Motor parameter identification method and system and storage medium

Abstract

The invention relates to the technical field of motors, in particular to a motor parameter identification method and system and a storage medium. The method comprises the following steps: acquiring parameter values of motor parameters in different working states when a motor is in an offline state; fitting the parameter values of the motor parameters to obtain fitting curves of the motor in different working states; and in the operation process of the motor, obtaining the current parameter value of the motor parameter, and updating the current parameter value according to the fitted curve to obtain the updated current parameter value. According to the scheme, the theoretical curve can be designed in an off-line fitting mode, and then the current parameter value of the motor parameter is corrected and modified in real time by calling the fitting curve, so that the accuracy of motor parameter identification is improved, it can be ensured that the motor can keep the optimal performance in various working states, and the reliability of motor parameter identification is improved. And the purpose of high-reliability control is achieved.

Description

Technical Field

[0001] The present disclosure relates to the field of motor technology, and in particular to a motor parameter identification method, system, and storage medium. Background Art

[0002] When implementing motor control, it is necessary to determine the motor parameters as a basis, such as stator resistance, stator inductance, etc. The current methods used to determine motor parameters include offline identification and online identification. Among them, when using offline identification, the motor parameters are identified offline before the motor is running, and the motor is adjusted with a fixed proportional integral differential (PID). However, during the operation of the motor, the temperature and load of the motor itself change, thereby changing the performance of the motor itself, causing the motor parameters to change and thus generating errors; in addition, when using online identification, the state considered is not perfect, which will also lead to large errors in the identified motor parameters, thereby greatly affecting the stable control of the motor, causing the performance of the motor to decline and the efficiency to decrease. At the same time, jitter will occur, reducing the performance of the entire control system. Summary of the Invention

[0003] The present disclosure aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first objective of the present disclosure is to propose a motor parameter identification method to improve the accuracy of motor parameter identification.

[0005] The second objective of the present disclosure is to provide a motor parameter identification system.

[0006] The third objective of the present disclosure is to provide a motor control system.

[0007] A fourth object of the present disclosure is to provide a computer-readable storage medium.

[0008] A fifth object of the present disclosure is to provide a computer program product.

[0009] To achieve the above objectives, a first embodiment of the present disclosure provides a method for identifying motor parameters, comprising:

[0010] Get the parameter values of the motor parameters under different working states when the motor is offline;

[0011] Fitting the parameter values of the motor parameters to obtain fitting curves of the motor under different working conditions;

[0012] During the operation of the motor, the current parameter value of the motor parameter is obtained, and the current parameter value is updated according to the fitting curve to obtain an updated current parameter value.

[0013] Optionally, the working state includes load information and temperature, the motor parameters include stator resistance and stator inductance, and obtaining parameter values of the motor parameters under different working states when the motor is in an offline state includes:

[0014] Different levels of voltage and current are injected into the D-axis and Q-axis of the motor under different load information and temperatures to obtain the parameter values of the stator resistance and stator inductance of the motor at different levels of voltage and current under different working conditions.

[0015] Optionally, fitting the parameter values of the motor parameters to obtain fitting curves of the motor under different working states includes:

[0016] Parameter fitting is performed on the parameter values of voltage, current, load information, temperature, stator resistance, and stator inductance to obtain fitting curves of the motor under different working conditions.

[0017] Optionally, fitting the parameter values of the motor parameters includes:

[0018] Determining an acquisition time corresponding to a parameter value of the motor parameter;

[0019] Determining, according to the acquisition time, a weight corresponding to the parameter value of the motor parameter;

[0020] Performing weighted processing on the parameter values of the motor parameters according to the weights to obtain weighted parameter values;

[0021] The weighted parameter values are fitted.

[0022] Optionally, after obtaining the fitting curves of the motor in different working states, the method further includes:

[0023] Comparing parameter values in the fitting curve with parameter values of the motor parameters to obtain parameter values of a plurality of accuracy parameters, wherein the accuracy parameters include at least one of a coefficient of determination, a mean square error, and a root mean square error;

[0024] When the parameter value of the accuracy parameter is less than the parameter value of the preset parameter, the fitting curve is refitted.

[0025] Optionally, after obtaining the current parameter value of the motor parameter, the method further includes:

[0026] When the difference between the current parameter value and the preset parameter value is greater than a preset threshold, the current parameter value is discarded.

[0027] Optionally, after obtaining the current parameter value of the motor parameter, the method further includes:

[0028] The current parameter value is recorded and stored.

[0029] To achieve the above objectives, a second embodiment of the present disclosure provides a motor parameter identification system, comprising:

[0030] The parameter acquisition module is used to obtain the parameter values of the motor parameters under different working states when the motor is in an offline state;

[0031] A parameter fitting module, used for fitting the parameter values of the motor parameters to obtain a fitting curve of the motor under different working states;

[0032] The parameter identification module is used to obtain the current parameter value of the motor parameter during the operation of the motor, and update the current parameter value according to the fitting curve to obtain an updated current parameter value.

[0033] To achieve the above objectives, a third embodiment of the present disclosure provides a motor control system, comprising:

[0034] a memory for storing executable program code;

[0035] A processor is used to call and run the executable program code from the memory, so that the motor control system executes the method shown in any one of the first aspects above.

[0036] To achieve the above-mentioned purpose, the fourth aspect of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed, it implements the method shown in any one of the above-mentioned first aspects.

[0037] To achieve the above-mentioned objectives, an embodiment of the fifth aspect of the present disclosure proposes a computer program product, including a computer program, which implements the method shown in any one of the above-mentioned first aspects when executed by a processor.

[0038] In summary, the method, system and storage medium provided by the present invention design a theoretical curve through offline fitting. Then, by calling the fitting curve, the current parameter values of the motor parameters are corrected and modified in real time, thereby improving the accuracy of motor parameter identification, ensuring that the motor can maintain optimal performance under various working conditions and achieving the purpose of highly reliable control.

[0039] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and / or additional aspects and advantages of the present disclosure will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0041] Figure 1 A flow chart of a motor parameter identification method provided by an embodiment of the present disclosure;

[0042] Figure 2 A schematic diagram of the structure of a motor parameter identification system provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0044] The present disclosure is described in detail below with reference to specific embodiments.

[0045] In the first embodiment, if Figure 1 As shown, Figure 1 This is a flow chart of a motor parameter identification method provided by an embodiment of the present disclosure. The method can be implemented using a computer program and can be run on a system for performing motor parameter identification. The computer program can be integrated into an application or run as a standalone tool application.

[0046] The motor parameter identification method may be executed by a motor control system.

[0047] For example, the motor parameter identification method includes the following steps:

[0048] S101, obtaining parameter values of motor parameters under different working states when the motor is in an offline state;

[0049] According to some embodiments, the working status includes but is not limited to load information and temperature.

[0050] In some embodiments, the load information is used to indicate the load value of the motor. The load condition of the motor can be determined based on the load value. The load condition includes but is not limited to no load, light load, heavy load, etc.

[0051] For example, when the load value is less than the first load threshold, the load condition is no-load; when the load value is not less than the first load threshold and less than the second load threshold, the load condition is light load; when the load value is not less than the second load threshold and less than the third load threshold, the load condition is heavy load.

[0052] The first load threshold, the second load threshold, and the third load threshold do not specifically refer to a fixed threshold and can be determined according to actual application scenarios.

[0053] According to some embodiments, motor parameters include but are not limited to stator resistance, stator inductance, speed, torque, etc.

[0054] In some embodiments, the motor parameters may be measured at multiple different operating points of the motor to ensure the accuracy and representativeness of the data.

[0055] S102, fitting the parameter values of the motor parameters to obtain fitting curves of the motor under different working states;

[0056] According to some embodiments, the fitting curve can be used to predict the performance of the motor under unmeasured operating conditions, or it can be used as input when controlling the operation of the motor and applied to the motor control strategy. By using the fitting curve to dynamically adjust the control parameters to adapt to different operating conditions, the performance of the motor is optimized and the performance and efficiency of the motor control system are improved.

[0057] S103 , during the operation of the motor, obtaining current parameter values of the motor parameters, and updating the current parameter values according to the fitting curve to obtain updated current parameter values.

[0058] For example, during the operation of the motor, the current parameter values of the motor parameters are A1, B1 and C1, and the updated current parameter values obtained according to the fitting curve are A2, B2 and C2. The updated current parameter value A2 replaces the current parameter value A1, the updated current parameter value B2 replaces the current parameter value B1, and the updated current parameter value C2 replaces the current parameter value C1.

[0059] In summary, the method provided in this embodiment designs a theoretical curve through offline fitting. Afterwards, by calling the fitting curve, the current parameter values of the motor parameters are corrected and modified in real time, thereby improving the accuracy of motor parameter identification, ensuring that the motor can maintain optimal performance under various working conditions, achieving the purpose of highly reliable control, and can be beneficial for adjusting the performance of the motor under different working conditions, and is suitable for different application scenarios.

[0060] This embodiment also provides another motor parameter identification method, which can be executed by a motor control system.

[0061] For example, the motor parameter identification method may include the following steps:

[0062] S201, injecting different levels of voltage and current into the D-axis and Q-axis of the motor under different load information and temperatures, to obtain parameter values of the stator resistance and stator inductance of the motor under different levels of voltage and current under different working conditions;

[0063] Among them, the parameter value of the stator resistance, that is, the calculation formula of the electronic resistance value is: Among them, R S is the stator resistance, U f is the voltage value at different frequencies under a certain temperature and load, i f It is the current value at different frequencies under a certain temperature and load.

[0064] Among them, the parameter value of the stator inductance, that is, the calculation formula of the stator inductance value is: Among them, L QD is the stator inductance of the DQ axis, U fDQ is the voltage value of the DQ axis at different frequencies under a certain temperature and load, i fDQ is the current value of the DQ axis at different frequencies under a certain temperature and load, and f is the frequency.

[0065] According to some embodiments, the load value of the motor may be determined first, and then different temperatures may be applied to the motor to obtain the parameter values of the motor parameters. The following steps may be used to obtain the motor parameters of the motor under a certain load value:

[0066] S2011, use special heating equipment to heat the motor until the motor temperature rises from -40℃ to 125℃, and maintain the temperature of the motor for 30 minutes every 10℃ to ensure the internal and external temperature balance of the motor;

[0067] S2012, injecting different levels of voltage into the D-axis of the motor at different temperatures, detecting current values corresponding to the injected voltages, and calculating the stator resistance value of the motor at each voltage level;

[0068] The D-axis voltage may be injected in increments of 10% of the rated voltage of the motor, with the maximum injected voltage being 1.5 times the rated voltage.

[0069] Among them, the detection and calculation process corresponding to each voltage level can be executed multiple times to obtain a set of stator resistance values of the motor at each voltage level. The average value of the stator resistance value set is taken to obtain the stator resistance value of the motor at each voltage level, thereby improving the accuracy of obtaining the stator resistance value.

[0070] S2013, injecting voltages of different frequencies into the D-axis of the motor at different temperatures, detecting current values corresponding to the injected voltages, and calculating the stator inductance of the D-axis of the motor at each frequency level;

[0071] The D-axis voltage frequency may be injected in increments of 10% of the motor's control frequency, up to 1.5 times the control frequency.

[0072] Among them, the detection and calculation process corresponding to each frequency level can be executed multiple times to obtain a set of stator inductance values of the motor D axis at each frequency level. The stator inductance value set of the motor D axis is averaged to obtain the stator inductance value of the motor D axis at each frequency level, thereby improving the accuracy of obtaining the stator inductance value of the motor D axis.

[0073] At step S2014, voltages of different frequencies are injected into the Q-axis of the motor at different temperatures, and current values corresponding to the injected voltages are detected to calculate the stator inductance of the Q-axis of the motor at each frequency level.

[0074] The Q-axis voltage frequency can be injected in increments of 10% of the motor's control frequency, up to 1.5 times the control frequency.

[0075] Among them, the detection and calculation process corresponding to each frequency level can be executed multiple times to obtain a set of stator inductance values of the motor Q axis at each frequency level. The average value of the stator inductance value set of the motor Q axis is taken to obtain the stator inductance value of the motor Q axis at each frequency level, thereby improving the accuracy of obtaining the stator inductance value of the motor Q axis.

[0076] It should be noted that in the process of obtaining the parameter values of the motor parameters, by detecting different data, the data can also be analyzed and compared, thereby having better control quality and stronger interference suppression ability, and effectively improving the robustness of parameter identification control.

[0077] S202, performing parameter fitting on the parameter values of voltage, current, load information, temperature, stator resistance, and stator inductance to obtain fitting curves of the motor under different operating states;

[0078] According to some embodiments, the fitting curve may be a curve showing the stator resistance and stator inductance of the motor as it changes with temperature under different voltages, frequencies, and loads. The fitting curve may also be a fitting curve model including multiple curves such as a voltage-current curve and a temperature-efficiency curve.

[0079] In some embodiments, the fitting curve may be recorded and stored for subsequent use.

[0080] According to some embodiments, before fitting the parameter values of the motor parameters, the parameter values of the motor parameters may be subjected to data preprocessing to facilitate subsequent parameter fitting. The data preprocessing methods include, but are not limited to, cleaning the data, removing outliers and noise, and normalizing or standardizing.

[0081] In some embodiments, when the fitting curve is a fitting curve model, if the relationship between the motor parameters and the operating state is relatively simple, a corresponding mathematical model can be selected for fitting based on the relationship between the motor parameters and different operating states. The selectable mathematical models include, but are not limited to, linear models, polynomial models, exponential models, logarithmic models, etc. If the relationship between the motor parameters and the operating state is more complex, a nonlinear model or machine learning method can be used for fitting.

[0082] In some embodiments, the model parameters of the mathematical model may be determined by minimizing an error function (eg, least squares method) so that the mathematical model can best reflect the data points.

[0083] According to some embodiments, parameter fitting may be performed using fitting tools or library functions in statistical software or programming languages including MATLAB and Python.

[0084] In some embodiments, when fitting the parameter values of the motor parameters, the acquisition time corresponding to the parameter values of the motor parameters can also be determined; based on the acquisition time, the weights corresponding to the parameter values of the motor parameters are determined; the parameter values of the motor parameters are weighted according to the weights to obtain weighted parameter values; and the weighted parameter values are fitted. Thus, the reliability of the motor parameters can be improved.

[0085] According to some embodiments, after obtaining the fitting curve, the fitting curve may be evaluated to determine the accuracy of the fitting curve. For example, the parameter values in the fitting curve may be compared with the parameter values of the motor parameters to obtain the parameter values of multiple accuracy parameters; if the parameter value of the accuracy parameter is less than the parameter value of the preset parameter, the fitting curve may be refitted. The accuracy parameters include the coefficient of determination (R 2 ), at least one of the mean square error (MSE) and the root mean square error (RMSE).

[0086] In some embodiments, when refitting the fitting curve, the mathematical model may be reselected or the model parameters of the mathematical model may be adjusted.

[0087] S203, obtaining current parameter values of motor parameters during the operation of the motor;

[0088] According to some embodiments, sensors, including but not limited to current sensors, voltage sensors, and temperature sensors, may be installed at key locations of the motor to collect signals from these sensors to obtain current parameter values of the motor parameters.

[0089] In some embodiments, the load value of the motor can be calculated indirectly using a torque sensor or by measuring the current and voltage of the motor.

[0090] In some embodiments, a data acquisition system (DAQ) may be used to collect sensor signals, but it is necessary to ensure that the DAQ system has sufficient sampling rate and accuracy to capture rapid changes in motor operation.

[0091] In some embodiments, the collected analog signals from the sensors may be subjected to signal processing such as filtering and amplification to improve signal quality. Furthermore, the analog signals may be converted into digital signals for easier computer processing.

[0092] According to some embodiments, real-time monitoring software can be developed or used to display and record the voltage, current, temperature, load and other operating parameters of the motor, monitor the operating status of the motor in real time, and provide query and analysis functions for historical data, as well as determine the normal operating range of the current motor parameters. When it is detected that the current motor parameters exceed the normal operating range, an alarm message is issued, and abnormal detection is performed, such as trend analysis, threshold judgment, etc., to prevent potential faults. In addition, the collected data can also be fed back to the motor's frequency converter and programmable logic controller (PLC) control system, so that the motor control system can adjust the motor's operating parameters according to real-time data to achieve the optimal control effect and realize feedback control of the motor. Secondly, a remote monitoring function can also be realized, allowing engineers to remotely access the motor's operating data, which helps to discover and solve problems in a timely manner and reduce downtime.

[0093] In some embodiments, the current parameter values of the motor parameters can be recorded and stored. For example, the collected current parameter values of the motor parameters can be stored in a database to facilitate subsequent analysis and processing. For example, data analysis tools or algorithms can be used to analyze the operating trends of the motor and identify potential problems and optimization points.

[0094] According to some embodiments, motor parameters, including but not limited to voltage, current, temperature, and load, are crucial components of motor monitoring and control. Real-time acquisition and monitoring of these parameters during online motor operation can effectively improve motor efficiency, helping to ensure efficient operation, extend service life, reduce maintenance costs, and optimize performance. This also facilitates intelligent motor management and fault prevention.

[0095] In some embodiments, when the difference between the current parameter value and the preset parameter value is greater than a preset threshold, the current parameter value can be discarded and PID adjustment can be performed to control with the current actual parameter value, and the parameter fitting can be re-performed according to the new parameter value to obtain and store a new fitting curve as the basis for the next parameter.

[0096] The preset parameter value and the preset threshold value do not specifically refer to a fixed value, and can be determined according to actual application scenarios.

[0097] S204: Update the current parameter value according to the fitting curve to obtain an updated current parameter value.

[0098] According to some embodiments, the current parameter value collected in real time may be compared with the fitting curve to determine the expected parameter value under the current working state; and the motor may be controlled and adjusted in real time according to the expected parameter value.

[0099] In some embodiments, when making real-time control adjustments to a motor, a correction amount can be determined based on expected and actual parameter values. The motor's control parameters, such as the motor's pulse width modulation (PWM) signal and speed setting, can be adjusted based on the correction amount to compensate for deviations. By rapidly responding to these adjustments, the motor control system can ensure that the motor's performance is consistent with expectations, with high precision and high response speed. This provides better data for changes in motor parameters, enabling more accurate calculation of motor parameter values.

[0100] In some embodiments, by continuously monitoring motor parameters and making real-time corrections based on fitted curves, a feedback control loop can be implemented. This allows for real-time correction and adjustment, improving motor control reliability and reducing failures and downtime caused by parameter deviations. This is crucial for ensuring stable motor operation in critical applications such as industrial automation and electric vehicle drives. Furthermore, this closed-loop control mechanism helps maintain the motor in optimal operating condition, even when load or environmental conditions change.

[0101] It should be noted that by performing PID adjustments based on parameters such as motor temperature, load, and current, motor control stability can be greatly increased, motor heat and noise can be effectively reduced, and motor reliability can be improved. This theory is relatively simple and easy to understand, and has great significance for practical engineering applications. Using temperature as a basis for parameter identification and performing PID adjustments can ensure the reliability of motor parameter identification and improve the stability of the entire motor control system.

[0102] According to some embodiments, the accuracy of the fitting curve and the performance of the motor control system can be regularly evaluated, and the fitting curve can be optimized based on the evaluation results. Through continuous system optimization, the accuracy and reliability of the motor control can be further improved.

[0103] In summary, the method provided in this embodiment addresses the limitations and shortcomings of existing permanent magnet synchronous motor parameter identification methods. By monitoring changes in load, voltage, current and temperature, the parameter values of the motor parameters are calculated. At the same time, through offline fitting, a theoretical curve is designed to compensate and accurately identify the stator resistance and magnetic flux. It can accurately and timely identify the stator resistance and stator inductance of the vector motor in various operating states, and can ensure real-time monitoring of the motor's own parameters during operation and change the control parameters. It solves the system instability caused by load changes in traditional weak parameter identification methods, improves the reliability of the motor control system, improves the performance of the motor, improves the efficiency, and reduces jitter, thereby enhancing the performance of the entire motor control system.

[0104] In order to implement the above embodiments, the present disclosure also proposes a motor parameter identification system.

[0105] For example, Figure 2 This is a schematic diagram of the structure of a motor parameter identification system provided by an embodiment of the present disclosure. Figure 2 As shown, the motor parameter identification system 200 includes:

[0106] The parameter acquisition module 210 is used to obtain the parameter values of the motor parameters under different working states when the motor is in an offline state;

[0107] The parameter fitting module 220 is used to fit the parameter values of the motor parameters to obtain a fitting curve of the motor under different working states;

[0108] The parameter identification module 230 is used to obtain the current parameter value of the motor parameter during the operation of the motor, and update the current parameter value according to the fitting curve to obtain an updated current parameter value.

[0109] Optionally, the working state includes load information and temperature, and the motor parameters include stator resistance and stator inductance. The parameter acquisition module 210 is used to obtain parameter values of the motor parameters under different working states when the motor is in an offline state, specifically for:

[0110] Different levels of voltage and current are injected into the D-axis and Q-axis of the motor under different load information and temperatures to obtain the parameter values of the stator resistance and stator inductance of the motor at different levels of voltage and current under different working conditions.

[0111] Optionally, the parameter fitting module 220 is used to fit the parameter values of the motor parameters to obtain the fitting curve of the motor under different working states, specifically for:

[0112] Parameter fitting is performed on parameter values of voltage, current, load information, temperature, stator resistance, and stator inductance to obtain fitting curves of the motor under different working conditions.

[0113] Optionally, the parameter fitting module 220 includes a time acquisition submodule 221, a weight determination submodule 222, a parameter weighting submodule 223, and a parameter fitting submodule 224. The parameter fitting module 220 is configured to fit the parameter values of the motor parameters:

[0114] The time acquisition submodule 221 is used to determine the acquisition time corresponding to the parameter value of the motor parameter;

[0115] The weight determination submodule 222 is used to determine the weight corresponding to the parameter value of the motor parameter according to the acquisition time;

[0116] The parameter weighting submodule 223 is used to perform weighted processing on the parameter values of the motor parameters according to the weights to obtain weighted parameter values;

[0117] The parameter fitting submodule 224 is used to fit the weighted parameter values.

[0118] Optionally, the parameter fitting module 220 includes a parameter comparison submodule 225 and a parameter determination submodule 226. After obtaining the fitting curves of the motor under different working states:

[0119] a parameter comparison submodule 225 for comparing parameter values in the fitting curve with parameter values of the motor parameters to obtain parameter values of a plurality of accuracy parameters, wherein the accuracy parameters include at least one of a coefficient of determination, a mean square error, and a root mean square error;

[0120] The parameter determination submodule 226 is configured to refit the fitting curve when the parameter value of the accuracy parameter is less than the parameter value of the preset parameter.

[0121] Optionally, the parameter fitting module 220 includes a parameter adjustment submodule 227, which, after obtaining the current parameter values of the motor parameters:

[0122] The parameter adjustment submodule 227 discards the current parameter value when the difference between the current parameter value and the preset parameter value is greater than a preset threshold.

[0123] Optionally, the parameter fitting module 220 includes a parameter storage submodule 228, which, after obtaining the current parameter values of the motor parameters:

[0124] The parameter storage submodule 228 is used to record and store current parameter values.

[0125] It should be noted that the above explanation of the motor parameter identification method embodiment is also applicable to the motor parameter identification system of this embodiment, and will not be repeated here.

[0126] In summary, the system provided by the embodiment of the present disclosure designs a theoretical curve through offline fitting. Then, by calling the fitting curve, the current parameter values of the motor parameters are corrected and modified in real time, thereby improving the accuracy of motor parameter identification, ensuring that the motor can maintain optimal performance under various working conditions and achieving the purpose of highly reliable control.

[0127] In order to implement the above embodiments, the present disclosure also proposes a motor control system, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0128] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0129] In order to implement the above embodiments, the present disclosure further provides a computer program product, including a computer program, which implements the methods provided in the above embodiments when executed by a processor.

[0130] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this disclosure are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0131] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal data and ensure that others with access to personal data comply with its privacy policies and procedures.

[0132] This disclosure contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0133] In the descriptions of the aforementioned embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean 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 disclosure. In this specification, the schematic expressions 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, unless they are mutually inconsistent.

[0134] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0135] 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 disclosure includes additional implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0136] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or flash memory, a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0137] It should be understood that various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement the present invention: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0138] Those skilled in the art will appreciate that all or part of the steps in the method for implementing the above-mentioned embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0139] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing module, each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0140] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. A person of ordinary skill in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A motor parameter identification method, characterized in that: include: Get the parameter values of the motor parameters under different working states when the motor is offline; Fitting the parameter values of the motor parameters to obtain fitting curves of the motor under different working conditions; During the operation of the motor, the current parameter value of the motor parameter is obtained, and the current parameter value is updated according to the fitting curve to obtain an updated current parameter value.

2. The method according to claim 1, characterized in that The working state includes load information and temperature, the motor parameters include stator resistance and stator inductance, and obtaining parameter values of the motor parameters under different working states when the motor is in an offline state includes: Different levels of voltage and current are injected into the D-axis and Q-axis of the motor under different load information and temperatures to obtain the parameter values of the stator resistance and stator inductance of the motor at different levels of voltage and current under different working conditions.

3. The method according to claim 2, characterized in that The step of fitting the parameter values of the motor parameters to obtain a fitting curve of the motor under different working states includes: Parameter fitting is performed on the parameter values of voltage, current, load information, temperature, stator resistance, and stator inductance to obtain fitting curves of the motor under different working conditions.

4. The method according to claim 1, wherein The step of fitting the parameter values of the motor parameters includes: Determining an acquisition time corresponding to a parameter value of the motor parameter; Determining, according to the acquisition time, a weight corresponding to the parameter value of the motor parameter; Performing weighted processing on the parameter values of the motor parameters according to the weights to obtain weighted parameter values; The weighted parameter values are fitted.

5. The method according to claim 1, wherein After obtaining the fitting curves of the motor under different working states, the method further includes: Comparing parameter values in the fitting curve with parameter values of the motor parameters to obtain parameter values of a plurality of accuracy parameters, wherein the accuracy parameters include at least one of a coefficient of determination, a mean square error, and a root mean square error; When the parameter value of the accuracy parameter is less than the parameter value of the preset parameter, the fitting curve is refitted.

6. The method according to claim 1, wherein After obtaining the current parameter value of the motor parameter, the method further includes: When the difference between the current parameter value and the preset parameter value is greater than a preset threshold, the current parameter value is discarded.

7. The method according to claim 1, characterized in that After obtaining the current parameter value of the motor parameter, the method further includes: The current parameter value is recorded and stored.

8. A motor parameter identification system, characterized in that: include: The parameter acquisition module is used to obtain the parameter values of the motor parameters under different working states when the motor is in an offline state; A parameter fitting module, used for fitting the parameter values of the motor parameters to obtain a fitting curve of the motor under different working states; The parameter identification module is used to obtain the current parameter value of the motor parameter during the operation of the motor, and update the current parameter value according to the fitting curve to obtain an updated current parameter value.

9. A motor control system, characterized in that: The motor control system includes: a memory for storing executable program code; A processor is configured to call and run the executable program code from the memory, so that the motor control system executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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