High-speed small propeller propulsion power integration test system and method

Abstract

The invention discloses a high-speed small propeller propulsion power integration test system and method, and relates to the technical field of propeller test. The system comprises a test main body, a multi-physics-field parameter acquisition module, a collaborative correction module and a dynamic compensation execution module, the test main body provides test basic support, and the multi-physics-field parameter acquisition module acquires propeller aeroelastic deformation, motor thermal field and wind field turbulence parameters; the collaborative correction module fuses the collected parameters and calculates a correction coefficient, and the dynamic compensation execution module adjusts electric speed controller output and motor driving parameters in the test process according to the correction coefficient; the problem that an existing system cannot process multi-factor cooperative interference is solved, the consistency of test data and actual working conditions is achieved, the test precision and reliability of a power system are improved, and the system is suitable for research and development verification and performance evaluation of a high-speed small propeller.

Description

Technical Field

[0001] This invention relates to the field of propeller performance testing technology, specifically to a high-speed small propeller propulsion power integrated testing system and method. Background Technology

[0002] As a core power component of lightweight drones, the high-speed, small propeller directly determines the drone's response speed, endurance, and flight stability. Currently, testing systems for such propellers often focus on acquiring single mechanical or electrical parameters, neglecting the combined interference of multiple physical factors in actual operating scenarios. Under high-speed rotation, propeller blades undergo elastic deformation due to aerodynamic loads. This deformation alters the aerodynamic shape of the blades, causing deviations between actual thrust and theoretical calculations. Simultaneously, prolonged high-load operation of the motor generates significant heat. Increased motor temperature leads to increased winding resistance and decreased output torque, creating a thermal coupling effect that further impacts the power system's output performance. Furthermore, the turbulent winds encountered during drone flight cause unstable propeller velocity, exacerbating blade stress fluctuations and reducing the repeatability and accuracy of test data.

[0003] Existing testing systems lack effective correction mechanisms for the combined interference of aeroelastic deformation, motor thermal coupling, and wind turbulence. They rely solely on single-parameter test data under static conditions to guide power system optimization, leading to a disconnect between test data and actual operating conditions. For example, in rapid acceleration tests of racing drones, the thrust data collected by existing systems does not consider the combined effects of blade deformation and motor temperature rise, failing to accurately reflect the power output characteristics of the drone during actual flight. In wind field testing scenarios, existing systems can only provide a uniform inflow environment and cannot simulate turbulent interference, resulting in test data that cannot support power system matching design under complex aerodynamic environments. This testing method not only increases the trial-and-error costs of power system development but may also lead to drone flight loss of control or component damage due to test data deviations, severely restricting the technological iteration efficiency of high-speed small propeller drones and related drone models.

[0004] Based on the above problems, there is an urgent need for a high-speed small propeller propulsion power integration test system that can simultaneously process multi-physics field cooperative interference and achieve dynamic compensation, so as to improve the authenticity and reliability of test data and meet the high-precision requirements of power system research and development. Summary of the Invention

[0005] The purpose of this invention is to provide a high-speed, small-sized propeller propulsion power integration test system, comprising a test body, which consists of a power support, a system control box, a safety isolation net, and a test toolbox. The power support is used to install the power system under test. The system control box houses an adjustable power supply, a circuit board, and a computer. The safety isolation net provides protection. The test toolbox stores tools. The system also includes a multi-physics parameter acquisition module, a collaborative correction module, and a dynamic compensation execution module. The multi-physics parameter acquisition module is electrically connected to the collaborative correction module to transmit the acquired parameter signals. The collaborative correction module is electrically connected to the dynamic compensation execution module to transmit the calculated correction signals. The dynamic compensation execution module is electrically connected to the power system under test to output compensation control signals. The multi-physics parameter acquisition module is used to acquire propeller aeroelastic deformation parameters, motor thermal field parameters, and wind turbulence parameters. The collaborative correction module is used to fuse the acquired parameters and calculate dynamic correction coefficients. The dynamic compensation execution module is used to adjust the PWM throttle signal to the electronic speed controller (ESC) according to the correction coefficients, thereby regulating the ESC output voltage and frequency.

[0006] Preferably, according to the above-mentioned high-speed small propeller propulsion power integrated test system, the multi-physics parameter acquisition module includes an aeroelastic sensor, a motor thermal field sensor, and a wind field turbulence sensor; the aeroelastic sensor is installed at the root and middle of the propeller blade under test to collect the blade strain value and deformation displacement; the motor thermal field sensor is installed near the casing and stator winding of the motor under test to collect the motor surface temperature and winding temperature; the wind field turbulence sensor is installed inside the wind wall at the front of the system's main control box to collect the turbulence intensity and turbulence frequency of the wind field; the aeroelastic sensor, the motor thermal field sensor, and the wind field turbulence sensor are all electrically connected to the collaborative correction module through shielded cables to achieve anti-interference transmission of parameter signals.

[0007] Preferably, according to the above-mentioned high-speed small propeller propulsion power integration test system, the collaborative correction module includes a data fusion unit and a correction logic unit; the data fusion unit is used to receive the parameter signals transmitted by the multi-physics parameter acquisition module, and to perform spatiotemporal alignment and redundancy verification of multi-source parameters through a data fusion algorithm, and output a unified parameter set after fusion; the correction logic unit has a built-in preset correction calculation model, which is used to call the parameters in the unified parameter set to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient and the wind field turbulence correction coefficient, and integrate the three types of correction coefficients into a total dynamic correction signal; the data fusion unit and the correction logic unit are electrically connected through an internal data bus to realize the real-time transmission of the parameter set.

[0008] Preferably, according to the above-mentioned high-speed small propeller propulsion power integrated test system, the dynamic compensation execution module includes an electronic speed controller (ESC) compensation circuit and a motor drive adjustment unit; the ESC compensation circuit is used to receive the total dynamic correction signal transmitted by the collaborative correction module, and convert the total dynamic correction signal into an ESC voltage compensation amount to adjust the voltage value output by the adjustable power supply to the ESC; the motor drive adjustment unit is used to generate a PWM duty cycle adjustment amount according to the total dynamic correction signal, and change the duty cycle of the PWM drive signal output to the motor under test in real time; the ESC compensation circuit and the motor drive adjustment unit are connected through a control signal line to realize the synchronous execution of the compensation action.

[0009] Preferably, according to the above-mentioned high-speed small propeller propulsion power integration test system, the formula for calculating the aeroelastic correction coefficient by the correction logic unit is:

[0010] ;

[0011] In the formula, This is the aeroelastic correction factor, dimensionless. The maximum strain value of the blade, dimensional , The real-time rotational speed of the propeller is expressed in rad / s. The turbulence intensity of the wind field is expressed in m / s. The elastic modulus of the blade material, in units of GPa. The maximum allowable deformation of the blade is expressed in mm.

[0012] Preferably, according to the above-mentioned high-speed small propeller propulsion power integration test system, the formula for calculating the motor thermal coupling correction coefficient by the correction logic unit is as follows:

[0013] ;

[0014] In the formula, This is the thermal coupling correction factor for the motor, dimensionless. The ambient temperature was measured in degrees Celsius (°C). The rated operating temperature of the motor, in degrees Celsius (°C). The real-time temperature of the motor casing, in degrees Celsius (°C). This represents the real-time temperature of the motor stator winding, in degrees Celsius (°C).

[0015] Preferably, according to the above-mentioned high-speed small propeller propulsion power integration test system, the formula for the correction logic unit to integrate the total dynamic correction signal is:

[0016] ;

[0017] In the formula, The total dynamic compensation is measured in units that match the test parameters, such as thrust in N and torque in N·m. Basic test parameter values, dimensions and Consistent, The turbulence frequency of the wind field is expressed in Hz. The maximum design turbulence frequency of the wind field is expressed in Hz.

[0018] Preferably, according to the above-mentioned high-speed small propeller propulsion power integrated test system, the aeroelastic sensor is a fiber optic grating sensor, which is attached to the blade surface with epoxy resin. The center wavelength of the fiber optic grating sensor changes with the blade strain. The aeroelastic sensor converts the wavelength change into a strain value through a fiber optic demodulator, and then obtains the blade deformation displacement through a displacement conversion model. The motor thermal field sensor is a combination of an infrared temperature sensor and a platinum resistance temperature sensor. The infrared temperature sensor is used for non-contact acquisition of the motor casing temperature, and the platinum resistance temperature sensor is pre-embedded in the gap of the motor stator winding for contact acquisition of the winding temperature.

[0019] Preferably, according to the above-mentioned high-speed small propeller propulsion power integrated test system, the data fusion unit uses a federated Kalman filter algorithm for data fusion. The federated Kalman filter algorithm includes sub-filters and a main filter. The sub-filters perform local filtering processing on the parameter signals of the aeroelastic sensor, the motor thermal field sensor, and the wind field turbulence sensor, respectively, and output local optimal estimates. The main filter receives the local optimal estimates of each sub-filter, allocates the information weight of each sub-filter through information allocation coefficients, and then performs global optimal fusion calculation to output the unified parameter set. The information allocation coefficients are dynamically adjusted according to the sampling accuracy of each sensor. The higher the sampling accuracy, the greater the information weight.

[0020] Preferably, a high-speed small propeller propulsion power integration test method, applied to the high-speed small propeller propulsion power integration test system described in any one of the above, includes the following steps: First, the system is powered on and initialized. The adjustable voltage power supply of the test body is started and outputs an initial voltage. The computer starts the host computer software. The multi-physics parameter acquisition module completes sensor zeroing and benchmark calibration. The collaborative correction module loads a preset correction calculation model and data fusion algorithm. The dynamic compensation execution module is in a ready-to-trigger state. Second, the power system under test is installed to the power support, the safety isolation net is fixed, and the basic threshold values ​​of the test parameters are set through the host computer software, including basic speed, basic load current, and basic wind speed. Third, the wind wall is activated. The multi-physics parameter acquisition module collects blade strain values, motor temperature values, and wind speed according to a preset sampling period. The turbulence parameters are collected and transmitted to the collaborative correction module. In the fourth step, the data fusion unit of the collaborative correction module performs spatiotemporal alignment and redundancy verification on the parameter signals, outputting a unified parameter set to the correction logic unit. The correction logic unit then uses formulas to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient, and the total dynamic compensation. In the fifth step, the dynamic compensation execution module receives the total dynamic compensation, the electronically controlled compensation circuit adjusts the output voltage of the adjustable power supply, and the motor drive adjustment unit adjusts the duty cycle of the PWM drive signal to achieve dynamic compensation of the test parameters. In the sixth step, the host computer software collects the compensated test data in real time and compares it with the basic threshold. If the data deviation exceeds the allowable range, steps three through five are repeated until the test data stabilizes. If the test is complete, the windbreak and the tested power system are shut down, the test data is saved, and a test report is generated.

[0021] Compared with the prior art, the present invention has the following advantages:

[0022] The inventive aspect of this invention lies in constructing an integrated testing architecture encompassing multi-physics parameter acquisition, collaborative correction, and dynamic compensation. The multi-physics parameter acquisition module simultaneously acquires aeroelastic, motor thermal, and wind turbulence parameters. The collaborative correction module achieves multi-source data fusion and multi-coefficient linkage calculation. The dynamic compensation execution module adjusts the ESC and motor drive parameters in real time. This architecture solves the problem of test data deviation caused by multi-factor collaborative interference in the prior art, achieving consistency between test data and actual operating conditions, improving the accuracy and reliability of high-speed small propeller propulsion power testing, and providing accurate data support for power system optimization. Attached Figure Description

[0023] Figure 1 This is a connection block diagram of a high-speed small propeller propulsion power integration test system according to the present invention;

[0024] Figure 2This is a flowchart of a high-speed small propeller propulsion power integration test method according to the present invention. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0026] Traditional high-speed small propeller testing systems only collect single mechanical or electrical parameters and cannot simultaneously handle the combined interference of multiple factors such as aeroelastic deformation, motor thermal coupling, and wind turbulence. This results in large deviations between the test data and the actual operating conditions, and cannot provide accurate basis for power system optimization.

[0027] Based on this, please refer to Figure 1 This embodiment provides a high-speed small propeller propulsion power integration test system, including a test body composed of a power support, a system control box, a safety isolation net, and a test toolbox. The power support is used to install the power system under test. The system control box houses an adjustable power supply, a circuit board, and a computer. The safety isolation net provides protection. The test toolbox stores tools. The system is characterized by further including a multi-physics parameter acquisition module, a collaborative correction module, and a dynamic compensation execution module. The multi-physics parameter acquisition module is electrically connected to the collaborative correction module to transmit the acquired parameter signals. The collaborative correction module is electrically connected to the dynamic compensation execution module to transmit the calculated correction signals. The dynamic compensation execution module is electrically connected to the power system under test to output compensation control signals. The multi-physics parameter acquisition module is used to acquire propeller aeroelastic deformation parameters, motor thermal field parameters, and wind turbulence parameters. The collaborative correction module is used to fuse the acquired parameters and calculate dynamic correction coefficients. The dynamic compensation execution module is used to adjust the ESC output voltage and the motor drive PWM signal according to the correction coefficients to compensate for the influence of multiple factors on the test results.

[0028] The core of this technical solution is to break through the limitations of traditional single-parameter testing and construct a closed-loop testing architecture of "acquisition-correction-compensation". The main testing unit provides basic support for the system. The power bracket is made of aluminum alloy and is fixed to the upper surface of the system control box with four M8 screws to ensure the stable installation of the power system under test. The internal layout of the system control box adopts a layered layout, with the adjustable power supply installed on the left, the circuit board installed in the middle, and the computer installed on the right. Each component is supported and isolated by copper pillars to reduce electromagnetic interference. The safety isolation net is made of nylon with a mesh size of 5mm×5mm and is fixed to the edge of the system control box with spring clamps to prevent the blades from falling off and causing safety hazards during testing. The test toolbox is a pull-out structure made of ABS plastic and has internal compartments for storing commonly used tools such as screwdrivers and wrenches. The multi-physics parameter acquisition module is the core of data input, employing dedicated sensors designed for three key interference factors: aeroelastic deformation, motor thermal field, and wind turbulence, enabling synchronous acquisition of multi-dimensional parameters. The collaborative correction module is the core of data processing, eliminating spatiotemporal deviations and redundancy errors of multi-source parameters through data fusion, and then calculating dynamic correction coefficients through a correction model to quantify the impact of multi-factor interference. The dynamic compensation execution module is the core of control execution, converting the correction coefficients into specific voltage and PWM adjustment values ​​to compensate for test deviations caused by multi-factor interference in real time. These three new modules work collaboratively with the test entity to form a complete multi-factor collaborative correction test system, solving the problem of traditional systems being unable to handle multi-physics interference. This technical solution achieves multi-factor collaborative correction, improving the consistency between test data and actual operating conditions, and providing accurate data support for power system development.

[0029] Existing test systems often use a single sensor for parameter acquisition modules, which cannot specifically acquire parameters of multiple physical fields such as aeroelastic deformation, motor thermal field, and wind turbulence. Furthermore, signal transmission is susceptible to electromagnetic interference, resulting in low accuracy and poor reliability of the acquired data.

[0030] Based on this, the multiphysics parameter acquisition module includes an aeroelastic sensor, a motor thermal field sensor, and a wind turbulence sensor. The aeroelastic sensor is installed at the root and middle of the propeller blade under test to collect the blade strain value and deformation displacement. The motor thermal field sensor is installed near the casing and stator windings of the motor under test to collect the motor surface temperature and winding temperature. The wind turbulence sensor is installed inside the wind wall at the front of the system's main control box to collect the turbulence intensity and turbulence frequency of the wind field. The aeroelastic sensor, motor thermal field sensor, and wind turbulence sensor are all electrically connected to the collaborative correction module through shielded cables to achieve interference-resistant transmission of parameter signals.

[0031] This technical solution ensures accurate acquisition and interference-resistant transmission of multi-dimensional parameters by refining the composition and installation method of the multi-physics parameter acquisition module. The aeroelastic sensor uses a fiber Bragg grating sensor, which features electromagnetic interference resistance and high measurement accuracy. It is adhered to the root and middle of the blade with epoxy resin, with two sensors attached to each blade to acquire axial and radial strain values ​​respectively. The optical fiber of the sensor is led out through a waterproof connector and connected to a fiber optic demodulator. The demodulator converts the change in the center wavelength of the fiber Bragg grating into a strain value, and then calculates the blade deformation displacement using a displacement conversion model. The motor thermal field sensors employ a combined design. An infrared temperature sensor is mounted 10mm in front of the motor housing via a bracket, acquiring the motor surface temperature non-contactly, with a measurement range of -70℃ to 380℃ and an accuracy of ±0.5℃. A platinum resistance temperature sensor is pre-embedded in the stator winding gap, acquiring the winding temperature in contact, with a measurement range of -40℃ to 260℃ and an accuracy of ±0.1℃. The signal outputs of both types of sensors are connected to a signal conditioning circuit for filtering and amplification. The wind turbulence sensor is a hot-wire anemometer, installed inside the wind wall. It acquires the turbulence intensity and frequency of the wind field through a hot-wire probe, with a sampling frequency of 1kHz, capable of capturing instantaneous fluctuations in the wind field. The shielded cable features a double-shielded design with a characteristic impedance of 50Ω. BNC connectors at both ends connect the sensor to the collaborative correction module, effectively suppressing electromagnetic interference and ensuring the integrity of the parameter signals during transmission. This technical solution achieves accurate and interference-resistant acquisition of multiple physical field parameters, providing a reliable data foundation for subsequent collaborative correction.

[0032] Existing testing systems lack effective multi-source data processing mechanisms. After acquiring multi-physics parameters, they are directly used for test calculations without spatiotemporal alignment and redundancy verification, and there is no unified correction logic. This results in the inability to quantify the impact of multi-factor interference, leading to large deviations in test data.

[0033] Based on this, the collaborative correction module includes a data fusion unit and a correction logic unit. The data fusion unit receives parameter signals transmitted by the multi-physics parameter acquisition module and performs spatiotemporal alignment and redundancy verification on the multi-source parameters through a data fusion algorithm, outputting a unified parameter set after fusion. The correction logic unit has a built-in preset correction calculation model, which is used to call the parameters in the unified parameter set to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient, and the wind field turbulence correction coefficient, and integrate the three types of correction coefficients into a total dynamic correction signal. The data fusion unit and the correction logic unit are electrically connected through an internal data bus to realize the real-time transmission of the parameter set.

[0034] This technical solution constructs a systematic multi-source data processing system by dividing the data into two functional units: data fusion and correction logic. The data fusion unit uses a microcontroller as the core processor and incorporates a federated Kalman filter algorithm, which can effectively handle the fusion problem of multi-source heterogeneous data. First, the data fusion unit receives parameter signals from the aeroelastic sensor, motor thermal field sensor, and wind turbulence sensor. It achieves spatiotemporal alignment through timestamp synchronization, unifying the sampling data from different sensors into the same time coordinate system. Then, it performs redundancy checks on the synchronized parameter signals. If the sampling data from a certain sensor exceeds a preset reasonable range, it is determined to be abnormal data and replaced with normal data from adjacent times using a weighted averaging algorithm to ensure data reliability. Finally, it performs data fusion using a federated Kalman filter algorithm. Sub-filters in the algorithm perform local filtering on their respective received parameter signals, outputting locally optimal estimates. The main filter receives these locally optimal estimates and dynamically allocates information weights based on the sampling accuracy of each sensor. For example, the fiber optic grating sensor has high sampling accuracy and is assigned an information weight of 0.4; the infrared temperature sensor and hot-wire anemometer have relatively low sampling accuracy and are each assigned an information weight of 0.3. A unified parameter set is then obtained through global optimal fusion calculation. This parameter set includes key parameters such as the maximum strain value of the blades, the motor casing temperature, the motor winding temperature, the wind turbulence intensity, and the wind turbulence frequency. The data update frequency is 100Hz. The correction logic unit uses an ARM processor as its core and has a built-in preset correction calculation model. The correction logic unit receives a unified parameter set output by the data fusion unit through an internal data bus. First, it extracts the parameters needed to calculate the correction coefficients from the parameter set. Then, it calls preset correction formulas to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient, and the wind field turbulence correction coefficient respectively. Finally, based on the influence weights of the three types of correction coefficients (0.4 for aeroelasticity, 0.3 for motor thermal coupling, and 0.3 for wind field turbulence), the total dynamic correction signal is obtained. The output format of the correction signal is a 16-bit digital quantity, which facilitates reception and processing by the dynamic compensation execution module. The internal data bus uses differential signal transmission, which can effectively suppress electromagnetic interference within the collaborative correction module and ensure the real-time and accurate transmission of the unified parameter set. This technical solution realizes the systematic processing of multi-source data and the integration of multiple correction coefficients, quantifies the influence of multi-factor interference, and provides a precise correction basis for dynamic compensation.

[0035] The existing testing system lacks a dynamic compensation execution mechanism. Even if it obtains correction information for multi-physics parameters, it cannot convert the correction information into actual control actions, thus failing to compensate for the impact of multi-factor interference on the test results and making it difficult to improve test accuracy.

[0036] Based on this, the dynamic compensation execution module includes an electronic speed controller (ESC) compensation circuit and a motor drive adjustment unit. The ESC compensation circuit receives the total dynamic correction signal transmitted by the collaborative correction module and converts the total dynamic correction signal into an ESC voltage compensation amount to adjust the voltage value output from the adjustable power supply to the ESC. The motor drive adjustment unit generates a PWM duty cycle adjustment amount based on the total dynamic correction signal and changes the duty cycle of the PWM drive signal output to the tested motor in real time. The ESC compensation circuit and the motor drive adjustment unit are connected via control signal lines to achieve synchronous execution of the compensation action.

[0037] This technical solution utilizes two execution units—Electronic Speed ​​Regulator (ESR) compensation and motor drive adjustment—to convert correction signals into specific control actions, achieving dynamic compensation during the testing process. The ESR compensation circuit is centered around a 16-bit high-precision DAC chip, which converts the 16-bit digital dynamic correction signal transmitted by the collaborative correction module into an analog voltage signal. This analog voltage signal is amplified by an operational amplifier circuit and then input as a control signal to the voltage control terminal of the adjustable power supply. The adjustable power supply adjusts its output voltage according to the control signal, forming the ESR voltage compensation value. The voltage adjustment range is 0-14V, with an adjustment resolution of 1mV, enabling precise compensation for voltage attenuation caused by motor thermal coupling.

[0038] The existing testing system has not established a quantitative correction model for aeroelastic deformation, and cannot accurately calculate the degree of influence of blade deformation on test parameters, resulting in test data such as thrust and torque failing to reflect actual aerodynamic performance.

[0039] Based on this, the formula for calculating the aeroelastic correction coefficient by the correction logic unit is as follows:

[0040] ;

[0041] In the formula, This is the aeroelastic correction factor, dimensionless. The maximum strain value of the blade, dimensional , The real-time rotational speed of the propeller is expressed in rad / s. The turbulence intensity of the wind field is expressed in m / s. The elastic modulus of the blade material, in units of GPa. The maximum allowable deformation of the blade is expressed in mm.

[0042] This technical solution quantifies the synergistic effects of blade deformation, rotational speed, and wind turbulence on test parameters by constructing an aeroelastic correction coefficient formula. The selection and calculation of each parameter in the formula are based on fluid mechanics and materials mechanics theories, ensuring the accuracy and rationality of the correction coefficient. As an aeroelastic correction factor, its value ranges from 0.7 to 1.0. When the blade deformation is smaller, the rotational speed is lower, and the wind field is more stable, The closer the value is to 1.0, the smaller the impact of aeroelastic disturbances on the test parameters; conversely, the smaller the value is, the smaller the impact of aeroelastic disturbances on the test parameters. The smaller the value, the greater the interference. This represents the maximum strain value of the blade, obtained by comparing strain data collected by aeroelastic sensors. It reflects the degree of blade deformation; for example, when a carbon fiber blade rotates at high speed... Typically 500-1500× . The real-time propeller rotation speed is calculated from the frequency signal collected by the speed sensor. When converting the unit to rad / s, it needs to be multiplied by . High-speed small propeller Typically, it ranges from 2094 to 5236 rad / s.

[0043] The wind turbulence intensity is directly collected by a wind turbulence sensor and reflects the degree of wind field fluctuation. In conventional tests, the wind turbulence intensity is usually 0.5-2.0 m / s. The elastic modulus of the blade material is determined based on the blade material, such as carbon fiber composites. Approximately 70-100 GPa, made of plastic. It is approximately 2-5 GPa, and this parameter is pre-stored as a known quantity in the memory of the correction logic unit. The maximum allowable deformation of the blade is determined based on the blade design parameters, and is typically 1%-3% of the blade length, for example, for a 10-inch blade. The diameter is approximately 2.5-7.6 mm, and this parameter is also pre-stored in memory. The calculation process of the formula is executed by the ARM processor of the correction logic unit, first extracting from the unified parameter set. , , Call the pre-stored and Then calculate the molecule first ( ), and then calculate the denominator ( Finally, the steps of calculating the difference (1 - numerator / denominator) yield the result. The calculation accuracy is retained to four decimal places. This technical solution achieves quantitative correction of aeroelastic disturbances, providing an accurate aeroelastic correction basis for total dynamic compensation.

[0044] The existing testing system does not consider the influence of motor thermal coupling effect, does not establish a correlation model between temperature and motor output performance, cannot correct the test data deviation caused by motor temperature rise, and the test results cannot reflect the actual working state of the motor.

[0045] Based on this, the formula for calculating the motor thermal coupling correction coefficient by the correction logic unit is as follows:

[0046] ;

[0047] In the formula, This is the thermal coupling correction factor for the motor, dimensionless. The ambient temperature was measured in degrees Celsius (°C). The rated operating temperature of the motor, in degrees Celsius (°C). The real-time temperature of the motor casing, in degrees Celsius (°C). This represents the real-time temperature of the motor stator winding, in degrees Celsius (°C).

[0048] This technical solution quantifies the correlation between motor temperature and output performance by constructing a motor thermal coupling correction coefficient formula, thereby correcting test deviations caused by motor temperature rise. The formula is designed based on motor theory, which states that the resistance of the motor windings increases with temperature, leading to a decrease in motor output torque and power. Therefore, a correction coefficient is calculated using temperature parameters to compensate for this attenuation effect. As a correction factor for motor thermal coupling, its value ranges from 0.6 to 1.0. The closer the actual motor temperature is to the rated operating temperature, the better. The closer the value is to 1.0, the smaller the impact of motor thermal coupling interference on the test parameters; when the motor temperature exceeds the rated operating temperature, The smaller the value, the greater the interference. To test the ambient temperature, an ambient temperature sensor was used. This sensor is integrated inside the system's main control box and has a measurement range of -10℃ to 50℃ with an accuracy of ±0.5℃, for example, under typical laboratory conditions. The temperature is usually 20-25℃. The rated operating temperature of the motor is determined according to the motor model and is input by the user via the host computer software and pre-stored in the correction logic unit before testing. For example, this applies to brushless motors. The temperature is usually 60-80℃. The real-time temperature of the motor casing is collected by an infrared temperature sensor within the motor's thermal field sensor. The measurement range is -70℃ to 380℃, with an accuracy of ±0.5℃. This temperature is measured during motor operation. The temperature is usually 40-80℃. The real-time temperature of the motor stator windings is collected by a platinum resistance temperature sensor in the motor thermal field sensor. The measurement range is -200℃ to 650℃, with an accuracy of ±0.1℃. The winding temperature is typically 10-20℃ higher than the casing temperature. Typically, the temperature is 50-100℃. The calculation process of the formula is executed by the ARM processor of the correction logic unit, first extracting from the unified parameter set. , , Call the pre-stored Then calculate the molecule first ( ), and then calculate the denominator ( Finally, the steps of calculating the ratio (numerator / denominator) yield the result. The calculation accuracy is retained to four decimal places. This technical solution achieves quantitative correction of motor thermal coupling interference, providing an accurate basis for motor thermal field correction for total dynamic compensation.

[0049] Existing testing systems lack an integration mechanism for multiple correction coefficients. The correction coefficients for aeroelasticity, motor thermal coupling, and wind turbulence are independent, failing to comprehensively reflect the synergistic interference of multiple factors. This results in a lack of unified control basis for dynamic compensation, leading to poor compensation performance. Therefore, according to claim 5 or 6, the high-speed small propeller propulsion power integration testing system is characterized by the following formula for integrating the total dynamic correction signal by the correction logic unit:

[0050] ;

[0051] In the formula, The total dynamic compensation is measured in units that match the test parameters, such as thrust in N and torque in N·m. Basic test parameter values, dimensions and Consistent, The turbulence frequency of the wind field is expressed in Hz. The maximum design turbulence frequency of the wind field is expressed in Hz.

[0052] This technical solution constructs a formula for total dynamic compensation, integrating aeroelastic correction coefficients, motor thermal coupling correction coefficients, and wind field turbulence parameters to form a unified basis for dynamic compensation, achieving comprehensive compensation for multi-factor synergistic interference. The combination of parameters in the formula is based on multiphysics coupling theory, ensuring that the total dynamic compensation can fully reflect the synergistic effects of multiple factors. The total dynamic compensation amount serves as the control basis for the dynamic compensation execution module. Its specific dimensions are determined based on the test parameters, such as when testing thrust. The dimension of is N, N·m when testing torque, and W when testing power; The value changes dynamically based on the degree of interference from multiple factors; the greater the interference, the lower the value. and The larger the difference, the better. These are the basic test parameter values, which are theoretical test values ​​without considering interference from multiple factors. They are set by the host computer software according to the test requirements, such as when testing the thrust of a certain type of propeller. It can be set to 50N. and These are the aeroelastic correction coefficient and the motor thermal coupling correction coefficient calculated in claims 5 and 6, respectively. Their product reflects the combined interference effect of mechanical and thermal factors. The wind turbulence frequency is collected by a wind turbulence sensor and reflects the frequency of wind field fluctuations. In conventional tests, the wind turbulence frequency is usually 1-10Hz. The maximum design turbulence frequency for the wind field is determined based on the wind wall performance of the test system and is pre-stored in the correction logic unit, such as the wind wall frequency of this system. Set to 20Hz; The term is a wind field turbulence correction term, with a value ranging from 1.0 to 1.2. The higher the wind field turbulence frequency, the larger the value of this term, reflecting the more significant the impact of wind field fluctuations on the test parameters. 0.2 is an empirical coefficient, determined through extensive experimental verification to ensure the accuracy of the wind field correction. The calculation process of the formula is executed by the ARM processor of the correction logic unit, first obtaining... (Received from host computer software) and (Calculations completed) (Extracted from a unified parameter set) (Pre-stored parameters), then calculate the wind field turbulence correction term first, and then multiply them sequentially to obtain... The calculation process is executed step by step, and the accuracy is maintained according to the test parameter requirements. For example, thrust is retained to one decimal place, and torque is retained to two decimal places. This technical solution integrates multiple correction coefficients with wind field parameters, providing a unified and comprehensive control basis for dynamic compensation and improving the compensation effect of multi-factor collaborative interference.

[0053] The existing testing system suffers from improper selection and installation of aeroelastic sensors and motor thermal field sensors, resulting in low parameter acquisition accuracy and poor reliability, which fails to meet the requirements for accurate testing of multiple physical field parameters.

[0054] Based on this, the aeroelastic sensor adopts a fiber optic grating sensor, which is attached to the blade surface with epoxy resin. The center wavelength of the fiber optic grating sensor changes with the blade strain. The aeroelastic sensor converts the wavelength change into a strain value through a fiber optic demodulator, and then obtains the blade deformation displacement through a displacement conversion model. The motor thermal field sensor adopts a combination of an infrared temperature sensor and a platinum resistance temperature sensor. The infrared temperature sensor is used for non-contact acquisition of the motor casing temperature, and the platinum resistance temperature sensor is pre-embedded in the gap of the motor stator winding for contact acquisition of the winding temperature.

[0055] This technical solution optimizes sensor selection and installation to ensure accurate acquisition of aeroelastic deformation parameters and motor thermal field parameters. The aeroelastic sensor is a fiber Bragg grating sensor, whose core component is a single-mode optical fiber etched with a grating. When the blade deforms, the period of the fiber Bragg grating changes, causing a center wavelength shift. The wavelength shift is linearly related to the strain value, enabling high-precision strain measurement. The sensor installation process strictly follows process requirements. First, the blade bonding surface is polished and cleaned, then epoxy resin is applied, and the sensor is adhered to the root and middle of the blade. The bonding pressure is controlled at 0.1 MPa to ensure a tight fit between the sensor and the blade surface, reducing measurement errors. The sensor's optical fiber is led out through a waterproof connector to prevent moisture intrusion during testing from affecting signal transmission. The fiber optic demodulator is connected to a fiber Bragg grating sensor. The demodulator uses a broadband light source and a spectrometer to detect the reflection spectrum of the fiber Bragg grating. The center wavelength shift is calculated, and then converted into a strain value based on the sensitivity coefficient. The displacement conversion model is based on beam bending theory in materials mechanics. Based on the blade's moment of inertia, material elastic modulus, and strain distribution, the deformation displacement at different locations on the blade is calculated. For example, the strain value at the blade root is 1000 × [missing value]. At that time, the root deformation displacement was calculated to be approximately 0.5 mm through model calculation. The motor thermal field sensor adopts a combined design. The infrared temperature sensor uses a TO-39 package with a field of view of 90°. It is installed 10 mm in front of the motor housing via an aluminum alloy bracket. The bracket is fixed to the system control box with screws to ensure that the sensor and the motor housing maintain a fixed distance to avoid measurement deviation caused by mechanical vibration. The sensor's output signal is an I2C digital signal, which is directly transmitted to the collaborative correction module, enabling non-contact and interference-free acquisition of the motor housing temperature. The platinum resistance temperature sensor uses a glass package with dimensions of Φ1.5 mm × 10 mm. It is installed in the gap of the motor stator winding through a pre-embedding method. During installation, the motor end cover must be removed first, the sensor is inserted into the winding gap, ensuring that the sensor is in close contact with the winding wire, and then fixed with high-temperature resistant silicone to prevent the sensor from shifting when the motor rotates. The sensor's output signal is a resistance signal, which is converted into a voltage signal through a signal conditioning circuit and then transmitted to the collaborative correction module to achieve high-precision winding temperature acquisition. This technical solution ensures the accurate acquisition of aeroelastic deformation parameters and motor thermal field parameters, providing reliable data support for subsequent collaborative correction.

[0056] The data fusion algorithm of the existing test system is simple, using only basic methods such as weighted averaging. It cannot handle the spatiotemporal deviation and redundancy error of multi-source parameters, resulting in low accuracy of the fused data and failing to meet the requirements of multi-factor collaborative correction.

[0057] Based on this, the data fusion unit uses a federated Kalman filter algorithm for data fusion. The federated Kalman filter algorithm includes sub-filters and a main filter. The sub-filters perform local filtering on the parameter signals of the aeroelastic sensor, the motor thermal field sensor, and the wind field turbulence sensor, respectively, and output local optimal estimates. The main filter receives the local optimal estimates of each sub-filter, allocates the information weights of each sub-filter through information allocation coefficients, and then performs global optimal fusion calculation to output the unified parameter set. The information allocation coefficients are dynamically adjusted according to the sampling accuracy of each sensor; the higher the sampling accuracy, the greater the information weight.

[0058] This technical solution employs a federated Kalman filter algorithm to achieve high-precision data fusion of multi-source parameters, eliminating spatiotemporal bias and redundant errors. The federated Kalman filter algorithm is a distributed filtering algorithm based on information fusion theory, suitable for multi-sensor data fusion scenarios. Its core idea is to decompose the global filtering task into multiple local sub-filtering tasks, and then perform global fusion through a main filter, effectively improving the accuracy and reliability of data fusion. The number of sub-filters corresponds to the sensor type, with three sub-filters set to process parameter signals from aeroelastic sensors, motor thermal field sensors, and wind turbulence sensors, respectively. Each sub-filter uses the Kalman filter algorithm, including two steps: prediction and update. In the prediction step, the parameter estimate and error covariance matrix at the current moment are predicted based on the sensor's dynamic model. In the update step, the sensor sampling data at the current moment are compared with the predicted values, and the error covariance matrix is ​​adjusted through Kalman gain to obtain a locally optimal estimate. The sampling frequency of each sub-filter is consistent with the sampling frequency of its corresponding sensor: 500Hz for the aeroelastic sensor, 100Hz for the motor thermal field sensor, and 1kHz for the wind turbulence sensor. Time stamp synchronization ensures the sampling time alignment of each sub-filter. After receiving the locally optimal estimates from each sub-filter, the main filter first calculates the information allocation coefficient. This coefficient is dynamically adjusted based on the sampling accuracy of each sensor. The sampling accuracy is quantified by the standard deviation of the sensor's measurement error; for example, the standard deviation of the aeroelastic sensor's measurement error is 5 × 10⁻⁶. The motor thermal field sensor has a sampling rate of 0.1℃, and the wind turbulence sensor has a sampling rate of 0.05m / s. Higher sampling accuracy results in a smaller standard deviation of measurement error and a larger information allocation coefficient. For example, in a certain test scenario, the information allocation coefficients for the aeroelastic sensor, motor thermal field sensor, and wind turbulence sensor are 0.4, 0.3, and 0.3, respectively. Then, the main filter decomposes the global information matrix into local information matrices for each sub-filter based on the information allocation coefficients. The local optimal estimates of each sub-filter are then fused with the local information matrices to calculate the global optimal estimate, forming a unified parameter set. The unified parameter set updates at 100Hz and includes key parameters such as the maximum blade strain, motor casing temperature, motor winding temperature, wind turbulence intensity, and wind turbulence frequency. Each parameter is accompanied by an error covariance matrix to evaluate data accuracy. This technical solution achieves high-precision data fusion of multiple sources, providing an accurate and reliable unified parameter set for collaborative correction.

[0059] Existing testing methods are simple in process, but lack systematic initialization, parameter acquisition, collaborative correction and dynamic compensation steps. The automation level of the testing process is low and there is no data stability judgment mechanism, resulting in low testing efficiency and poor data reliability.

[0060] Based on this, please refer to Figure 2 This embodiment provides a high-speed small propeller propulsion power integration test method, applied to the high-speed small propeller propulsion power integration test system described in any one of the above, including the following steps:

[0061] The first step is to power on and initialize the system. The adjustable power supply of the test body starts up and outputs the initial voltage. The computer starts the host computer software. The multi-physics parameter acquisition module completes sensor zeroing and benchmark calibration. The collaborative correction module loads the preset correction calculation model and data fusion algorithm. The dynamic compensation execution module is in a state of waiting to be triggered.

[0062] The second step is to install the power system under test to the power support, fix the safety isolation net, and set the basic threshold values ​​of the test parameters through the host computer software, including the basic speed, basic load current and basic wind speed.

[0063] The third step is to activate the wind wall. The multi-physics parameter acquisition module collects blade strain values, motor temperature values ​​and wind field turbulence parameters according to a preset sampling period, and transmits the collected parameter signals to the collaborative correction module.

[0064] Fourth step, the data fusion unit of the collaborative correction module performs spatiotemporal alignment and redundancy verification on the parameter signals, and outputs a unified parameter set to the correction logic unit. The correction logic unit calls the formula to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient and the total dynamic compensation amount.

[0065] Fifth step: The dynamic compensation execution module receives the total dynamic compensation amount, the electronically adjustable compensation circuit adjusts the output voltage of the adjustable power supply, and the motor drive adjustment unit adjusts the duty cycle of the PWM drive signal to achieve dynamic compensation of the test parameters.

[0066] Step 6: The host computer software collects the compensated test data in real time and compares it with the basic threshold. If the data deviation exceeds the allowable range, steps 3 to 5 are repeated until the test data is stable. If the test is completed, the wind wall and the tested power system are shut down, the test data is saved, and a test report is generated.

[0067] This technical solution achieves automated and high-precision testing of high-speed small propeller propulsion power through a systematic testing procedure. The first step, system power-on initialization, is the fundamental preparation stage for testing. After the adjustable power supply starts, it outputs an initial voltage, which is monitored in real time by a voltmeter to ensure stable output. The computer starts the host computer software, which automatically detects the connection status of each hardware module. If any connection abnormality is found, a pop-up notification is displayed. The sensor zeroing and benchmark calibration of the multi-physics parameter acquisition module are automatically completed by the software. For example, the zeroing process of the aeroelastic sensor involves acquiring the center wavelength of the sensor under strain-free conditions as the reference wavelength. The collaborative correction module loads a preset correction calculation model and data fusion algorithm, and verifies the integrity of the model and algorithm through a self-test program. After initialization, the dynamic compensation execution module is in a ready-to-trigger state. The DAC chip of the electronically controlled compensation circuit outputs an initial voltage, and the motor drive adjustment unit outputs an initial PWM duty cycle. The second step is the pre-test preparation stage. The power system under test is fixed to the power bracket by the motor mounting plate. The mounting plate and the power bracket are fixed with four M6 screws with a torque of 5 N·m to ensure a stable installation. The safety isolation net is fixed to the edge of the system control box by spring clamps. The tightness of the clamps is checked to prevent them from falling off during the test. The host computer software sets the basic threshold of the test parameters. The basic speed is determined according to the propeller model. For example, the basic speed of a 10-inch propeller is set to 30,000 r / min. The basic load current is set according to the rated current of the motor. The basic wind speed is set according to the test requirements. After the parameters are set, they are saved to the test plan through the software. Steps three through five constitute the test execution phase. After the wind wall is activated, the wind speed is adjusted to the base wind field speed via a frequency converter. The wind speed is monitored in real time by a wind field turbulence sensor to ensure stability. The multi-physics parameter acquisition module collects parameter signals according to a preset sampling period: 500Hz for the aeroelastic sensor, 100Hz for the motor thermal field sensor, and 1kHz for the wind field turbulence sensor. These signals are then transmitted to the collaborative correction module via shielded cables. The data fusion unit performs spatiotemporal alignment and redundancy verification on the parameter signals, removes abnormal data, and outputs a unified parameter set. The correction logic unit calls formulas to calculate the three types of correction coefficients and the total dynamic compensation amount. The dynamic compensation execution module adjusts the ESC voltage and PWM duty cycle according to the total dynamic compensation amount to achieve dynamic compensation. The sixth step is the test completion stage. The host computer software collects the compensated test data in real time and compares it with the basic threshold. The allowable deviation range is set to ±5%. If the data deviation exceeds the range, steps three to five are repeated until the data deviation for five consecutive sampling cycles is within the allowable range, and the data is judged to be stable. After the test is completed, the software automatically shuts down the wind wall and the tested power system, saves the test data to an Excel file, including timestamps, parameter values, compensation amounts, and other information, and generates a test report, including test parameters, data curves, and analysis conclusions.

[0068] This technical solution automates and systematizes the testing process, improves testing efficiency and data reliability, and meets the high-precision testing requirements of high-speed small propeller propulsion power.

[0069] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A high-speed, small propeller propulsion power integration test system, comprising a test body, the test body consisting of a power support, a system control box, a safety isolation net, and a test toolbox, wherein the power support is used to install the power system under test, the system control box houses an adjustable power supply, a circuit board, and a computer, the safety isolation net is used for protection, and the test toolbox is used to store tools, characterized in that... It also includes a multiphysics parameter acquisition module, a collaborative correction module, and a dynamic compensation execution module. The multiphysics parameter acquisition module is electrically connected to the collaborative correction module to transmit the acquired parameter signals. The collaborative correction module is electrically connected to the dynamic compensation execution module to transmit the calculated correction signals. The dynamic compensation execution module is electrically connected to the power system under test to output compensation control signals. The multiphysics parameter acquisition module is used to acquire propeller aeroelastic deformation parameters, motor thermal field parameters, and wind turbulence parameters. The collaborative correction module is used to fuse the acquired parameters and calculate dynamic correction coefficients. The dynamic compensation execution module is used to adjust the ESC output voltage and the motor drive PWM signal according to the correction coefficients to compensate for the influence of multi-factor interference on the test results.

2. The high-speed small propeller propulsion power integration test system according to claim 1, characterized in that, The multiphysics parameter acquisition module includes an aeroelastic sensor, a motor thermal field sensor, and a wind turbulence sensor. The aeroelastic sensor is installed at the root and middle of the propeller blade under test to collect the blade strain value and deformation displacement. The motor thermal field sensor is installed near the casing and stator windings of the motor under test to collect the motor surface temperature and winding temperature. The wind turbulence sensor is installed inside the wind wall at the front of the system's main control box to collect the turbulence intensity and turbulence frequency. The aeroelastic sensor, motor thermal field sensor, and wind turbulence sensor are all electrically connected to the collaborative correction module via shielded cables to achieve interference-resistant transmission of parameter signals.

3. The high-speed small propeller propulsion power integration test system according to claim 1, characterized in that, The collaborative correction module includes a data fusion unit and a correction logic unit. The data fusion unit receives parameter signals transmitted by the multi-physics parameter acquisition module and performs spatiotemporal alignment and redundancy verification on the multi-source parameters through a data fusion algorithm, outputting a unified parameter set after fusion. The correction logic unit has a built-in preset correction calculation model, which is used to call the parameters in the unified parameter set to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient, and the wind field turbulence correction coefficient, and integrate the three types of correction coefficients into a total dynamic correction signal. The data fusion unit and the correction logic unit are electrically connected through an internal data bus to realize the real-time transmission of the parameter set.

4. The high-speed small propeller propulsion power integration test system according to claim 1, characterized in that, The dynamic compensation execution module includes an electronic speed controller (ESC) compensation circuit and a motor drive adjustment unit. The ESC compensation circuit receives the total dynamic correction signal transmitted by the collaborative correction module and converts the total dynamic correction signal into an ESC voltage compensation amount to adjust the voltage value output from the adjustable power supply to the ESC. The motor drive adjustment unit generates a PWM duty cycle adjustment amount based on the total dynamic correction signal and changes the duty cycle of the PWM drive signal output to the tested motor in real time. The ESC compensation circuit and the motor drive adjustment unit are connected via control signal lines to achieve synchronous execution of the compensation action.

5. The high-speed small propeller propulsion power integration test system according to claim 3, characterized in that, The formula for calculating the aeroelastic correction coefficient by the correction logic unit is as follows: ； In the formula, This is the aeroelastic correction factor. This represents the maximum strain value of the blade. This refers to the real-time rotational speed of the propeller. For wind field turbulence intensity, The elastic modulus of the blade material. This represents the maximum allowable deformation of the blade.

6. The high-speed small propeller propulsion power integration test system according to claim 3, characterized in that, The formula for calculating the motor thermal coupling correction coefficient by the correction logic unit is as follows: ； In the formula, This is the thermal coupling correction factor for the motor. To test the ambient temperature, The rated operating temperature of the motor. This refers to the real-time temperature of the motor casing. This refers to the real-time temperature of the motor stator windings.

7. The high-speed small propeller propulsion power integration test system according to claim 5 or 6, characterized in that, The formula for integrating the total dynamic correction signal by the correction logic unit is: ； In the formula, This represents the total dynamic compensation amount. Based on the basic test parameter values, For wind field turbulence frequency, This is the maximum design turbulence frequency for the wind field.

8. The high-speed small propeller propulsion power integration test system according to claim 2, characterized in that, The aeroelastic sensor employs a fiber Bragg grating sensor, which is adhered to the blade surface using epoxy resin adhesive. The center wavelength of the fiber Bragg grating sensor varies with the blade strain. The aeroelastic sensor converts the wavelength change into a strain value using a fiber optic demodulator, and then obtains the blade deformation displacement using a displacement conversion model. The motor thermal field sensor combines an infrared temperature sensor and a platinum resistance temperature sensor. The infrared temperature sensor is used for non-contact acquisition of the motor casing temperature, while the platinum resistance temperature sensor is pre-embedded in the gap of the motor stator windings for contact acquisition of the winding temperature.

9. The high-speed small propeller propulsion power integration test system according to claim 3, characterized in that, The data fusion unit employs a federated Kalman filter algorithm for data fusion. This algorithm includes sub-filters and a main filter. The sub-filters perform local filtering on the parameter signals from the aeroelastic sensor, motor thermal field sensor, and wind turbulence sensor, respectively, outputting locally optimal estimates. The main filter receives the locally optimal estimates from each sub-filter, assigns information weights to each sub-filter using information allocation coefficients, and then performs global optimal fusion calculations to output the unified parameter set. The information allocation coefficients are dynamically adjusted based on the sampling accuracy of each sensor; higher sampling accuracy results in greater information weights.

10. A method for testing the integrated propulsion power of a high-speed small propeller, applied to the integrated propulsion power testing system of any one of claims 1-9, characterized in that, Includes the following steps: The first step is to power on and initialize the system. The adjustable power supply of the test body starts up and outputs the initial voltage. The computer starts the host computer software. The multi-physics parameter acquisition module completes sensor zeroing and benchmark calibration. The collaborative correction module loads the preset correction calculation model and data fusion algorithm. The dynamic compensation execution module is in a state of waiting to be triggered. The second step is to install the power system under test to the power support, fix the safety isolation net, and set the basic threshold values ​​of the test parameters through the host computer software, including the basic speed, basic load current and basic wind speed. The third step is to activate the wind wall. The multi-physics parameter acquisition module collects blade strain values, motor temperature values ​​and wind field turbulence parameters according to a preset sampling period, and transmits the collected parameter signals to the collaborative correction module. Fourth step, the data fusion unit of the collaborative correction module performs spatiotemporal alignment and redundancy verification on the parameter signals, and outputs a unified parameter set to the correction logic unit. The correction logic unit calls the formula to calculate the aeroelastic correction coefficient, the motor thermal coupling correction coefficient and the total dynamic compensation amount. Fifth step: The dynamic compensation execution module receives the total dynamic compensation amount, the electronically adjustable compensation circuit adjusts the output voltage of the adjustable power supply, and the motor drive adjustment unit adjusts the duty cycle of the PWM drive signal to achieve dynamic compensation of the test parameters. The sixth step involves the host computer software collecting the compensated test data in real time and comparing it with the basic threshold. If the data deviation exceeds the allowable range, steps three through five are repeated until the test data stabilizes. If the test is completed, shut down the wind wall and the tested power system, save the test data and generate a test report.

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