, the program continues to run; if a fault is reported, the program exits and reports a communication failure. Step Z9: The software controls the host computer system to read the DSP data of the tested frequency converter; Step Z10: Based on the rated power data returned by the DSP, the host computer system sends a command to the motor control PLC to control QF18 or QF20 or QF22 or QF24 or QF26 or QF28 or QF30 or QF32 or QF34 to close, so that the output of the tested frequency converter is electrically connected to the motor module. Step Z11: The software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system. Step Z12: The software controls QF19 or QF21 or QF23 or QF25 or QF27 or QF29 or QF31 or QF33 or QF35 to close, so that the output of the test frequency converter is electrically connected to the motor module. Step Z13: The software controls QF8, QF9 or QF10, QF11 or QF12, QF13 or QF14, QF15 to close, and QF16, QF17 to close, so that the bus of the test frequency converter is electrically connected to the energy recovery system. In step Z14, the software controls QF7 to close, making the energy recovery system output electrically connected to the power system.

9. A method for implementing intelligent loading in an intelligent frequency converter testing system, characterized in that, The intelligent frequency converter testing system according to any one of claims 1-7 includes the following steps: Step Y1: The software controls the test inverter to start running, reaching the set output frequency of the test inverter, and then proceeds to the next step after 1 minute. In step Y2, the software controls the test inverter to apply reverse torque to the motor connected to the output of the test inverter until the output current of the tested inverter reaches the rated current.

10. A method for energy recovery in an intelligent frequency converter testing system, characterized in that, The intelligent inverter testing system according to any one of claims 1-7 includes the following specific components: a bus voltage detection module detects the bus voltage of the inverter under test, processes the detected voltage signal, and sends it to the energy recovery system DSP; when the detected voltage signal is higher than the preset value of the energy recovery system DSP, the energy recovery system DSP sends a drive signal to control the inverter module IGBT to turn on and feed energy back to the grid; when the detected voltage signal is lower than the preset value of the energy recovery system DSP, the energy recovery system DSP has no signal output.

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