Motor loss separation test method, device, system and readable storage medium

Abstract

The present application relates to the field of motor testing technology, and provides a motor loss separation test method, device, system and readable storage medium. The method includes: determining the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor; determining the load iron loss of the motor based on simulation analysis and actual load testing; determining the motor body loss based on the motor operating parameters at the speed measurement point; determining the stray loss of the motor based on the AC side electric power; and outputting the no-load iron loss, load iron loss, motor body loss, stray loss and assembly iron loss respectively. The present application realizes the separation test of motor loss, and the motor losses obtained from these separation tests can provide a reliable basis for motor design and optimization, thereby helping to improve motor performance.

Description

Technical Field

[0001] The present application relates to the technical field of motor testing, and in particular to a motor loss separation testing method, device, system and readable storage medium. Background Art

[0002] During motor operation, its efficiency is affected by multiple losses, including no-load iron loss, loaded iron loss, stray losses, and mechanical losses. To improve motor efficiency, these losses need to be accurately measured and analyzed. However, traditional testing methods often fail to accurately separate and quantify these different types of losses. Summary of the Invention

[0003] In view of this, the embodiments of the present application provide a motor loss separation test method, device, system and readable storage medium to solve the technical problem of how to separate and measure motor losses.

[0004] According to a first aspect of an embodiment of the present application, a motor loss separation test method is provided, which includes: determining the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor; determining the load iron loss of the motor based on simulation analysis and actual load testing; determining the motor body loss based on the motor operating parameters of the motor at the speed measurement point; determining the stray loss of the motor based on the AC side electric power; and outputting the no-load iron loss, load iron loss, motor body loss, stray loss and assembly iron loss respectively, wherein the assembly iron loss includes the sum of the no-load iron loss, load iron loss, motor body loss and stray loss.

[0005] According to a second aspect of an embodiment of the present application, a motor loss separation test device is provided, which includes: a no-load iron loss test module, configured to determine the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor; a load iron loss test module, configured to determine the load iron loss of the motor based on simulation analysis and actual load testing; a body loss test model, configured to determine the motor body loss based on the motor operating parameters of the motor at the speed measurement point; a stray loss test module, configured to determine the stray loss of the motor based on the AC side electric power; a test result processing module, configured to output the no-load iron loss, load iron loss, motor body loss, stray loss and assembly iron loss respectively, and the assembly iron loss includes the sum of the no-load iron loss, load iron loss, motor body loss and stray loss.

[0006] According to a third aspect of an embodiment of the present application, a motor loss separation test system is provided, which is applied to a car including a motor, a motor controller, a vehicle controller, a battery management system, a power battery and a power control system. The motor loss separation test system includes a motor test bench, multiple sensors, a data acquisition system and a data analysis device. The motor is connected to the motor test bench by transmission, the sensor is installed on the motor test bench, the data acquisition system is connected to the sensor, and the data analysis device is connected to the data acquisition system. The data analysis device includes at least a memory, a processor and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0007] According to a fourth aspect of an embodiment of the present application, a readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0008] The beneficial effect of the embodiments of the present application compared with the prior art is that the above-mentioned motor loss separation test method obtains the different losses and assembly losses of the motor by separating and accurately measuring the no-load iron loss, load iron loss, stray loss and mechanical loss of the motor. These separately measured different losses can provide a reliable basis for motor design and optimization, thereby helping to improve motor performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0010] Figure 1 1 is a flow chart of a motor loss separation test method provided in an embodiment of the present application;

[0011] Figure 2 1 is a schematic structural diagram of a motor loss separation test device provided in an embodiment of the present application;

[0012] Figure 3 This is a schematic diagram of a partial structure of a car provided in an embodiment of the present application;

[0013] Figure 4 It is a structural diagram of a data analysis device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0014] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0015] In existing technology, the efficiency of electric motors (hereinafter referred to as motors) is affected by no-load iron loss, loaded iron loss, stray losses, and mechanical losses (also known as motor losses). To improve efficiency, these losses need to be accurately measured and analyzed, but traditional testing methods are generally unable to accurately separate and quantify these losses.

[0016] In view of the above problems, an embodiment of the present application provides a motor loss separation test method, which can effectively separate and accurately measure the no-load iron loss, load iron loss, stray loss and mechanical loss of the motor. The separate measurement of these different losses can also provide a reliable basis for motor design and optimization, thereby helping to improve motor performance.

[0017] See also Figure 1 In a first embodiment of the present application, a motor loss separation test method is provided, comprising the steps of:

[0018] S101, determining the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and the drag torque at each speed measurement point of the motor;

[0019] S102, determining the load iron loss of the motor based on simulation analysis and actual load testing;

[0020] S103, determining the motor body loss according to the motor operating parameters at the speed measurement point;

[0021] S104, determining the stray loss of the motor based on the AC side electric power;

[0022] S105 , outputting the no-load iron loss, loaded iron loss, motor body loss, stray loss and total iron loss respectively, where the total iron loss includes the sum of the no-load iron loss, loaded iron loss, motor body loss and stray loss.

[0023] This embodiment separates and accurately measures the no-load iron loss, loaded iron loss, stray loss, and mechanical loss of the motor to obtain the different losses and assembly losses of the motor. These separately measured different losses can provide a reliable basis for motor design and optimization, thereby helping to improve motor performance.

[0024] In the actual test, the motor to be tested is mounted on a test bench (e.g., a motor stand) and connected to the sensors required for the test to ensure that all sensors are functioning properly. Next, the motor is started and operated under no-load conditions, gradually increasing the speed and torque to a predetermined value while collecting corresponding test data, including but not limited to torque, temperature, and current data. Afterwards, the no-load iron loss, loaded iron loss, motor body loss, and stray loss of the motor are separated and measured according to the above steps S101 to S104.

[0025] It is worth mentioning that in the motor loss separation test method provided above, steps S101 to S104 should be performed in sequence to test the motor's no-load iron loss, loaded iron loss, motor body loss, and stray loss respectively. Furthermore, there is no single way to test each type of loss.

[0026] The no-load loss of the motor can be calculated by testing the motor drag torque in the non-magnetized and magnetized states, and then multiplying the difference between the two by the angular velocity.

[0027] In some optional embodiments, the no-load iron loss of the motor at the corresponding speed measurement point is determined based on the mechanical torque and drag torque at each speed measurement point of the motor, including: measuring the drag torque of the motor at each speed measurement point when the magnet is not magnetized; measuring the drag torque of the motor at each speed measurement point when the magnet is magnetized; and determining the no-load iron loss at the corresponding speed measurement point based on the drag torque measured when the magnet is not magnetized and the drag torque measured when the magnet is magnetized.

[0028] Here, a speed measurement point refers to the point at which performance is measured at a specific speed during the motor loss separation test. Each specific speed value is a speed measurement point. For example, motor speeds of 1000 rpm, 2000 rpm, 3000 rpm, and 4000 rpm are used as speed measurement points.

[0029] Specifically, when testing the no-load iron loss, first install the unmagnetized magnets into the rotor assembly and assemble it into a dynamometer. Then gradually increase the speed at a specified speed step size until the maximum speed. During this process, only the motor temperature is monitored, and the drag torque T1 (or the first drag torque) is measured at each speed measurement point. After completion, the magnetized magnets are installed into the rotor assembly and assembled into a dynamometer again. Repeat the above steps to measure the drag torque T1 to measure the drag torque T2 (or the second drag torque). Finally, the no-load iron loss of the motor is calculated using the following formula:

[0030] P 空载铁损 =(T2-T1)*ω;

[0031] Among them, P 空载铁损 represents the no-load iron loss, and ω is the angular velocity.

[0032] The embodiment of the present application measures the drag torque of the motor when the magnet is not magnetized and magnetized respectively, and then multiplies the difference between the two with the angular velocity to determine the no-load iron loss at each speed measurement point, thereby realizing the separate measurement of the no-load iron loss of the motor.

[0033] The load iron loss of the motor can be calculated through simulation analysis and actual load testing.

[0034] In some optional embodiments, the load iron loss of the motor is determined based on simulation analysis and actual load testing, including: constructing a three-dimensional model of the motor; simulating the operating state of the motor under different loads based on the three-dimensional model, and determining the simulated iron loss data of the motor under each load; and determining the load iron loss of the motor under the corresponding load based on the actual load test data and the simulated iron loss data of the motor.

[0035] Specifically, a simulation tool can be used to build a three-dimensional model of the motor. The simulation tool can be optionally a finite element analysis software. For example, when performing a motor load iron loss test, a finite element analysis software is first used to build a three-dimensional model of the motor. The three-dimensional model includes but is not limited to the stator, rotor, and air gap part, and sets material properties and electromagnetic parameters such as magnetic permeability and loss coefficient. Then, different load conditions are applied to the three-dimensional model, and corresponding currents and voltages are set to simulate the operating state of the motor under different loads, and the iron loss data under each load condition is calculated. Finally, the iron loss data obtained by simulation is compared and corrected with the actual load test data, and a comprehensive analysis is performed to obtain an accurate load iron loss value, i.e., load iron loss.

[0036] Furthermore, the iron loss data obtained by simulation is compared and corrected with the actual load test data, specifically including: by comparing the simulation results with the actual test results, adjusting the parameters in the simulation model to improve the simulation accuracy, thereby obtaining a more accurate motor load iron loss value.

[0037] For example, in simulation, different load conditions (such as different currents and voltages) are set for the motor to simulate its operation and calculate the iron loss under these load conditions. For example, the simulated iron loss of the motor at a speed measurement point of 1000 rpm is 10W, and the simulated iron loss at a speed measurement point of 2000 rpm is 25W. At the same time, in an actual load test, the iron loss of the motor is measured at the same speed. For example, the actual measured iron loss is 12W at a speed measurement point of 1000 rpm and 28W at a speed measurement point of 2000 rpm. In this scenario, by comparing the iron loss data of the simulation and actual test, it is found that the simulation results are lower than the actual test results. For example, the iron loss measured at a speed measurement point of 1000 rpm in the simulation is 10W, while the actual value is 12W, a difference of 2W. The iron loss measured at a speed measurement point of 2000 rpm in the simulation is 25W, while the actual value is 28W, a difference of 3W. Based on the comparison results between the iron loss data obtained from the simulation and the actual load test data, the relevant parameters of the motor in the three-dimensional model are adjusted, including but not limited to material parameters, air gap settings, and electromagnetic parameters. After that, the simulation is run again, which may result in more accurate results. For example, after adjustment, the simulated iron loss value at the speed measurement point of 1000rpm is close to 12W, and the iron loss value at the speed measurement point of 2000rpm is close to 28W. In this way, through the comparison and correction of the comprehensive simulation data and the actual test data, a more accurate load iron loss value is finally obtained. In addition, through the correction of actual data, the accuracy of the simulation model has been improved, and it can be better used to predict the load iron loss at other speed measurement points in the future.

[0038] This embodiment of the application uses a simulation tool to build a three-dimensional model of the motor, simulate its operating state under different load conditions, and calculate and obtain load iron loss data. The simulation results are then compared and corrected with actual test data to ultimately obtain accurate load iron loss values. This achieves the beneficial effect of isolating and accurately measuring the motor's load iron loss, providing a reliable basis for motor design and optimization.

[0039] The motor loss can be measured by measuring the efficiency performance diagram of the motor at rated voltage and recording the motor loss at each operating point (including the speed measurement point).

[0040] In some optional embodiments, the motor body loss is determined based on the motor operating parameters of the motor at the speed measurement point, including: when the motor operates at rated voltage, the speed and torque of the motor are adjusted accordingly using a preset speed interval and a preset step size, and an efficiency performance diagram of the motor is generated; based on the efficiency performance diagram of the motor, the input power and output power of the motor at different speeds and torques are determined; based on the input power and output power, the motor body loss is determined.

[0041] Specifically, an efficiency performance graph is a two-dimensional chart that shows the efficiency distribution of a motor under different operating conditions. It typically uses motor speed and torque as coordinate axes, and uses color gradients or contour lines to represent efficiency changes. In practice, motor operating parameters such as speed and torque are recorded at different speed and torque measurement points, and the corresponding efficiency performance graph is calculated based on these parameters.

[0042] For example, in this embodiment, a motor test is performed using a motor test bench, and the magnetized magnets are respectively installed in the rotor assembly to assemble a dynamometer. Then, the motor is controlled to work at the rated voltage to ensure that the test environment meets the standard conditions (such as ambient temperature, humidity, pressure, etc.); then, the motor speed measurement points are set from 500, 1000, 1500, 2000...maximum speed, including the inflection point speed, with a speed interval of 500rpm, and at each speed point, the torque is gradually increased from 0Nm to full load torque, such as 0, 10, 20...250Nm, with a step size of 10 Nm; when the motor reaches each measuring point (specified speed and torque), the motor is controlled to stabilize and maintain a preset time, which can be selected as 2 seconds (of course, other time values ​​can also be used in practice), and the input electrical power and output mechanical power of each measuring point (i.e., specified speed and torque) are automatically recorded to calculate efficiency. Of course, other motor operating parameters at the measuring point can also be recorded, including but not limited to DC voltage, current and power, wheel-end output speed and torque, coolant temperature and flow, oil temperature, ambient temperature, motor winding temperature, IGBT (abbreviation of Insulated Gate Bipolar Transistor in English, translated as insulated gate bipolar transistor) temperature, controller / oil pump low voltage and current, given speed and torque, etc.; finally, the software is used to automatically generate an efficiency performance graph containing all measuring points and automatically save it. Preferably, tools such as MATLAB, Excel or Python can be used to generate a two-dimensional graph, in which colors or contour lines are used to represent different efficiency areas. It is worth mentioning that the efficiency performance graph at the corresponding measuring point can be generated during the test of no-load iron loss and load iron loss.

[0043] When the efficiency performance diagram of the motor is obtained, the input power and output power at each measuring point are obtained from the efficiency performance diagram. The motor body loss is equal to the difference between the input power and the output power, so the motor body loss is calculated using the efficiency performance diagram data of the motor.

[0044] The embodiment of the present application generates a corresponding efficiency performance diagram during the motor testing process, and determines the input electrical power and output mechanical power of the motor at each measuring point from the efficiency performance diagram, and then calculates the motor's body loss based on the difference between the input electrical power and the output mechanical power, thereby achieving separate measurement of the motor's body loss at each measuring point.

[0045] In practice, although the motor's efficiency performance at rated voltage is measured to isolate the motor's losses at each side point, the accuracy of the measured motor losses still needs to be improved. For example, machine learning can be used to further optimize the measured motor losses.

[0046] In some optional embodiments, the motor body loss is determined based on the motor operating parameters of the motor at the speed measurement point, including: using the loss data of the motor at different temperatures, lubrication conditions and material wear to construct a regression model with speed, temperature, lubrication condition and material wear as independent variables and motor body loss as dependent variable; inputting the temperature, lubrication condition and material wear measurement values ​​of the motor at the speed measurement point into the regression model, and the regression model outputs the corresponding motor body loss.

[0047] Specifically, measurement data of the motor in all speed ranges are collected in advance, including mechanical loss data under different temperatures, lubrication conditions and material wear. Then, multi-factor regression analysis is used to establish a regression model of motor body loss, considering the influence of factors such as temperature, lubrication condition, material wear and so on on motor body loss.

[0048] Alternatively, the regression model of motor body loss can be expressed as:

[0049] P motor body loss = β0 + β1 * speed + β2 * temperature + β3 * lubrication state + β4 * material wear,

[0050] Among them, the regression analysis can be used to obtain the size values ​​of β0, β1, β2, β3 and β4, so that the influence of different factors can be obtained based on the regression results.

[0051] After the regression model is trained, it can be placed in the motor controller. Then, the motor operating parameters at the speed measurement point, including but not limited to speed, temperature, lubrication status and material wear, are input into the trained regression model, and the regression model outputs the corresponding motor body loss.

[0052] The embodiment of the present application uses machine learning to pre-establish a regression model with speed, temperature, lubrication status and material wear as independent variables through actual test results, so that the corresponding motor operating parameters at the speed measurement point during the motor test can be input into the regression model to obtain the motor body loss, thereby achieving the effect of separating and accurately measuring the motor body loss.

[0053] During motor operation, energy loss caused by various non-ideal factors (such as electromagnetic interference, material inhomogeneity, structural asymmetry, etc.) is called stray loss. In practice, stray loss is usually difficult to measure directly. This application will provide a separate measurement method for stray loss.

[0054] In some optional embodiments, the stray loss of the motor is determined based on the AC side electric power, including: calculating the AC side electric power of the motor; obtaining the stray loss of the motor based on the product of a preset ratio value and the AC side electric power, where the preset ratio value is less than 1.

[0055] Specifically, AC side power refers to the total power input to the motor when the motor is running. In practice, the calculation method of stray loss varies depending on the type of motor.

[0056] For example, when the motor is a single-phase AC motor, the AC side power of the motor is:

[0057] P=V*I*cos(φ);

[0058] Where V is voltage, I is current, and φ is the phase difference between current and voltage.

[0059] When the motor is a three-phase AC motor, the AC side power of the motor is:

[0060] P=3×V L ×I L ×cos(φ);

[0061] Among them, V L is the line voltage, that is, the voltage between any two phases; I L is the line current, that is, the current passing through any phase, and φ represents the phase difference between the current and the voltage.

[0062] Specifically, the preset ratio value may be a value set based on experience, and its value is greater than 0 and less than 1.

[0063] Preferably, the stray loss of the motor can be calculated using the following formula:

[0064] P 杂散损耗 =0.5%×P 交流侧电功率 .

[0065] The embodiment of the present application calculates the stray loss through a preset empirical formula combined with empirical values, thereby achieving the beneficial effect of separating and accurately measuring the stray loss.

[0066] During the motor loss separation test, in addition to separately measuring the motor body loss, no-load iron loss, load iron loss and stray loss, the motor's copper loss can also be further measured.

[0067] In some optional embodiments, the above-mentioned motor loss separation test method also includes: determining the copper loss of the motor based on the motor body loss, no-load iron loss, load iron loss and stray loss; output copper loss and assembly iron loss, the assembly iron loss also includes copper loss.

[0068] Specifically, copper loss, also known as copper loss, refers to the energy loss caused by resistance when current passes through the winding coil in a motor or transformer. Preferably, based on the measured motor body loss, no-load iron loss, loaded iron loss and stray loss, the motor's copper loss can be calculated using the following formula:

[0069] Copper loss = motor body loss - stray loss - load iron loss - no-load loss.

[0070] By separately measuring the copper loss of the motor, the embodiment of the present application can make better decisions in the design, maintenance and operation management of the equipment, thereby improving the reliability and efficiency of the motor.

[0071] All of the above optional technical solutions can be combined in any way to form optional embodiments of the present application, and will not be described in detail here.

[0072] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0073] See also Figure 2 In a second embodiment of the present application, a motor loss separation test device is provided, comprising:

[0074] The no-load iron loss test module 201 is configured to determine the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor;

[0075] A load iron loss testing module 202 is configured to determine the load iron loss of the motor based on simulation analysis and actual load testing;

[0076] The body loss test model 203 is configured to determine the motor body loss according to the motor operating parameters at the speed measurement point;

[0077] The stray loss test module 204 is configured to determine the stray loss of the motor according to the AC side electric power;

[0078] The test result processing module 205 is configured to output no-load iron loss, loaded iron loss, motor body loss, stray loss and total iron loss respectively. The total iron loss includes the sum of no-load iron loss, loaded iron loss, motor body loss and stray loss.

[0079] According to the technical solution provided in the embodiments of the present application, the different losses and assembly losses of the motor are obtained by separating and accurately measuring the no-load iron loss, load iron loss, stray loss and mechanical loss of the motor. These separately measured different losses can provide a reliable basis for motor design and optimization, thereby helping to improve motor performance.

[0080] In some optional embodiments, the no-load iron loss test module 201 is configured to measure the drag torque of the motor at each speed in a non-magnetized state; measure the mechanical torque of the motor at each speed in a magnetized state; and determine the no-load iron loss at the corresponding speed based on the drag torque and the mechanical torque.

[0081] In some optional embodiments, the load iron loss test module 202 is configured to construct a three-dimensional model of the motor; simulate the operating state of the motor under different loads according to the three-dimensional model, and determine the simulated iron loss data of the motor under each load; and determine the load iron loss of the motor under the corresponding load according to the actual load test data and the simulated iron loss data.

[0082] In some optional embodiments, the above-mentioned body loss test model 203 is configured to adjust the speed and torque of the motor accordingly using a preset speed interval and a preset step size when the motor operates at rated voltage, and generate an efficiency performance diagram of the motor; based on the efficiency performance diagram of the motor, determine the input power and output power of the motor at different speeds and torques; and determine the motor body loss based on the input power and output power.

[0083] In some optional embodiments, the motor loss test model 203 is configured to utilize motor loss data at different temperatures, lubrication conditions, and material wear to construct a regression model with speed, temperature, lubrication condition, and material wear as independent variables and motor loss as a dependent variable. The motor speed, temperature, lubrication condition, and material wear detected at the speed measurement point are input into the regression model, which then outputs the corresponding motor loss.

[0084] In some optional embodiments, the stray loss test module 204 is configured to calculate the AC side electric power of the motor; the stray loss of the motor is obtained according to the product of a preset ratio value and the AC side electric power, and the preset ratio value is less than 1.

[0085] In some optional embodiments, the motor loss separation testing device further includes:

[0086] The motor copper loss test module 206 is configured to determine the motor copper loss based on the motor body loss, no-load iron loss, load iron loss and stray loss; output the copper loss and the total iron loss, where the total iron loss also includes the copper loss.

[0087] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0088] See also Figure 3 and Figure 4In a third embodiment of the present application, a motor loss separation test system is provided, which is applied to a car 3 including a motor, a motor controller, a vehicle controller, a battery management system, a power battery, and a power control system. The motor loss separation test system includes a motor test bench 41, multiple sensors 42, a data acquisition system 43, and a data analysis device 44. The motor is connected to the motor test bench 41 in a transmission manner, the sensor 42 is installed on the motor test bench, the data acquisition system 43 is connected to the sensor, and the data analysis device 44 is connected to the data acquisition system 43. The data analysis device 44 at least includes a processor 441, a memory 442, and a computer program 443 stored in the memory 442 and executable on the processor 441. When the processor 441 executes the computer program 443, the steps of the above-mentioned method embodiments are implemented. Alternatively, when the processor 441 executes the computer program 443, the functions of the modules in the above-mentioned device embodiments are implemented.

[0089] Specifically, in a car, the power battery provides power, and the battery management system (BMS) monitors the battery status and performs balancing management. The BMS transmits the battery's energy, high-voltage power-on and power-off instructions, and allowed charge and discharge power to the vehicle control unit (VCU). As the core control unit, the VCU comprehensively coordinates the operation of the entire electric system, receives data from the BMS, and sends instructions such as switch and energy conversion status and accelerator pedal opening to the power control system. At the same time, the VCU transmits torque and torque setting instructions to the motor controller (MCU), and receives motor status feedback from the MCU. The MCU controls the operation of the motor and maintains data exchange with the motor test bench and motor to ensure the normal operation and status feedback of the motor. In the embodiment of the present application, a real-time temperature compensation algorithm is added between the VCU and the MCU to ensure efficient operation and stability of the motor and battery under different temperature conditions. In addition, the VCU has an intelligent load distribution function that can dynamically adjust energy distribution according to battery status and motor requirements to improve the overall efficiency and life of the system. This application also introduces a multi-redundant control mechanism to ensure that if any control unit fails, the system automatically switches to a backup control mode to maintain normal vehicle operation. Tightly integrating the power control system with the VCU optimizes energy conversion and transmission paths, reduces energy loss, and improves system response speed.

[0090] In practice, in addition to the motor test bench, it generally also includes a motor test bench with variable speed control, which is used to install the motor under test and can run at different speeds.

[0091] In addition, sensors installed on the motor test bench include but are not limited to torque sensors, temperature sensors, and current sensors. The torque sensor is mounted on the motor output shaft to measure the motor's output torque at different speeds. Temperature sensors are located in key areas of the motor, such as the windings and core, to measure the motor's temperature. Current sensors are used to measure the motor's input current and phase current.

[0092] The data acquisition system includes but is not limited to high-precision data acquisition cards and data processing software, which are used to collect and store sensor data in real time.

[0093] The data analysis device includes, but is not limited to, a high-performance computer and specialized analysis software, which is used to process and analyze the collected data and isolate various losses. Optionally, in some embodiments, the data analysis device is used to perform simulation analysis in conjunction with finite element analysis software, compare and calibrate the data with actual load test data, and obtain accurate load iron loss values, providing a reliable basis for motor design and optimization.

[0094] The data analysis device may include but is not limited to a processor 441 and a memory 442. It will be understood by those skilled in the art that Figure 4 This is merely an example of the electronic device 4 and does not limit the electronic device 4 . The electronic device 4 may include more or fewer components than shown in the figure, or different components.

[0095] The processor 441 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0096] Memory 442 can be an internal storage unit of electronic device 4, such as a hard drive or memory of electronic device 4. Memory 442 can also be an external storage device of electronic device 4, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Memory 442 can also include both an internal storage unit of electronic device 4 and an external storage device. Memory 442 is used to store computer programs and other programs and data required by the electronic device.

[0097] The technical solutions provided in the embodiments of the present application have at least the following beneficial effects:

[0098] 1. Accurately separate and measure various motor losses through high-precision data acquisition system and professional analysis software.

[0099] 2. Real-time temperature compensation algorithm ensures efficient operation and stability under different temperature conditions.

[0100] 3. Multiple redundant control mechanisms ensure that the system can automatically switch to backup mode when the control unit fails, maintaining normal operation and improving system reliability.

[0101] 4. Intelligent load distribution function dynamically adjusts energy distribution, improves overall system efficiency and life, and reduces energy loss.

[0102] 5. Combine simulation analysis and actual testing to reduce the number of repeated tests, saving time and cost.

[0103] 6. Comprehensive sensor data monitoring and high-precision analysis and processing to ensure safe motor operation.

[0104] 7. Suitable for various types of motors, with wide applicability and compatibility.

[0105] 8. Compact test device design and optimized energy conversion and transmission paths reduce system footprint.

[0106] In addition, those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional modules in the embodiment can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated module is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium (such as a computer-readable storage medium). Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, which may be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0108] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A motor loss separation test method, characterized in that: include: Determine the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor; Determine the motor's load iron loss based on simulation analysis and actual load testing; determining the motor body loss according to the motor operating parameters at the speed measurement point; Determine the stray loss of the motor based on the AC side electric power; The no-load iron loss, loaded iron loss, motor body loss, stray loss and assembly iron loss are output respectively, and the assembly iron loss includes the sum of the no-load iron loss, loaded iron loss, motor body loss and stray loss.

2. The method according to claim 1, characterized in that Based on the mechanical torque and drag torque at each speed measurement point of the motor, determine the no-load iron loss of the motor at the corresponding speed measurement point, including: Measure the drag torque of the motor at each speed when it is not magnetized; Measure the mechanical torque of the motor at each speed in the magnetized state; The no-load iron loss at the corresponding speed is determined according to the drag torque and the mechanical torque.

3. The method according to claim 1, characterized in that Based on simulation analysis and actual load testing, the motor's load iron loss is determined, including: Build a 3D model of the motor; Simulate the motor's operating state under different loads based on the three-dimensional model and determine the simulated iron loss data of the motor under each load; The load iron loss of the motor under the corresponding load is determined based on the actual load test data and the simulated iron loss data.

4. The method according to claim 1, wherein Determining the motor body loss according to the motor operating parameters at the speed measurement point includes: When the motor is operating at rated voltage, the motor speed and torque are adjusted accordingly using a preset speed interval and a preset step size, and an efficiency performance graph of the motor is generated; According to the motor's efficiency performance diagram, determine the motor's input power and output power at different speeds and torques; The motor body loss is determined according to the input power and the output power.

5. The method according to claim 1, characterized in that Determining the motor body loss according to the motor operating parameters at the speed measurement point includes: Using the loss data of the motor under different temperatures, lubrication conditions and material wear, a regression model is constructed with speed, temperature, lubrication condition and material wear as independent variables and motor body loss as the dependent variable. The speed, temperature, lubrication state and material wear of the motor detected at the speed measurement point are input into the regression model, and the regression model outputs the corresponding motor body loss.

6. The method according to claim 1, characterized in that Determine the stray losses of the motor based on the AC side power, including: Calculate the AC side electric power of the motor; The stray loss of the motor is obtained according to the product of a preset ratio value and the AC side electric power, and the preset ratio value is less than 1.

7. The method according to any one of claims 1 to 6, characterized in that Also includes: Determine the motor's copper loss based on the motor's body loss, no-load iron loss, loaded iron loss, and stray loss; The copper loss and the total iron loss are output, wherein the total iron loss also includes the copper loss.

8. A motor loss separation test device, characterized in that: include: The no-load iron loss test module is configured to determine the no-load iron loss of the motor at the corresponding speed measurement point based on the mechanical torque and drag torque at each speed measurement point of the motor; A load iron loss test module is configured to determine the load iron loss of the motor based on simulation analysis and actual load testing; a body loss test model configured to determine the motor body loss based on the motor operating parameters at the speed measurement point; a stray loss test module configured to determine the stray loss of the motor based on the AC side electric power; The test result processing module is configured to output the no-load iron loss, loaded iron loss, motor body loss, stray loss and assembly iron loss respectively, and the assembly iron loss includes the sum of the no-load iron loss, loaded iron loss, motor body loss and stray loss.

9. A motor loss separation test system, applied to a vehicle including a motor, a motor controller, a vehicle controller, a battery management system, a power battery, and a power control system, the motor loss separation test system comprising a motor test bench, multiple sensors, a data acquisition system, and a data analysis device, wherein the motor is drivingly connected to the motor test bench, the sensors are mounted on the motor test bench, the data acquisition system is connected to the sensors, and the data analysis device is connected to the data acquisition system, and the data analysis device comprises at least: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.

10. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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