Intelligent motor control method and system based on adaptive control algorithm

Abstract

The invention discloses a motor intelligent control method and system based on a self-adaptive control algorithm, and the method comprises the steps: obtaining motor operation parameters, and determining an overall control target according to the motor operation parameters; on the basis of the overall control target and the current working condition information, initial control parameters are calculated through a self-adaptive control algorithm; monitoring interaction parameters between the motor and the load; the initial control parameters are dynamically adjusted, and the running state of the motor is optimized; in a preset motor prediction model, based on the historical operation data and the current real-time data of the motor, predicting the operation state change of the motor, obtaining a motor prediction result, formulating an adjustment control strategy, and triggering a motor control instruction; the actual operation state of the motor is collected, and a state difference value is calculated; if the state difference value exceeds the threshold range, triggering a generator exception processing instruction; adjusting control parameters are obtained; triggering an adjustment instruction based on the adjustment control parameter; the control effect and the self-adaptive capability of the motor control system are improved.

Description

Technical Field

[0001] The present application relates to the technical field of motor intelligent control, and in particular to a motor intelligent control method and system with an adaptive control algorithm. Background Art

[0002] Motor control systems are widely used in many fields such as industrial automation, household appliances, and electric vehicles. However, traditional motor control systems mostly use fixed control parameters. When faced with complex and changeable working conditions, they cannot be adjusted in real time according to the actual working conditions, resulting in poor control effects and high energy consumption. This makes the robustness and adaptability of traditional control methods poor, and the stability is poor when faced with external interference, so improvement is urgently needed. Summary of the invention

[0003] In order to improve the control effect and adaptive capability of a motor control system, the present application provides a motor intelligent control method and system with an adaptive control algorithm.

[0004] In the first aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A motor intelligent control method with an adaptive control algorithm, comprising: Acquire motor operating parameters, and determine an overall control target based on the motor operating parameters; the overall control target includes a target speed, a target torque, and an energy efficiency index of the motor; Identify the current working condition information of the motor; calculate the initial control parameters through the adaptive control algorithm based on the overall control target and the current working condition information; monitor the interaction parameters between the motor and the load; the interaction parameters include torque fluctuation, speed response time and efficiency change; According to the interaction parameters and the overall control target, the initial control parameters are dynamically adjusted to optimize the operating state of the motor; In a preset motor prediction model, based on the acquired historical operation data and current real-time data of the motor, the operation state change of the motor within a specified time period is predicted to obtain a motor prediction result, and an adjustment control strategy is formulated based on the motor prediction result to trigger a motor control instruction; Collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, trigger the motor abnormality processing instruction; According to the motor abnormality processing instruction, an adjustment control parameter is obtained; based on the adjustment control parameter, an adjustment instruction is triggered.

[0005] By adopting the above technical solution, a motor control system based on an adaptive control algorithm is provided. According to the actual motor operating parameters, such as current, voltage, and load conditions, the target speed, target torque, and energy efficiency index of the motor that the motor needs to achieve are formulated, that is, the overall control target of the motor is determined, and then the current operating condition information of the motor is identified to ensure that the motor can maintain a stable operating state under different operating conditions, thereby enhancing the robustness and adaptability of the motor control system; in the next step, the control parameters are dynamically and accurately adjusted through the adaptive control algorithm, the interaction parameters, and the motor prediction results, to obtain an adjustment control strategy that matches the overall control target of the motor, and by predicting the changes in the operating state of the motor within a specified time period, the optimization can be performed in advance. Optimize resource allocation; based on the adjustment control strategy, accurately control the real-time operating status of the motor when the motor is running. At the same time, when the motor is actually running, collect the actual operating status of the motor and calculate the state difference value, so as to timely discover abnormal conditions in the operation of the motor, such as overload, overheating, etc., effectively prevent motor damage or safety accidents, so as to timely detect the motor control effect and operation status, respond to changes in the actual operation of the motor, improve the response speed and dynamic performance of the intelligent control system, and then be able to obtain adjustment control parameters according to the motor abnormality processing instructions to further realize the intelligent control and control adjustment of the motor, thereby improving the reliability and control effect of the intelligent control system and enhancing the adaptive ability of the intelligent control system.

[0006] In a preferred example of the present application, the step of obtaining the motor operating parameters and determining the overall control target according to the motor operating parameters specifically includes: Acquire motor operating parameters, wherein the motor operating parameters include current, voltage, speed and load condition, and calculate the current energy efficiency value of the motor from the motor operating parameters; Determine the target speed, target torque and energy efficiency index of the motor according to the preset speed range, torque requirement and energy efficiency standard, combined with the motor operating parameters and the current energy efficiency value of the motor; The target speed, target torque and energy efficiency index of the motor are associated to determine the overall control target.

[0007] By adopting the above technical solution, the current, voltage, speed and load condition of the motor can be detected in real time to accurately evaluate the operating status of the motor; this is beneficial to improving the energy efficiency of the motor and reducing energy consumption; and the optimal overall control target considering multiple comprehensive factors is determined by the preset speed range, torque requirement and energy efficiency standard, which is beneficial to improving the data reliability and applicability of the motor intelligent control target.

[0008] In a preferred example of the present application: the current working condition information includes the load type, ambient temperature and power supply stability of the motor; the initial control parameters include the parameter settings of the controller, the voltage and current instructions of the vector control and the frequency output of the inverter; the current working condition information of the motor is identified; based on the overall control target and the current working condition information, the initial control parameters are calculated by the adaptive control algorithm, specifically including: Identify the current working condition information of the motor through the sensor monitoring device; Based on the overall control target and current operating condition information, the current parameter value of the controller, the current voltage of the vector control, the current current of the vector control and the current frequency of the inverter are obtained, and the initial control parameters are calculated by an adaptive control algorithm.

[0009] By adopting the above technical solution, based on the actual current operating condition information of the motor, the actual operating status of the motor can be understood more accurately, and the initial control parameters calculated by the adaptive control algorithm can be closer to the actual needs of the motor, so as to improve the control accuracy of the motor intelligent control. When an abnormal situation is found through the adaptive algorithm, timely measures can be taken to make adjustments to improve the stability of the system, and accurate calculation and dynamic adjustment of the motor control parameters can be achieved through automation and intelligent means.

[0010] In a preferred example of the present application: the monitoring of the interaction parameters between the motor and the load specifically includes: Monitor the motor's torque output in real time and calculate the torque fluctuation value; The time from when the motor receives the control command to when it reaches the target speed is recorded as the speed response time; Monitor the actual efficiency of the motor, compare the actual efficiency with the corresponding theoretical efficiency, and calculate the efficiency change value.

[0011] By adopting the above technical solution, the torque fluctuation value can reflect the dynamic response characteristics of the motor under load. Monitoring the torque fluctuation value is helpful to improve the control accuracy and stability of the motor. The speed response time is an indicator for evaluating the motor speed control performance to meet the real-time monitoring requirements of motor control. The efficiency change value can reflect the energy efficiency level of the motor in actual operation, which is helpful to maximize the energy efficiency of the motor through monitoring and adjustment.

[0012] In a preferred example of the present application, the step of obtaining an adjustment control parameter according to the motor abnormality processing instruction and triggering an adjustment instruction based on the adjustment control parameter specifically includes: According to the motor abnormality processing instruction, partition adjustment control parameter information is obtained; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor; Comparing the partition adjustment control parameter information with the preset control parameter thresholds corresponding to each control area; If the adjustment value of any control area is not within the corresponding preset control parameter threshold range, the adjustment instruction of the corresponding control area is triggered according to the control parameter information of the partition; If the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter thresholds, and the state difference between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, a secondary adjustment instruction is triggered, and according to the secondary adjustment instruction, secondary adjustment control state information is obtained, and secondary adjustment control is performed based on the secondary adjustment control state parameter information.

[0013] By adopting the above technical solution, the motor intelligent control system adopts refined zoning control and dynamic threshold management to ensure the rationality and safety of the motor adjustment process, and is conducive to more accurately responding to the operation changes of the motor under different working conditions, and improving the effectiveness and efficiency of motor control; by triggering the adjustment command when the adjustment value in any control area is not within the corresponding preset control parameter threshold range, it can respond and adjust to correct the deviation of the motor in operation in real time, and the secondary adjustment mechanism is conducive to more accurate adjustment of the control parameters to cope with complex and changeable working conditions, enhance the adaptability of the motor control system, and improve the intelligence level of the motor control system.

[0014] In a preferred example of the present application, after comparing the partition adjustment control parameter information with the preset control parameter thresholds corresponding to each control area, the method further includes: Based on the historical operation data and real-time operation status data of the motor, the optimal adjustment amount required for each control area to reach the preset motor operation status threshold range is obtained; Compare the optimal adjustment amount of each control area with the critical adjustment threshold and the limit adjustment threshold; When the optimal adjustment amount of a certain control area is less than the corresponding critical adjustment threshold, an adjustment instruction of the control area is automatically triggered; When the optimal adjustment amount of a certain control area is greater than or equal to the corresponding critical adjustment threshold and less than the corresponding limit adjustment threshold, a text box for inputting adjustment parameters is sent to a preset control user terminal based on the area identifier associated with the control area; When the optimal adjustment amounts of all control areas are greater than the corresponding limit adjustment thresholds, a change prompt message is sent to a preset control user terminal.

[0015] By adopting the above technical solution, a hierarchical response method is provided, and the motor intelligent control system is set to a combination of automation and intelligence. The manual judgment based on the optimal adjustment amount and the flexible adjustment method are beneficial to assist users to promptly discover possible serious problems in the motor on the basis of enhancing the user experience, which is beneficial to reducing the motor maintenance cost.

[0016] In the second aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A motor intelligent control system with an adaptive control algorithm, the system comprising: A data acquisition module, used to obtain motor operating parameters, and determine the overall control target according to the motor operating parameters; the overall control target includes the motor's target speed, target torque and energy efficiency index; An adaptive control algorithm module is used to identify the current working condition information of the motor; based on the overall control target and the current working condition information, calculate the initial control parameters through the adaptive control algorithm; monitor the interaction parameters between the motor and the load; the interaction parameters include torque fluctuation, speed response time and efficiency change; A self-learning module, used for dynamically adjusting the initial control parameters according to the interaction parameters and the overall control target to optimize the operation state of the motor; A prediction model and command triggering module is used to predict the change of the running state of the motor within a specified time period based on the historical running data and current real-time data of the motor acquired in a preset motor prediction model, obtain the motor prediction result, formulate an adjustment control strategy based on the motor prediction result, and trigger the motor control command; The running state monitoring module is used to collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, the motor abnormality processing instruction is triggered; The feedback adjustment module is used to obtain adjustment control parameters according to the motor abnormality processing instruction; and trigger the adjustment instruction based on the adjustment control parameters.

[0017] By adopting the above technical solution, a motor control system based on an adaptive control algorithm is provided. According to the actual motor operating parameters, such as current, voltage, and load conditions, the target speed, target torque, and energy efficiency index of the motor that the motor needs to achieve are formulated, that is, the overall control target of the motor is determined, and then the current operating condition information of the motor is identified to ensure that the motor can maintain a stable operating state under different operating conditions, thereby enhancing the robustness and adaptability of the motor control system; in the next step, the control parameters are dynamically and accurately adjusted through the adaptive control algorithm, the interaction parameters, and the motor prediction results, to obtain an adjustment control strategy that matches the overall control target of the motor, and by predicting the changes in the operating state of the motor within a specified time period, the optimization can be performed in advance. Optimize resource allocation; based on the adjustment control strategy, accurately control the real-time operating status of the motor when the motor is running. At the same time, when the motor is actually running, collect the actual operating status of the motor and calculate the state difference value, so as to timely discover abnormal conditions in the operation of the motor, such as overload, overheating, etc., effectively prevent motor damage or safety accidents, so as to timely detect the motor control effect and operation status, respond to changes in the actual operation of the motor, improve the response speed and dynamic performance of the intelligent control system, and then be able to obtain adjustment control parameters according to the motor abnormality processing instructions to further realize the intelligent control and control adjustment of the motor, thereby improving the reliability and control effect of the intelligent control system and enhancing the adaptive ability of the intelligent control system.

[0018] In a preferred example of the present application: the feedback adjustment module includes: A partition adjustment parameter acquisition unit, used to acquire partition adjustment control parameter information according to the motor abnormality processing instruction; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor; A regional parameter comparison unit, used to compare the regional adjustment control parameter information with the preset control parameter thresholds corresponding to each control area; The regional feedback adjustment unit is used to trigger the adjustment instruction of the corresponding control area according to the partition adjustment control parameter information if the adjustment value of any control area is not within the corresponding preset control parameter threshold range; if the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter threshold, and the state difference value between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, then the secondary adjustment instruction is triggered, and the secondary adjustment control state information is obtained according to the secondary adjustment instruction, and the secondary adjustment control is performed based on the secondary adjustment control state parameter information.

[0019] In summary, the present application includes at least one of the following beneficial technical effects: 1. A motor control system based on an adaptive control algorithm is provided. According to the actual motor operating parameters, such as current, voltage, and load conditions, the target speed, target torque, and energy efficiency index of the motor that the motor needs to achieve are formulated, that is, the overall control target of the motor is determined, and then the current operating condition information of the motor is identified to ensure that the motor can maintain a stable operating state under different operating conditions, thereby enhancing the robustness and adaptability of the motor control system. In the next step, the control parameters are dynamically and accurately adjusted through the adaptive control algorithm, the interaction parameters, and the motor prediction results to obtain an adjustment control strategy that matches the overall control target of the motor. By predicting the changes in the operating state of the motor within a specified time period, resource allocation can be optimized in advance. Based on the adjustment control strategy, the real-time operating state of the motor is accurately controlled when the motor is running. At the same time, when the motor is actually running, the actual operating state of the motor is collected and the state difference value is calculated to timely discover abnormal conditions in the operation of the motor, such as overload, overheating, etc., effectively prevent motor damage or safety accidents, so as to timely detect the motor control effect and operating status, respond to changes in the actual operation of the motor, improve the response speed and dynamic performance of the intelligent control system, and then be able to obtain adjustment control parameters according to the motor abnormality processing instructions to further realize the intelligent control and control adjustment of the motor, thereby improving the reliability and control effect of the intelligent control system and enhancing the adaptive ability of the intelligent control system; 2. Real-time detection of the motor's current, voltage, speed and load conditions to accurately evaluate the motor's operating status; this helps improve motor energy efficiency and reduce energy consumption; by determining the optimal overall control target based on multiple comprehensive factors through the preset speed range, torque requirements and energy efficiency standards, this helps improve the data reliability and applicability of the motor's intelligent control target; 3. Provide a hierarchical response method, set the motor intelligent control system to a combination of automation and intelligence, based on manual judgment and flexible adjustment of the optimal adjustment amount, which is conducive to assisting users to promptly discover possible serious problems in the motor on the basis of enhancing user experience, and is conducive to reducing motor maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a motor intelligent control method of an adaptive control algorithm according to an embodiment of the present application; Figure 2 It is a flowchart of step S1 in a motor intelligent control method of an adaptive control algorithm in one embodiment of the present application; Figure 3 It is a flowchart of step S2 in a motor intelligent control method of an adaptive control algorithm in one embodiment of the present application; Figure 4 This is a flow chart of step S6 in a motor intelligent control method of an adaptive control algorithm in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The present application is further described in detail below in conjunction with the accompanying drawings.

[0022] In one embodiment, if Figure 1 As shown, the present application discloses a motor intelligent control method with an adaptive control algorithm, which specifically includes the following steps: S1: Obtain motor operating parameters, and determine the overall control target based on the motor operating parameters; the overall control target includes the motor's target speed, target torque, and energy efficiency index.

[0023] In this embodiment, the motor operating parameters include current, voltage, speed, torque, temperature and load conditions; the motor operating parameters are collected in real time by measuring sensors installed on the motor (such as speed sensors, torque sensors, temperature sensors, etc.); the collected data is processed and analyzed to extract key information, such as current speed, current torque, and temperature, and the target speed, target torque and energy efficiency index of the motor are set as the overall control target according to the design specifications, application scenarios and user needs of the motor. The overall control target should be set within a reasonable target range considering the physical limitations and safety requirements of the motor.

[0024] S2: Identify the current operating condition information of the motor; based on the overall control target and the current operating condition information, calculate the initial control parameters through the adaptive control algorithm; monitor the interaction parameters between the motor and the load; the interaction parameters include torque fluctuation, speed response time and efficiency change.

[0025] In this embodiment, the initial control parameters include the parameter settings of the controller, the voltage and current instructions of the vector control, and the frequency output of the inverter; the current operating condition information of the motor is obtained through additional ambient temperature sensors, power quality monitors, etc., or external system interfaces, that is, during the operation of the motor, the interaction parameters such as torque fluctuations, speed response time and efficiency changes are continuously monitored.

[0026] S3: Dynamically adjust the initial control parameters according to the interaction parameters and the overall control objectives to optimize the operating state of the motor.

[0027] In this embodiment, the effect of the current control parameters is evaluated. If the evaluation result shows that the control effect is not ideal, the control parameters are dynamically adjusted through an adaptive control algorithm to optimize the operating state of the motor.

[0028] Specifically, the adjustment strategy should be based on the feedback control principle to ensure the stability and convergence of the system, and the adjustment process should be carried out step by step to avoid excessive adjustment range that may lead to system instability.

[0029] S4: In the preset motor prediction model, based on the acquired historical operation data and current real-time data of the motor, the operation state change of the motor within a specified time period is predicted to obtain the motor prediction result, and the adjustment control strategy is formulated based on the motor prediction result to trigger the motor control instruction.

[0030] In this embodiment, the motor prediction model is used to predict the running state of the motor within a specified time period to obtain a motor prediction result.

[0031] S5: Collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, trigger the motor abnormality processing instruction.

[0032] Specifically, if the state difference value exceeds a preset threshold range, it is determined that the motor is abnormal.

[0033] S6: According to the motor abnormality processing instruction, an adjustment control parameter is obtained; based on the adjustment control parameter, an adjustment instruction is triggered.

[0034] In this embodiment, by real-time monitoring and adjustment of control parameters, it is ensured that the motor can maintain the optimal operating state under different working conditions and improve the control accuracy. The application of adaptive control algorithms and motor prediction models enables the system to predict and respond to potential problems in advance, thereby enhancing the stability and reliability of the system.

[0035] In one embodiment, if Figure 2 As shown, in step S1, the motor operating parameters are obtained, and the overall control target is determined according to the motor operating parameters, which specifically includes: S11: Acquire motor operating parameters, which include current, voltage, speed and load conditions, and calculate the current energy efficiency value of the motor from the motor operating parameters.

[0036] In this embodiment, the operating parameters of the motor are collected in real time by using a variety of sensors installed on the motor, including current sensors, voltage sensors, speed sensors, and load sensors. The current energy efficiency value of the motor is calculated based on the motor's power output (which can be calculated by current, voltage, and load conditions) and input power (the product of voltage and current).

[0037] S12: According to a preset speed range, torque requirement and energy efficiency standard, combined with motor operating parameters and the current energy efficiency value of the motor, a target speed, target torque and energy efficiency index of the motor are determined.

[0038] Specifically, a comprehensive evaluation is conducted based on the motor operating parameters, current energy efficiency values, and preset conditions, and the physical limitations of the motor (such as maximum speed, maximum torque) and safety requirements must be considered during the evaluation process.

[0039] S13: Correlate the target speed, target torque and energy efficiency index of the motor to determine the overall control target.

[0040] In this embodiment, the optimal overall control target considering multiple comprehensive factors is determined by a preset speed range, torque requirement and energy efficiency standard, which is beneficial to improving the data reliability and applicability of the motor intelligent control target.

[0041] In one embodiment, the current operating condition information includes the load type, ambient temperature and power supply stability of the motor; the initial control parameters include the parameter settings of the controller, the voltage and current instructions of the vector control and the frequency output of the inverter; in step S2, the current operating condition information of the motor is identified; based on the overall control target and the current operating condition information, the initial control parameters are calculated by the adaptive control algorithm, specifically including: S21: Identify the current working condition information of the motor through the sensor monitoring device.

[0042] Specifically, appropriate sensors are installed in the motor and its surrounding environment, such as load type identification sensors (which can be indirectly judged by measuring the torque changes or vibration characteristics of the motor), ambient temperature sensors, and power quality monitoring sensors (used to monitor the stability and harmonic content of voltage and current, etc.).

[0043] S22: Based on the overall control target and the current operating condition information, the current parameter value of the controller, the current voltage of the vector control, the current current of the vector control and the current frequency of the inverter are obtained, and the initial control parameters are calculated by the adaptive control algorithm.

[0044] In this embodiment, the adaptive control algorithm calculates the initial control parameters through a complex calculation and optimization process based on the input overall control target and current operating condition information, combined with the current parameter values ​​of the controller and the vector control and current instructions of the inverter.

[0045] In one embodiment, if Figure 3 As shown, in step S2, the interaction parameters between the motor and the load are monitored, specifically including: S201: Monitor the torque output of the motor in real time and calculate the torque fluctuation value.

[0046] Specifically, a high-precision torque sensor is installed on the output shaft of the motor to measure the torque output of the motor in real time; the output signal of the torque sensor is collected periodically or continuously through a data acquisition system to record the real-time torque value of the motor; the collected torque data is processed, including filtering and denoising, to improve the accuracy of the data; and the torque fluctuation value is calculated based on the processed torque data.

[0047] S202: Record the time from when the motor receives the control instruction to when it reaches the target speed as the speed response time.

[0048] Specifically, at the moment the motor receives the control instruction, a start timestamp is recorded; the speed change of the motor is monitored in real time through the speed sensor; when the speed of the motor reaches the preset target speed, an end timestamp is recorded; based on the start timestamp and the end timestamp, the time from the motor receiving the control instruction to reaching the target speed, that is, the speed response time, is calculated.

[0049] S203: monitor the actual efficiency of the motor, compare the actual efficiency with the corresponding theoretical efficiency, and calculate the efficiency change value.

[0050] In this embodiment, the actual efficiency of the motor is calculated based on the input power (such as the product of voltage and current) and output power (such as the product of torque and speed) of the motor; the corresponding theoretical efficiency is obtained by looking up a table or calculating according to the design parameters of the motor and the current operating conditions (such as load type, ambient temperature, etc.); then the actual efficiency is compared with the theoretical efficiency, and the efficiency change value, that is, the difference between the actual efficiency and the theoretical efficiency, is calculated.

[0051] In one embodiment, if Figure 4 As shown, in step S6, according to the motor abnormality processing instruction, the adjustment control parameter is obtained; based on the adjustment control parameter, the adjustment instruction is triggered, which specifically includes: S61: According to the motor abnormality processing instruction, obtain partition adjustment control parameter information; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor.

[0052] In this embodiment, based on the situation where multiple motors are provided in the same motor control device or the same control range, the same control range is divided into multiple control areas for the convenience of distinguishing the areas where motors with motor abnormalities or control abnormalities are located; the partition adjustment control parameter information should record the adjustment direction and amplitude of each control area in detail for subsequent comparison and adjustment.

[0053] S62: Compare the partition adjustment control parameter information with the preset control parameter thresholds corresponding to each control area.

[0054] Specifically, each control area is associated with a pre-set reasonable preset control parameter threshold. The setting of the threshold needs to take into account the dynamic characteristics and safety margins of the motor to ensure that the adjusted parameters can meet the control requirements without causing damage to the motor.

[0055] S63: If the adjustment value of any control area is not within the corresponding preset control parameter threshold range, the adjustment instruction of the corresponding control area is triggered according to the partition adjustment control parameter information.

[0056] Specifically, if the comparison result shows that the adjustment value of any control area is not within the preset threshold range, it is determined that the area needs to be adjusted.

[0057] S64: If the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter thresholds, and the state difference between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, the secondary adjustment instruction is triggered, and the secondary adjustment control state information is obtained according to the secondary adjustment instruction, and the secondary adjustment control is performed based on the secondary adjustment control state parameter information.

[0058] Specifically, if the adjustment values ​​of all control areas do not exceed the preset threshold, but the state difference between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, the secondary adjustment process is entered. Based on the analysis results, a secondary adjustment instruction is generated, and the control areas and parameters that need to be adjusted are clarified.

[0059] In one embodiment, after step S62, a motor intelligent control method using an adaptive control algorithm further includes: S621: Based on the historical operation data and real-time operation status data of the motor, obtain the optimal adjustment amount required for each control area to reach a preset motor operation status threshold range.

[0060] In this embodiment, the collected data is processed and analyzed to identify the gap between the current motor operating state and the preset state threshold; based on the dynamic model and control theory of the motor, the optimal adjustment amount required for each control area to reach the preset state threshold is calculated.

[0061] S622: Compare the optimal adjustment amount of each control area with the critical adjustment threshold and the limit adjustment threshold.

[0062] Specifically, a critical adjustment threshold and a limit adjustment threshold are set for each control area, and the optimal adjustment amount of each control area is compared with the corresponding critical adjustment threshold and limit adjustment threshold to determine the adjustment range to which it belongs.

[0063] S623: When the optimal adjustment amount of a certain control area is less than the corresponding critical adjustment threshold, an adjustment instruction of the control area is automatically triggered.

[0064] Specifically, when the optimal adjustment amount of a control area is less than the corresponding critical adjustment threshold, it is considered that the area can reach a preset state through automatic adjustment. At this time, the adjustment instruction of the control area is automatically triggered and sent to the corresponding control module or actuator to implement the adjustment operation.

[0065] S624: When the optimal adjustment amount of a certain control area is greater than or equal to the corresponding critical adjustment threshold and less than the corresponding limit adjustment threshold, a text box for inputting adjustment parameters is sent to a preset control user terminal based on the area identifier associated with the control area.

[0066] Specifically, when the optimal adjustment amount of a certain control area is greater than or equal to the corresponding critical adjustment threshold and less than the corresponding limit adjustment threshold, it is considered that the adjustment of the area requires manual intervention; a text box containing adjustment parameter input items is generated on the preset control user terminal. The text box should clearly mark the control area to be adjusted, the current status, the recommended adjustment range and other information; a notification is sent to the control user terminal to prompt the user to adjust the parameters or perform maintenance and / or replacement operations according to the actual working conditions.

[0067] S625: When the optimal adjustment amounts of all control areas are greater than the corresponding limit adjustment thresholds, a change prompt message is sent to a preset control user terminal.

[0068] Specifically, when the optimal adjustment amounts of all control areas are greater than the corresponding limit adjustment thresholds, it is considered that the motor may have a serious fault or has reached the limit of its service life; based on the judgment result, a message containing replacement prompt information is generated, and the replacement prompt information clearly points out the problems with the motor, possible consequences, and recommended solutions (such as replacing the motor, repairing, etc.); by calculating the optimal adjustment amount and comparing it with the threshold, fine adjustment of the motor control parameters is achieved, and the adjustment precision and accuracy are improved; according to the different ranges of the adjustment amount, the adjustment command is automatically triggered or manual intervention is requested, thereby enhancing the flexibility and adaptability of the system.

[0069] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0070] In one embodiment, a motor intelligent control system with an adaptive control algorithm is provided. The motor intelligent control system with an adaptive control algorithm corresponds to a motor intelligent control method with an adaptive control algorithm in the above embodiment.

[0071] An intelligent motor control system with an adaptive control algorithm includes a data acquisition module, an adaptive control algorithm module, a self-learning module, a prediction model and command trigger module, an operation status monitoring module, and a feedback adjustment module. The detailed description of each functional module is as follows: The data acquisition module is used to obtain the motor operating parameters and determine the overall control target according to the motor operating parameters; the overall control target includes the motor's target speed, target torque and energy efficiency index; The adaptive control algorithm module is used to identify the current working condition information of the motor; based on the overall control target and the current working condition information, the initial control parameters are calculated by the adaptive control algorithm; the interaction parameters between the motor and the load are monitored; the interaction parameters include torque fluctuation, speed response time and efficiency change; A self-learning module is used to dynamically adjust the initial control parameters according to the interaction parameters and the overall control objectives to optimize the operation status of the motor; The prediction model and command trigger module is used to predict the change of the motor's operating state within a specified time period in a preset motor prediction model based on the acquired historical motor operation data and current real-time data, obtain the motor prediction result, formulate an adjustment control strategy based on the motor prediction result, and trigger the motor control command; The running state monitoring module is used to collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, the motor abnormality processing instruction is triggered; The feedback adjustment module is used to obtain adjustment control parameters according to the motor abnormality processing instruction; based on the adjustment control parameters, the adjustment instruction is triggered.

[0072] Optionally, the feedback adjustment module includes: A partition adjustment parameter acquisition unit is used to acquire partition adjustment control parameter information according to the motor abnormality processing instruction; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor; A regional parameter comparison unit, used to compare the regional adjustment control parameter information with the preset control parameter threshold corresponding to each control area; The regional feedback adjustment unit is used to trigger the adjustment instruction of the corresponding control area according to the partition adjustment control parameter information if the adjustment value of any control area is not within the corresponding preset control parameter threshold range; if the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter threshold, and the state difference value between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, then the secondary adjustment instruction is triggered, and the secondary adjustment control state information is obtained according to the secondary adjustment instruction, and the secondary adjustment control is performed based on the secondary adjustment control state parameter information.

[0073] For the specific limitations of a motor intelligent control system of an adaptive control algorithm, please refer to the limitations of a motor intelligent control method of an adaptive control algorithm in the above text, which will not be repeated here; each module in the above-mentioned motor intelligent control system of an adaptive control algorithm can be implemented in whole or in part through software, hardware and a combination thereof; each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0074] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0075] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A motor intelligent control method based on an adaptive control algorithm, characterized in that: include: Acquire motor operating parameters, and determine overall control targets according to the motor operating parameters; The overall control target includes the target speed, target torque and energy efficiency index of the motor; Identify the current working condition information of the motor; Based on the overall control target and the current working condition information, initial control parameters are calculated by an adaptive control algorithm; interaction parameters between the motor and the load are monitored; the interaction parameters include torque fluctuation, speed response time and efficiency change; According to the interaction parameters and the overall control target, the initial control parameters are dynamically adjusted to optimize the operating state of the motor; In a preset motor prediction model, based on the acquired historical operation data and current real-time data of the motor, the operation state change of the motor within a specified time period is predicted to obtain a motor prediction result, and an adjustment control strategy is formulated based on the motor prediction result to trigger a motor control instruction; Collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, trigger the motor abnormality processing instruction; According to the motor abnormality processing instruction, obtaining adjustment control parameters; Based on the adjustment control parameter, an adjustment instruction is triggered.

2. The motor intelligent control method of the adaptive control algorithm according to claim 1 is characterized in that: The obtaining of the motor operating parameters and determining the overall control target according to the motor operating parameters specifically includes: Acquire motor operating parameters, wherein the motor operating parameters include current, voltage, speed and load condition, and calculate the current energy efficiency value of the motor from the motor operating parameters; Determine the target speed, target torque and energy efficiency index of the motor according to the preset speed range, torque requirement and energy efficiency standard, combined with the motor operating parameters and the current energy efficiency value of the motor; The target speed, target torque and energy efficiency index of the motor are associated to determine the overall control target.

3. The motor intelligent control method of the adaptive control algorithm according to claim 1 is characterized in that: The current working condition information includes the load type, ambient temperature and power supply stability of the motor; the initial control parameters include the parameter settings of the controller, the voltage and current instructions of the vector control and the frequency output of the inverter; the current working condition information of the motor is identified; Based on the overall control target and the current operating condition information, the initial control parameters are calculated by the adaptive control algorithm, specifically including: Identify the current working condition information of the motor through the sensor monitoring device; Based on the overall control target and current operating condition information, the current parameter value of the controller, the current voltage of the vector control, the current current of the vector control and the current frequency of the inverter are obtained, and the initial control parameters are calculated by an adaptive control algorithm.

4. The motor intelligent control method of the adaptive control algorithm according to claim 1 is characterized in that: The monitoring of the interaction parameters between the motor and the load specifically includes: Monitor the motor's torque output in real time and calculate the torque fluctuation value; The time from when the motor receives the control command to when it reaches the target speed is recorded as the speed response time; Monitor the actual efficiency of the motor, compare the actual efficiency with the corresponding theoretical efficiency, and calculate the efficiency change value.

5. The motor intelligent control method of the adaptive control algorithm according to claim 1 is characterized in that: According to the motor abnormality processing instruction, obtaining adjustment control parameters; Based on the adjustment control parameter, triggering an adjustment instruction specifically includes: According to the motor abnormality processing instruction, partition adjustment control parameter information is obtained; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor; Comparing the partition adjustment control parameter information with the preset control parameter thresholds corresponding to each control area; If the adjustment value of any control area is not within the corresponding preset control parameter threshold range, the adjustment instruction of the corresponding control area is triggered according to the control parameter information of the partition; If the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter thresholds, and the state difference between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, a secondary adjustment instruction is triggered, and according to the secondary adjustment instruction, secondary adjustment control state information is obtained, and secondary adjustment control is performed based on the secondary adjustment control state parameter information.

6. The motor intelligent control method of the adaptive control algorithm according to claim 5 is characterized in that: After comparing the partition adjustment control parameter information with the preset control parameter thresholds corresponding to each control area, the method further includes: Based on the historical operation data and real-time operation status data of the motor, the optimal adjustment amount required for each control area to reach the preset motor operation status threshold range is obtained; Compare the optimal adjustment amount of each control area with the critical adjustment threshold and the limit adjustment threshold; When the optimal adjustment amount of a certain control area is less than the corresponding critical adjustment threshold, an adjustment instruction of the control area is automatically triggered; When the optimal adjustment amount of a certain control area is greater than or equal to the corresponding critical adjustment threshold and less than the corresponding limit adjustment threshold, a text box for inputting adjustment parameters is sent to a preset control user terminal based on the area identifier associated with the control area; When the optimal adjustment amounts of all control areas are greater than the corresponding limit adjustment thresholds, a change prompt message is sent to a preset control user terminal.

7. A motor intelligent control system with an adaptive control algorithm, characterized in that: The system comprises: A data acquisition module, used to obtain motor operating parameters, and determine the overall control target according to the motor operating parameters; the overall control target includes the motor's target speed, target torque and energy efficiency index; An adaptive control algorithm module is used to identify the current working condition information of the motor; based on the overall control target and the current working condition information, calculate the initial control parameters through the adaptive control algorithm; monitor the interaction parameters between the motor and the load; the interaction parameters include torque fluctuation, speed response time and efficiency change; A self-learning module, used for dynamically adjusting the initial control parameters according to the interaction parameters and the overall control target to optimize the operation state of the motor; A prediction model and command triggering module is used to predict the change of the running state of the motor within a specified time period based on the historical running data and current real-time data of the motor acquired in a preset motor prediction model, obtain the motor prediction result, formulate an adjustment control strategy based on the motor prediction result, and trigger the motor control command; The running state monitoring module is used to collect the actual running state of the motor, compare the actual running state with the predicted running state of the motor prediction result, and calculate the state difference value; if the state difference value exceeds the preset threshold range, the motor abnormality processing instruction is triggered; The feedback adjustment module is used to obtain adjustment control parameters according to the motor abnormality processing instruction; and trigger the adjustment instruction based on the adjustment control parameters.

8. The motor intelligent control system of the adaptive control algorithm according to claim 7 is characterized in that: The feedback adjustment module comprises: A partition adjustment parameter acquisition unit, used to acquire partition adjustment control parameter information according to the motor abnormality processing instruction; the partition adjustment control parameter information includes adjustment values ​​of initial control parameters of different control areas of the motor; A regional parameter comparison unit, used to compare the regional adjustment control parameter information with the preset control parameter thresholds corresponding to each control area; The regional feedback adjustment unit is used to trigger the adjustment instruction of the corresponding control area according to the partition adjustment control parameter information if the adjustment value of any control area is not within the corresponding preset control parameter threshold range; if the adjustment values ​​of all control areas do not exceed the corresponding preset control parameter threshold, and the state difference value between the actual operating state and the predicted operating state of the motor exceeds the preset threshold range, then the secondary adjustment instruction is triggered, and the secondary adjustment control state information is obtained according to the secondary adjustment instruction, and the secondary adjustment control is performed based on the secondary adjustment control state parameter information.

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