Motor drive control method and device, computer device and storage medium

Abstract

The application relates to a motor driving control method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a current running state parameter of a motor to be controlled in a current control period; inputting the current running state parameter into a running state prediction model to obtain a plurality of predicted running state parameters of the motor to be controlled in a preset period; the plurality of predicted running state parameters correspond to a plurality of candidate control voltages for controlling the motor to be controlled; inputting the plurality of predicted running state parameters into a tracking error processing model to obtain a tracking error corresponding to each candidate control voltage; in the case that the tracking error meets a preset condition, taking the candidate control voltage corresponding to the tracking error as a target control voltage; and in a next control period of the current control period, driving and controlling the motor by using the target control voltage. The method can reduce the multi-stage cascaded control structure, thereby improving the response speed of motor control.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and in particular to a motor drive control method, apparatus, computer equipment, and storage medium. Background Technology

[0002] The operating mechanism of a high-voltage circuit breaker is the mechanism that controls the opening and closing operations of the circuit breaker, playing a crucial role in its performance and reliability. Currently, commonly used operating mechanisms include electromagnetic, spring, pneumatic, and hydraulic mechanisms.

[0003] The motor-driven operating mechanism is a new type of high-voltage circuit breaker operating mechanism. Compared with traditional operating mechanisms, the motor-driven operating mechanism has only one rotating motor rotor component, resulting in fewer moving parts and direct impact points, and lower noise. The motor-driven operating mechanism directly connects the motor to the high-voltage circuit breaker and achieves real-time position tracking through position servo control of the motor, thereby realizing real-time control of the circuit breaker's opening and closing operations. In actual operation, motors often cannot operate in a steady state continuously. Especially considering the motors used in operating mechanisms, whose action time is on the order of milliseconds, the motor operation is constantly changing over time. Therefore, control methods that better meet the requirements of speed and tracking are necessary.

[0004] PMSMs (Permanent Magnet Synchronous Motors), which are key drive components of motor-driven operating mechanisms, are currently often controlled using vector control methods. However, vector control can lead to problems such as slow dynamic response speed in the motor. Summary of the Invention

[0005] Therefore, it is necessary to provide a motor drive control method, device, computer equipment, and storage medium that can improve response speed in response to the above-mentioned technical problems.

[0006] In a first aspect, this application provides a motor drive control method, the method comprising:

[0007] Obtain the current operating status parameters of the motor to be controlled in the current control cycle;

[0008] The current operating status parameters are input into the operating status prediction model to predict multiple predicted operating status parameters of the motor to be controlled within a preset period; the multiple predicted operating status parameters correspond to multiple candidate control voltages for controlling the motor to be controlled.

[0009] By inputting multiple predicted operating state parameters into the tracking error processing model, the tracking error corresponding to each candidate control voltage is obtained.

[0010] If the tracking error meets the preset conditions, the candidate control voltage corresponding to the tracking error will be used as the target control voltage.

[0011] In the next control cycle of the current control cycle, the motor is driven and controlled using the target control voltage.

[0012] In one embodiment, the generation method of the running state prediction model includes:

[0013] Establish the continuous state equations for current, speed, and position of the motor to be controlled;

[0014] Based on the continuous state equations of current, rotational speed, and position, an operational state prediction model is generated.

[0015] In one embodiment, an operating state prediction model is generated based on the current continuous state equation, the rotational speed continuous state equation, and the position continuous state equation, including:

[0016] By using Taylor series expansion, the continuous state equations for current, rotational speed, and position are discretized respectively, resulting in Taylor series expansions for current, rotational speed, and position.

[0017] Based on the Taylor series expansions of current, rotational speed, and position, a predictive model for the operating state is generated.

[0018] In one embodiment, establishing a position-continuous state equation includes:

[0019] The moment of inertia, number of pole pairs, flux linkage, and coefficient of friction of the motor to be controlled are obtained, as well as the load torque of the motor to be controlled.

[0020] A positional continuity state equation is established based on the moment of inertia, number of pole pairs, flux linkage, coefficient of friction, and load torque.

[0021] In one embodiment, the current operating status parameters include the current motor speed and the current motor current;

[0022] Obtain the load torque of the motor to be controlled, including:

[0023] By inputting the current motor speed and current into the load torque observation model, the load torque of the motor to be controlled can be obtained.

[0024] In one embodiment, the generation method of the tracking error processing model includes:

[0025] Obtain the reference current, reference speed, and reference position;

[0026] Obtain the current tracking error for current, the speed tracking error for rotational speed, and the position tracking error for location;

[0027] A tracking error processing model is generated based on current tracking error, rotational speed tracking error, and position tracking error.

[0028] In one embodiment, the motor is driven and controlled using a target control voltage, including:

[0029] Obtain the initial position value and preset position value of the motor to be controlled in the next control cycle;

[0030] Based on the initial position value and the preset position value, obtain the duty cycle corresponding to the control time of the target control voltage;

[0031] The motor drive is controlled based on the target control voltage and duty cycle.

[0032] Secondly, this application also provides a motor drive control device, the device comprising:

[0033] The current parameter acquisition module is used to acquire the current operating status parameters of the motor to be controlled in the current control cycle;

[0034] The prediction parameter acquisition module is used to input the current operating status parameters into the operating status prediction model to obtain multiple predicted operating status parameters of the motor to be controlled within a preset period; the multiple predicted operating status parameters correspond to multiple candidate control voltages for controlling the motor to be controlled.

[0035] The tracking error acquisition module is used to input multiple predicted operating state parameters into the tracking error processing model to obtain the tracking error corresponding to each candidate control voltage.

[0036] The voltage determination module is used to select the candidate control voltage corresponding to the tracking error as the target control voltage when the tracking error meets the preset conditions.

[0037] The drive control module is used to drive the motor using the target control voltage in the next control cycle of the current control cycle.

[0038] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0039] Fourthly, this application also provides a computer-readable storage medium. This computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the above-described method.

[0040] The aforementioned motor drive control method, device, computer equipment, and storage medium acquire the current operating state parameters of the motor to be controlled in the current control cycle; input the current operating state parameters into an operating state prediction model to predict multiple predicted operating state parameters of the motor to be controlled within a preset cycle; these multiple predicted operating state parameters correspond to multiple candidate control voltages for controlling the motor; input these multiple predicted operating state parameters into a tracking error processing model to obtain the tracking error corresponding to each candidate control voltage; if the tracking error meets a preset condition, the candidate control voltage corresponding to the tracking error is used as the target control voltage; and in the next control cycle of the current control cycle, the motor is driven and controlled using the target control voltage. This application directly predicts multiple predicted operating state parameters, directly obtains the tracking error under each candidate control voltage based on these directly predicted operating state parameters, and directly obtains the target control voltage from the multiple candidate control voltages based on the tracking error. Compared with traditional technologies, this application directly predicts operating state parameters and directly obtains the target control voltage for the next cycle based on the prediction results, without relying on a multi-stage cascaded structure for motor control, reducing the impact of the multi-stage cascaded control structure and thus improving the response speed of motor control. Attached Figure Description

[0041] Figure 1 This is an application environment diagram of the motor drive control method in one embodiment;

[0042] Figure 2 This is a flowchart illustrating a motor drive control method in one embodiment;

[0043] Figure 3 This is a flowchart illustrating the motor drive control method in another embodiment;

[0044] Figure 4 This is a schematic diagram illustrating the use of the final value method to obtain the duty cycle in another embodiment;

[0045] Figure 5 This is a schematic diagram of the data flow of a permanent magnet synchronous motor servo system based on direct predictive position control in a specific embodiment.

[0046] Figure 6 This is a flowchart illustrating a specific embodiment of a motor control method.

[0047] Figure 7 This is a structural block diagram of a motor drive control device in one embodiment;

[0048] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0050] The motor drive control method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located on a cloud or other network server. The data storage system can store current operating status parameters, operating status prediction models, and other relevant data. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0051] In one embodiment, such as Figure 2 As shown, a motor drive control method is provided, which is applied to... Figure 1 Taking the server in the example, the following steps are included:

[0052] Step S202: Obtain the current operating status parameters of the motor to be controlled in the current control cycle.

[0053] The motor to be controlled can be a PMSM (Permanent Magnet Synchronous Motor). The current control cycle refers to the control cycle in which the current moment occurs. The current operating status parameters refer to the parameters collected from the motor to be controlled in the current cycle.

[0054] For example, during the current control cycle, parameters are collected from the motor to be controlled to obtain the current operating status parameters of the motor. These current operating status parameters may include the d-axis stator current, q-axis stator current, d-axis stator inductance, q-axis stator inductance, d-axis stator voltage, q-axis stator voltage, angular velocity, rotor position, etc. Fixed parameters specific to the motor to be controlled can also be directly obtained, such as stator resistance, number of pole pairs, and flux linkage of the permanent magnets.

[0055] Step S204: Input the current operating status parameters into the operating status prediction model to predict multiple predicted operating status parameters of the motor to be controlled within a preset period; the multiple predicted operating status parameters correspond to multiple candidate control voltages used to control the motor to be controlled.

[0056] The current operating state parameters can be the current, speed, and position of the motor to be controlled, while the predicted operating state parameters can be the predicted current, predicted speed, and predicted position of the motor to be controlled. The operating state prediction model can be a model that directly predicts the current, speed, and position of the motor to be controlled. Multiple predicted operating state parameters refer to the predicted parameters generated based on the operating state prediction model. One predicted operating state parameter corresponds to a prediction under a candidate control voltage. The candidate control voltage is a voltage vector that can control the motor.

[0057] For example, by using an operational state prediction model and the current operational state parameters, multiple predicted operational state parameters corresponding to the multiple candidate control voltages are predicted when the motor is controlled by multiple candidate control voltages. For instance, by inputting the current operational state parameters into the operational state prediction model, the model generates a first predicted operational state parameter for the first candidate control voltage. This first predicted operational state parameter is the predicted operational state parameter when the motor is controlled by the first candidate control voltage. By directly predicting the operational state parameters, the slow response speed problem caused by multi-level cascaded control structures can be avoided.

[0058] Step S206: Input multiple predicted operating state parameters into the tracking error processing model to obtain the tracking error corresponding to each candidate control voltage.

[0059] The tracking error processing model can be a model that obtains the tracking errors corresponding to the current, speed, and position of the motor to be controlled. The tracking error refers to the error between the predicted operating state parameters and the corresponding reference values, which can be used to judge or determine the effectiveness of different candidate control voltages in controlling the motor.

[0060] For example, multiple predicted operating state parameters are input into the tracking error processing model, and the tracking error corresponding to each candidate control voltage is generated by the tracking error processing model.

[0061] Step S208: If the tracking error meets the preset conditions, the candidate control voltage corresponding to the tracking error is taken as the target control voltage.

[0062] The preset condition can be the condition that minimizes the tracking error, that is, the minimum tracking error is determined from multiple tracking errors. The target control voltage refers to the voltage used to control the motor in the next cycle, and can be a voltage vector.

[0063] For example, based on the tracking error, the candidate control voltage corresponding to the smallest tracking error is taken as the target control voltage.

[0064] Step S210: In the next control cycle of the current control cycle, drive the motor using the target control voltage.

[0065] For example, in the Kth cycle, the operating state parameters of the motor to be controlled are predicted, and the target control voltage is determined based on the tracking error after prediction. The target control voltage is then applied to the motor control in the K+1 cycle.

[0066] In this embodiment, multiple predicted operating state parameters are obtained by direct prediction. Based on the predicted operating state parameters obtained by direct prediction, the tracking error corresponding to each candidate control voltage is directly obtained. Based on the tracking error, the target control voltage is directly obtained from multiple candidate control voltages. Compared with traditional technology, this application directly predicts the operating state parameters and directly obtains the target control voltage for the next cycle based on the prediction results. It does not rely on a multi-level cascaded structure to control the motor, reducing the impact of the multi-level cascaded control structure, thereby improving the response speed of motor control.

[0067] In one embodiment, the generation method of the runtime state prediction model includes:

[0068] Establish the continuous state equations for current, speed, and position of the motor to be controlled;

[0069] Based on the continuous state equations of current, rotational speed, and position, an operational state prediction model is generated.

[0070] Among them, the current continuous state equation refers to the continuous state equation of the current of the motor to be controlled. The speed continuous state equation refers to the continuous state equation of the speed of the motor to be controlled. The position continuous state equation refers to the continuous state equation of the position (rotation angle) of the motor to be controlled.

[0071] For example, an operating state prediction model is generated based on the current continuous state equation, the rotational speed continuous state equation, and the position continuous state equation.

[0072] In this embodiment, the operating state prediction model is directly generated by the continuous state equations of current, speed, and position. The current, speed, and position can be predicted directly based on the operating state prediction model without relying on layer-by-layer prediction, which can improve the response speed of the control motor.

[0073] In a specific embodiment, the runtime state prediction model is expressed as follows:

[0074]

[0075] Among them, u d For d-axis stator voltage, u q i is the q-axis stator voltage; d For d-axis stator current, iq L is the q-axis stator current; s For stator inductance; R s Stator resistance; ψ f ω is the flux linkage of the permanent magnet; p is the number of pole pairs; ω m θ is the rotor's mechanical angular velocity. m T represents the rotor position. e T is the electromagnetic torque. L For load torque; J m B is the moment of inertia. m is the coefficient of friction.

[0076] The above expression (1) is the continuous state equation set of the motor to be controlled in the two-phase rotating dq coordinate system. Among them, the dq coordinate system refers to the coordinate system established with the d and q axes of the motor to be controlled; the d axis of the motor to be controlled is the direct axis of the motor, and the q axis is the quadrature axis of the motor. In a synchronous motor, the direction of the direct axis is on the center line of the rotor magnetic poles, and the direction of the quadrature axis is on the perpendicular bisector between two adjacent magnetic poles.

[0077] In this embodiment, by modeling using the above expressions, the continuous states corresponding to the d-axis stator current, q-axis stator current, rotational speed (mechanical angular velocity), and position (rotor position, angle) can be directly predicted. This method, which does not rely on layer-by-layer prediction, improves the response speed of the controlled motor.

[0078] In one embodiment, an operating state prediction model is generated based on the current continuous state equation, the rotational speed continuous state equation, and the position continuous state equation, including:

[0079] By using Taylor series expansion, the continuous state equations for current, rotational speed, and position are discretized respectively, resulting in Taylor series expansions for current, rotational speed, and position.

[0080] Based on the Taylor series expansions of current, rotational speed, and position, a predictive model for the operating state is generated.

[0081] For example, by generating an operating state prediction model based on the Taylor series expansions of current, speed, and position, a direct prediction of current, speed, and position can be achieved, thereby improving the response speed of motor control.

[0082] In this embodiment, by performing Taylor expansion on the continuous state equations of current, rotational speed, and position, the prediction accuracy of current, rotational speed, and position can be improved compared to discretization using the forward Euler method.

[0083] In a specific embodiment, expression (1) can be discretized using Taylor expansion to obtain the following expressions (2) and (3):

[0084]

[0085]

[0086] Among them, T s This represents the control cycle of the motor to be controlled. d (k+1) represents the predicted d-axis electron current for the next period, i q (k+1) represents the predicted value of the q-axis electron current in the next period, ω m (k+1) represents the predicted rotational speed for the next cycle, θ m (k+1) is the predicted position value for the next cycle.

[0087] In this embodiment, by using Taylor expansion to discretize the continuous state equations, a predictive model of the operating state is obtained, which can directly predict the values ​​of the operating state parameters in the next cycle, thereby improving the response speed of motor control.

[0088] In one embodiment, establishing a position-continuous state equation includes:

[0089] The moment of inertia, number of pole pairs, flux linkage, and coefficient of friction of the motor to be controlled are obtained, as well as the load torque of the motor to be controlled.

[0090] A positional continuity state equation is established based on the moment of inertia, number of pole pairs, flux linkage, coefficient of friction, and load torque.

[0091] Among these parameters, moment of inertia, number of pole pairs, flux linkage, and coefficient of friction are fixed parameters of the motor under control, which can be directly obtained from the preset parameters of the motor. Load torque can be obtained using a load observer. The load observer can be set on the motor under control to monitor its operating status.

[0092] For example, fixed parameters of the motor to be controlled, such as moment of inertia, number of pole pairs, flux linkage, and coefficient of friction, can be directly obtained; and the load torque of the motor to be controlled can be obtained through a load observer. Based on the moment of inertia, number of pole pairs, flux linkage, coefficient of friction, and load torque, a position continuous state equation is established.

[0093] In this embodiment, a position continuous state equation is established based on the moment of inertia, number of pole pairs, flux linkage, coefficient of friction, and load torque. This equation can directly predict the position of the motor to be controlled in the next cycle, thereby improving the response speed of motor control.

[0094] In one embodiment, the current operating status parameters include the current motor speed and the current motor current;

[0095] Obtain the load torque of the motor to be controlled, including:

[0096] By inputting the current motor speed and current into the load torque observation model, the load torque of the motor to be controlled can be obtained.

[0097] Here, "current motor speed" refers to the motor speed acquired during the current cycle. "Current motor current" refers to the motor current acquired during the current cycle. "Load torque observation model" refers to the model used to acquire load torque.

[0098] For example, the current motor speed and current motor current are input into the load torque observation model, and the load torque of the motor to be controlled is obtained through the load torque observation model.

[0099] In this embodiment, the load torque of the motor to be controlled is obtained through the load torque observation model, which can provide a data foundation for establishing an operating state prediction model.

[0100] In a specific embodiment, the load torque observation model is expressed as follows:

[0101]

[0102] in, The observed value of the motor speed within period k+1. Let ω be the observed value of the motor speed over period k. m (k) represents the actual rotational speed of the motor within period k, i q (k) represents the q-axis stator current of the motor during period k. Let k be the observed values ​​of the load torque over period k. This represents the observed load torque over period k+1. l1 and l2 are feedback gain coefficients, both of which can be set according to actual conditions.

[0103] In this embodiment, by establishing a load torque observation model, a data foundation can be provided for establishing an operating state prediction model.

[0104] In one embodiment, such as Figure 3 As shown, the generation method of the tracking error processing model includes:

[0105] Step S302: Obtain the reference current, reference speed, and reference position;

[0106] Step S304: Obtain the current tracking error for current, the speed tracking error for rotational speed, and the position tracking error for position.

[0107] Step S306: Based on the current tracking error, speed tracking error, and position tracking error, a tracking error processing model is generated.

[0108] Among them, the reference current refers to the reference current for the motor under control, which corresponds to the predicted current. The reference speed refers to the reference speed for the motor under control, which corresponds to the predicted speed. The reference position refers to the reference position for the motor under control, which corresponds to the predicted position.

[0109] For example, a tracking error processing model is generated based on current tracking error, speed tracking error, and position tracking error. Based on the tracking error processing model, the tracking errors between the predicted current, predicted speed, and predicted position and their respective reference values ​​can be obtained. Based on the tracking errors, the target control voltage for the next cycle can be determined.

[0110] In this embodiment, by establishing a tracking error processing model, a basis can be provided for obtaining the tracking error. Furthermore, the tracking error between the operating state parameters and the reference value can be obtained directly based on the tracking error processing model, thereby improving the response speed of the motor to be controlled.

[0111] In a specific embodiment, the tracking error processing model can be established through a cost function, as shown in the following expression (5):

[0112]

[0113] in, For reference speed, For reference position, This is the reference value for the q-axis stator current. This is the reference value for the d-axis stator current. J DPPC This refers to the tracking error of the operating parameters.

[0114] Where, f(i) d i q ,ω m ) is the limiting term, as shown in expression (6). The main purpose of setting the limiting term is to prevent the voltage vector of overcurrent or overspeed from being selected.

[0115]

[0116] I max ω is the maximum current value. max This represents the maximum rotational speed.

[0117] In this embodiment, a tracking error processing model is established using a cost function, which provides a basis for obtaining the tracking error. Furthermore, the tracking error between the operating state parameters and the reference value can be directly obtained based on the tracking error processing model, thereby improving the response speed of the motor to be controlled.

[0118] In one embodiment, the motor is driven and controlled using a target control voltage, including:

[0119] Obtain the initial position value and preset position value of the motor to be controlled in the next control cycle;

[0120] Based on the initial position value and the preset position value, obtain the duty cycle corresponding to the control time of the target control voltage;

[0121] The motor drive is controlled based on the target control voltage and duty cycle.

[0122] The initial position value refers to the initial position of the motor to be controlled in the next control cycle. The preset position value refers to the preset position of the motor to be controlled in the next control cycle. There may be an error between the initial position value and the preset position value.

[0123] For example, the duty cycle corresponding to the control time of the target control voltage can be calculated based on the position error between the initial position value and the preset position value. The control time of the target control voltage is then determined based on the duty cycle. In the next control cycle, the motor to be controlled is controlled according to the determined control time.

[0124] In this embodiment, the duty cycle is determined by the position error, and the control time of the target control voltage is determined based on the duty cycle. During the control time, the target control voltage is used to control the motor under control, avoiding the low control accuracy caused by using the target control voltage to control the motor under control throughout the entire cycle. This can improve the prediction error reduction and control performance.

[0125] In a specific embodiment, the duty cycle modulation method is used to determine the effective voltage vector's duration t1 and the zero voltage vector's duration t2 within the next control cycle (k+1) based on the motor position and the influence of different voltage vectors on the position change, as shown in expression (7):

[0126]

[0127] Where d is the duty cycle, t1 is the control time of the effective voltage vector (target control voltage), and t2 is the control time of the zero voltage vector.

[0128] For example, the duty cycle d is determined by the final value method, such as... Figure 4As shown, kTs is the initial time of period k, and (k+1)Ts is the initial time of period k+1. The control objective of the final value method is to ensure that the actual position value accurately follows the set value at the end of each control cycle.

[0129] According to the control objective of the final value method, the absolute value of the position error is shown in expression (8):

[0130] E=|θ e +θ1t1+θ2t2| (8)

[0131] Where θe=θm-θm* is the initial error of the motor position, and θm and θm* are the initial value and set value of the motor position, respectively. θ1*t1 and θ2*t2 are the changes in motor position under the action of the effective voltage vector and the zero voltage vector within the current control cycle k, respectively. To facilitate calculation and solution, expression (8) is rewritten as:

[0132] E = θ1 2 t1 2 +(2θ e θ1+θ1 2 +θ1θ2t2)t1+[(θ e ) 2 +2θ e θ2t2+θ2 2 t2 2 (9) Differentiate expression (9) with respect to t1 to obtain the minimum value of the action time t1:

[0133]

[0134] Combining expressions (7) and (10), the duty cycle d can be obtained. Since the duty cycle ranges from [0,1], the expression for the duty cycle d is:

[0135]

[0136] In this embodiment, the duty cycle is determined by the initial error of the motor position, and the control time of the effective voltage vector and the zero voltage vector is determined based on the duty cycle. During the cycle time, the motor to be controlled is controlled using the effective voltage vector and the zero voltage vector. This avoids the low control accuracy caused by using the effective voltage vector to control the motor to be controlled throughout the entire cycle, thereby improving the prediction error and control performance.

[0137] In one specific embodiment, a permanent magnet synchronous motor servo system based on direct predictive position control, such as... Figure 5 As shown. Current data i for the current period k is collected from the PMSM. a，b，c (k), rotational speed ω m (k), position θm (k), through coordinate transformation, obtain the d-axis stator current and the q-axis stator current i. d，q (k), rotational speed ω m (k) and position θ m (k), through the load observer, obtain the observed value of the load torque within k cycles. The d-axis stator current and the q-axis stator current i d，q (k), rotational speed ω m (k), position θ m (k) and load torque The input is fed into the operating state prediction model, which is designed for 8 voltage vectors u 0,1，…，7 The control state is used to predict the d-axis stator current, q-axis stator current, position, and speed, and to obtain the predicted value i of the q-axis electronic current for the next cycle k+1. q (k+1), predicted d-axis electron current i d (k+1), predicted rotational speed ω m (k+1), Predicted location value θ m (k+1). Let i... q (k+1),i d (k+1), ω m (k+1), θ m (k+1) and reference speed Reference position Reference value of q-axis stator current Reference value of d-axis stator current Substituting this into the cost function yields the control voltage vector for the next cycle k+1. This control voltage vector is then used to control the corresponding switch S. a or S b or S c This allows for further control of the PMSM (Permanent Magnet Synchronous Motor) via an inverter.

[0138] In a specific embodiment, the process of each control cycle is as follows: Figure 6 As shown, each control cycle can be divided into five parts, four of which are used to implement the motor control method, and the remaining part is idle time. The method implementation includes four steps: motor variable sampling, prediction calculation, cost function evaluation, and optimal voltage vector output.

[0139] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0140] Based on the same inventive concept, this application also provides a motor drive control device for implementing the motor drive control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the motor drive control device provided below can be found in the limitations of the motor drive control method described above, and will not be repeated here.

[0141] In one embodiment, such as Figure 7 As shown, a motor drive control device is provided, including: a current parameter acquisition module 710, a predicted parameter acquisition module 720, a tracking error acquisition module 730, a voltage determination module 740, and a drive control module 750, wherein:

[0142] The current parameter acquisition module 710 is used to acquire the current operating status parameters of the motor to be controlled in the current control cycle.

[0143] The prediction parameter acquisition module 720 is used to input the current operating status parameters into the operating status prediction model to predict multiple predicted operating status parameters of the motor to be controlled within a preset period; the multiple predicted operating status parameters correspond to multiple candidate control voltages for controlling the motor to be controlled.

[0144] The tracking error acquisition module 730 is used to input multiple predicted operating state parameters into the tracking error processing model to obtain the tracking error corresponding to each candidate control voltage.

[0145] The voltage determination module 740 is used to select the candidate control voltage corresponding to the tracking error as the target control voltage when the tracking error meets the preset conditions.

[0146] The drive control module 750 is used to drive the motor using the target control voltage in the next control cycle of the current control cycle.

[0147] In one embodiment, the device further includes a prediction model generation module. The prediction model generation module is used to establish the current continuous state equation, the speed continuous state equation, and the position continuous state equation of the motor to be controlled; and to generate an operating state prediction model based on the current continuous state equation, the speed continuous state equation, and the position continuous state equation.

[0148] In one embodiment, the prediction model generation module is used to discretize the current continuous state equation, the rotational speed continuous state equation, and the position continuous state equation using Taylor series expansion, respectively, to obtain the current Taylor series expansion, the rotational speed Taylor series expansion, and the position Taylor series expansion, respectively; and to generate an operating state prediction model based on the current Taylor series expansion, the rotational speed Taylor series expansion, and the position Taylor series expansion.

[0149] In one embodiment, the prediction model generation module is used to obtain the moment of inertia, number of pole pairs, flux linkage, and coefficient of friction of the motor to be controlled, as well as the load torque of the motor to be controlled; and to establish a position continuous state equation based on the moment of inertia, number of pole pairs, flux linkage, coefficient of friction, and load torque.

[0150] In one embodiment, the current operating state parameters include the current motor speed and the current motor current. The prediction model generation module is used to input the current motor speed and current motor current into the load torque observation model to obtain the load torque of the motor to be controlled.

[0151] In one embodiment, the device further includes a processing model generation module. The processing model generation module is used to acquire a reference current, a reference rotational speed, and a reference position; acquire current tracking error for the current, rotational speed tracking error for the rotational speed, and position tracking error for the position; and generate a tracking error processing model based on the current tracking error, rotational speed tracking error, and position tracking error.

[0152] In one embodiment, the drive control module is used to obtain the initial position value and the preset position value of the motor to be controlled in the next control cycle; obtain the duty cycle corresponding to the control time of the target control voltage based on the initial position value and the preset position value; and control the drive of the motor based on the target control voltage and the duty cycle.

[0153] Each module in the aforementioned motor drive control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0154] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows:Figure 8 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a motor drive control method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0155] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0156] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0157] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0158] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0159] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0160] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0161] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A motor drive control method, characterized in that, The method includes: Obtain the current operating status parameters of the motor to be controlled in the current control cycle; The current operating state parameters are input into the operating state prediction model to predict multiple predicted operating state parameters of the motor to be controlled within a preset period; the multiple predicted operating state parameters correspond to multiple candidate control voltages for controlling the motor to be controlled; wherein, the method of generating the operating state prediction model includes: establishing the current continuous state equation, the speed continuous state equation, and the position continuous state equation of the motor to be controlled; and generating the operating state prediction model based on the current continuous state equation, the speed continuous state equation, and the position continuous state equation. The multiple predicted operating state parameters are input into the tracking error processing model to obtain the tracking error corresponding to each candidate control voltage. If the tracking error meets the preset conditions, the candidate control voltage corresponding to the tracking error is taken as the target control voltage. In the next control cycle of the current control cycle, the motor is driven and controlled using the target control voltage; wherein, the initial position value and preset position value of the motor to be controlled in the next control cycle are obtained; based on the initial position value and the preset position value, the duty cycle corresponding to the control time of the target control voltage is obtained; the drive of the motor is controlled based on the target control voltage and the duty cycle; the expression for the duty cycle is: in, This represents the initial error in the motor position. These are the initial position value and the preset position value, respectively; These are the changes in the motor position under the action of the target control voltage and the zero voltage vector during the current control cycle, respectively. The duty cycle is... The control time for the target control voltage. The control time of the zero voltage vector; The duration of the current control cycle.

2. The method according to claim 1, characterized in that, The step of generating the operating state prediction model based on the current continuous state equation, the rotational speed continuous state equation, and the position continuous state equation includes: Using Taylor series expansion, the continuous state equations of current, rotational speed, and position are discretized to obtain Taylor series expansions for current, rotational speed, and position, respectively. The operating state prediction model is generated based on the Taylor series expansion of the current, the Taylor series expansion of the rotational speed, and the Taylor series expansion of the position.

3. The method according to claim 1 or 2, characterized in that, The establishment of the positional continuous state equation includes: The moment of inertia, number of pole pairs, flux linkage, and coefficient of friction of the motor to be controlled are obtained, as well as the load torque of the motor to be controlled. Based on the moment of inertia, the number of pole pairs, the magnetic flux linkage, the coefficient of friction, and the load torque, the position continuity state equation is established.

4. The method according to claim 3, characterized in that, The current operating status parameters include the current motor speed and the current motor current; The step of obtaining the load torque of the motor to be controlled includes: The current motor speed and current are input into the load torque observation model to obtain the load torque of the motor to be controlled.

5. The method according to claim 1, characterized in that, The method for generating the tracking error processing model includes: Obtain the reference current, reference speed, and reference position; Obtain the current tracking error for current, the speed tracking error for rotational speed, and the position tracking error for location; The tracking error processing model is generated based on the current tracking error, the rotational speed tracking error, and the position tracking error.

6. A motor drive control device, characterized in that, The device includes: The current parameter acquisition module is used to acquire the current operating status parameters of the motor to be controlled in the current control cycle; The prediction parameter acquisition module is used to input the current operating state parameters into the operating state prediction model to predict multiple predicted operating state parameters of the motor to be controlled within a preset period; the multiple predicted operating state parameters correspond to multiple candidate control voltages for controlling the motor to be controlled; wherein, the generation method of the operating state prediction model includes: establishing the current continuous state equation, the speed continuous state equation, and the position continuous state equation of the motor to be controlled; and generating the operating state prediction model based on the current continuous state equation, the speed continuous state equation, and the position continuous state equation. The tracking error acquisition module is used to input the multiple predicted operating state parameters into the tracking error processing model to obtain the tracking error corresponding to each candidate control voltage. The voltage determination module is used to take the candidate control voltage corresponding to the tracking error as the target control voltage when the tracking error meets the preset conditions. A drive control module is configured to drive the motor using the target control voltage in the next control cycle of the current control cycle; wherein, it acquires the initial position value and a preset position value of the motor to be controlled in the next control cycle; acquires the duty cycle corresponding to the control time of the target control voltage based on the initial position value and the preset position value; and controls the drive of the motor based on the target control voltage and the duty cycle; the expression for the duty cycle is: in, This represents the initial error in the motor position. These are the initial position value and the preset position value, respectively; These are the changes in the motor position under the action of the target control voltage and the zero voltage vector during the current control cycle, respectively. The duty cycle is... The control time for the target control voltage. The control time of the zero voltage vector; The duration of the current control cycle.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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