Motor temperature calibration method, system and device and storage medium

Abstract

The invention relates to the technical field of equipment health management, in particular to a motor temperature calibration method, system and equipment and a storage medium. The method comprises the following steps: acquiring design parameters, material characteristic information and application demand information of a motor; analyzing the structure and thermal characteristics of the motor, and determining the position information of a plurality of temperature acquisition points; acquiring various operation condition information set by the motor; temperature data are acquired in real time through temperature sensors arranged on the temperature acquisition points; processing the temperature data, and establishing a mathematical model between the motor temperature and the working condition parameters according to the processed temperature data; according to the design parameters, the material characteristic information and the application demand information of the motor, safe temperature intervals of the motor under different operation conditions are calculated and determined; and applying the established mathematical model and the safe temperature interval to a control system of the motor. The application has the effect of improving the safety and health management efficiency and accuracy of the motor application.

Description

Technical Field

[0001] The present application relates to the technical field of equipment health management, and in particular to a motor temperature calibration method, system, equipment and storage medium. Background Art

[0002] In electric aircraft, especially EVTO products, the motor is one of the core components, and its performance and safety are of vital importance. In low-voltage platform applications, it is common to open windows in the motor housing and use propeller airflow to dissipate heat. However, in high-voltage platform applications, for electrical safety and insulation considerations, the motor must have a protection level of IP65 or above, that is, the motor housing must be sealed, which makes monitoring the internal temperature of the motor the key to ensuring application safety.

[0003] In the current conventional motor design, a temperature sensor is usually built into the motor, and the external control device monitors the motor temperature by reading the sensor data. This is a common practice in the industry. However, in some important application scenarios, although there are designs with two or more temperature sensors built into the motor, there are problems such as complex wiring layout, cumbersome interfaces and wiring processes, and it is impossible to cover the temperature collection of multiple heating areas inside the motor by unlimitedly adding sensors. Therefore, the efficiency and accuracy of motor application safety and health management are low.

[0004] Therefore, based on the above problems, the prior art still needs to be improved. Summary of the invention

[0005] The purpose of this application is to provide a motor temperature calibration method, system, device and storage medium, aiming to solve the problem of low efficiency and accuracy in the application safety and health management of motors.

[0006] The first object of this application is to provide a motor temperature calibration method, comprising: Obtain the motor's design parameters, material properties, and application requirements; Analyze the structure and thermal characteristics of the motor to determine the location information of several temperature collection points; Acquiring various operating condition information set for the motor; Acquire temperature data in real time through the temperature sensor provided at the temperature collection point; Processing the temperature data, and establishing a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; Calculate and determine the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; The established mathematical model and safe temperature range are applied to the control system of the motor.

[0007] By adopting the above technical solutions, the design parameters, material property information and application requirement information of the motor are fully obtained, providing accurate basic data for subsequent temperature calibration, so that the calibration results are more in line with the actual application scenarios. Analyzing the motor structure and thermal characteristics to determine the temperature collection points can ensure that the collected temperature data accurately reflects the temperature changes of key parts inside the motor. Obtaining a variety of operating condition information and obtaining temperature data in real time through temperature sensors provides rich data support for establishing accurate mathematical models. The mathematical model between the motor temperature and the operating parameters established after processing the temperature data can accurately predict the temperature changes of the motor under different operating conditions, providing a basis for taking temperature control measures in advance. The safe temperature range calculated based on various information can ensure that the motor is always within the safe temperature range under different operating conditions, avoiding damage to the motor due to excessive temperature. Finally, the mathematical model and safe temperature range are applied to the motor control system to realize real-time monitoring and intelligent control of the motor temperature, improve the safety, stability and reliability of the motor, and extend the service life of the motor. At the same time, it also provides a more reliable temperature management solution for application scenarios with high requirements for motor performance, such as electric aircraft.

[0008] In a possible implementation manner of the present application, the step of analyzing the structure and thermal characteristics of the motor and determining the position information of a plurality of temperature collection points includes: Acquiring structural information, thermal characteristic data and cooling system parameters of the motor; Combining the structural information, thermal characteristic data and cooling system parameters of the motor, analyzing the specific impact of the heat dissipation method and cooling system on the temperature distribution of the motor, and obtaining analysis results; Based on the analysis result, the position of the temperature collection point is dynamically adjusted.

[0009] By adopting the above technical solution, the structural information, thermal characteristics data and cooling system parameters of the motor can be obtained, and the physical characteristics and working environment of the motor can be fully understood, providing a rich information basis for accurately determining the temperature collection points. By combining this information for analysis, we can deeply understand the specific impact of the heat dissipation method and cooling system on the temperature distribution of the motor, so as to obtain more targeted analysis results. Based on this analysis result, the position of the temperature collection point is dynamically adjusted to ensure that the collected temperature data more accurately reflects the key temperature change area of ​​the motor under different working conditions. This can improve the reliability and effectiveness of the temperature data and provide a more accurate basis for the subsequent establishment of an accurate mathematical model and the determination of a safe temperature range. At the same time, the dynamic adjustment of the position of the temperature collection point also makes the temperature monitoring more flexible to adapt to the actual operation of the motor, which helps to timely discover potential temperature problems and take corresponding control measures, improve the safety and stability of the motor, extend the service life of the motor, and provide a strong guarantee for the reliable operation of the motor in various complex application scenarios.

[0010] In a possible implementation manner of the present application, the steps after calculating and determining the safe temperature range of the motor under different operating conditions include: Acquiring insulation material characteristic data of the motor, including initial insulation performance parameters, material aging rate model, and usage time record of the motor; At the same time, historical temperature data and corresponding operating parameters of the motor under different operating conditions are obtained; Based on the insulation material characteristic data, the aging degree of the insulation material is calculated, and the influence trend of the material aging on the motor temperature is analyzed in combination with the historical temperature data and the operating condition parameters; Based on the impact trend, the safe temperature range is adjusted.

[0011] By adopting the above technical solution, the insulation material characteristic data of the motor is obtained, including the initial insulation performance parameters, the material aging rate model and the motor usage time record, so as to accurately grasp the performance changes of the motor insulation material. At the same time, the historical temperature data and corresponding operating parameters of the motor under different operating conditions are obtained, providing comprehensive data support for the analysis. The degree of aging of the insulation material is calculated based on the insulation material characteristic data, and the influence trend of material aging on the motor temperature is analyzed in combination with the historical temperature data and operating parameters, so that the understanding of the motor temperature change is more in-depth and accurate. Adjusting the safe temperature range based on the influence trend can ensure that the motor is always within the safe temperature range under different operating conditions, and effectively prevent the abnormal temperature increase caused by the aging of the insulation material from damaging the motor. This not only improves the safety and reliability of the motor and extends the service life of the motor, but also provides a strong guarantee for the stable operation of the motor in various complex working environments.

[0012] In a possible implementation manner of the present application, the method further includes: Continuously obtain real-time temperature data, operating parameters and performance index data of the motor under different operating conditions; Obtaining test data of the motor under various actual verification scenarios, including test results simulating different environmental conditions and load changes; Based on the real-time temperature data, operating parameters and performance index data of the motor, obtaining the prediction result of the mathematical model; Comparing the prediction result with the test result to obtain a comparison result; Based on the comparison result, the mathematical model is updated online, and the parameters of the mathematical model are adjusted using an incremental learning algorithm to adapt to the operating state of the motor in an actual verification scenario.

[0013] By adopting the above technical solutions, the real-time temperature data, operating parameters and performance index data of the motor under different operating conditions can be continuously obtained, so that the operating status of the motor can be mastered in real time, providing the latest basis for accurate analysis and adjustment. The test data of the motor in various actual verification scenarios, including the test results simulating different environmental conditions and load changes, enriches the data source and makes the analysis more comprehensive. The prediction results of the mathematical model are obtained based on real-time data, and compared with the test results, so that the deviations and deficiencies of the model can be discovered in time. The mathematical model is updated online based on the comparison results, and the model parameters are adjusted using the incremental learning algorithm, so that the mathematical model can quickly adapt to the operating status of the motor under the actual verification scenario, improving the accuracy and reliability of the model. This ensures that the motor can obtain accurate temperature prediction and effective control under different working conditions and environments, improves the safety, stability and adaptability of the motor, and extends the service life of the motor, providing a strong guarantee for the reliable operation of the motor in complex and changeable application scenarios.

[0014] In a possible implementation manner of the present application, the method further includes: Obtaining the prediction results of the mathematical model and the corresponding actual temperature data in different time periods; Performing deviation analysis on the prediction result and the actual temperature data; The improvement effect of the mathematical model is determined based on the deviation analysis results. If the deviation is within an acceptable range, the mathematical model continues to be used for temperature prediction and safe temperature range adjustment. If the deviation exceeds the acceptable range, the data characteristics and model parameters are re-analyzed and the mathematical model is optimized and adjusted.

[0015] By adopting the above technical solution, the prediction results of the mathematical model and the corresponding actual temperature data in different time periods are obtained, which provides a rich basis for evaluating the accuracy and reliability of the model. Deviation analysis of the prediction results and actual temperature data can accurately quantify the degree of deviation of the model, and then determine the improvement effect of the mathematical model based on the deviation analysis results. If the deviation is within an acceptable range, the mathematical model can continue to be used for temperature prediction and safe temperature range adjustment to ensure that the motor operates in a stable state, thereby improving the efficiency and safety of the motor operation. When the deviation exceeds the acceptable range, the data characteristics and model parameters are re-analyzed and optimized, so that the mathematical model can continuously adapt to the actual operating conditions of the motor and improve the accuracy and adaptability of the model. This dynamic adjustment mechanism makes the motor temperature calibration method more scientific and accurate, and provides a strong guarantee for the safe operation of the motor under various complex working conditions.

[0016] In a possible implementation manner of the present application, the method further includes: Obtain the temperature changes during the actual operation of the motor and the adjustment of the safe temperature range; The temperature changes and the adjustment of the safe temperature range are fed back to the motor design and manufacturing process.

[0017] By adopting the above technical solution, the temperature changes and the adjustment of the safe temperature range during the actual operation of the motor can be obtained, and real-time monitoring information can be provided for the operating status of the motor. Feeding this information back to the motor design and manufacturing process can allow the designers and manufacturers to understand the performance of the motor in actual use, and provide a basis for further optimizing the design and manufacturing of the motor. This helps to improve the structure, heat dissipation method, and insulation materials of the motor, and improve the reliability and durability of the motor. At the same time, timely feedback can also prompt the designers and manufacturers to continuously improve the temperature calibration method to make it more adaptable to different application scenarios and working conditions, thereby improving the overall performance and quality of the motor, and laying a solid foundation for the safe and stable operation of the motor in various complex environments.

[0018] In a possible implementation manner of the present application, the method further includes: Obtain relevant data for motor temperature calibration, including motor structure and thermal characteristics analysis results, temperature collection point locations, mathematical model establishment and update process, and dynamic adjustment of safe temperature range; Generate a visual interface to display the relevant data of the motor temperature calibration.

[0019] By adopting the above technical solution, relevant data of motor temperature calibration are obtained, covering motor structure and thermal characteristics analysis results, temperature collection point location, mathematical model establishment and update process, and dynamic adjustment of safe temperature range, etc., providing a rich information basis for a comprehensive understanding of motor temperature calibration. Generate a visual interface to display these relevant data, so that users can intuitively grasp the various links and states of motor temperature calibration, and facilitate real-time monitoring of motor operation. The visual interface helps to quickly discover potential problems and anomalies, and take corresponding measures to adjust and optimize in time. At the same time, it also provides convenient tools for motor design, manufacturing and maintenance personnel, facilitating their data analysis and decision-making, and improving work efficiency and accuracy. This solution further enhances the practicality and reliability of the motor temperature calibration method, and provides a strong guarantee for the safe and stable operation of the motor.

[0020] The second object of this application is to provide a motor temperature calibration system, the system comprising: Motor information acquisition module: obtains motor design parameters, material property information and application requirement information; Temperature collection point determination module: analyzes the structure and thermal characteristics of the motor and determines the location information of several temperature collection points; A module for acquiring information of various operating conditions: acquiring information of various operating conditions set for the motor; Temperature data acquisition module: acquires temperature data in real time through the temperature sensor set at the temperature collection point; Mathematical model building module: processes the temperature data, and builds a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; A safe temperature range calculation module: calculates and determines the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; Motor control system application module: applies the established mathematical model and safe temperature range to the motor control system.

[0021] By adopting the above technical solutions, the design parameters, material property information and application requirement information of the motor are fully obtained, providing accurate basic data for subsequent temperature calibration, so that the calibration results are more in line with the actual application scenarios. Analyzing the motor structure and thermal characteristics to determine the temperature collection points can ensure that the collected temperature data accurately reflects the temperature changes of key parts inside the motor. Obtaining a variety of operating condition information and obtaining temperature data in real time through temperature sensors provides rich data support for establishing accurate mathematical models. The mathematical model between the motor temperature and the operating parameters established after processing the temperature data can accurately predict the temperature changes of the motor under different operating conditions, providing a basis for taking temperature control measures in advance. The safe temperature range calculated based on various information can ensure that the motor is always within the safe temperature range under different operating conditions, avoiding damage to the motor due to excessive temperature. Finally, the mathematical model and safe temperature range are applied to the motor control system to realize real-time monitoring and intelligent control of the motor temperature, improve the safety, stability and reliability of the motor, and extend the service life of the motor. At the same time, it also provides a more reliable temperature management solution for application scenarios with high requirements for motor performance, such as electric aircraft.

[0022] The third object of this application is to provide a motor temperature calibration device, which includes: A memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the above-mentioned motor temperature calibration method.

[0023] The fourth objective of this application is to provide a storage medium.

[0024] The fourth application objective of this application is achieved through the following technical solutions: A storage medium stores a computer program that can be loaded by a processor and execute the above-mentioned motor temperature calibration method.

[0025] In summary, the present application includes at least one of the following beneficial technical effects: 1. Improved the intelligent management level of motors. Through comprehensive acquisition, analysis and processing of various motor data, as well as continuous updating and adjustment of mathematical models and safe temperature ranges, intelligent monitoring and control of motor temperature is achieved. This intelligent management can reduce the need for manual intervention, reduce the risk of operational errors, improve the stability and reliability of motor operation, and provide strong support for the application of motors in automated production and complex systems.

[0026] 2. Enhanced the adaptability of the motor to different application environments. This technical solution takes into account multiple factors such as the motor's structure, thermal characteristics, insulation material aging, and changes in operating conditions, and can be dynamically adjusted according to different application requirements and environmental conditions. Whether in a closed environment on a high-voltage platform or in a complex and changing working scenario, it can ensure that the motor operates within a safe temperature range, broadening the application range of the motor and improving the versatility and practicality of the motor in different fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a motor temperature calibration method provided in an embodiment of the present application; Figure 2 It is a virtual structural diagram of a motor temperature calibration system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0029] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0030] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0031] The present application provides a method for calibrating motor temperature. Figure 1 , the main process of the method is described as follows: S1: Obtain the design parameters, material property information and application requirement information of the motor; The detailed design parameters of the motor are obtained, including but not limited to the power, speed, voltage, current and other parameters of the motor. The material property information used in the motor is collected, such as the heat resistance and thermal conductivity of the insulation material, as well as the material properties of the motor housing, windings and other components. According to actual needs, the application requirement information of the motor is preset, including the use environment, workload, and operating time requirements of the motor. S2: Analyze the structure and thermal characteristics of the motor and determine the position information of several temperature collection points; Among them, the structural information of the motor is obtained based on the three-dimensional image of the motor, including the motor's external dimensions, internal structure, heat dissipation channels, etc. The thermal characteristic data of the motor is obtained, such as thermal conductivity, heat capacity, etc. The cooling system parameters of the motor are obtained, such as cooling method, flow rate of cooling medium, temperature, etc. The structural information, thermal characteristic data and cooling system parameters of the motor are combined, and the specific influence of the heat dissipation method and cooling system on the temperature distribution of the motor is analyzed using thermal analysis algorithms or theoretical calculation methods. According to the analysis results, several key locations are determined as temperature collection points, such as hot spots of motor windings, bearing parts, shell surfaces, etc.

[0032] S3: Acquiring various operating condition information set for the motor; Among them, various operating conditions that the motor may face in actual applications are obtained, including different load conditions, speed ranges, ambient temperatures, etc. Through experiments or simulations, the operating parameters of the motor under different operating conditions, such as current, voltage, power, etc., are determined. The data is stored in the database and called when the system obtains various operating condition information set for the motor.

[0033] S4: acquiring temperature data in real time through a temperature sensor provided at the temperature collection point; Among them, install appropriate temperature sensors, such as thermocouples, thermal resistors, etc., at the determined temperature collection points. Connect the temperature sensor to the data acquisition system to ensure that temperature data can be collected in real time. Set the frequency and time interval of data collection, and determine the appropriate collection parameters according to the operating characteristics and requirements of the motor.

[0034] S5: Processing the temperature data, and establishing a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; Among them, the collected temperature data is preprocessed, including removing outliers, filtering, calibration and other operations to ensure the accuracy and reliability of the data; the relationship between the temperature data and the operating parameters of the motor is analyzed, and a mathematical model between the motor temperature and the operating parameters is established using mathematical statistical methods or machine learning algorithms; the established mathematical model is verified and optimized, and the parameters and structure of the model are adjusted by comparing it with the actual temperature data to improve the accuracy and generalization ability of the model.

[0035] S6: Calculate and determine the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; Among them, the maximum allowable temperature and minimum operating temperature of the motor are determined in combination with the design parameters and material property information of the motor; the upper and lower limits of the safe temperature range are determined by considering the application demand information of the motor, such as workload, operating time requirements, etc.; the rationality and effectiveness of the safe temperature range are verified through experiments or simulations, and adjustments and optimizations are made according to actual conditions, and the relevant experimental data are stored in the database waiting to be called.

[0036] S7: Apply the established mathematical model and safe temperature range to the control system of the motor.

[0037] Among them, the established mathematical model and safe temperature range are input into the control system of the motor as the basis for temperature control; the control system uses the mathematical model to predict the temperature change trend of the motor based on the real-time collected temperature data and the working parameters of the motor, and takes corresponding control measures in advance, such as adjusting the motor speed, load, etc., to ensure that the motor operates within the safe temperature range; the mathematical model and safe temperature range are regularly updated and optimized to adapt to changes in motor performance and changes in the working environment. When the operator establishes a communication connection between the motor control system and the motor, by judging the model of the motor, the mathematical model and safe temperature range corresponding to the motor of this model are retrieved; the operator operates the motor through the motor control system. Even if there is no temperature sensor in the motor, the temperature calibration system can predict or simulate the temperature changes at each temperature collection point of the motor according to the actual operation of the motor, and the motor control system can timely regulate the operation of the electrode according to the safe temperature range, thereby improving the efficiency and accuracy of the application safety and health management of the motor.

[0038] Specifically, in some possible embodiments, the step of analyzing the structure and thermal characteristics of the motor and determining the position information of a plurality of temperature collection points includes: Acquiring structural information, thermal characteristic data and cooling system parameters of the motor; Combining the structural information, thermal characteristic data and cooling system parameters of the motor, analyzing the specific impact of the heat dissipation method and cooling system on the temperature distribution of the motor, and obtaining analysis results; Based on the analysis result, the position of the temperature collection point is dynamically adjusted.

[0039] Among them, obtain the structural information of the motor, understand the motor's overall dimensions, internal structure, winding layout, core structure and other detailed information, so as to facilitate subsequent thermal analysis. Obtain the temperature distribution of the motor under different working conditions, and retrieve and record the temperature of the motor surface and key parts using equipment such as infrared thermal imagers. Thermophysical parameters of motor materials, such as thermal conductivity, specific heat capacity, etc. Obtain the cooling method of the motor, such as natural cooling, air cooling, water cooling, etc., and understand the specific parameters of the cooling system, such as the fan air volume, coolant flow and temperature, etc. Check the layout and connection method of the cooling system, and record information such as the size and location of the cooling channel.

[0040] Use professional thermal analysis software, such as ANSYS, COMSOL, etc., to establish a thermal analysis model of the motor based on the motor's structural information, thermal characteristics data and cooling system parameters; consider the motor's heat source, such as winding resistance loss, core loss, etc., as well as heat dissipation pathways, such as conduction, convection and radiation, etc. in the model. In the thermal analysis model, simulate the temperature distribution of the motor under different operating conditions, including different loads, speeds, ambient temperatures, etc.; analyze the effects of the heat dissipation method and cooling system on the motor's temperature distribution, for example, the effects of the fan position and air volume on the motor surface temperature under air cooling, and the effects of the coolant flow and temperature on the motor's internal temperature under water cooling. Based on the simulation results, obtain the temperature distribution of the motor under different operating conditions, determine the hot spots and areas with large temperature gradients; analyze the effectiveness of the heat dissipation method and cooling system, and determine whether it is necessary to optimize the cooling system design or adjust the heat dissipation method.

[0041] According to the analysis results, determine the adjustment principle of the temperature collection point. For example, if the hot spot area changes, the temperature collection point should be moved to the new hot spot area; if the area with a large temperature gradient has a greater impact on the motor performance, a temperature collection point should be added to this area; according to the adjustment principle, the position of the temperature collection point is dynamically adjusted. You can use a movable temperature sensor or set multiple reserved temperature collection points on the motor so that you can adjust it as needed; during the adjustment process, ensure that the installation position of the temperature collection point is accurate and reliable and does not affect the normal operation of the motor. After adjusting the position of the temperature collection point, perform an actual operation test to verify the adjustment effect; compare the temperature data before and after the adjustment to determine whether the position of the temperature collection point is reasonable and whether it can more accurately reflect the temperature status of the motor; based on the verification results, further optimize the position of the temperature collection point to ensure the accuracy and reliability of motor temperature monitoring.

[0042] Specifically, in some possible embodiments, the steps after calculating and determining the safe temperature range of the motor under different operating conditions include: Acquiring insulation material characteristic data of the motor, including initial insulation performance parameters, material aging rate model, and usage time record of the motor; At the same time, historical temperature data and corresponding operating parameters of the motor under different operating conditions are obtained; Based on the insulation material characteristic data, the aging degree of the insulation material is calculated, and the influence trend of the material aging on the motor temperature is analyzed in combination with the historical temperature data and the operating condition parameters; Based on the impact trend, the safe temperature range is adjusted.

[0043] Among them, obtain the initial insulation performance parameters of the insulation materials used in the motor, such as insulation resistance, dielectric strength, heat resistance grade, etc.; perform insulation performance tests on new motors to verify the accuracy of the initial parameters. Obtain the aging rate model of the motor insulation material. The aging rate model is usually related to factors such as temperature, humidity, and voltage, and can be expressed in the form of mathematical formulas or graphs; consider the actual operating environment and working conditions of the motor, and make appropriate corrections and adjustments to the aging rate model. Set a timer in the motor control system or use special equipment to record the running time of the motor; when regularly maintaining and inspecting the motor, record the cumulative use time and operating history of the motor.

[0044] Extract historical temperature data from the motor's temperature monitoring system, including temperature measurements at different time points and under different operating conditions; organize and classify the temperature data, and group them according to operating conditions (such as load, speed, ambient temperature, etc.). Obtain the motor's operating parameters under different operating conditions, such as current, voltage, power, speed, load, etc.; ensure the time correspondence between the operating parameters and the historical temperature data for subsequent analysis.

[0045] According to the aging rate model of the insulation material, select an appropriate calculation method to determine the aging degree of the insulation material. Common methods include time-based aging calculation, temperature-based aging calculation, etc. Consider the impact of multiple factors on aging, such as temperature, humidity, voltage, etc., and establish a comprehensive aging calculation model; substitute the acquired motor usage time, historical temperature data and operating condition parameters into the aging calculation model to calculate the aging degree of the insulation material.

[0046] Use data analysis techniques, such as regression analysis, trend analysis, and correlation analysis, to study the relationship between material aging and motor temperature; determine appropriate analysis indicators, such as temperature change rate, maximum temperature, average temperature, etc., to better understand the impact of material aging on motor temperature. Correlate historical temperature data and operating parameters with the aging degree of insulation materials to find out the trend of the impact of material aging on motor temperature; for example, as the aging degree of insulation materials increases, the temperature of the motor may gradually increase, or the amplitude of temperature change may increase.

[0047] According to the trend of the impact of material aging on motor temperature, determine the adjustment principle of the safe temperature range. For example, if material aging causes the motor temperature to rise, the upper limit of the safe temperature range should be appropriately lowered; if the amplitude of temperature change increases, the range of the safe temperature range should be expanded. According to the adjustment principle, the safe temperature range of the motor under different operating conditions should be adjusted; when adjusting the safe temperature range, the actual operating needs and safety requirements of the motor should be considered to ensure that the adjusted safe temperature range can not only guarantee the normal operation of the motor, but also effectively prevent damage to the motor due to excessive temperature; verify and monitor the adjusted safe temperature range to ensure its effectiveness and rationality.

[0048] The effect of adjusting the safe temperature range can be verified by actual operation test, simulation analysis, etc. The temperature of the motor and the aging degree of the insulation material should be monitored regularly, and the safe temperature range should be adjusted in time according to the actual situation to ensure the safe operation of the motor.

[0049] Specifically, in some possible embodiments, the method further includes: Continuously obtain real-time temperature data, operating parameters and performance index data of the motor under different operating conditions; Obtaining test data of the motor under various actual verification scenarios, including test results simulating different environmental conditions and load changes; Based on the real-time temperature data, operating parameters and performance index data of the motor, obtaining the prediction result of the mathematical model; Comparing the prediction result with the test result to obtain a comparison result; Based on the comparison result, the mathematical model is updated online, and the parameters of the mathematical model are adjusted using an incremental learning algorithm to adapt to the operating state of the motor in an actual verification scenario.

[0050] Among them, by establishing a connection with the sensor and data acquisition system installed on the motor, the temperature, current, voltage and other data are received in real time. At the same time, the motor operating condition information, such as load condition, speed, etc., and performance index data, such as power, efficiency, etc., are obtained from the motor control system. These data are stored and sorted in chronological order for subsequent analysis. Receive test result data simulating different environmental conditions and load changes uploaded by the test equipment. These test data may include motor operation data under different temperatures, humidity, and altitudes, as well as performance data under different load types and sizes. The computer classifies and stores these test data to establish a test database. The received real-time data is input into the established mathematical model. By running the model algorithm, the temperature prediction value of the motor under the current working condition is calculated. At the same time, the performance of the motor is predicted based on the performance index data and working condition parameters. The predicted results of the mathematical model are compared with the test results point by point. For the temperature prediction value, the error between the predicted value and the test value is calculated, such as the mean absolute error, the root mean square error, etc. For the prediction of performance, the difference between the predicted power, efficiency and other indicators and the test results is compared. These errors and differences are statistically analyzed to obtain comparison results. If the comparison results show that the errors are large, the computer adjusts the parameters of the mathematical model according to the incremental learning algorithm. First, the direction and magnitude of the parameter adjustment are determined. For example, if the temperature prediction value is too high, the temperature-related parameter values ​​in the model may need to be reduced. Then, new real-time data and test data are used for training, and the model parameters are gradually adjusted to better adapt to the operating status of the motor in the actual verification scenario. During the update process, the computer continuously monitors the performance of the model to ensure that the updated model can improve the accuracy and reliability of the prediction. At the same time, the computer can also regularly verify the updated model and compare it with new test data to ensure the stability and generalization ability of the model.

[0051] Specifically, in some possible embodiments, the method further includes: Obtaining the prediction results of the mathematical model and the corresponding actual temperature data in different time periods; Performing deviation analysis on the prediction result and the actual temperature data; The improvement effect of the mathematical model is determined based on the deviation analysis results. If the deviation is within an acceptable range, the mathematical model continues to be used for temperature prediction and safe temperature range adjustment. If the deviation exceeds the acceptable range, the data characteristics and model parameters are re-analyzed and the mathematical model is optimized and adjusted.

[0052] The computer periodically retrieves the prediction results of the mathematical model for the motor temperature in different time periods from the storage system. At the same time, the actual temperature data of the corresponding time period is extracted from the real-time data record of the temperature sensor. It ensures that the prediction results and the actual temperature data correspond accurately in time to facilitate subsequent deviation analysis.

[0053] The obtained prediction results and actual temperature data are sorted and arranged in chronological order to form data pairs. For each data pair, the deviation between the predicted temperature and the actual temperature is calculated; the degree of deviation can be quantified using methods such as absolute deviation (the absolute value of the predicted value minus the actual value) and relative deviation (absolute deviation divided by the actual value); the deviations of all data pairs are statistically analyzed, and statistical indicators such as average deviation and standard deviation are calculated to understand the overall distribution of deviations.

[0054] According to the application requirements and accuracy requirements of the motor, an acceptable range of deviation is pre-set. This range can be a specific numerical interval or a threshold based on statistical indicators; compare the deviation analysis results with the acceptable range to evaluate the improvement effect of the mathematical model. If the deviation is within the acceptable range, it means that the performance of the mathematical model is good, and the model can continue to be used for temperature prediction and safe temperature range adjustment. If the deviation exceeds the acceptable range, the mathematical model needs to be optimized and adjusted.

[0055] Continue to use mathematical models for temperature prediction and safe temperature range adjustment. The computer regularly obtains new motor operation data, inputs it into the mathematical model for prediction, and dynamically adjusts the safe temperature range based on the prediction results. At the same time, the deviation is continuously monitored, and once the deviation is found to be beyond the acceptable range, the optimization and adjustment process is immediately initiated.

[0056] The computer conducts a more in-depth analysis of the motor operation data, including the distribution, trend, correlation and other characteristics of the data. Find abnormal data points or data patterns that may cause deviations, and determine whether the data needs to be preprocessed, such as removing outliers and smoothing. Check the parameter settings of the mathematical model and analyze the impact of the parameters on the prediction results. Through methods such as sensitivity analysis, it can be determined which parameters have a greater impact on the deviation so that targeted adjustments can be made. According to the analysis results of data characteristics and model parameters, the mathematical model is optimized and adjusted. The accuracy and stability of the model can be improved by adjusting the model structure, adding new feature variables, and changing the algorithm. During the optimization and adjustment process, a portion of the data is used for training and verification to ensure that the adjusted model can effectively reduce the deviation.

[0057] Specifically, in some possible embodiments, the method further includes: Obtain the temperature changes during the actual operation of the motor and the adjustment of the safe temperature range; The temperature changes and the adjustment of the safe temperature range are fed back to the motor design and manufacturing process.

[0058] Among them, the computer continuously obtains real-time temperature data from the temperature sensor installed on the motor. By analyzing these data, the temperature changes of the motor during actual operation are determined, including the temperature fluctuation range, rising trend, falling trend, etc.; the computer tracks and records the adjustment of the safe temperature range. This may include the expansion, reduction or movement of the safe temperature range due to changes in the operating conditions of the motor, the influence of environmental factors or other reasons. The computer organizes the acquired temperature changes and the adjustment of the safe temperature range, and converts the data into a format that is easy to understand and analyze. For example, temperature change curves, statistical reports, adjustment record documents, etc. can be generated; through network connections or data transmission interfaces, feedback channels are established with relevant systems in the motor design and manufacturing links. This can be a dedicated database interface, email notification, data sharing platform, etc.; the sorted feedback information is sent to the motor design and manufacturing link. Ensure the accuracy and completeness of the information, and attach relevant timestamps, motor identification and other information so that design and manufacturing personnel can accurately locate and analyze problems; after sending the feedback information, store and back up the data for subsequent query and analysis. This can provide historical data support for motor performance improvement and optimization; the computer should ensure the security and confidentiality of the data to prevent the leakage of sensitive information. At the same time, the computer can regularly generate reports summarizing the temperature changes of the motor and the adjustment of the safe temperature range, providing more comprehensive feedback and suggestions for the motor design and manufacturing process.

[0059] Specifically, in some possible embodiments, the method further includes: Obtain relevant data for motor temperature calibration, including motor structure and thermal characteristics analysis results, temperature collection point locations, mathematical model establishment and update process, and dynamic adjustment of safe temperature range; Generate a visual interface to display the relevant data of the motor temperature calibration.

[0060] Among them, the computer collects relevant data for motor temperature calibration by establishing connections with various data sources. This includes obtaining motor structure information and thermal characteristics analysis results from the motor design database; obtaining temperature collection point location data from the temperature sensor system; obtaining data on the mathematical model establishment and update process from the mathematical model storage module; and obtaining dynamic adjustment data from the safe temperature range management system; sorting and classifying the collected data to ensure that the data format is unified and easy to process. Different types of data can be stored in different data structures, such as arrays, lists, database tables, etc.; the sorted data can be stored in a local or cloud storage system for subsequent visualization and query. A database management system or a file storage system can be used to implement data storage and management.

[0061] Choose appropriate visualization tools or development frameworks to create visualization interfaces. Consider using data visualization software such as Tableau, PowerBI, etc., or programming languages ​​and graphics libraries such as Python's Matplotlib, JavaScript's D3.js, etc.; design the layout of the visualization interface based on the characteristics of the data and user needs. It can include the following parts: Motor structure display: Use a three-dimensional model or graphic to represent the structure of the motor and mark the location of the temperature collection points.

[0062] Thermal characteristics analysis results display: Display the thermal characteristics analysis results of the motor in the form of charts or graphs, such as temperature distribution curves, heat conduction paths, etc.

[0063] Mathematical model presentation: Demonstrate the process of establishing and updating the mathematical model using flowcharts, algorithm descriptions, etc.

[0064] Dynamic adjustment display of the safe temperature range: The adjustment of the safe temperature range is displayed in the form of dynamic charts or animations, allowing users to intuitively understand the impact of temperature changes on the safe range.

[0065] Data query and filtering: Provides data query and filtering functions, allowing users to query and analyze data based on specific conditions.

[0066] Data visualization: Visualize the stored motor temperature calibration data and convert it into a form suitable for display on a visualization interface. You can use different chart types, such as bar charts, line charts, pie charts, etc., to display different types of data. For complex data relationships, you can use advanced visualization techniques such as network diagrams and heat maps.

[0067] Interaction design: Add interactive features to the visualization interface so that users can interact with the data. For example, users can click on a point or area on the chart to get detailed data information; they can adjust the visualization parameters by dragging a slider or entering parameters; and they can switch between different display modes by selecting different view modes.

[0068] Testing and optimization: After generating the visual interface, test and optimize it to ensure the stability, performance, and usability of the interface. Users can be invited to test, collect feedback, and improve and perfect the interface.

[0069] Another embodiment of the present application provides a motor temperature calibration system, wherein, referring to Figure 2 , a motor temperature calibration system, comprising: Motor information acquisition module 100: acquires design parameters, material property information and application requirement information of the motor; The temperature collection point determination module 200 is used to analyze the structure and thermal characteristics of the motor and determine the position information of several temperature collection points; A plurality of operating condition information acquisition module 300 is used to acquire a plurality of operating condition information set for the motor; Temperature data acquisition module 400: acquires temperature data in real time through the temperature sensor provided at the temperature collection point; Mathematical model building module 500: processes the temperature data, and builds a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; The safe temperature range calculation module 600 calculates and determines the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; The motor control system application module 700 applies the established mathematical model and safe temperature range to the control system of the motor.

[0070] A motor temperature calibration system provided in this embodiment can implement the various steps of the aforementioned embodiment due to the functions of its modules themselves and the logical connections between each other, and thus can achieve the same technical effects as the aforementioned embodiment. The principle analysis can refer to the relevant description of the steps of the aforementioned motor temperature calibration method, which will not be repeated here.

[0071] An embodiment of the present application further provides a motor temperature calibration device, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the above-mentioned motor temperature calibration method.

[0072] An embodiment of the present application further provides a storage medium, in which a computer program capable of being loaded by a processor and executing the above-mentioned motor temperature calibration method is stored.

[0073] The storage medium provided in this embodiment can achieve the same technical effects as the aforementioned embodiments because the computer program therein implements the various steps of the aforementioned embodiments after being loaded and run on the processor. The principle analysis can be found in the relevant description of the aforementioned method steps, which will not be repeated here.

[0074] The storage medium includes, for example, various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0075] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0076] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0077] In addition, the term "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined, and is only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features.

[0078] Thus, any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0079] The embodiments of this specific implementation method are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, all equivalent changes made based on the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A motor temperature calibration method, characterized in that: include: Obtain the motor's design parameters, material properties, and application requirements; Analyze the structure and thermal characteristics of the motor to determine the location information of several temperature collection points; Acquiring various operating condition information set for the motor; Acquire temperature data in real time through the temperature sensor provided at the temperature collection point; Processing the temperature data, and establishing a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; Calculate and determine the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; The established mathematical model and safe temperature range are applied to the control system of the motor.

2. A motor temperature calibration method according to claim 1, characterized in that: The steps of analyzing the structure and thermal characteristics of the motor and determining the position information of a plurality of temperature collection points include: Acquiring structural information, thermal characteristic data and cooling system parameters of the motor; Combining the structural information, thermal characteristic data and cooling system parameters of the motor, analyzing the specific impact of the heat dissipation method and cooling system on the temperature distribution of the motor, and obtaining analysis results; Based on the analysis result, the position of the temperature collection point is dynamically adjusted.

3. A motor temperature calibration method according to claim 1, characterized in that: The steps after calculating and determining the safe temperature range of the motor under different operating conditions include: Acquiring insulation material characteristic data of the motor, including initial insulation performance parameters, material aging rate model, and usage time record of the motor; At the same time, historical temperature data and corresponding operating parameters of the motor under different operating conditions are obtained; Based on the insulation material characteristic data, the aging degree of the insulation material is calculated, and the influence trend of the material aging on the motor temperature is analyzed in combination with the historical temperature data and the operating condition parameters; Based on the impact trend, the safe temperature range is adjusted.

4. A motor temperature calibration method according to claim 1, characterized in that: The method also includes: Continuously obtain real-time temperature data, operating parameters and performance index data of the motor under different operating conditions; Obtaining test data of the motor under various actual verification scenarios, including test results simulating different environmental conditions and load changes; Based on the real-time temperature data, operating parameters and performance index data of the motor, obtaining the prediction result of the mathematical model; Comparing the prediction result with the test result to obtain a comparison result; Based on the comparison result, the mathematical model is updated online, and the parameters of the mathematical model are adjusted using an incremental learning algorithm to adapt to the operating state of the motor in an actual verification scenario.

5. A motor temperature calibration method according to claim 4, characterized in that: The method also includes: Obtaining the prediction results of the mathematical model and the corresponding actual temperature data in different time periods; Performing deviation analysis on the prediction result and the actual temperature data; The improvement effect of the mathematical model is determined based on the deviation analysis results. If the deviation is within an acceptable range, the mathematical model continues to be used for temperature prediction and safe temperature range adjustment. If the deviation exceeds the acceptable range, the data characteristics and model parameters are re-analyzed and the mathematical model is optimized and adjusted.

6. A motor temperature calibration method according to claim 4, characterized in that: The method also includes: Obtain the temperature changes during the actual operation of the motor and the adjustment of the safe temperature range; The temperature changes and the adjustment of the safe temperature range are fed back to the motor design and manufacturing process.

7. A motor temperature calibration method according to claim 4, characterized in that: The method also includes: Obtain relevant data for motor temperature calibration, including motor structure and thermal characteristics analysis results, temperature collection point locations, mathematical model establishment and update process, and dynamic adjustment of safe temperature range; Generate a visual interface to display the relevant data of the motor temperature calibration.

8. A motor temperature calibration system, characterized in that: include: Motor information acquisition module: obtains motor design parameters, material property information and application requirement information; Temperature collection point determination module: analyzes the structure and thermal characteristics of the motor and determines the location information of several temperature collection points; A module for acquiring information of various operating conditions: acquiring information of various operating conditions set for the motor; Temperature data acquisition module: acquires temperature data in real time through the temperature sensor set at the temperature collection point; Mathematical model building module: processes the temperature data, and builds a mathematical model between the motor temperature and the operating parameters according to the processed temperature data; A safe temperature range calculation module: calculates and determines the safe temperature range of the motor under different operating conditions according to the design parameters, material property information and application requirement information of the motor; Motor control system application module: applies the established mathematical model and safe temperature range to the motor control system.

9. A motor temperature calibration device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any one of the motor temperature calibration methods according to claims 1-7.

10. A storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute any one of the motor temperature calibration methods according to claims 1-7.

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