A control method and device of a direct-current brushless motor

Abstract

The application provides a control method and device of a direct-current brushless motor, comprising the following steps: acquiring first operation data of motor operation through a position sensor, acquiring a first estimated parameter related to a load through a first position sensorless algorithm, updating a second position sensorless algorithm in a cloud server through the first operation data and the first estimated parameter to obtain a third position sensorless algorithm, and acquiring the third position sensorless algorithm sent from the cloud server; then updating the first position sensorless algorithm through the third position sensorless algorithm, and controlling the motor operation based on the updated first position sensorless algorithm. Since the control advantages of the position sensor and the position sensorless algorithm are considered, the updated first position sensorless algorithm can significantly improve the accuracy of the motor rotor position detection result, and the probability of abnormal starting of the direct-current brushless motor is minimized, so that the application has wide applicability.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and in particular to a control method and device for a brushless DC motor. Background Technology

[0002] Rotor position detection of brushless DC motors is a critical issue in motor control. Common rotor position detection methods include sensor-based control and sensorless control. In sensor-based control, significant motor vibration or sensor failure can lead to system failure. Sensorless control suffers from poor load adaptability. Therefore, accurately detecting the motor rotor position has become a hot research topic.

[0003] It should be noted that the above introduction to the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of this application and facilitating understanding by those skilled in the art. It should not be assumed that these technical solutions are known to those skilled in the art simply because they have been described in the background section of this application. Summary of the Invention

[0004] This application provides a control method and apparatus for a brushless DC motor.

[0005] The first aspect of this application proposes a control method for a brushless DC motor, including:

[0006] Acquire first operating data during motor operation, wherein the first operating data is acquired based on a position sensor;

[0007] Obtain a first estimation parameter related to the load, and send the first running data and the first estimation parameter to the cloud server, wherein the first estimation parameter is obtained based on a first sensorless algorithm;

[0008] The system receives a third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server.

[0009] The first sensorless algorithm is updated based on the third sensorless algorithm, and the motor is controlled to run based on the updated first sensorless algorithm.

[0010] A second aspect of this application provides a control method for a brushless DC motor, comprising:

[0011] Receive the first running data and the first estimated parameters;

[0012] Based on the first operating data and the first estimated parameters, a third sensorless algorithm is determined;

[0013] The third sensorless algorithm is sent to the controller of the motor.

[0014] A third aspect of this application provides a control device for a brushless DC motor, comprising:

[0015] The first acquisition module is used to acquire first operating data when the motor is running, wherein the first operating data is acquired based on a position sensor;

[0016] The second acquisition module is used to acquire a first estimation parameter related to the load, and send the first running data and the first estimation parameter to the cloud server, wherein the first estimation parameter is acquired based on a first sensorless algorithm;

[0017] A first receiving module is used to receive a third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server.

[0018] The control module is used to update the first sensorless algorithm based on the third sensorless algorithm, and to control the operation of the motor based on the updated first sensorless algorithm.

[0019] The fourth aspect of this application provides a control device for a brushless DC motor, comprising:

[0020] The second receiving module receives the first operating data and the first estimated parameters;

[0021] The third acquisition module is used to determine a third sensorless algorithm based on the first running data and the first estimation parameters.

[0022] A sending module is used to send the third sensorless algorithm to the controller of the motor.

[0023] A fifth aspect of this application provides an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the control method for a brushless DC motor proposed in the first and second aspects of this application.

[0024] A sixth aspect of this application provides a non-transitory computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is able to perform the methods proposed in the first and second aspects of this application.

[0025] A seventh aspect of this application provides a computer program product including a computer program that, when executed by a processor in a communication device, implements the methods proposed in the first and second aspects of this application.

[0026] The technical solutions provided by the embodiments of this application have at least the following beneficial effects:

[0027] The system acquires first operating data of the motor using a position sensor, obtains first estimated parameters related to the load using a first sensorless algorithm, updates a second sensorless algorithm in the cloud server using the first operating data and the first estimated parameters, and acquires a third sensorless algorithm sent from the cloud server. The third sensorless algorithm is then used to update the first sensorless algorithm, and the motor operation is controlled based on the updated first sensorless algorithm. By combining the control advantages of both position sensors and sensorless systems, the updated first sensorless algorithm significantly improves the accuracy of the motor rotor position detection results and minimizes the probability of abnormal starting of the brushless DC motor, thus exhibiting wide applicability.

[0028] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0029] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0030] Figure 1 This is a schematic diagram of the structure of a brushless DC motor system provided in an embodiment of this application;

[0031] Figure 2 This is a flowchart illustrating a control method for a brushless DC motor provided in an embodiment of this application.

[0032] Figure 3 This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application.

[0033] Figure 4 This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application.

[0034] Figure 5This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application.

[0035] Figure 6 This is a schematic diagram of a DC brushless motor control process provided according to an embodiment of this application;

[0036] Figure 7 This is a schematic diagram of the structure of a control device for a brushless DC motor provided in an embodiment of this application;

[0037] Figure 8 A schematic diagram of the structure of another control device for a brushless DC motor provided in an embodiment of this application;

[0038] Figure 9 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application;

[0039] Figure 10 This is a schematic diagram of the structure of another electronic device provided according to an embodiment of this application. Detailed Implementation

[0040] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0041] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a” and “the” as used in the embodiments of this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0042] It should be understood that although the terms first, second, third, etc., may be used to describe various information in the embodiments of this application, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words "if" and "suppose" as used herein can be interpreted as "when," "when," or "in response to a determination."

[0043] Embodiments of this application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0044] It should be noted that the control method for a brushless DC motor provided in any embodiment of this application can be executed alone, or can be executed together with possible implementation methods in other embodiments, or can be executed together with any technical solution in related technologies.

[0045] The control method and apparatus for a brushless DC motor according to embodiments of this application are described below with reference to the accompanying drawings.

[0046] In one feasible implementation, Figure 1 This is a schematic diagram of a DC brushless motor system provided in an embodiment of this application.

[0047] like Figure 1 As shown, the microcontroller unit first needs to continuously monitor the operating status of the motor (i.e., the brushless DC motor), including parameters such as motor speed, torque, current, voltage, and back electromotive force. By comparing these parameters with preset thresholds or models, a mismatch between the motor and the load can be identified. Motor-load mismatch can be caused by various reasons, such as excessive load, frequent load changes, improper motor selection, or wear of mechanical components. Once a mismatch is identified, the microprocessor unit deployed outside the motor performs a series of operations and adjustments, such as adjusting motor operating parameters like voltage, current, and frequency; triggering a fault warning mechanism; or cutting off the power supply to prevent further damage or safety accidents. It should be noted that using position sensors (such as encoders and Hall effect sensors) to accurately measure the motor's rotor position provides higher control accuracy and stability, especially under conditions of large load variations, helping to reduce motor vibration and noise and extend motor lifespan.

[0048] The following can be combined Figure 1 The DC brushless motor system shown illustrates a control method for a DC brushless motor provided in the embodiments of this application.

[0049] Figure 2 This is a flowchart illustrating a control method for a brushless DC motor provided in an embodiment of this application. Figure 2 As shown, the method includes, but is not limited to, the following steps:

[0050] S201, acquire the first operating data when the motor is running, wherein the first operating data is acquired based on the position sensor.

[0051] In one feasible implementation, the rotation of the motor can be monitored using a position sensor. Common position sensors include Hall effect sensors, optical encoders, magnetic encoders, and resolvers, each with a specific output signal format, such as analog signals, digital pulses, or serial communication data. The output signal of the position sensor is then connected to a data acquisition device, which can be a microcontroller unit. Appropriate parameters are configured on the microcontroller unit to correctly read and process the position sensor signal. Configuration operations include setting the input channel, signal type (e.g., analog input, digital input, or serial communication interface), sampling rate, filters, etc. Depending on the type and configuration of the microcontroller unit, a program can be written to read the position sensor data. This program can acquire the position sensor output in real time and convert it into motor position information. This typically involves reading the values ​​from the input channels and converting them into actual position values ​​(e.g., angle, number of rotations) according to the position sensor specifications. During motor operation, the microcontroller unit monitors the motor's operating status using its configured parameters, records data from the position sensor, and extracts first operating data from the recorded data. This first operating data typically includes parameters such as rotor position, speed, torque, current, voltage, and back EMF. When the motor and load are matched, the first operating data is constant (e.g., speed, torque, current, voltage, and back EMF are constant). When the motor and load are mismatched, the first operating data is not constant. Generally, the first operating data when the motor and load are mismatched can be represented as second operating data. The microprocessor unit can further optimize the motor's control parameters based on the second operating data, including adjusting key parameters such as speed, torque, and current, as well as optimizing control algorithms and filter design.

[0052] S202, obtain the first estimation parameters related to the load, and send the first running data and the first estimation parameters to the cloud server, wherein the first estimation parameters are obtained based on the first sensorless algorithm.

[0053] In one feasible implementation, the load type of the motor is first determined, such as a constant torque load, a constant power load, or a fan / pump load. Different types of loads have different effects on parameters such as motor current, speed, and power factor. Then, based on the load type and the motor's operating characteristics, a suitable estimation method is selected. For example, for a three-phase motor, the formula "Power P = 1.732 × U × I × cosφ × Efficiency" can be used for estimation, where U is voltage, I is current, cosφ is power factor, and efficiency is the motor's operating efficiency. For a single-phase motor, a similar formula can be used, but different voltages and power factors need to be considered. Estimation can also be based on the motor's rated parameters and operating experience. For example, for a three-phase motor, the actual operating current value can be estimated based on its rated power and rated current. The first sensorless algorithm determines the first estimation parameter based on a selected estimation method and the motor's initial operating data (e.g., voltage, current, power factor, etc.). The first estimation parameter can be the motor's rotor position, actual load current, load power, or load torque. Taking rotor position as an example, before motor startup or commutation, the angle by which the rotor is dragged to the desired position is determined using a specific current vector. During motor operation, the final position reached by the rotor is compared to the desired position to verify the accuracy of the position information in the initial operating data. After obtaining accurate position information, the first estimation parameter related to the load can be estimated based on the relevant information in the initial operating data. By analyzing the distribution of the first estimation parameter in different regions or time periods, the load balance and stability can be understood.

[0054] Combination Figure 1 In the DC brushless motor system shown, after the microcontroller unit obtains the first operating data and the first estimated parameters, it can send them to the cloud server via the network. This operation typically involves: formatting the first operating data and the first estimated parameters to ensure that they meet the format requirements of the cloud server; selecting an appropriate network protocol (such as HTTP, FTP, etc.) to send the data according to the requirements of the cloud server and the network environment; sending the formatted data to the cloud server via the network and waiting for the cloud server's confirmation of receipt. If the data transmission fails, it may be necessary to resend or perform error handling.

[0055] S203, receive the third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server.

[0056] In one feasible implementation, combined with Figure 1In the illustrated brushless DC motor system, after receiving the first operating data and the first estimated parameters, the cloud server performs data cleaning, transformation, and aggregation to ensure the accuracy and consistency of the data. Based on the processed data, the cloud server runs one or more mathematical models or algorithms to determine a third sensorless algorithm. These models or algorithms may include machine learning models, statistical analysis methods, etc. As an example, the cloud server can update its second sensorless algorithm using the first operating data and the first estimated parameters to determine a third sensorless algorithm that meets the motor's requirements. The third sensorless algorithm is then output as a result to the microprocessor unit. This result may be a numerical value, a vector, a matrix, or other data structures that meet the requirements of the microprocessor unit. The third sensorless algorithm can be used for feedback control to adjust the motor's operating state. For example, the third sensorless algorithm can represent the motor's load condition or efficiency, thereby adjusting the motor's operating speed or power.

[0057] S204, update the first sensorless algorithm based on the third sensorless algorithm, and control the motor operation based on the updated first sensorless algorithm.

[0058] In one feasible implementation, combined with Figure 1 The illustrated brushless DC motor system first uses a microprocessor unit to re-determine whether the motor's operating state is stable. Since the third sensorless algorithm is obtained by updating the second sensorless algorithm in the cloud server using the first operating data and the first estimated parameters, the motor needs to operate under the conditions corresponding to the third sensorless algorithm. This means the motor control algorithm relies on the third sensorless algorithm to estimate the motor's position and speed. Based on the third sensorless algorithm, the motor control algorithm is adjusted to meet the requirements. This includes adjusting parameters such as the controller's gain and frequency response to ensure stable motor operation and to cope with various operating conditions under the constraints of the third sensorless algorithm. It should be noted that in practical applications, the microprocessor unit needs to be debugged and optimized to ensure stable motor operation under different operating modes and conditions. The debugging and optimization process involves adjusting control parameters and optimizing algorithms, which will not be elaborated here.

[0059] In summary, the control method for a brushless DC motor provided in this application acquires first operating data of the motor through a position sensor, acquires first estimated parameters related to the load through a first sensorless algorithm, updates a second sensorless algorithm in a cloud server using the first operating data and the first estimated parameters, acquires a third sensorless algorithm sent from the cloud server, updates the first sensorless algorithm using the third sensorless algorithm, and controls the motor operation based on the updated first sensorless algorithm. Because it combines the advantages of both position sensor and sensorless control, the updated first sensorless algorithm can significantly improve the accuracy of the motor rotor position detection results and minimize the probability of abnormal starting of the brushless DC motor, thus having wide applicability.

[0060] Figure 3 This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application. Figure 3 As shown, the method includes, but is not limited to, the following steps:

[0061] S301, acquire the first operating data during motor operation, wherein the first operating data is acquired based on the position sensor.

[0062] In one feasible implementation, combined with Figure 1 The DC brushless motor system shown collects initial operating data from position sensors (such as photoelectric encoders, Hall sensors, etc.). This initial operating data may include parameters such as the motor's position, speed, and acceleration, as well as related load information (such as load size, load changes, etc.). The initial operating data can be cleaned and processed to remove outliers and noise, and then the data can be standardized or normalized for subsequent analysis and comparison.

[0063] Features reflecting the matching state between the motor and load, such as motor inertia and load inertia, are extracted from the preprocessed first operating data. These features are then subjected to statistical analysis, spectral analysis, or time-domain analysis to identify mismatches between the motor and load. For example, analyzing motor current fluctuations can determine if the load is too large or too small, leading to motor overload or inefficient operation. Further, if the motor inertia and load inertia are consistent, the motor and load are considered matched; if they are inconsistent, a mismatch is identified. The first operating data under these mismatch conditions is represented as second operating data. The microprocessor unit can then further optimize the motor's control parameters based on this second operating data, including adjusting key parameters such as speed, torque, and current, as well as optimizing the control algorithm and filter design.

[0064] For further details on step S301, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0065] S302, based on parsing the first operating data, obtain the first estimation parameters related to the load, and send the first operating data and the first estimation parameters to the cloud server, wherein the first estimation parameters are obtained based on the first sensorless algorithm.

[0066] In one feasible implementation, combined with Figure 1 The illustrated brushless DC motor system uses a microprocessor unit to identify first operating data. Based on the motor's control objectives (e.g., achieving a specific speed, position, or torque), it selects an appropriate control strategy. In this embodiment, if the motor and load are matched, the rotor position extracted from the first operating data is consistent with the actual position; if the motor and load are mismatched, the rotor position extracted from the first operating data is inconsistent with the actual position. Three-phase current parameters and back EMF parameters can be extracted from the first operating data. These parameters are then input into a first sensorless algorithm (e.g., the first sensorless algorithm can be set via library functions or code in the microprocessor unit; specific settings are not detailed here) to obtain first estimated parameters related to the load. As an example, the first estimation parameter can be used to estimate the load current by the sum or average of the three-phase currents. Under balanced load, the sum of the three-phase currents should be zero (because they cancel each other out), so the average of the phase currents can be used as the estimated value of the load current. The magnitude of the load current reflects the load on the motor and is an important indicator for evaluating the motor's load status. In this case, the load current can be represented as the first estimation parameter. The first estimation parameter can also be used to calculate the load power using the motor's rated voltage and load current. The estimation formula is: P_load=V_rated*I_load*cos(φ), where V_rated is... The rated voltage of the motor, I_load is the load current, and cos(φ) is the power factor. The power factor can be obtained by measuring the phase difference between the motor's phase current and phase voltage. In this case, the load power can be represented as the first estimated parameter. The first estimated parameter can also be obtained from the load torque, which can be estimated by measuring the motor's speed and back electromotive force. When the motor is running stably (i.e., the motor is matched to the load), the load torque is directly proportional to the back electromotive force and inversely proportional to the speed. Then, a specific mathematical model or algorithm (such as a torque estimation formula based on motor parameters) is used to calculate the load torque, which can also be represented as the first estimated parameter. The method of obtaining the first estimated parameter should be selected according to specific needs, which will not be elaborated here.

[0067] For further details on step S302, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0068] S303, receive the third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server.

[0069] In one feasible implementation, the second sensorless algorithm relies on the motor's electrical parameters (such as current and voltage) to obtain the motor's position or speed information. The first operating data typically includes the motor's first position parameter, speed, current, and other parameters. The first estimated parameter is obtained based on the first sensorless algorithm and includes a first estimated position. The first position parameter and the first estimated position are used to obtain the difference between the positions. This difference is used to adjust the second sensorless algorithm until the difference is less than a preset threshold, at which point updates cease. The third sensorless algorithm is obtained when the second estimated position matches the first position parameter. The second estimated position is obtained by simulating the motor's state using the second sensorless algorithm when the difference in the first operating data is less than the preset threshold. It should be noted that the simulation process may include extended Kalman filtering, model reference adaptive control, high-frequency signal injection, etc. The simulation process should be set according to the specific application scenario, and will not be elaborated here.

[0070] It should be added that the update operation of the second sensorless algorithm in the cloud server based on the first running data and the first estimated parameters involves complex processes such as iterative calculations. By obtaining the difference between the first position parameter and the first estimated position, the second sensorless algorithm is continuously updated to ensure its accuracy and reliability. The update process may also require adjusting the model parameters of the second sensorless algorithm. The specific adjustment process will not be described in detail. The third sensorless algorithm obtained after the update will be used for closed-loop control of the motor.

[0071] For further details on step S303, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0072] S304, update the first sensorless algorithm based on the third sensorless algorithm, and control the motor operation based on the updated first sensorless algorithm.

[0073] In one feasible implementation, combined with Figure 1The illustrated brushless DC motor system involves a microcontroller unit that parses the third sensorless algorithm sent by the cloud server, extracting key information related to motor control, including parameters such as load torque, load power, and motor efficiency. Based on this information, the microcontroller unit updates the first sensorless algorithm and generates control commands. Executing these commands ensures that if the motor and load are matched, the control commands maintain the motor's current state; otherwise, they adjust the motor until they are matched. Furthermore, the microcontroller unit can obtain updated firmware from the cloud server via over-the-air (OTA) download. This updated firmware includes the third sensorless algorithm. The microcontroller unit then configures the motor controller based on this updated firmware, which is used for motor operation control.

[0074] For further details on step S304, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0075] In summary, the control method for a brushless DC motor provided in this application acquires first operating data of the motor through a position sensor, acquires first estimated parameters related to the load through a first sensorless algorithm, updates a second sensorless algorithm in a cloud server using the first operating data and the first estimated parameters, acquires a third sensorless algorithm sent from the cloud server, updates the first sensorless algorithm using the third sensorless algorithm, and controls the motor operation based on the updated first sensorless algorithm. Because it combines the advantages of both position sensor and sensorless control, the updated first sensorless algorithm can significantly improve the accuracy of the motor rotor position detection results and minimize the probability of abnormal starting of the brushless DC motor, thus having wide applicability.

[0076] Figure 4 This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application. Figure 4 As shown, the method includes, but is not limited to, the following steps:

[0077] S401 receives the first running data and the first estimated parameters.

[0078] In one possible implementation, the cloud server receives first estimated parameters based on location sensor acquisition and based on a first sensorless algorithm.

[0079] For further details regarding step S401, please refer to the relevant descriptions in the above embodiments; they will not be repeated here.

[0080] S402, based on the first operating data and the first estimated parameters, determine the third sensorless algorithm.

[0081] In one feasible implementation, a first position parameter can be extracted from the first operating data, and a first estimated position can be extracted from the first estimation parameter. Then, the difference between the first position parameter and the first estimated position is obtained, and it is determined whether the difference exceeds a predetermined threshold. If the difference exceeds the preset threshold, a second sensorless algorithm in the cloud server is adjusted until the difference is less than the preset threshold, at which point updates cease, resulting in a third sensorless algorithm. Optionally, in response to first operating data where the difference is less than the preset threshold, the second sensorless algorithm is adjusted to simulate the motor's operating state to obtain a second estimated position. If the second estimated position matches the first position parameter, updates to the second sensorless algorithm cease, resulting in a third sensorless algorithm.

[0082] For further details on step S402, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0083] S403 sends a third sensorless algorithm to the motor controller.

[0084] In one feasible implementation, the firmware of the motor-adaptive load is updated according to a third sensorless algorithm to obtain updated firmware; the generator controller under the updated firmware is configured according to OTA.

[0085] For further details on step S403, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0086] In summary, the control method for a brushless DC motor provided in this application acquires first operating data of the motor through a position sensor, acquires first estimated parameters related to the load through a first sensorless algorithm, updates a second sensorless algorithm in a cloud server using the first operating data and the first estimated parameters, acquires a third sensorless algorithm sent from the cloud server, updates the first sensorless algorithm using the third sensorless algorithm, and controls the motor operation based on the updated first sensorless algorithm. Because it combines the advantages of both position sensor and sensorless control, the updated first sensorless algorithm can significantly improve the accuracy of the motor rotor position detection results and minimize the probability of abnormal starting of the brushless DC motor, thus having wide applicability.

[0087] Figure 5 This is a flowchart illustrating another control method for a brushless DC motor provided in an embodiment of this application. Figure 5 As shown, the method includes, but is not limited to, the following steps:

[0088] S501 receives the first running data and the first estimated parameters.

[0089] For further details on step S501, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0090] S502, obtain the first position parameter in the first running data and the first estimated position in the first estimation parameter.

[0091] It should be noted that if the motor and the load are matched, the first position parameter is obtained from the first operating data; if the motor and the load are not matched, the first operating data can be represented as the second operating data, and the first position parameter is obtained from the second operating data.

[0092] For further details on step S502, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0093] S503, determine the third sensorless algorithm based on the difference between the first position parameter and the first estimated position.

[0094] For further details on step S503, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0095] S504 sends a third sensorless algorithm to the motor controller.

[0096] For further details regarding step S504, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0097] In summary, the control method for a brushless DC motor provided in this application acquires first operating data of the motor through a position sensor, acquires first estimated parameters related to the load through a first sensorless algorithm, updates a second sensorless algorithm in a cloud server using the first operating data and the first estimated parameters, acquires a third sensorless algorithm sent from the cloud server, updates the first sensorless algorithm using the third sensorless algorithm, and controls the motor operation based on the updated first sensorless algorithm. Because it combines the advantages of both position sensor and sensorless control, the updated first sensorless algorithm can significantly improve the accuracy of the motor rotor position detection results and minimize the probability of abnormal starting of the brushless DC motor, thus having wide applicability.

[0098] The control process of a brushless DC motor will now be described in conjunction with the control method for the brushless DC motor provided in the embodiments of this application. Figure 6 This is a schematic diagram of a DC brushless motor control process according to an embodiment of this application. Figure 6As shown, the system acquires first operating data via a position sensor; the microcontroller unit uses a first sensorless algorithm to detect the position of the brushless DC motor and obtains first estimated parameters related to the load; the cloud server updates its second sensorless algorithm based on the received first operating data and first estimated parameters to output a control strategy for a third sensorless algorithm; the speed PID is obtained based on PWM control and current PID (where P represents proportional; I represents integral; D represents derivative, i.e., PID control strategy); the current PID is obtained through current detection by the microcontroller unit's first sensorless algorithm; the cloud server outputs the control strategy for the third sensorless algorithm, and the algorithm iterates under the adjustment of the control strategy, with the iteration results used for PWM control and current PID adjustment respectively; through PWM control, the third sensorless algorithm updates the first sensorless algorithm, and the brushless DC motor is controlled based on the updated first sensorless algorithm.

[0099] Figure 7 This is a schematic diagram of the structure of a control device for a brushless DC motor provided in an embodiment of this application. Figure 7 As shown, the control device 700 for the brushless DC motor includes:

[0100] The first acquisition module 701 is used to acquire first operating data when the motor is running, wherein the first operating data is acquired based on a position sensor;

[0101] The second acquisition module 702 is used to acquire a first estimation parameter related to the load, and send the first operating data and the first estimation parameter to the cloud server. The first estimation parameter is acquired based on a first sensorless algorithm.

[0102] The first receiving module 703 is used to receive the third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server.

[0103] The control module 704 is used to update the first sensorless algorithm based on the third sensorless algorithm, and to control the operation of the motor based on the updated first sensorless algorithm.

[0104] Figure 8 This is a schematic diagram of the structure of another control device for a brushless DC motor provided in an embodiment of this application. Figure 8 As shown, the control device 800 for the brushless DC motor includes:

[0105] The second receiving module 801 is used to receive the first operating data and the first estimated parameters;

[0106] The third acquisition module 802 is used to determine the third sensorless algorithm based on the first operating data and the first estimated parameters.

[0107] The transmitting module 803 is used to send a third sensorless algorithm to the motor controller.

[0108] Figure 9 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application. Figure 9 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0109] like Figure 9 As shown, the electronic device 900 includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a memory 906 into a random access memory (RAM) 903. The RAM 903 also stores various programs and data required for the operation of the electronic device 900. The processor 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0110] The following components are connected to I / O interface 905: memory 906 including hard disk; and communication section 907 including network interface card such as LAN (Local Area Network) card, modem, etc., communication section 907 performs communication processing via a network such as the Internet; driver 808 is also connected to I / O interface 905 as needed.

[0111] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 907. When the computer program is executed by processor 901, it performs the functions defined in the methods of this application.

[0112] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory including instructions, which can be executed by a processor 901 of an electronic device 900 to perform the above-described method. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0113] In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can transmit, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wireline, optical fiber, RF, etc., or any suitable combination thereof.

[0114] Figure 10 This is a schematic diagram of the structure of another electronic device provided according to an embodiment of this application. Figure 10 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this application. Figure 10 As shown, the electronic device 1000 includes a processor 1001 and a memory 1002. The memory 1002 is used to store program code, and the processor 1001 is connected to the memory 1002 and is used to read program code from the memory 1002 to implement the control method of the brushless DC motor in the above embodiment.

[0115] Optionally, the number of processors 1001 can be one or more.

[0116] Optionally, the electronic device may also include an interface 903, and the number of interfaces 903 may be multiple. The interface 903 can be connected to an application and can receive data from external devices such as sensors.

[0117] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0118] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A control method for a brushless DC motor, characterized in that, The control method includes: Acquire first operating data during motor operation, wherein the first operating data is acquired based on a position sensor; Obtain a first estimation parameter related to the load, and send the first running data and the first estimation parameter to the cloud server, wherein the first estimation parameter is obtained based on a first sensorless algorithm; The system receives a third sensorless algorithm from the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server to obtain the third sensorless algorithm. The first sensorless algorithm is updated based on the third sensorless algorithm, and the motor is controlled to run based on the updated first sensorless algorithm.

2. The control method according to claim 1, characterized in that, The acquisition of the first estimation parameter related to the load includes: Extract the three-phase current parameters and back electromotive force parameters from the first operating data; The three-phase current parameters and back electromotive force parameters are input into the first sensorless algorithm to obtain the first estimation parameters related to the load.

3. The control method according to claim 1, characterized in that, The control of the motor operation based on the updated first sensorless algorithm includes: Based on the updated first sensorless algorithm, control commands are generated. If the motor matches the load, the control command maintains the current state of the motor; if the motor does not match the load, the control command adjusts the motor until the motor and load match.

4. The control method according to claim 1, characterized in that, The control method further includes: Obtain the motor inertia and load inertia; In response to the consistency between the motor inertia and the load inertia, it is determined that the motor and the load are matched; In response to the inconsistency between the motor inertia and the load inertia, it is determined that the motor and the load are mismatched.

5. The control method according to claim 1, characterized in that, The first running data and the first estimated parameters are used to update the second sensorless algorithm in the cloud server, including: The first running data includes a first position parameter, and the first estimation parameter includes a first estimated position; the first position parameter and the first estimated position are used to obtain the difference between the positions, wherein the difference is used to adjust the second sensorless algorithm until the difference is less than a preset threshold and the update stops.

6. The control method according to claim 5, characterized in that, The third sensorless algorithm is obtained when the second estimated position matches the first position parameter. The second estimated position is obtained by simulating the state of the motor through the second sensorless algorithm when the difference is less than a preset threshold in the first operating data.

7. The control method according to any one of claims 1-6, characterized in that, The control method further includes: The updated firmware sent by the cloud server is obtained via over-the-air (OTA) download, and the updated firmware includes the third sensorless algorithm. The controller of the motor is configured based on the updated firmware, which is used to control the operation of the motor.

8. A control method for a brushless DC motor, characterized in that, The control method includes: Receive the first running data and the first estimated parameters; Based on the first operating data and the first estimated parameters, a third sensorless algorithm is determined; The third sensorless algorithm is sent to the controller of the motor.

9. The control method according to claim 8, characterized in that, The step of determining the third sensorless algorithm based on the first operating data and the first estimated parameters includes: Extract the first position parameter from the first running data and the first estimated position from the first estimation parameter; Obtain the difference between the first position parameter and the first estimated position; If the difference exceeds a preset threshold, the second sensorless algorithm in the cloud server is adjusted until the difference is less than the preset threshold and the update stops, thus obtaining the third sensorless algorithm.

10. The method according to claim 9, characterized in that, The adjustment of the second sensorless algorithm in the cloud server until the difference is less than the preset threshold and the update stops, to obtain the third sensorless algorithm, includes: In response to the first operating data where the difference is less than the preset threshold, the second sensorless algorithm is adjusted to simulate the operating state of the motor to obtain a second estimated position; If the second estimated position matches the first position parameter, stop updating the second sensorless algorithm and obtain the third sensorless algorithm.

11. The method according to claim 8, characterized in that, Sending the third sensorless algorithm to the controller of the motor includes: Based on the third sensorless algorithm, the firmware of the motor-adaptive load is updated to obtain the updated firmware. The updated firmware is sent to the motor controller via OTA for configuration.

12. A control device for a brushless DC motor, characterized in that, include: The first acquisition module is used to acquire first operating data when the motor is running, wherein the first operating data is acquired based on a position sensor; The second acquisition module is used to acquire a first estimation parameter related to the load, and send the first running data and the first estimation parameter to the cloud server, wherein the first estimation parameter is acquired based on a first sensorless algorithm; A first receiving module is used to receive a third sensorless algorithm sent by the cloud server, wherein the first running data and the first estimation parameters are used to update the second sensorless algorithm in the cloud server. The control module is used to update the first sensorless algorithm based on the third sensorless algorithm, and to control the operation of the motor based on the updated first sensorless algorithm.

13. A control device for a brushless DC motor, characterized in that, include: The second receiving module receives the first operating data and the first estimated parameters; The third acquisition module is used to determine a third sensorless algorithm based on the first running data and the first estimation parameters. A sending module is used to send the third sensorless algorithm to the controller of the motor.

14. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 7 or 8 to 11.

15. A non-transitory computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform the method as described in any one of claims 1 to 7 or 8 to 11.

16. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7 or 8 to 11.

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