Motor parameter identification method, motor, storage medium and air conditioner

Abstract

This application relates to the field of motor technology, specifically providing a motor parameter identification method, a motor, a storage medium, and an air conditioner. It aims to address the problems of existing online motor parameter identification methods being computationally complex, requiring high chip computing power, and unsuitable for home appliance control scenarios. To this end, the motor parameter identification method of this application, in response to motor startup, acquires motor parameters, which include at least resistance and inductance. Based on the motor parameters and / or valid motor parameters stored in a preset memory, it acquires control loop parameters, and then drives the motor to run based on these control loop parameters. When the motor is stopped, it verifies the validity of the motor parameters based on the motor's operating data, and updates the valid motor parameters in the preset memory based on the verified valid motor parameters. This application achieves motor parameter identification and self-learning, and the solution has low computational load and low resource consumption, making it suitable for cost-sensitive home appliance applications.

Description

Technical Field

[0001] This application relates to the field of motor technology, specifically providing a method for identifying motor parameters, a motor, a storage medium, and an air conditioner. Background Technology

[0002] Motor parameter identification technology has been widely used in general-purpose variable frequency control, but general-purpose inverters are expensive and difficult to apply to cost-sensitive home appliances such as air conditioners. Furthermore, existing general-purpose inverters mostly use offline parameter identification methods, lacking parameter self-adaptation and online relearning capabilities. During motor operation, due to changes in operating conditions and the environment, motor parameters can drift, leading to controller parameter mismatch. This not only reduces control performance but can also, in severe cases, cause malfunctions and shutdowns.

[0003] Current technologies attempt to address this problem. For example, a method for parameter identification of permanent magnet synchronous motors based on a population iterative algorithm is disclosed. This method constructs a theoretical model and an actual model of the permanent magnet synchronous motor, outputs corresponding current values, and builds a fitness function based on the error between the two. Then, within a set parameter range, multiple initial estimates of stator resistance, inductance, and rotor flux linkage are generated, and the population iterative algorithm is used to continuously optimize the results, ultimately obtaining a better parameter combination. However, this method relies on complex iterative calculations, placing high demands on the computing power and resources of the main control chip. It is difficult to adapt to the stringent requirements of the home appliance industry for low-cost, low-power embedded platforms, and therefore, it is not yet suitable for large-scale application in actual products.

[0004] Accordingly, a new parameter identification scheme is needed in this field to solve the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned shortcomings, this application is made to provide a solution or at least a partial solution to the technical problems of existing online motor parameter identification methods being algorithmically complex, requiring high chip computing power, and unable to meet the needs of low-cost, low-power embedded platforms in the home appliance industry.

[0006] In a first aspect, this application provides a method for identifying motor parameters, the method comprising: in response to motor startup, acquiring motor parameters; wherein the motor parameters include at least resistance and inductance; acquiring control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory; driving the motor to run based on the control loop parameters; verifying the validity of the motor parameters based on the motor's operating process data when the motor is stopped; and updating the valid motor parameters in the preset memory based on the verified valid motor parameters.

[0007] In one technical solution of the above-mentioned motor parameter identification method, the step of verifying the validity of the motor parameters based on the motor's operating process data includes: determining whether the motor's operating process data meets preset normal operating conditions; if so, determining that the motor parameters are valid, storing the valid motor parameters in a preset memory to update the valid motor parameters in the preset memory; if not, determining that the motor parameters are invalid.

[0008] In one technical solution of the above-mentioned motor parameter identification method, when the motor parameter is determined to be invalid, the method further includes: obtaining the number of consecutive times the motor parameter is determined to be invalid; if the number of consecutive times reaches a preset threshold, then the valid motor parameters in the preset memory are kept unchanged.

[0009] In one technical solution of the above-mentioned motor parameter identification method, the step of obtaining control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory includes: determining whether valid motor parameters are stored in the preset memory; if not, storing the motor parameters in the preset memory and obtaining control loop parameters based on the motor parameters; if yes, inputting the motor parameters into a filter, the filter performing a weighted fusion filtering process on the motor parameters based on the valid motor parameters stored in the preset memory, and obtaining control loop parameters based on the filtered motor parameters.

[0010] In one technical solution of the above-mentioned motor parameter identification method, the control loop parameters include current loop quadrature-axis control parameters, current loop direct-axis control parameters, speed loop proportional gain, and speed loop integral gain; obtaining the control loop parameters includes: obtaining the current loop quadrature-axis control parameters based on the resistor and the inductor; wherein the current loop quadrature-axis control parameters include quadrature-axis proportional gain and quadrature-axis integral gain; obtaining the current loop direct-axis control parameters based on the resistor and the inductor; wherein the current loop direct-axis control parameters include direct-axis proportional gain and direct-axis integral gain; obtaining the speed loop proportional gain based on the quadrature-axis proportional gain; and obtaining the speed loop integral gain based on the direct-axis proportional gain.

[0011] In one technical solution of the above-mentioned motor parameter identification method, the step of obtaining motor parameters includes: obtaining motor operating data, which includes duty cycle, bus voltage, control frequency, and current data; determining the resistance based on Kirchhoff's laws and Ohm's law using the duty cycle, bus voltage, and current data; and determining the inductance using a preset formula based on the duty cycle, bus voltage, control frequency, and current data.

[0012] In one technical solution of the above-mentioned motor parameter identification method, the method further includes: obtaining motor factory parameters; wherein the motor factory parameters include at least factory resistance and factory inductance; calculating the resistance difference between the resistance and the factory resistance, and the inductance difference between the inductance and the factory inductance; determining whether the resistance difference and the inductance difference exceed corresponding preset thresholds; if at least one of the resistance difference and the inductance difference exceeds the corresponding preset threshold, then performing a fault warning prompt and triggering shutdown protection.

[0013] In a second aspect, this application provides an electric motor, which includes a motor body, a processor, and a memory. The memory is adapted to store multiple program codes, which are adapted to be loaded and run by the processor to perform the motor parameter identification method described in any of the above-described technical solutions.

[0014] In a third aspect, this application provides a computer-readable storage medium storing a plurality of program codes adapted to be loaded and run by a processor to perform the motor parameter identification method described in any of the above-described technical solutions.

[0015] In a fourth aspect, this application provides an air conditioner that includes the motor described above.

[0016] The above-described technical solutions of this application have at least one or more of the following beneficial effects:

[0017] The motor parameter identification method of this application includes: acquiring motor parameters in response to motor startup; wherein the motor parameters include at least resistance and inductance; acquiring control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory; driving the motor to run based on the control loop parameters; verifying the validity of the motor parameters based on the motor's operation process data when the motor is stopped; and updating the preset memory based on the verified valid motor parameters. This application achieves motor parameter identification and self-learning by acquiring motor parameters at motor startup, combining them with valid parameters in the preset memory to generate control loop parameters, thereby driving the motor to run, and verifying the validity of the motor parameters using operation process data after shutdown. This effectively addresses parameter drift caused by long-term motor operation, avoids control mismatch, and significantly improves the accuracy and operational stability of motor drive control. Furthermore, compared to complex online iterative algorithms, the solution of this application has low computational load and low resource consumption, making it suitable for cost-sensitive home appliance applications. Attached Figure Description

[0018] The preferred embodiments of this application are described below with reference to the accompanying drawings, in which:

[0019] Figure 1 This is a schematic flowchart of the main steps of a motor parameter identification method according to an embodiment of this application;

[0020] Figure 2 This is a schematic diagram of a single-phase energized motor according to an embodiment of this application;

[0021] Figure 3 This is a schematic flowchart of obtaining control loop parameters according to an embodiment of this application;

[0022] Figure 4 This is a schematic diagram of a process for updating a preset memory according to an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of motor control logic according to an embodiment of this application;

[0024] Figure 6 This is a schematic block diagram of the main structure of a motor according to an embodiment of this application;

[0025] Figure 7 This is a schematic diagram of the main structure of an air conditioner according to an embodiment of this application.

[0026] List of reference numerals in the attached diagram:

[0027] 10: Motor; 11: Memory; 12: Processor. Detailed Implementation

[0028] Some embodiments of this application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application.

[0029] In the description of this application, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and can also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media includes any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0030] Currently, although motor parameter identification technology has been used in general-purpose variable frequency control, existing solutions are costly, mostly employ offline identification, and lack online adaptive capabilities. During motor operation, parameters are easily affected by operating conditions and the environment, leading to drift, decreased control performance, or even shutdown. Existing methods, such as permanent magnet synchronous motor parameter identification based on population iterative algorithms, can obtain relatively optimal parameters through optimization, but they are computationally complex and resource-intensive, making it difficult to meet the requirements of low-cost, low-power embedded platforms for home appliances, and thus not yet suitable for large-scale application.

[0031] To address this, this application provides a motor parameter identification method, comprising: acquiring motor parameters in response to motor startup; wherein the motor parameters include at least resistance and inductance; acquiring control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory; driving the motor to run based on the control loop parameters; verifying the validity of the motor parameters based on the motor's operating process data when the motor is stopped; and updating the preset memory based on the verified valid motor parameters. This application achieves motor parameter identification and self-learning by acquiring motor parameters during motor startup, combining them with valid parameters in the preset memory to generate control loop parameters, thereby driving the motor to run, and verifying the validity of the motor parameters using operating process data after shutdown. This effectively addresses parameter drift caused by long-term motor operation, avoids control mismatch, and significantly improves the accuracy and operational stability of motor drive control. Furthermore, compared to complex online iterative algorithms, the solution in this application has low computational load and low resource consumption, making it suitable for cost-sensitive home appliance applications.

[0032] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a motor parameter identification method according to an embodiment of this application. Figure 1 As shown, the motor parameter identification method in this application embodiment mainly includes the following steps S101-S105.

[0033] Step S101: In response to motor start-up, obtain motor parameters; wherein the motor parameters include at least resistance and inductance.

[0034] Step S102: Obtain control loop parameters based on the motor parameters and / or valid motor parameters stored in the preset memory.

[0035] Step S103: Drive the motor to run based on the control loop parameters.

[0036] Step S104: In the motor stopped state, verify the validity of the motor parameters based on the motor's operating process data.

[0037] Step S105: Based on the verified valid motor parameters, update the valid motor parameters in the preset memory.

[0038] Based on steps S101-S105 above, this application acquires motor parameters during motor startup, combines them with valid parameters in a preset memory to generate control loop parameters, thereby driving the motor to run. After shutdown, the validity of the motor parameters is verified using running data. This achieves motor parameter identification and self-learning, effectively addressing parameter drift caused by long-term motor operation, avoiding control mismatch, and significantly improving the accuracy and operational stability of motor drive control. Furthermore, compared to complex online iterative algorithms, this application's solution has low computational load and low resource consumption, making it suitable for cost-sensitive home appliance applications.

[0039] The following sections will provide further explanation of steps S101-S105.

[0040] Regarding step S101, in one embodiment, obtaining motor parameters includes: obtaining motor operating data, which includes duty cycle, bus voltage, control frequency, and current data; determining the resistance based on Kirchhoff's laws and Ohm's law using the duty cycle, bus voltage, and current data; and determining the inductance using a preset formula based on the duty cycle, bus voltage, control frequency, and current data.

[0041] Specifically, this involves controlling the energization of a specific phase of the motor (e.g., phase V), such as... Figure 2 As shown. Motor operating data is acquired, including the duty cycle of the target phase, bus voltage, control frequency, and current data.

[0042] According to Kirchhoff's laws, the relationship between the three-phase currents is as follows:

[0043]

[0044] In the formula, Let V be the current of the motor. This represents the current in the U-phase of the motor. This is the current in phase W of the motor.

[0045] Based on the characteristic that the three phases of the motor have the same resistance, the following can be derived:

[0046]

[0047] According to Ohm's law, we have:

[0048]

[0049] In the formula, Let V be the resistance, V be the voltage, and I be the current.

[0050] The phase voltage is obtained by multiplying the bus voltage and the duty cycle. The resistance is then calculated using the current data. In this embodiment, the calculated resistance is the phase resistance, and the formula for calculating the phase resistance is:

[0051]

[0052] In the formula, For phase resistance, is the bus voltage, duty is the duty cycle of phase V, and I is the current data.

[0053] Phase inductance can be calculated using the following formula:

[0054]

[0055] In the formula, The total impedance of the motor; For phase voltage phasors; The phase current phasor; j is the imaginary unit; Represents the motor speed; It is an inductor.

[0056] If we disregard the phase relationship, then we have:

[0057]

[0058] In the formula, f is the control frequency.

[0059] The calculation method for motor phase inductance is derived from the calculation method for phase resistance. Substituting the resistance, current data, and control frequency into the following formula determines the phase inductance. :

[0060]

[0061] See appendix Figure 3 , Figure 3 This is a detailed flowchart illustrating the steps involved in obtaining control loop parameters according to an embodiment of this application.

[0062] like Figure 3 As shown, regarding step S102, in one embodiment, obtaining control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory includes: determining whether valid motor parameters are stored in the preset memory; if not, storing the motor parameters in the preset memory and obtaining control loop parameters based on the motor parameters; if yes, inputting the motor parameters into a filter, the filter performing weighted fusion filtering on the motor parameters based on the valid motor parameters stored in the preset memory, and obtaining control loop parameters based on the filtered motor parameters.

[0063] Specifically, after obtaining the motor parameters calculated in this operation, it is determined whether valid motor parameters are stored in the preset memory. The preset memory can be an electrically erasable programmable read-only memory (EEPROM). If the preset memory does not record valid motor parameters, the motor parameters calculated in this operation are written into the preset memory, and the control loop parameters are obtained based on the motor parameters.

[0064] In one embodiment, if the preset memory does not record valid motor parameters, the motor parameters calculated this time will also be used as the initial reference values ​​of the filter to perform filtering processing on the motor parameters calculated subsequently.

[0065] If the preset memory stores valid motor parameters, these parameters are input to the filter. The filter, based on these valid motor parameters, uses a weighted fusion method to filter the resistance and inductance of the motor parameters separately. The control loop parameters are then obtained based on the filtered motor parameters. The filtering formula for the weighted fusion method is as follows:

[0066] Filter the resistors:

[0067]

[0068] In the formula, The resistor after filtering. The filter coefficients for the resistors are... The resistance is the value used in this calculation. The effective resistance stored in the preset memory.

[0069] Filter the inductor:

[0070]

[0071] In the formula, The inductor after filtering. The filter coefficient of the inductor is... For the inductance calculated in this case, The effective inductance stored in the preset memory.

[0072] In one embodiment, the control loop parameters include current loop quadrature-axis control parameters, current loop direct-axis control parameters, speed loop proportional gain, and speed loop integral gain; obtaining the control loop parameters includes: obtaining the current loop quadrature-axis control parameters based on the resistor and the inductor; wherein the current loop quadrature-axis control parameters include quadrature-axis proportional gain and quadrature-axis integral gain; obtaining the current loop direct-axis control parameters based on the resistor and the inductor; wherein the current loop direct-axis control parameters include direct-axis proportional gain and direct-axis integral gain; obtaining the speed loop proportional gain based on the quadrature-axis proportional gain; and obtaining the speed loop integral gain based on the direct-axis proportional gain.

[0073] Specifically, the quadrature-axis proportional gain is calculated based on the inductance and carrier period, using the following formula:

[0074]

[0075] In the formula, The cross-axis proportional gain is Td, which represents the carrier period.

[0076] The cross-axis integral gain is calculated based on the resistance and carrier period, using the following formula:

[0077]

[0078] In the formula, This is the cross-axis integral gain.

[0079] The direct-axis proportional gain is calculated based on the inductance and carrier period, using the following formula:

[0080]

[0081] In the formula, This is the direct-axis proportional gain.

[0082] The direct-axis integral gain is calculated based on the resistance and carrier period, using the following formula:

[0083]

[0084] In the formula, This is the direct-axis integral gain.

[0085] The velocity loop proportional gain is calculated based on the cross-axis proportional gain and calibration coefficients, using the following formula:

[0086]

[0087] In the formula, is the speed loop proportional gain, and m is a coefficient calibrated for different motors.

[0088] The velocity loop integral gain is calculated based on the direct-axis proportional gain and calibration coefficients, using the following formula:

[0089]

[0090] In the formula, ki is the speed loop integral gain, and n is a coefficient calibrated for different motors.

[0091] Regarding step S103, in one embodiment, the motor is driven to run based on the control loop parameters.

[0092] Specifically, the motor is driven to run based on the control loop parameters, and the motor's operation data is acquired when the motor is stopped.

[0093] See appendix Figure 4 , Figure 4 This is a schematic flowchart illustrating the process of updating valid motor parameters in a preset memory according to an embodiment of this application.

[0094] like Figure 4 As shown, regarding step S104, in one embodiment, verifying the validity of the motor parameters based on the motor's operating process data includes: determining whether the motor's operating process data meets preset normal operating conditions; if yes, then determining that the motor parameters are valid, storing the valid motor parameters in a preset memory to update the valid motor parameters in the preset memory; if no, then determining that the motor parameters are invalid.

[0095] Specifically, when the motor is stopped, the system determines whether the preset normal operating conditions are met based on the motor's operating process data. The operating process data may include fault status records, speed fluctuation data, current / voltage sampling data, etc. during motor operation. The preset normal operating conditions are used to determine whether no faults are reported during motor operation. Faults include, but are not limited to, common fault types of household appliance motors such as overcurrent faults, overvoltage faults, overheating faults, and three-phase current imbalance faults.

[0096] If the motor parameters are determined to meet the preset normal operating conditions, the identified motor parameters are deemed valid. The valid motor parameters are stored in the preset memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), and the previously stored historical valid motor parameters in the preset memory are updated. The updated valid motor parameters will be used as the filtering reference for the next motor start-up, thus completing the closed-loop optimization of the parameters.

[0097] In one embodiment, if the motor parameter is determined to be invalid, the method further includes: obtaining the number of consecutive times the motor parameter has been determined to be invalid; if the number of consecutive times reaches a preset threshold, then maintaining the valid motor parameter in the preset memory unchanged.

[0098] Specifically, if a motor parameter is determined to be invalid because it does not meet the preset normal operating conditions, the identified motor parameter is deemed invalid. After each invalidation, the number of consecutive invalidations is automatically incremented. If the number of consecutive invalidations is greater than or equal to a preset threshold, the valid motor parameters in the preset memory are kept unchanged to prevent abnormal parameter updates from causing motor failures and to ensure operational stability. In a specific embodiment, the preset threshold can be set to 5 times, which can be adjusted according to different motor models.

[0099] If the number of consecutive attempts is less than the preset threshold, the historical valid motor parameters in the preset memory will remain unchanged. When the motor starts again, the process of parameter identification, filtering, and obtaining control loop parameters and driving the motor will still be executed, and the validity analysis of the motor parameters will continue.

[0100] If the number of consecutive counts is less than the preset threshold, and the new motor parameters are verified to be valid, the number of consecutive counts is reset to zero, and the historical valid motor parameters in the preset memory are updated. The count of invalid counts will then restart.

[0101] This application verifies the validity of motor parameters by judging whether the operation process data meets the preset normal operation conditions after shutdown, and avoids the influence of random errors by controlling the number of invalid consecutive times. This ensures that the parameters are adapted to the current working conditions, and also ensures the stability of operation by preserving the opportunity for parameter self-learning and optimization, while relying on the historical valid motor parameters in the preset memory.

[0102] In one embodiment, the method further includes: acquiring motor factory parameters; wherein the motor factory parameters include at least factory resistance and factory inductance; calculating the resistance difference between the resistance and the factory resistance, and the inductance difference between the inductance and the factory inductance; determining whether the resistance difference and the inductance difference exceed corresponding preset thresholds; if at least one of the resistance difference and the inductance difference exceeds the corresponding preset threshold, then performing a fault warning prompt and triggering shutdown protection.

[0103] Specifically, before leaving the factory, each motor has standard factory parameters, which include at least factory resistance and inductance, serving as benchmark thresholds for parameter drift judgment. After each motor parameter calculation, the difference between the calculated resistance and the factory resistance, and the difference between the calculated inductance and the factory inductance, are calculated. These resistance differences are compared to preset resistance difference thresholds, and the inductance differences are compared to preset inductance difference thresholds. If neither the inductance nor the resistance difference exceeds its corresponding threshold, it indicates no abnormal parameter drift, and subsequent control and effectiveness verification procedures are executed normally.

[0104] If at least one of the inductance difference and resistance difference exceeds the corresponding threshold, it indicates that the motor parameters have drifted beyond the safe operating range, posing risks such as burnt windings and motor jamming. In this case, a fault warning is output, which can be achieved through indicator light flashing or a buzzer alarm on the appliance controller, informing the user of the motor malfunction. A shutdown protection mechanism is also triggered, cutting off the motor drive power and forcing the motor to stop until the fault is resolved and the motor is manually reset. This application uses real-time calculations of motor parameters based on factory parameter difference verification, which can prevent long-term drift risks and ensure the stability and safety of the motor in long-term operating scenarios.

[0105] See appendix Figure 5 , Figure 5 This is a schematic diagram of motor control logic according to an embodiment of this application. Figure 5 As shown, the processor acquires motor operating data and calculates motor parameters (resistance, inductance). Then, the processor interacts with the preset memory. Depending on whether the preset memory stores valid motor parameters, it can choose to store the motor parameters in the preset memory and obtain control loop parameters based on the motor parameters; or it can choose to input the motor parameters to the filter, so that the filter uses a weighted fusion method to filter the motor parameters based on the valid motor parameters stored in the preset memory, and then obtains control loop parameters based on the filtered motor parameters to drive the motor.

[0106] When the motor stops, the processor acquires the motor's operating process data and determines the validity of the motor parameters based on whether the motor's operating process data meets the preset normal operating conditions. The processor then uses the valid motor parameters to update the historical valid motor parameters stored in the preset memory.

[0107] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of this application, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of this application.

[0108] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0109] Furthermore, this application also provides a motor. In one embodiment of the motor according to this application, the motor includes a motor body, a processor, and a memory. The memory can be configured to store a program for executing the motor parameter identification method of the above-described method embodiments, and the processor can be configured to execute the program in the memory. This program includes, but is not limited to, a program for executing the motor parameter identification method of the above-described method embodiments. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The motor can be a motor device comprising various electronic devices. See Appendix Figure 6 , Figure 6 The example shows the motor body 10, memory 11 and processor 12 connected via a bus communication.

[0110] Furthermore, this application also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to this application, the computer-readable storage medium can be configured to store a program that performs the motor parameter identification method of the above-described method embodiment. This program can be loaded and run by a processor to implement the above-described motor parameter identification method. For ease of explanation, only the parts related to the embodiments of this application are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of this application. The computer-readable storage medium can be a memory device formed by various electronic devices. Optionally, in the embodiments of this application, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0111] Furthermore, this application also provides an air conditioner, see appendix. Figure 7 , Figure 7 This is a schematic block diagram of the main structure of an air conditioner according to one embodiment of the present application. In one embodiment of the air conditioner according to the present application, the air conditioner includes a motor.

[0112] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device described in this application, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of both. Therefore, the number of modules shown in the figures is merely illustrative.

[0113] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of this application; therefore, the technical solutions after splitting or combining will fall within the protection scope of this application.

[0114] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. Without departing from the principles of this application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of this application.

Claims

1. A method for identifying motor parameters, characterized in that, The method includes: In response to motor startup, motor parameters are acquired; wherein the motor parameters include at least resistance and inductance; Based on the motor parameters and / or the valid motor parameters stored in the preset memory, obtain the control loop parameters; Based on the control loop parameters, the motor is driven to run; With the motor stopped, the validity of the motor parameters is verified based on the motor's operating data. Based on the verified valid motor parameters, the valid motor parameters in the preset memory are updated.

2. The motor parameter identification method according to claim 1, characterized in that, The verification of the validity of the motor parameters based on the motor's operating data includes: Determine whether the motor's operating process data meets the preset normal operating conditions; If so, the motor parameters are determined to be valid, and the valid motor parameters are stored in a preset memory to update the valid motor parameters in the preset memory; If not, the motor parameters are deemed invalid.

3. The motor parameter identification method according to claim 2, characterized in that, If the motor parameters are determined to be invalid, the method further includes: The number of consecutive times the motor parameters were deemed invalid is obtained; If the number of consecutive occurrences reaches a preset threshold, the valid motor parameters in the preset memory will remain unchanged.

4. The motor parameter identification method according to claim 1, characterized in that, The step of obtaining control loop parameters based on the motor parameters and / or valid motor parameters stored in a preset memory includes: Determine whether valid motor parameters are stored in the preset memory; If not, the motor parameters are stored in the preset memory, and the control loop parameters are obtained based on the motor parameters; If so, the motor parameters are input into the filter. The filter performs a weighted fusion process on the motor parameters based on the valid motor parameters stored in the preset memory, and obtains the control loop parameters based on the filtered motor parameters.

5. The motor parameter identification method according to claim 4, characterized in that, The control loop parameters include the current loop quadrature axis control parameters, the current loop direct axis control parameters, the speed loop proportional gain, and the speed loop integral gain; The acquisition of control loop parameters includes: Based on the resistor and the inductor, the current loop quadrature axis control parameters are obtained; wherein, the current loop quadrature axis control parameters include the quadrature axis proportional gain and the quadrature axis integral gain; Based on the resistor and the inductor, the direct-axis control parameters of the current loop are obtained; wherein, the direct-axis control parameters of the current loop include the direct-axis proportional gain and the direct-axis integral gain; Based on the cross-axis proportional gain, obtain the velocity loop proportional gain; Based on the direct-axis proportional gain, the velocity loop integral gain is obtained.

6. The motor parameter identification method according to claim 1, characterized in that, The acquisition of motor parameters includes: Acquire motor operating data, including duty cycle, bus voltage, control frequency, and current data; Based on Kirchhoff's laws and Ohm's law, the resistance is determined using the duty cycle, the bus voltage, and the current data. Based on the duty cycle, the bus voltage, the control frequency, and the current data, the inductance is determined using a preset formula.

7. The motor parameter identification method according to claim 1, characterized in that, The method further includes: Obtain the motor's factory parameters; wherein, the motor's factory parameters include at least the factory resistance and the factory inductance; Calculate the resistance difference between the resistor and the factory-installed resistor, and the inductance difference between the inductor and the factory-installed inductor; Determine whether the resistance difference and the inductance difference exceed the corresponding preset thresholds; If at least one of the resistance difference and the inductance difference exceeds the corresponding preset threshold, a fault warning will be issued and a shutdown protection will be triggered.

8. An electric motor, comprising a motor body, a processor, and a memory, wherein the memory is adapted to store multiple lines of program code, characterized in that, The program code is adapted to be loaded and run by the processor to perform the motor parameter identification method according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform the motor parameter identification method according to any one of claims 1 to 7.

10. An air conditioner, characterized in that, The air conditioner includes the motor as described in claim 8.

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