Excitation winding voltage modulation method, excitation winding system and electro-magnetic motor

Abstract

The invention discloses an excitation winding voltage modulation method, an excitation winding system and an electro-magnetic motor, and the method comprises the steps: carrying out the offline pre-definition of a mode switching value of a hysteresis comparator, a unipolar control parameter of a unipolar PI controller, and a bipolar control parameter of a bipolar PI controller through an optimization algorithm; the voltage of the excitation winding is modulated through various parameters predefined offline by an optimization algorithm, and control parameters of the unipolar PI controller and the bipolar PI controller are dynamically adjusted through a fuzzy algorithm in the modulation process, so that expert experience does not need to be relied on, the control parameters can be dynamically adjusted, and the control efficiency is improved. The flexibility and adaptive capacity of excitation winding voltage modulation are improved, and the balance between the excitation current dynamic response speed and the electromagnetic torque stability of a motor system is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of electrically excited motors, and in particular to an excitation winding voltage modulation method, an excitation winding system, and an electrically excited motor. Background Art

[0002] The wound field synchronous machine (WFSM) is a key branch of the flux adjustable synchronous machine (FASM). WFSMs offer excellent magnetic tuning performance and do not require permanent magnets. They are widely used in wind power generation, electric vehicles, and household appliances.

[0003] Although the introduction of the excitation winding has greatly improved the system's flux regulation performance, the induced voltage pulsation of the excitation winding will also affect the performance of the motor system. At present, in order to reduce the impact of the induced voltage pulsation of the excitation winding on the performance of the motor system, the excitation winding voltage pulsation is generally weakened by optimizing the motor body topology, such as adding stator damping windings and optimizing the rotor pole structure. However, when weakening the excitation winding voltage pulsation, the existing technology generally takes the overall performance of the motor system as the starting point and controls the excitation winding voltage pulsation based on expert experience. This will not only lead to a strong reliance on expert experience, but also have the problems of low flexibility and poor robustness.

[0004] Therefore existing technology still needs to be improved and improved. Summary of the Invention

[0005] The technical problem to be solved by the present application is to provide an excitation winding voltage modulation method, an excitation winding system and an electromagnetic excitation motor in view of the deficiencies in the prior art.

[0006] In order to solve the above technical problems, the first aspect of the present application provides a method for modulating the voltage of the excitation winding of an electrically excited synchronous motor, using an excitation voltage modulation controller, the excitation voltage modulation controller including a hysteresis comparator, a unipolar PI controller, and a bipolar PI controller; the voltage modulation method of the excitation winding of the electrically excited synchronous motor specifically includes:

[0007] The mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller are predefined offline through an optimization algorithm;

[0008] The excitation voltage modulation controller is used to perform online voltage modulation on the excitation winding, wherein, during the voltage modulation process, the unipolar PI controller and the bipolar PI controller both dynamically adjust their respective configured control parameters through a fuzzy algorithm.

[0009] In the method for modulating the excitation winding voltage of an electrically excited motor, the offline predefining of the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller by an optimization algorithm specifically includes:

[0010] Collecting a plurality of offline simulation data of the electrically excited motor system, wherein the offline simulation data includes excitation current and output torque curves;

[0011] Based on the offline simulation data, an objective function is constructed based on an overshoot of the excitation winding current, a regulation time of the excitation winding current, a standard deviation of the output electromagnetic torque, and a steady-state error of the excitation current;

[0012] Based on the objective function, determining target parameters by a preset optimization algorithm, wherein the target parameters include a mode switching value, a unipolar control parameter, and a bipolar control parameter;

[0013] The mode switching value is configured in a hysteresis comparator, the unipolar control parameter is configured in a unipolar PI controller, and the bipolar control parameter is configured in a bipolar PI controller.

[0014] In the method for modulating the excitation winding voltage of an electrically excited motor, the preset optimization algorithm is a particle swarm optimization algorithm, and the objective function of the particle swarm optimization algorithm is:

[0015] z=os·a+ts·b+std·c+error·d

[0016] Where z represents the objective function, os represents the overshoot of the excitation winding current, ts represents the adjustment time of the excitation winding current, std represents the standard deviation of the output electromagnetic torque, error represents the steady-state error of the excitation current, and a, b, c, and d represent constant coefficients.

[0017] The method for modulating the excitation winding voltage of an electrically excited motor, wherein the step of performing online voltage modulation on the excitation winding using the excitation voltage modulation controller specifically includes:

[0018] obtaining an excitation current error, and inputting the excitation current error into the hysteresis comparator to determine a system operating mode through the hysteresis comparator;

[0019] When the system operating mode is a unipolar mode, the excitation current error is input into the unipolar PI controller, the excitation winding voltage duty cycle is outputted by the unipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle;

[0020] When the system operating mode is a bipolar mode, the excitation current error is input into the bipolar PI controller, the excitation winding voltage duty cycle is output through the bipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle.

[0021] In the method for modulating the excitation winding voltage of an electrically excited motor, the process of dynamically adjusting the control parameters using a fuzzy algorithm specifically includes:

[0022] When the excitation current error is input into the target controller, the error change rate is obtained, wherein the target controller is a unipolar PI controller or a bipolar PI controller;

[0023] The excitation current error and the error change rate are used as input variables of a fuzzy algorithm, a control parameter adjustment value of a target controller is output through the fuzzy algorithm, and the control parameters configured by the target controller are adjusted based on the control parameter adjustment value.

[0024] The method for modulating the excitation winding voltage of an electrically excited motor, wherein inputting the excitation current error into the hysteresis comparator to determine the system operating mode through the hysteresis comparator specifically includes:

[0025] Inputting the excitation current error into the hysteresis comparator, and comparing the excitation current error with its configured mode switching value through the hysteresis comparator;

[0026] If the excitation current error is less than the mode switching value, outputting the unipolar mode as the system operating mode;

[0027] If the excitation current error is greater than or equal to the mode switching value, the bipolar mode is output as the system operating mode.

[0028] A second aspect of the present application provides an excitation voltage modulation controller, which includes a hysteresis comparator, a unipolar PI controller and a bipolar PI controller. The mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller are determined by a preset optimization algorithm; the excitation voltage modulation controller is used to perform voltage modulation on the excitation winding, wherein, during the voltage modulation process, the unipolar PI controller and the bipolar PI controller both dynamically adjust the control parameters of their respective configurations through a fuzzy algorithm.

[0029] The excitation voltage modulation controller, wherein the hysteresis comparator is used to determine the system operating mode of the excitation winding voltage modulation system; the unipolar PI controller is used to determine the excitation winding voltage duty cycle, and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle; the bipolar PI controller is used to determine the excitation winding voltage duty cycle, and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle.

[0030] A third aspect of the present application provides an excitation winding system, which includes the excitation voltage modulation controller as described above.

[0031] A fourth aspect of the present application provides an electrically excited motor, which includes the excitation winding system described above.

[0032] Beneficial effect: Compared with the prior art, the present application provides an excitation winding voltage modulation method, an excitation winding system and an electrically excited motor, the method comprising offline predefining a mode switching value of a hysteresis comparator, a unipolar control parameter of a unipolar PI controller and a bipolar control parameter of a bipolar PI controller through an optimization algorithm; the excitation winding is voltage modulated using the excitation voltage modulation module controller, and during the voltage modulation process, both the unipolar PI controller and the bipolar PI controller dynamically adjust the control parameters of their respective configurations through a fuzzy algorithm. This application determines the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller through an offline particle swarm optimization algorithm, and modulates the excitation winding voltage through various parameters determined offline by a preset optimization algorithm. During the modulation process, the control parameters of the unipolar PI controller and the bipolar PI controller are dynamically adjusted through a fuzzy algorithm. This not only does not require reliance on expert experience, but also allows dynamic adjustment of the control parameters, thereby improving the flexibility and adaptability of the excitation winding voltage modulation, and achieving a balance between the dynamic response speed of the excitation current and the stability of the electromagnetic torque of the motor system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 This is the overall block diagram of the electrically excited synchronous motor control system.

[0035] Figure 2 This is the block diagram of the excitation winding control system of the electrically excited synchronous motor.

[0036] Figure 3 The present invention is a flow chart of a method for modulating the voltage of an excitation winding of an electrically excited motor.

[0037] Figure 4 The diagram shows the unipolar / bipolar switching sign of the motor excitation winding and the excitation winding voltage under step response.

[0038] Figure 5 The figure shows the excitation current results of the motor under unipolar, bipolar, unipolar / bipolar mixed and PSO-based unipolar / bipolar mixed control under step response.

[0039] Figure 6 The figure shows the motor output torque results under single / bipolar hybrid and single / bipolar hybrid control based on PSO in steady state after step response.

[0040] Figure 7 The FFT result diagram of the motor output torque under single / bipolar hybrid and single / bipolar hybrid control based on PSO in steady state after step response.

[0041] Figure 8 This is the result diagram of the electrically excited synchronous motor tracking the sinusoidal speed signal.

[0042] Figure 9 The result diagram of single / bipolar PI parameters of an electrically excited synchronous motor under fuzzy control when tracking a sinusoidal speed signal.

[0043] Figure 10 Schematic diagram of the motor excitation winding single / bipolar switching mark and excitation winding voltage when tracking the sinusoidal speed signal.

[0044] Figure 11 The output torque results of the electrically excited synchronous motor under hybrid voltage modulation, hybrid voltage modulation based on PSO, and hybrid voltage modulation based on fuzzy PSO when tracking a sinusoidal speed signal.

[0045] Figure 12 Figure 2 is the particle swarm iterative optimization process diagram for the control parameters of the unipolar PI controller.

[0046] Figure 13 Figure 2 is the particle swarm iterative optimization process diagram for the control parameters of the bipolar PI controller.

[0047] Figure 14 Graph showing the particle swarm iterative optimization process for the mode switching value of the hysteresis comparator.

[0048] Figure 15 This is the convergence diagram of the cost curve of the particle swarm optimization system. DETAILED DESCRIPTION

[0049] The present application provides an excitation winding voltage modulation method, an excitation winding system, and an electrically excited motor. To clarify the objectives, technical solutions, and effects of the present application, the present application is further described below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the present application and are not intended to limit the present application.

[0050] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or wireless couplings. The term "and / or" used herein includes all or any units and all combinations of one or more associated listed items.

[0051] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0052] It should be understood that the sequence numbers and sizes of the steps in this embodiment do not imply the order of execution. The order of execution of each process is determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of this application.

[0053] Research has shown that the wound field synchronous machine (WFSM) is an important branch of the flux adjustable synchronous machine (FASM). WFSMs offer excellent magnetic field adjustment and do not require permanent magnets. They are widely used in wind power generation, electric vehicles, and household appliances.

[0054] While the introduction of the excitation winding significantly improves the system's flux regulation performance, the induced voltage ripple in the excitation winding also affects the motor system's performance. To reduce the impact of this induced voltage ripple on the motor system's performance, the excitation winding voltage ripple can be weakened through motor topology optimization, such as adding stator damping windings and optimizing the rotor pole structure. However, existing technologies for reducing excitation winding voltage ripple generally focus on the overall performance of the motor system, without focusing on the voltage ripple phenomenon of the excitation winding.

[0055] Research has shown that the pulse width modulation strategy, controller parameters, and winding bus voltage of the armature winding and excitation winding of the electromagnetic motor will all affect the voltage ripple. Among them, for the pulse width modulation strategy of the excitation winding, the system using a unipolar H-bridge full-bridge inverter circuit has better steady-state performance, while the system using a bipolar H-bridge full-bridge inverter circuit has a faster dynamic response. The scenario requirements can be met by switching between unipolar / bipolar H-bridge full-bridge circuits to achieve a balance between steady-state and dynamic. However, the switching of unipolar / bipolar H-bridge full-bridge circuits is generally controlled based on expert experience. On the one hand, this will create a strong reliance on expert experience, and on the other hand, it will also have the problems of low flexibility and poor robustness.

[0056] To solve the above problems, in an embodiment of the present application, the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller are predefined offline through an optimization algorithm; the excitation voltage modulation module controller is used to modulate the voltage of the excitation winding, and during the voltage modulation process, the unipolar PI controller and the bipolar PI controller dynamically adjust their configured control parameters through a fuzzy algorithm. The present application determines the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller offline through a preset optimization algorithm, and modulates the excitation winding voltage through various parameters predefined offline by the optimization algorithm. During the modulation process, the control parameters of the unipolar PI controller and the bipolar PI controller are dynamically adjusted through a fuzzy algorithm. This not only eliminates the need to rely on expert experience, but also allows for dynamic adjustment of the control parameters, thereby improving the flexibility and adaptability of the excitation winding voltage modulation and achieving a balance between the dynamic response speed of the excitation current and the stability of the electromagnetic torque of the motor system.

[0057] The application content will be further explained below through description of embodiments in conjunction with the accompanying drawings.

[0058] An application scenario of the method for modulating the voltage of the excitation winding of an electric excitation motor provided in this embodiment is as follows: Figure 1 As shown. Figure 1In this application scenario, the excitation winding voltage modulation method of the electromagnetic motor is applied to the WFSM system, using field-oriented control (FOC) to achieve more precise and direct current control. Specifically, the WFSM system includes an excitation winding system and an armature winding system. The excitation winding system includes an excitation winding and an excitation winding voltage modulation module, and the armature winding system includes an armature winding and an armature winding voltage modulation module. The excitation winding and the armature winding respectively use an H-bridge full-bridge inverter circuit and a three-phase six-leg inverter circuit. The armature winding voltage modulation module uses space vector pulse width modulation (SVPWM) technology. The excitation winding system includes an excitation voltage modulation controller, which includes a hysteresis comparator, a unipolar PI controller, and the bipolar PI controller. The unipolar PI controller and the bipolar PI controller are parallel and cascaded with the hysteresis comparator. The hysteresis controller is used to determine the unipolar / bipolar operating state (i.e., system operating mode) of the excitation winding voltage modulation system. Both the unipolar PI controller and the bipolar PI controller are used to control the opening / closing of the switch in the inverter circuit and thereby adjust the duty cycle of the pulse width modulation (PWM) square wave. The unipolar PI controller is used in the unipolar operating state, and the bipolar PI controller is used in the bipolar operating state. The excitation voltage modulation controller can be configured as follows: Figure 2 The excitation winding control strategy shown responds to the excitation winding voltage modulation method of the electrically excited motor provided in the present application by executing the excitation winding control strategy.

[0059] Here, an electrically excited synchronous motor is taken as an example for explanation. Of course, in practical applications, it can also be a flux-adjustable motor system with an excitation winding, such as a hybrid excitation synchronous motor.

[0060] For Figure 1 The mathematical model of the electrically excited synchronous motor shown in the figure in the synchronous rotating coordinate system (d, q) includes the voltage equation, the flux equation, the torque equation, and the motion equation, where the voltage equation is:

[0061]

[0062] Among them, u d Indicates the voltage on the d-axis of the electrically excited synchronous motor, u q It represents the voltage on the q axis of the electrically excited synchronous motor, i d represents the current on the d-axis of the electrically excited synchronous motor, i q represents the current on the q axis of the electrically excited synchronous motor, ψ drepresents the magnetic flux of the electrically excited synchronous motor on the d-axis, ψ q represents the magnetic flux of the electrically excited synchronous motor on the q axis, R s represents the resistance of the armature winding, ω e Indicates the electrical angular velocity of the rotor.

[0063] The magnetic flux equation can be expressed as:

[0064]

[0065] Among them, L d Indicates the self-inductance of the electrically excited synchronous motor on the d-axis, L q It represents the self-inductance of the electrically excited synchronous motor on the q axis, M d It represents the mutual inductance of the electrically excited synchronous motor on the d-axis, M q represents the mutual inductance of the electrically excited synchronous motor on the q axis, M df It represents the mutual inductance between the d-axis and the excitation winding of the electrically excited synchronous motor, M qf represents the mutual inductance between the q-axis and the excitation winding of the electrically excited synchronous motor, i f Indicates the excitation winding current.

[0066] Furthermore, due to M df and M qf The influence on the excitation winding voltage ripple suppression and output torque is extremely small and can be ignored. In the embodiment of the present application, M df and M qf Set to 0. Therefore, the electromagnetic torque equation can be expressed as:

[0067]

[0068] Among them, p n Indicates the number of motor pole pairs.

[0069] The equation of motion can be expressed as:

[0070]

[0071] Among them, ω m Indicates the rotor mechanical angular velocity, T l represents the motor load torque, J represents the rotor moment of inertia, and B represents the damping coefficient.

[0072] The excitation winding voltage modulation method of the electrically excited motor provided in the embodiment of the present application will apply the above-mentioned excitation voltage modulation controller, and configure control parameters for the hysteresis comparator, unipolar PI controller and the bipolar PI controller in the excitation voltage modulation controller offline through a preset optimization algorithm, and then perform voltage modulation on the excitation winding through the excitation voltage modulation controller with the configured control parameters, and during the control process, the control parameters of the unipolar PI controller and the bipolar PI controller will be dynamically adjusted online through a fuzzy algorithm.

[0073] The method for modulating the excitation winding voltage of an electrically excited synchronous motor provided in the embodiments of the present application aims to optimize the excitation winding voltage modulation strategy of the electrically excited synchronous motor, achieving a balance between the dynamic response speed of the excitation current and the stability of the electromagnetic torque of such motor systems. The method for modulating the excitation winding voltage of an electrically excited synchronous motor provided in the embodiments of the present application adopts an "id=0" control strategy, which simplifies the control strategy and ensures that the current in the WFSM is fully used to generate torque, helping the system operate at the maximum torque per ampere (MTPA) ratio and reducing the system copper loss.

[0074] Specifically, if Figure 3 As shown, the method for modulating the excitation winding voltage of the electromagnetic motor specifically includes:

[0075] S10 , pre-defining the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller offline through an optimization algorithm.

[0076] Specifically, a hysteresis comparator is used to determine the system operating mode. Its input is the excitation current error, and its output is a system operating mode selection flag. The system operating mode selection flag includes a unipolar switching mode selection flag and a bipolar switching mode selection flag. The mode switching value determines the excitation current error threshold for the hysteresis comparator to determine the system operating mode. The hysteresis comparator compares the excitation current error with the excitation current error to output the system operating mode selection flag.

[0077] When an H-bridge full-bridge inverter circuit is used in the excitation winding, it has both unipolar and bipolar switching modes. In unipolar switching mode, the excitation winding current ripple is small but the current dynamic response is slow, while in bipolar switching mode, the excitation winding current ripple is large but the current dynamic response is fast. When an electrically excited synchronous motor operates smoothly, the excitation current does not need to be rapidly adjusted, and system stability is prioritized, making the unipolar switching mode suitable. However, when an electrically excited synchronous motor faces sudden changes (such as sudden changes in reference current, load, or other disturbances), the excitation current needs to be rapidly adjusted to the new desired value. During this process, the stability requirements for the electrically excited synchronous motor are lower, making the unipolar switching mode suitable. Therefore, when the excitation current error is compared with the mode switching value via a hysteresis comparator, if the input excitation current error is less than the mode switching value, a unipolar switching mode selection flag is output, and the system subsequently operates in unipolar mode. If the input excitation current error is greater than or equal to the mode switching value, a bipolar switching mode selection flag is output, and the system subsequently operates in bipolar mode.

[0078] A unipolar PI controller controls the excitation winding voltage duty cycle in unipolar switching mode, while a bipolar PI controller controls the excitation winding voltage duty cycle in bipolar switching mode. The input of both the unipolar and bipolar PI controllers is the excitation current error, and their output is the excitation winding voltage duty cycle.

[0079] It should be noted that the unipolar switch mode selection flag and the bipolar switch mode selection flag are both pre-set, and are only used as identifiers of the unipolar switch mode and the bipolar switch mode. They only need to be agreed upon in advance. For example, the unipolar switch mode selection flag is pre-agreed to be 1 and the bipolar switch mode selection flag is pre-agreed to be 0; or, the unipolar switch mode selection flag is pre-agreed to be 0 and the bipolar switch mode selection flag is pre-agreed to be 1, etc.

[0080] Furthermore, the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller are all determined offline by a preset optimization algorithm. In an embodiment of the present application, the preset optimization algorithm adopts a particle swarm optimization algorithm. Particle swarm optimization (PSO) is an evolutionary algorithm that finds the optimal solution through the collaborative efforts and information sharing of individual particles. When determining the optimal optimization target through the offline particle swarm optimization algorithm, the electromagnetic motor system can be simulated first to obtain a number of offline simulation data, and then the optimization target can be optimized based on the several offline simulation data.

[0081] The optimization objectives of the particle swarm optimization algorithm are the mode switching value, unipolar control parameters, and bipolar control parameters. Both unipolar control parameters and bipolar control parameters include proportional gain and integral gain. Therefore, the optimization objective of the particle swarm optimization algorithm can be expressed as a five-dimensional matrix:

[0082] Obj=[K p -Uni K i -Uni K p -Bi K i -Bi sp]

[0083] Among them, Obj represents the optimization target, K p -Uni represents the proportional gain of the unipolar PI controller, K i -Uni represents the integral gain of the unipolar PI controller, K p -Bi represents the proportional gain of the bipolar PI controller, K i -Bi represents the integral gain of the bipolar PI controller, and sp represents the mode switching value of the hysteresis comparator.

[0084] Exemplarily, the offline predefining of the mode switching value of the hysteresis comparator, the unipolar control parameter of the unipolar PI controller, and the bipolar control parameter of the bipolar PI controller by the optimization algorithm specifically includes:

[0085] Collect some offline simulation data of the electromagnetic motor system;

[0086] Based on the offline simulation data, an objective function is constructed based on an overshoot of the excitation winding current, a regulation time of the excitation winding current, a standard deviation of the output electromagnetic torque, and a steady-state error of the excitation current;

[0087] Based on the objective function, determining target parameters by a preset optimization algorithm, wherein the target parameters include a mode switching value, a unipolar control parameter, and a bipolar control parameter;

[0088] The mode switching value is configured in a hysteresis comparator, the unipolar control parameter is configured in a unipolar PI controller, and the bipolar control parameter is configured in a bipolar PI controller.

[0089] Specifically, the offline simulation data is obtained by simulating the offline simulation data. The offline simulation data may include excitation current and output torque curves. Some of the offline simulation data are actually collected when different control parameters are configured for the hysteresis comparator, the unipolar PI controller, and the bipolar PI controller. That is, in the simulation scenario, different mode switching values are configured for the hysteresis comparator, different unipolar control parameters are configured for the unipolar PI controller, and different bipolar control parameters are configured for the bipolar PI controller. Simulation data under different parameters are then acquired to obtain the plurality of offline simulation data.

[0090] Furthermore, after obtaining a number of offline simulation data, the iteration parameters for particle swarm optimization are configured. The iteration parameters may include the population size, the maximum number of iterations N, the objective function z, the search space, the cognitive coefficient c1, the social coefficient c2, and the inertia weight w. In addition, during the iteration process, the inertia weight w is gradually reduced by the gradient descent method. Of course, in actual applications, adjustments can also be made based on actual conditions (such as the accuracy of the optimization target). For example, only some of the above iteration parameters may be included, or other single parameter information may be included in addition to the above iteration parameters.

[0091] In addition, the process of determining the search space of the optimization target can be: first calculate the time constant of the motor excitation winding Where R represents the resistance of the motor excitation winding and L represents the inductance of the motor excitation winding. Then, the bandwidth of the excitation voltage modulation controller is determined based on the time constant and the pre-determined motor system operation target. Finally, the search space for the optimization target is set based on the bandwidth. For example, for an electrically excited synchronous motor with the motor parameters shown in Table 1, the optimization target Obj = [K p -Uni K i -Uni K p -Bi K i The search space of -Bi sp] can be:

[0092] UpperLimit=[505050500.5]

[0093] LowerLimit=[10.010.010.010.01]

[0094] Among them, UpperLimit represents the upper limit set of the search space, and LowerLimit represents the lower limit set of the search space.

[0095] Table 1 Motor parameters

[0096]

[0097] Furthermore, under the system step response, the objective function of the particle swarm optimization algorithm is:

[0098] z=os·a+ts·b+std·c+error·d

[0099] Where z represents the objective function, os represents the overshoot of the excitation winding current, ts represents the adjustment time of the excitation winding current, std represents the standard deviation of the output electromagnetic torque, error represents the steady-state error of the excitation current, and a, b, c, and d represent constant coefficients. For example, a = 100, b = 3000, c = 5, and d = 5.

[0100] The particles in this application are a five-dimensional optimization target matrix composed of the control parameters of 5 excitation voltage modulation controllers. The objective function is a weighted expression that can reflect the dynamic and steady-state performance of the motor, and the closer the objective function value is to 0, the better the comprehensive performance of the excitation winding system. In each generation, different five-dimensional matrices are randomly selected by the particle swarm (the number is the size of the particle swarm), the same experiment is performed under each set of parameter matrices and the objective function value under the set of parameters is calculated, and the optimal parameter matrix is selected according to the objective function value. In this way, iterative optimization is performed (the number of iterations is the maximum number of iterations or the number of iterations that makes the objective function value 0), and finally a set of control parameters that makes the system performance optimal is selected to obtain the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller. For example, the particle swarm size of the PSO optimization process used in the embodiment of the present application is 40, the number of iterations is 40, the parameter optimization process and the cost converge within 40 generations, and the particle swarm iterative optimization process of the control parameters of the unipolar PI controller is as follows: Figure 12 As shown in the figure, the particle swarm iterative optimization process of the control parameters of the bipolar PI controller is as follows: Figure 13 As shown in the figure, the particle swarm iterative optimization process of the mode switching value of the hysteresis comparator is as follows: Figure 14 As shown, the cost curve convergence diagram of the particle swarm optimization system is as follows Figure 15 shown.

[0101] The embodiment of the present application uses a particle swarm optimization algorithm to determine the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller using offline simulation data. It can obtain more accurate mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller. On the one hand, this can avoid dependence on expert experience, and on the other hand, it can improve the accuracy of voltage modulation.

[0102] Compared with the traditional hybrid voltage control strategy, the step response performance of the WFSM system under the offline particle swarm optimization algorithm is as follows: Figure 4-7As shown. Switch symbol and DC winding voltage curve are shown in Figure 4 , the operation results are consistent with the design principles. Figure 5 It can be seen that the unipolar voltage modulation control strategy has better steady-state performance, while the bipolar strategy responds faster. The stabilization time of the unipolar / bipolar hybrid control (HC) and the PSO-based unipolar / bipolar hybrid control (PHC) in the WFSM system are both short, 0.0177s respectively, while the stabilization time of the bipolar strategy is 0.0187s. Figure 6 and Figure 7 It can be seen that PHC performs better in suppressing output torque fluctuations, reducing them by 20.78%. The peak-to-peak electromagnetic torque of the HC is 2.0350 Nm, while that of the PHC is 1.5918 Nm. Furthermore, the total harmonic distortion rate under the PHC method is 13.35%, 2.91% lower than that of the HC method.

[0103] Of course, in subsequent research, other optimization algorithms can also be used to determine the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller. For example, genetic algorithms, differential evolution algorithms, ant colony algorithms, fish swarm algorithms, bat algorithms, gray wolf optimization algorithms, hawk attack algorithms, and artificial immune algorithms can be used.

[0104] S20: Use the excitation voltage modulation controller to perform online voltage modulation on the excitation winding.

[0105] Specifically, after obtaining the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller, the mode switching value, the unipolar control parameters and the bipolar control parameters are configured in the excitation voltage modulation controller, so that the hysteresis comparator can determine the system operating mode based on the mode switching value, and the unipolar PI controller and the bipolar PI controller use their respective configured control parameters as initial parameters to perform voltage modulation on the excitation winding.

[0106] Exemplarily, obtaining an excitation current error, and inputting the excitation current error into the hysteresis comparator to determine the system operating mode through the hysteresis comparator;

[0107] When the system operating mode is a unipolar mode, the excitation current error is input into the unipolar PI controller, the excitation winding voltage duty cycle is outputted by the unipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle;

[0108] When the system operating mode is a bipolar mode, the excitation current error is input into the bipolar PI controller, the excitation winding voltage duty cycle is output through the bipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle.

[0109] Specifically, the system operating modes include unipolar mode and bipolar mode. In unipolar mode, the excitation winding voltage duty cycle is determined by a unipolar PI controller, while in bipolar mode, the excitation winding voltage duty cycle is determined by a bipolar PI controller. A hysteresis comparator determines the system operating mode by comparing the excitation current error with its configured mode switching value. Specifically, after obtaining the excitation current error, the excitation current error is input into the hysteresis comparator, which then compares the excitation current error with its configured mode switching value. If the excitation current error is less than the mode switching value, the unipolar mode is output as the system operating mode; if the excitation current error is greater than or equal to the mode switching value, the bipolar mode is output as the system operating mode. In this embodiment of the present application, when the excitation current error is less than the mode switching value, the excitation winding control system operates in unipolar mode to reduce current ripple. Otherwise, the excitation winding control system operates in bipolar mode to more quickly reach the current reference value, ensuring a balance between the dynamic response speed of the excitation current and the stability of the electromagnetic torque.

[0110] To further enhance the ability of the excitation winding system to cope with changing conditions, during the voltage modulation process, both the unipolar PI controller and the bipolar PI controller are configured with a fuzzy algorithm to dynamically adjust the control parameters configured for each controller. The adjustment process of dynamically adjusting the control parameters using the fuzzy algorithm specifically includes:

[0111] When the excitation current error is input into the target controller, the error change rate is obtained;

[0112] The excitation current error and the error change rate are used as input variables of a fuzzy algorithm, a control parameter adjustment value of a target controller is output through the fuzzy algorithm, and the control parameters configured by the target controller are adjusted based on the control parameter adjustment value.

[0113] Specifically, the target controller is a unipolar PI controller or a bipolar PI controller. Here, the adjustment process is explained by taking the dynamic adjustment of the control parameters of the target controller through a fuzzy algorithm as an example. When the target controller is a unipolar PI controller, the control parameters are unipolar control parameters. When the target controller is a bipolar PI controller, the control parameters are bipolar control parameters.

[0114] Furthermore, the input variables of the fuzzy algorithm are the excitation current error and the error change rate, and the output variable is the control parameter adjustment value of the target controller. The error change rate can be represented by the derivative of the excitation current error. The domains of the input and output variables can be determined based on the actual operating conditions of the electromagnetic motor system. For example, the input domain of the input variable can be [-24, 24], and the output domain of the output variable can be [-3, 3].

[0115] When determining the control parameters through the fuzzy algorithm, the input variables can be converted into fuzzy language values through the membership function in advance to form an input fuzzy subset; then a fuzzy rule base is established based on expert experience, and the output fuzzy subset is obtained through the fuzzy rules in the fuzzy rule base. Then, the fuzzy subset is defuzzified through the center of gravity method and converted into a numerical output to obtain the control parameter adjustment value of the target controller. Among them, the membership function can adopt the seven-segment triangular membership function, trapezoidal, Gaussian, Bell, Sigmoid and other membership function shapes.

[0116] For example, assuming the fuzzy rules shown in Tables 2 and 3, and based on actual project conditions, the fuzzy subsets of the excitation winding current error e and its rate of change ec, the input variables, are {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, denoted as {NB, NM, NS, ZE, PS, PM, PB}. The error e and the error rate of change ec are quantized to the domain [-24, 24]. Simultaneously, the fuzzy subsets of the adjustment values ΔKp and ΔKi for the proportional gain P and integral gain I, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, denoted as {NB, NM, NS, ZE, PS, PM, PB}, are quantized to the domain [-3, 3].

[0117] Table 2 Fuzzy rule control table of proportional gain P in control parameters

[0118]

[0119] Table 3 Fuzzy rule control table of integral gain I in control parameters

[0120]

[0121] In order to illustrate the effect of the method adopted in the embodiment of the present application, the excitation winding system is operated with a sinusoidal speed signal under a load of 10 Nm, as shown in FIG. Figure 7 As shown, the hybrid voltage modulation strategy HC, the hybrid voltage modulation strategy based on PSO (i.e., only the preset optimization algorithm in the implementation of this application is used to determine the control parameters) and the fuzzy PHC control method (the method provided in the embodiment of this application) are respectively adopted. The online parameter adjustment process is as follows Figure 8 As shown, it can be seen that the control parameters vary around the base values given by the offline PSO. Figure 9The switch signs and DC winding voltage under fuzzy control are shown, and the output torque under different strategies is Figure 10 The verification results show that the fuzzy PHC has smaller torque fluctuations, eliminates system glitches, and is superior to the HC control method and the PHC control method.

[0122] Based on the above-mentioned method for modulating the excitation winding voltage of an electrically excited motor, this embodiment provides an excitation voltage modulation controller, which includes a hysteresis comparator, a unipolar PI controller, and a bipolar PI controller. The mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller are determined using a preset optimization algorithm; the excitation voltage modulation controller is used to perform voltage modulation on the excitation winding, wherein, during the voltage modulation process, the unipolar PI controller and the bipolar PI controller both dynamically adjust the control parameters configured respectively through a fuzzy algorithm.

[0123] The excitation voltage modulation controller, wherein the hysteresis comparator is used to determine the system operating mode of the excitation winding voltage modulation system; the unipolar PI controller is used to determine the excitation winding voltage duty cycle, and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle; the bipolar PI controller is used to determine the excitation winding voltage duty cycle, and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle.

[0124] Based on the above-mentioned excitation voltage modulation controller, this embodiment provides an excitation winding system, and the excitation winding system includes the above-mentioned excitation voltage modulation controller.

[0125] Based on the above-mentioned excitation winding system, this embodiment provides an electrically excited motor, which includes the above-mentioned excitation winding system.

[0126] Finally, it should be noted that the above embodiments 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, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these 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.

Claims

1. A method for modulating the excitation winding voltage of an electrically excited motor, characterized in that: An excitation voltage modulation controller is applied, and the excitation voltage modulation controller includes a hysteresis comparator, a unipolar PI controller, and a bipolar PI controller; the voltage modulation method of the excitation winding of the electrically excited synchronous motor specifically includes: The mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller are predefined offline through an optimization algorithm; The excitation voltage modulation controller is used to perform online voltage modulation on the excitation winding, wherein, during the voltage modulation process, the unipolar PI controller and the bipolar PI controller both dynamically adjust their respective configured control parameters through a fuzzy algorithm.

2. The method for modulating the excitation winding voltage of an electrically excited motor according to claim 1, wherein: The offline predefinition of the mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller, and the bipolar control parameters of the bipolar PI controller by the optimization algorithm specifically includes: Collecting a plurality of offline simulation data of the electrically excited motor system, wherein the offline simulation data includes excitation current and output torque curves; Based on the offline simulation data, an objective function is constructed based on an overshoot of the excitation winding current, a regulation time of the excitation winding current, a standard deviation of the output electromagnetic torque, and a steady-state error of the excitation current; Based on the objective function, determining target parameters by a preset optimization algorithm, wherein the target parameters include a mode switching value, a unipolar control parameter, and a bipolar control parameter; The mode switching value is configured in a hysteresis comparator, the unipolar control parameter is configured in a unipolar PI controller, and the bipolar control parameter is configured in a bipolar PI controller.

3. The method for modulating the excitation winding voltage of an electrically excited motor according to claim 2, wherein: The preset optimization algorithm is a particle swarm optimization algorithm, and the objective function of the particle swarm optimization algorithm is: z=os·a+ts·b+std·c+error·d Where z represents the objective function, os represents the overshoot of the excitation winding current, ts represents the adjustment time of the excitation winding current, std represents the standard deviation of the output electromagnetic torque, error represents the steady-state error of the excitation current, and a, b, c, and d represent constant coefficients.

4. The method for modulating the excitation winding voltage of an electrically excited motor according to claim 1, wherein: The method of performing online voltage modulation on the excitation winding by using the excitation voltage modulation controller specifically includes: obtaining an excitation current error, and inputting the excitation current error into the hysteresis comparator to determine a system operating mode through the hysteresis comparator; When the system operating mode is a unipolar mode, the excitation current error is input into the unipolar PI controller, the excitation winding voltage duty cycle is outputted by the unipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle; When the system operating mode is a bipolar mode, the excitation current error is input into the bipolar PI controller, the excitation winding voltage duty cycle is output through the bipolar PI controller, and the excitation winding voltage is modulated based on the excitation winding voltage duty cycle.

5. The method for modulating the excitation winding voltage of an electrically excited motor according to claim 4, characterized in that: The adjustment process of dynamically adjusting the control parameters through fuzzy algorithm specifically includes: When the excitation current error is input into the target controller, the error change rate is obtained, wherein the target controller is a unipolar PI controller or a bipolar PI controller; The excitation current error and the error change rate are used as input variables of a fuzzy algorithm, a control parameter adjustment value of a target controller is output through the fuzzy algorithm, and the control parameters configured by the target controller are adjusted based on the control parameter adjustment value.

6. The method for modulating the excitation winding voltage of an electrically excited motor according to claim 4, characterized in that: Inputting the excitation current error into the hysteresis comparator to determine the system operating mode through the hysteresis comparator specifically includes: Inputting the excitation current error into the hysteresis comparator, and comparing the excitation current error with its configured mode switching value through the hysteresis comparator; If the excitation current error is less than the mode switching value, outputting the unipolar mode as the system operating mode; If the excitation current error is greater than or equal to the mode switching value, the bipolar mode is output as the system operating mode.

7. An excitation voltage modulation controller, characterized in that: The excitation voltage modulation controller includes a hysteresis comparator, a unipolar PI controller and a bipolar PI controller. The mode switching value of the hysteresis comparator, the unipolar control parameters of the unipolar PI controller and the bipolar control parameters of the bipolar PI controller are determined by a preset optimization algorithm. The excitation voltage modulation controller is used to perform voltage modulation on the excitation winding. During the voltage modulation process, the unipolar PI controller and the bipolar PI controller both dynamically adjust the control parameters configured respectively through a fuzzy algorithm.

8. The excitation voltage modulation controller according to claim 7, characterized in that: The hysteresis comparator is used to determine the system operating mode of the excitation winding voltage modulation system; the unipolar PI controller is used to determine the excitation winding voltage duty cycle and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle; The bipolar PI controller is used to determine the excitation winding voltage duty cycle and perform voltage modulation on the excitation winding based on the excitation winding voltage duty cycle.

9. An excitation winding system, characterized in that: The excitation winding system includes the excitation voltage modulation controller according to claim 7 or 8.

10. An electromagnetic motor, characterized in that: The electrically excited motor comprises the field winding system according to claim 9 .

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