A method and system for optimizing motor performance

Abstract

The present invention discloses a method and system for optimizing the performance of a motor, and belongs to the field of motor control technology. The present invention includes: determining a high-frequency signal suitable for injection into a target motor, and attribute parameters of the target motor; after adjusting the target motor through the attribute parameters and injecting the high-frequency signal suitable for injection into the target motor, performing voltage compensation on the target motor under the condition of injecting the high-frequency signal, determining the rotor position of the target motor based on the high-frequency signal injected into the target motor, and performing closed-loop control on the target motor based on the rotor position through a control system; injecting the high-frequency signal suitable for injection into the target motor into the target motor, and adjusting the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimizing the control performance of the target motor through the voltage compensation and closed-loop control, and optimizing the control performance and electromagnetic performance of the target motor to optimize the performance of the target motor. The present invention can optimize the performance of the motor.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and more particularly, to a method and system for optimizing the performance of a motor. Background Art

[0002] The motor body with the characteristic of suppressing high-frequency harmonics has certain characteristics in terms of armature winding arrangement, stator and rotor tooth profiles, etc. How to understand and design the motor body that meets the control requirements is a key technical problem that needs to be solved. Summary of the invention

[0003] In view of the above problems, the present invention proposes a method for optimizing the performance of a motor, comprising:

[0004] Establishing an air gap magnetic field distribution model for the target motor, determining the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determining a high-frequency signal suitable for injection into the target motor and property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor;

[0005] After adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, voltage compensation is performed on the target motor when the high-frequency signal is injected, a rotor position of the target motor is determined based on the high-frequency signal injected into the target motor, and closed-loop control is performed on the target motor through a control system based on the rotor position;

[0006] The high-frequency signal suitable for injection into the target motor is injected into the target motor, and the target motor is adjusted according to the attribute parameters to optimize the electromagnetic performance of the target motor, and the control performance of the target motor is optimized through the voltage compensation and closed-loop control, and the performance of the target motor is optimized by optimizing the control performance and electromagnetic performance of the target motor.

[0007] Optionally, determine the impact of high frequency signal injection on the target motor electromagnetic field, including:

[0008] Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established;

[0009] Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor;

[0010] The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor;

[0011] The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established;

[0012] Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting the high frequency signal of the preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected;

[0013] The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

[0014] Optionally, the method further includes: generating a preferred strategy for injecting the high-frequency signal based on the impact of the high-frequency signal injection on the electromagnetic field of the target motor, and determining a high-frequency signal suitable for injecting into the target motor through the preferred strategy.

[0015] Optionally, the influencing parameters include at least one of the following: winding slot parameters, short distance parameters and air gap magnetic field distribution coefficient

[0016] Optionally, the cogging effect is a law in which the equivalent air gap magnetic resistance of the target motor changes due to rotor teeth.

[0017] Optionally, the air gap magnetic field distribution of the target motor is determined based on Maxwell spatial electromagnetic field analysis, including: establishing a Maxwell diffusion equation group for the air gap magnetic field of the target motor, solving the Maxwell diffusion equation group using a variable separation method, and solving the spatial magnetic field vector using the Bessel equation for the solution of the Maxwell diffusion equation group to determine the air gap magnetic field distribution of the target motor.

[0018] Optionally, a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air-gap magnetic resistance of the target motor is established, including:

[0019] Determine the relationship between the harmonics of the injected single high frequency signal or multiple high frequency signals and the harmonics of the air gap magnetic field of the target motor to determine the harmonic amplitude characteristics of the single high frequency signal or multiple high frequency signals and their impact on the frequency domain of the air gap magnetic field;

[0020] Based on the harmonic amplitude characteristics of a single high-frequency signal or multiple high-frequency signals and their impact on the frequency domain of the air gap magnetic field, determine the impact of injecting a single high-frequency signal or multiple high-frequency signals on the target motor torque and iron loss;

[0021] According to the impact of injecting a single high-frequency signal and multiple high-frequency signals on the target motor torque and iron loss,

[0022] A mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal to be injected and the equivalent air-gap magnetic resistance of the target motor is established.

[0023] Optionally, determine the property parameters of the target motor, including:

[0024] Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis;

[0025] Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor;

[0026] The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size;

[0027] determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor;

[0028] Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state;

[0029] The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

[0030] Optionally, the limiting factors include at least one of the following: high-frequency harmonic factors, torque pulsation factors, and electromagnetic loss factors.

[0031] Optionally, the control strategy includes: a control strategy for the stability of the motor control dynamic process and a control strategy for the inverter nonlinear factor compensation.

[0032] Optionally, the initial motor dimensions include: stator and rotor structural dimensions and armature winding distribution dimensions.

[0033] Optionally, after the simulation run, if the adjusted motor control model can meet the control performance requirements of the motor, it is determined whether the motor can reach a deep magnetic saturation state; if the adjusted motor control model cannot meet the control performance requirements of the motor, the intrinsic parameters of the target motor are adjusted, and then the parameters and control strategy of the initial motor control model are adjusted according to the adjusted intrinsic parameters, and the adjusted motor control model is obtained again.

[0034] Optionally, if the motor can reach a deep magnetic saturation state, the target motor's intrinsic parameters and the adjusted motor control model are used as the target motor's attribute parameters; if not, the motor's current intensity is increased to determine again whether the adjusted motor control model can meet the motor's control performance requirements.

[0035] Optionally, voltage compensation is performed on the target motor when the high frequency signal is injected, including:

[0036] Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model;

[0037] In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model;

[0038] Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

[0039] Optionally, establishing a discrete prediction model of the target motor based on the electrical parameters includes:

[0040] Normalizing the electrical parameters, using the normalized electrical parameters as input data of the single-layer neural network, and using the predicted value of the target motor current as output data of the single-layer neural network;

[0041] The input data and the output data are simultaneously input into a single-layer neural network and trained using a gradient descent method to obtain a discrete prediction model of the target motor.

[0042] Optionally, the established discrete prediction model is fitted based on the adaptability of the neural network to improve the robustness of the discrete prediction model.

[0043] Optionally, the influencing factors include at least one of the following: dead time, conduction judgment time, switch tube conduction voltage drop and parasitic capacitance.

[0044] Optionally, the method further includes: decoupling the mid-base frequency part and the high frequency part of the voltage error model to determine a high frequency component expression of the voltage error, and based on the high frequency component expression, correcting the voltage error curve determined by the voltage error model.

[0045] Optionally, closed-loop control of the target motor is performed, including:

[0046] After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme;

[0047] Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain a real-time objective function value of the objective function;

[0048] When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position;

[0049] After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered;

[0050] The rotor position is determined based on the filtered phase angle, which enables the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation.

[0051] Optionally, whether the objective function is a convex function is determined based on eigenvalues ​​of a Hessian matrix of the objective function.

[0052] Optionally, a threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is modified according to a time-varying characteristic of a target motor control system parameter.

[0053] Optionally, obtaining a real-time objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the real-time objective function value.

[0054] Optionally, the estimation accuracy of the monitoring estimation algorithm is compensated by eliminating the effects of lag and cross saturation of current sampling in the target motor on the position estimation.

[0055] Optionally, a preset envelope extraction scheme is established based on the peak hold circuit principle of the target motor.

[0056] Optionally, a preset envelope extraction scheme is used to obtain the phase angle of the two-phase current envelope of the target motor, including: using the preset envelope extraction scheme to extract the low-frequency component associated with the motor speed in the high-frequency current response of the target motor, determining the two-phase current envelope of the target motor based on the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​using an inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor.

[0057] Optionally, the phase angle is filtered by a phase-locked loop observer.

[0058] In another aspect, the present invention further provides a system for optimizing the performance of a motor, comprising:

[0059] A first optimization module is used to establish an air gap magnetic field distribution model for a target motor, determine the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determine a high-frequency signal suitable for injection into the target motor and property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor;

[0060] A second optimization module is used for adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, performing voltage compensation on the target motor when the high-frequency signal is injected, determining a rotor position of the target motor based on the high-frequency signal injected into the target motor, and performing closed-loop control on the target motor through a control system based on the rotor position;

[0061] The third optimization module is used to inject the high-frequency signal suitable for injecting into the target motor, and adjust the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimize the control performance of the target motor through the voltage compensation and closed-loop control, and optimize the performance of the target motor by optimizing the control performance and electromagnetic performance of the target motor.

[0062] Optionally, determine the impact of high frequency signal injection on the target motor electromagnetic field, including:

[0063] Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established;

[0064] Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor;

[0065] The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor;

[0066] The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established;

[0067] Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting the high frequency signal of the preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected;

[0068] The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

[0069] Optionally, the first optimization module is further used to include: generating a preferred strategy for injecting the high-frequency signal according to the impact of the high-frequency signal injection on the electromagnetic field of the target motor, and determining a high-frequency signal suitable for injecting into the target motor through the preferred strategy.

[0070] Optionally, the influencing parameters include at least one of the following: winding slot parameters, short distance parameters and air gap magnetic field distribution coefficient

[0071] Optionally, the cogging effect is a law in which the equivalent air gap magnetic resistance of the target motor changes due to rotor teeth.

[0072] Optionally, the air gap magnetic field distribution of the target motor is determined based on Maxwell spatial electromagnetic field analysis, including: establishing a Maxwell diffusion equation group for the air gap magnetic field of the target motor, solving the Maxwell diffusion equation group using a variable separation method, and solving the spatial magnetic field vector using the Bessel equation for the solution of the Maxwell diffusion equation group to determine the air gap magnetic field distribution of the target motor.

[0073] Optionally, a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air-gap magnetic resistance of the target motor is established, including:

[0074] Determine the relationship between the harmonics of the injected single high frequency signal or multiple high frequency signals and the harmonics of the air gap magnetic field of the target motor to determine the harmonic amplitude characteristics of the single high frequency signal or multiple high frequency signals and their impact on the frequency domain of the air gap magnetic field;

[0075] Based on the harmonic amplitude characteristics of a single high-frequency signal or multiple high-frequency signals and their impact on the frequency domain of the air gap magnetic field, determine the impact of injecting a single high-frequency signal or multiple high-frequency signals on the target motor torque and iron loss;

[0076] According to the impact of injecting a single high-frequency signal and multiple high-frequency signals on the target motor torque and iron loss,

[0077] A mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal to be injected and the equivalent air-gap magnetic resistance of the target motor is established.

[0078] Optionally, determine the property parameters of the target motor, including:

[0079] Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis;

[0080] Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor;

[0081] The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size;

[0082] determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor;

[0083] Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state;

[0084] The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

[0085] Optionally, the limiting factors include at least one of the following: high-frequency harmonic factors, torque pulsation factors, and electromagnetic loss factors.

[0086] Optionally, the control strategy includes: a control strategy for the stability of the motor control dynamic process and a control strategy for the inverter nonlinear factor compensation.

[0087] Optionally, the initial motor dimensions include: stator and rotor structural dimensions and armature winding distribution dimensions.

[0088] Optionally, after the simulation run, if the adjusted motor control model can meet the control performance requirements of the motor, it is determined whether the motor can reach a deep magnetic saturation state; if the adjusted motor control model cannot meet the control performance requirements of the motor, the intrinsic parameters of the target motor are adjusted, and then the parameters and control strategy of the initial motor control model are adjusted according to the adjusted intrinsic parameters, and the adjusted motor control model is obtained again.

[0089] Optionally, if the motor can reach a deep magnetic saturation state, the target motor's intrinsic parameters and the adjusted motor control model are used as the target motor's attribute parameters; if not, the motor's current intensity is increased to determine again whether the adjusted motor control model can meet the motor's control performance requirements.

[0090] Optionally, voltage compensation is performed on the target motor when the high frequency signal is injected, including:

[0091] Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model;

[0092] In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model;

[0093] Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

[0094] Optionally, establishing a discrete prediction model of the target motor based on the electrical parameters includes:

[0095] Normalizing the electrical parameters, using the normalized electrical parameters as input data of the single-layer neural network, and using the predicted value of the target motor current as output data of the single-layer neural network;

[0096] The input data and the output data are simultaneously input into a single-layer neural network and trained using a gradient descent method to obtain a discrete prediction model of the target motor.

[0097] Optionally, the adaptability of the neural network is used to fit the established discrete prediction model to improve the robustness of the discrete prediction model.

[0098] Optionally, the influencing factors include at least one of the following: dead time, conduction judgment time, switch tube conduction voltage drop and parasitic capacitance.

[0099] Optionally, the second optimization module is also used to: decouple the mid-base frequency part and the high frequency part of the voltage error model to determine the high frequency component expression of the voltage error, and based on the high frequency component expression, correct the voltage error curve determined by the voltage error model.

[0100] Optionally, closed-loop control of the target motor is performed, including:

[0101] After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme;

[0102] Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain a real-time objective function value of the objective function;

[0103] When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position;

[0104] After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered;

[0105] The rotor position is determined based on the filtered phase angle, which enables the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation.

[0106] Optionally, whether the objective function is a convex function is determined based on eigenvalues ​​of a Hessian matrix of the objective function.

[0107] Optionally, a threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is modified according to a time-varying characteristic of a target motor control system parameter.

[0108] Optionally, obtaining a real-time objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the real-time objective function value.

[0109] Optionally, the estimation accuracy of the monitoring estimation algorithm is compensated by eliminating the effects of lag and cross saturation of current sampling in the target motor on the position estimation.

[0110] Optionally, a preset envelope extraction scheme is established based on the peak hold circuit principle of the target motor.

[0111] Optionally, a preset envelope extraction scheme is used to obtain the phase angle of the two-phase current envelope of the target motor, including: using the preset envelope extraction scheme to extract the low-frequency component associated with the motor speed in the high-frequency current response of the target motor, determining the two-phase current envelope of the target motor based on the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​using an inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor.

[0112] Optionally, the phase angle is filtered by a phase-locked loop observer.

[0113] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0114] a processor for executing one or more programs;

[0115] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0116] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0117] Compared with the prior art, the present invention has the following beneficial effects:

[0118] The present invention provides a method for optimizing the performance of a motor, comprising: establishing an air gap magnetic field distribution model for a target motor, determining the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, determining a high-frequency signal suitable for injection into the target motor and the attribute parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor; after adjusting the target motor through the attribute parameters and injecting a high-frequency signal suitable for injection into the target motor, performing voltage compensation on the target motor under the condition of injecting the high-frequency signal, determining the rotor position of the target motor based on the high-frequency signal injected into the target motor, and performing closed-loop control on the target motor based on the rotor position through a control system; injecting the high-frequency signal suitable for injection into the target motor into the target motor, and adjusting the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimizing the control performance of the target motor through the voltage compensation and closed-loop control, and optimizing the control performance and electromagnetic performance of the target motor to optimize the performance of the target motor. The present invention can optimize the performance of the motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] Figure 1 is a flow chart of the method of the present invention;

[0120] Figure 2 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0121] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0122] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0123] Embodiment 1:

[0124] The present invention provides a method for optimizing the performance of a motor, such as Figure 1 As shown, including:

[0125] Step 1: Establish an air gap magnetic field distribution model for the target motor, determine the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determine the high-frequency signal suitable for injection into the target motor and the property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor;

[0126] Step 2: after adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, voltage compensation is performed on the target motor when the high-frequency signal is injected, a rotor position of the target motor is determined based on the high-frequency signal injected into the target motor, and closed-loop control is performed on the target motor through a control system based on the rotor position;

[0127] Step 3: Inject the high-frequency signal suitable for injecting into the target motor, and adjust the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimize the control performance of the target motor through the voltage compensation and closed-loop control, and optimize the performance of the target motor by optimizing the control performance and electromagnetic performance of the target motor.

[0128] Among them, determining the impact of high-frequency signal injection on the electromagnetic field of the target motor includes:

[0129] Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established;

[0130] Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor;

[0131] The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor;

[0132] The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established;

[0133] Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting the high frequency signal of the preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected;

[0134] The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

[0135] The method further includes: generating a preferred strategy for injecting the high-frequency signal according to the influence of the high-frequency signal injection on the electromagnetic field of the target motor, and determining the high-frequency signal suitable for injecting into the target motor through the preferred strategy.

[0136] Among them, the influencing parameters include at least one of the following: winding slot parameters, short distance parameters and air gap magnetic field distribution coefficient

[0137] Among them, the cogging effect is the law that the equivalent air gap magnetic resistance of the target motor changes due to the rotor teeth.

[0138] Among them, the air gap magnetic field distribution of the target motor is determined based on Maxwell spatial electromagnetic field analysis, including: establishing a Maxwell diffusion equation group for the air gap magnetic field of the target motor, using the variable separation method to solve the Maxwell diffusion equation group, and solving the spatial magnetic field vector through the Bessel equation for the solution of the Maxwell diffusion equation group to determine the air gap magnetic field distribution of the target motor.

[0139] Among them, the mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established, including:

[0140] Determine the relationship between the harmonics of the injected single high frequency signal or multiple high frequency signals and the harmonics of the air gap magnetic field of the target motor to determine the harmonic amplitude characteristics of the single high frequency signal or multiple high frequency signals and their impact on the frequency domain of the air gap magnetic field;

[0141] Based on the harmonic amplitude characteristics of a single high-frequency signal or multiple high-frequency signals and their impact on the frequency domain of the air gap magnetic field, determine the impact of injecting a single high-frequency signal or multiple high-frequency signals on the target motor torque and iron loss;

[0142] According to the impact of injecting a single high-frequency signal and multiple high-frequency signals on the target motor torque and iron loss,

[0143] A mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal to be injected and the equivalent air-gap magnetic resistance of the target motor is established.

[0144] The property parameters of the target motor are determined, including:

[0145] Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis;

[0146] Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor;

[0147] The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size;

[0148] determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor;

[0149] Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state;

[0150] The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

[0151] The limiting factors include at least one of the following: high-frequency harmonic factors, torque pulsation factors, and electromagnetic loss factors.

[0152] Among them, the control strategy includes: a control strategy for the stability of the dynamic process of motor control and a compensation strategy for the nonlinear factors of the inverter.

[0153] Among them, the initial motor size includes: stator and rotor structure size and armature winding distribution size.

[0154] Among them, after the simulation run, if the adjusted motor control model can meet the control performance requirements of the motor, it is determined whether the motor can reach a deep magnetic saturation state. If the adjusted motor control model cannot meet the control performance requirements of the motor, the body parameters of the target motor are adjusted, and then the parameters and control strategy of the initial motor control model are adjusted according to the adjusted body parameters, and the adjusted motor control model is obtained again.

[0155] Among them, if the motor can reach a deep magnetic saturation state, the main body parameters of the target motor and the adjusted motor control model will be used as the attribute parameters of the target motor. If not, the current intensity of the motor will be increased to determine again whether the adjusted motor control model can meet the control performance requirements of the motor.

[0156] The voltage compensation is performed on the target motor when the high-frequency signal is injected, including:

[0157] Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model;

[0158] In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model;

[0159] Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

[0160] Wherein, establishing a discrete prediction model of the target motor based on the electrical parameters includes:

[0161] Normalizing the electrical parameters, using the normalized electrical parameters as input data of the single-layer neural network, and using the predicted value of the target motor current as output data of the single-layer neural network;

[0162] The input data and the output data are simultaneously input into a single-layer neural network and trained using a gradient descent method to obtain a discrete prediction model of the target motor.

[0163] Among them, the established discrete prediction model is fitted based on the adaptability of the neural network to improve the robustness of the discrete prediction model.

[0164] The influencing factors include at least one of the following: dead time, conduction judgment time, switch tube conduction voltage drop and parasitic capacitance.

[0165] The method further includes: decoupling the mid-base frequency part and the high frequency part of the voltage error model to determine the high frequency component expression of the voltage error, and based on the high frequency component expression, correcting the voltage error curve determined by the voltage error model.

[0166] Among them, closed-loop control of the target motor includes:

[0167] After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme;

[0168] Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain a real-time objective function value of the objective function;

[0169] When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position;

[0170] After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered;

[0171] The rotor position is determined based on the filtered phase angle, which enables the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation.

[0172] Wherein, whether the objective function is a convex function is determined based on the Hessian matrix eigenvalue of the objective function.

[0173] Wherein, a threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is corrected according to a time-varying characteristic of a target motor control system parameter.

[0174] Wherein, obtaining the real-time objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the real-time objective function value.

[0175] Among them, the estimation accuracy of the monitoring estimation algorithm is compensated by eliminating the influence of the lag and cross saturation of the current sampling in the target motor on the position estimation.

[0176] Among them, the preset envelope extraction scheme is established according to the peak holding circuit principle of the target motor.

[0177] Among them, a preset envelope extraction scheme is used to obtain the phase angle of the two-phase current envelope of the target motor, including: using the preset envelope extraction scheme to extract the low-frequency component associated with the motor speed in the high-frequency current response of the target motor, determining the two-phase current envelope of the target motor based on the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​through the inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor.

[0178] The phase angle is filtered by a phase-locked loop observer.

[0179] The principle of the present invention is as follows:

[0180] The stability problem of the traditional salient pole tracking solution is reflected in the dynamic process of the motor's rapid acceleration or deceleration or torque disturbance. It is possible that the position observation converges to the opposite of the actual position due to large transient errors. From the perspective of fault diagnosis, the position estimation can be detected in real time, and fault tolerance processing can be quickly performed after a fault occurs to restore the system to normal steady-state operation.

[0181] When designing the scheme, it is planned to use the convex optimization theory in optimal control to extract the fault characteristics: the objective function is designed with the estimated speed and position as independent variables, and the Hessian matrix eigenvalues ​​are analyzed to determine that the objective function is a convex function, and the global minimum value appears when the estimated value is equal to the true value. The operation of the estimation algorithm is monitored by real-time calculation of the objective function. When the objective function value exceeds the set threshold, it is considered that the position estimation has converged incorrectly, and the position estimation is corrected to make the system return to a stable state.

[0182] The setting of the threshold should fully consider the impact of the estimation error in the dynamic process, and leave an appropriate margin to reduce the false alarm rate. Considering the time-varying characteristics of the parameters of the motor control system, the parameter sensitivity is studied by deriving the electrical parameters of the objective function, and the key parameters are obtained for online identification. In the absence of position sensors, the speed and position variables are also obtained by observation. Therefore, the parameter identification system is a multi-input and multi-output system, and the identification results affect each other. The erroneous convergence caused by the "lack of rank problem" in multi-parameter identification can be avoided by reasonably adding steady-state operating points; the stability of the identification system can also be improved by step-by-step identification of fast and slow time-varying parameters.

[0183] 2) Design a direct calculation scheme for the rotor position. The starting point of this scheme is to extract the low-frequency component related to the motor speed in the high-frequency current response, and directly calculate the phase angle through the inverse tangent function. From existing research results, it can be seen that when the high-frequency voltage is injected into the direct axis in the estimated two-phase rotating coordinate system, the frequency of the high-frequency current envelope after the motor salient polarity modulation in the two-phase stationary coordinate system is related to the motor speed. It is proposed to use the peak holding circuit principle to design an envelope extraction scheme that is conducive to the implementation of digital control systems, normalize the extracted two-phase current envelope to obtain the sine and cosine values, and use the inverse tangent function to calculate the phase angle. Since the direct calculation method is susceptible to noise interference, it is considered to filter the calculated phase angle through a phase-locked loop observer, and finally use it for closed-loop control.

[0184] This scheme avoids the unstable zero point problem existing in the traditional phase-locked scheme. However, since the position information is contained in the low-frequency component of the high-frequency current response, it is necessary to study the phase lag caused by low-pass filtering. At the same time, it is necessary to compensate for the influence of current sampling lag and cross-saturation on position estimation in order to improve the estimation accuracy.

[0185] Among the existing compensation schemes, the compensation scheme based on voltage pulse adjustment is the most widely used and most suitable for the specific application background of position sensor-free. The key points that determine the accuracy of such compensation schemes are: first, the accurate judgment of the current polarity in the zero current region, and second, the accuracy of the voltage error curve.

[0186] Regarding the first point, this project intends to design a current prediction scheme from the perspective of model prediction to solve the delay problem in digital implementation. The current prediction model can be obtained by Euler discretization of the stator current equation, but the model has strong parameter dependence. It is planned to use the adaptability of the neural network to fit the discrete function to improve the parameter robustness of the current prediction. From the perspective of reducing the computational complexity and combining the characteristics of the discrete prediction model, it is planned to select a single-layer neural network structure, treat the electrical parameter items as weight factors that need to be adjusted online, and use the predicted value of the current as the output of the neural network. The difference between the current and the sampled current is combined with the gradient descent method to train the neural network. In the specific implementation, the input items should be normalized to avoid possible numerical problems, and the influence of the learning step size on the convergence speed and prediction accuracy should be studied. In order to further improve the accuracy of current prediction, the current oversampling scheme within a single cycle is studied. The increased current sampling points help to accurately obtain the current change law under the conditions of known switch tube state and action time, thereby improving the function fitting accuracy. Regarding the second point, this project established a voltage error model that includes influencing factors such as dead time, conduction judgment time, switch tube conduction voltage drop, parasitic capacitance, etc., and designed the voltage error curve offline on this basis; studied the same-frequency fluctuation characteristics of the voltage error caused by repeated zero crossing of the high-frequency current in the zero current region when the high-frequency voltage signal was injected; by decoupling the fundamental frequency part and the high-frequency part in the voltage error model, the expression of the high-frequency component in the voltage error was obtained, and based on this, the voltage error curve in the zero current region was corrected.

[0187] 1) Preliminary design of motor body size based on electromagnetic field analysis theory; 2) Combined with the control model, analyze the amplitude-frequency characteristics of the optimal injection current signal; 3) Analyze the air gap magnetic field changes based on the signal characteristics, and further optimize the motor body size, including the stator and rotor structure and the armature winding distribution; 4) Improve the control model based on the optimized motor body structure, adjust the control strategy, and execute step 3; 5) Repeat steps 3-4-3 until the design meets the control performance. After the above algorithm is completed, the current intensity can be further increased, and steps 3-4-5 are repeated to complete the motor body design and control optimization under the working condition of severe magnetic saturation. After the above steps are completed, the motor body structure and control characteristics with high-frequency harmonic suppression are obtained, and the design and control integrated optimization criteria of this type of motor are proposed.

[0188] 1) Establish a spatial distribution model of magnetomotive force under three-phase sinusoidal AC excitation, considering the influence of winding slots, short distance, and distribution coefficient on harmonics; 2) Use Maxwell space electromagnetic field theory to analyze the air gap magnetic field distribution: use the variable separation method to solve the Maxwell diffusion equations, and use the Bessel equation to solve the spatial magnetic field vector to obtain the magnetic field distribution of the motor body; 3) For the convenience of simulation and experimental verification, further solve other parameters: use Poynting and energy conservation theory to calculate the loss of each component and the output torque. In the analysis model, since the salient pole structure of the motor under study is not obvious, the equivalent air gap between the stator and the rotor is not seriously time-varying, and each component is regarded as a coaxial hollow cylinder, which simplifies the difficulty of model construction. After the model is established, the tooth slot effect is further considered, that is, the law of the change of the equivalent air gap magnetic resistance with the rotor teeth.

[0189] However, the above model assumes that the magnetic field is not saturated. After this step is completed, the finite element method can be used for verification. Note that the BH curve of the silicon steel sheet is set to the ideal situation. However, when the motor power density is increased or the high-frequency signal is injected more obviously, obvious magnetic saturation will occur at the stator and rotor salient pole tooth tips. For this reason, the Cater constant or magnetic circuit model is introduced to estimate the equivalent air gap length. The Cater constant is suitable for occasions where the salient pole is not obvious or the magnetic flux density is not high. However, when the motor power density is increased and the injected signal is superimposed or the amplitude is more obvious, the strong tooth tip magnetic saturation leads to the estimation of the equivalent air gap. Constants should not be used. At this time, the magnetic circuit model is used, and it is noted that the time-varying additional magnetic resistance generated by magnetic saturation is incorporated into the magnetic resistance element representing the convex teeth.

[0190] The magnetic saturation effect is incorporated into the electromagnetic field analysis model, and the air gap magnetic field is analyzed under a given three-phase sinusoidal AC excitation.

[0191] After this step is completed, finite element verification can be further performed: the BH curve of the ferromagnetic material in the above-established finite element model can be converted into actual data.

[0192] After the analytical model is verified, the mapping relationship between the injected harmonic amplitude-frequency characteristics and the equivalent air gap magnetic resistance is established, which is divided into the following two steps: 1) Analyze the relationship between the injection of single and multiple high-frequency harmonics and the air gap magnetic field harmonics, analyze the influence of the signal amplitude-frequency on the frequency domain analysis of the air gap magnetic field, and then qualitatively obtain the influence of the injected signal on the torque and iron loss; 2) Study the relationship between the injected signal and the air gap harmonics. The specific operation is to inject one or more armature harmonic signals with different frequencies and amplitudes in sequence under three-phase sinusoidal alternating current excitation, and then propose the amplitude-frequency characteristics of the high-frequency signal injected to reduce torque pulsation and iron loss, and obtain the theoretical basis for the optimization of the high-frequency injection signal.

[0193] Embodiment 2:

[0194] The present invention also proposes a system 200 for optimizing the performance of a motor, such as Figure 2 As shown, including:

[0195] The first optimization module 201 is used to establish an air gap magnetic field distribution model for the target motor, determine the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determine the high-frequency signal suitable for injection into the target motor and the property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor;

[0196] A second optimization module 202 is used for adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, performing voltage compensation on the target motor when the high-frequency signal is injected, determining a rotor position of the target motor based on the high-frequency signal injected into the target motor, and performing closed-loop control on the target motor through a control system based on the rotor position;

[0197] The third optimization module 203 is used to inject the high-frequency signal suitable for injecting into the target motor, and adjust the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimize the control performance of the target motor through the voltage compensation and closed-loop control, and optimize the performance of the target motor by optimizing the control performance and electromagnetic performance of the target motor.

[0198] Among them, determining the impact of high-frequency signal injection on the electromagnetic field of the target motor includes:

[0199] Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established;

[0200] Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor;

[0201] The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor;

[0202] The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established;

[0203] Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting the high frequency signal of the preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected;

[0204] The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

[0205] The first optimization module is further used to include: generating a preferred strategy for injecting high-frequency signals according to the influence of high-frequency signal injection on the electromagnetic field of the target motor, and determining a high-frequency signal suitable for injecting into the target motor through the preferred strategy.

[0206] Among them, the influencing parameters include at least one of the following: winding slot parameters, short distance parameters and air gap magnetic field distribution coefficient

[0207] Among them, the cogging effect is the law that the equivalent air gap magnetic resistance of the target motor changes due to the rotor teeth.

[0208] Among them, the air gap magnetic field distribution of the target motor is determined based on Maxwell spatial electromagnetic field analysis, including: establishing a Maxwell diffusion equation group for the air gap magnetic field of the target motor, using the variable separation method to solve the Maxwell diffusion equation group, and solving the spatial magnetic field vector through the Bessel equation for the solution of the Maxwell diffusion equation group to determine the air gap magnetic field distribution of the target motor.

[0209] Among them, the mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established, including:

[0210] Determine the relationship between the harmonics of the injected single high frequency signal or multiple high frequency signals and the harmonics of the air gap magnetic field of the target motor to determine the harmonic amplitude characteristics of the single high frequency signal or multiple high frequency signals and their impact on the frequency domain of the air gap magnetic field;

[0211] Based on the harmonic amplitude characteristics of a single high-frequency signal or multiple high-frequency signals and their impact on the frequency domain of the air gap magnetic field, determine the impact of injecting a single high-frequency signal or multiple high-frequency signals on the target motor torque and iron loss;

[0212] According to the impact of injecting a single high-frequency signal and multiple high-frequency signals on the target motor torque and iron loss,

[0213] A mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal to be injected and the equivalent air-gap magnetic resistance of the target motor is established.

[0214] The property parameters of the target motor are determined, including:

[0215] Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis;

[0216] Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor;

[0217] The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size;

[0218] determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor;

[0219] Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state;

[0220] The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

[0221] The limiting factors include at least one of the following: high-frequency harmonic factors, torque pulsation factors, and electromagnetic loss factors.

[0222] Among them, the control strategy includes: a control strategy for the stability of the dynamic process of motor control and a compensation strategy for the nonlinear factors of the inverter.

[0223] Among them, the initial motor size includes: stator and rotor structure size and armature winding distribution size.

[0224] Among them, after the simulation run, if the adjusted motor control model can meet the control performance requirements of the motor, it is determined whether the motor can reach a deep magnetic saturation state. If the adjusted motor control model cannot meet the control performance requirements of the motor, the body parameters of the target motor are adjusted, and then the parameters and control strategy of the initial motor control model are adjusted according to the adjusted body parameters, and the adjusted motor control model is obtained again.

[0225] Among them, if the motor can reach a deep magnetic saturation state, the main body parameters of the target motor and the adjusted motor control model will be used as the attribute parameters of the target motor. If not, the current intensity of the motor will be increased to determine again whether the adjusted motor control model can meet the control performance requirements of the motor.

[0226] The voltage compensation is performed on the target motor when the high-frequency signal is injected, including:

[0227] Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model;

[0228] In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model;

[0229] Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

[0230] Wherein, establishing a discrete prediction model of the target motor based on the electrical parameters includes:

[0231] Normalizing the electrical parameters, using the normalized electrical parameters as input data of the single-layer neural network, and using the predicted value of the target motor current as output data of the single-layer neural network;

[0232] The input data and the output data are simultaneously input into a single-layer neural network and trained using a gradient descent method to obtain a discrete prediction model of the target motor.

[0233] Among them, the established discrete prediction model is fitted based on the adaptability of the neural network to improve the robustness of the discrete prediction model.

[0234] The influencing factors include at least one of the following: dead time, conduction judgment time, switch tube conduction voltage drop and parasitic capacitance.

[0235] Among them, the second optimization module is also used to: decouple the mid-base frequency part and the high-frequency part of the voltage error model to determine the high-frequency component expression of the voltage error, and based on the high-frequency component expression, correct the voltage error curve determined by the voltage error model.

[0236] Among them, closed-loop control of the target motor includes:

[0237] After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme;

[0238] Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain a real-time objective function value of the objective function;

[0239] When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position;

[0240] After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered;

[0241] The rotor position is determined based on the filtered phase angle, which enables the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation.

[0242] Wherein, whether the objective function is a convex function is determined based on the Hessian matrix eigenvalue of the objective function.

[0243] Wherein, a threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is corrected according to a time-varying characteristic of a target motor control system parameter.

[0244] Wherein, obtaining the real-time objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the real-time objective function value.

[0245] Among them, the estimation accuracy of the monitoring estimation algorithm is compensated by eliminating the influence of the lag and cross saturation of the current sampling in the target motor on the position estimation.

[0246] Among them, the preset envelope extraction scheme is established according to the peak holding circuit principle of the target motor.

[0247] Among them, a preset envelope extraction scheme is used to obtain the phase angle of the two-phase current envelope of the target motor, including: using the preset envelope extraction scheme to extract the low-frequency component associated with the motor speed in the high-frequency current response of the target motor, determining the two-phase current envelope of the target motor based on the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​through the inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor.

[0248] The phase angle is filtered by a phase-locked loop observer.

[0249] Embodiment 3:

[0250] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0251] Embodiment 4:

[0252] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0253] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0254] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0255] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0256] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0257] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0258] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing the performance of a motor, characterized in that: The method comprises: Establishing an air gap magnetic field distribution model for the target motor, determining the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determining a high-frequency signal suitable for injection into the target motor and property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor; After adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, voltage compensation is performed on the target motor when the high-frequency signal is injected, a rotor position of the target motor is determined based on the high-frequency signal injected into the target motor, and closed-loop control is performed on the target motor through a control system based on the rotor position; Injecting the high-frequency signal suitable for injecting into the target motor into the target motor, and adjusting the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimizing the control performance of the target motor through the voltage compensation and closed-loop control, and optimizing the performance of the target motor by optimizing the control performance and electromagnetic performance of the target motor; Perform closed-loop control of the target motor, including: After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme; Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain the objective function value of the objective function; When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position; After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered; Determine the rotor position based on the filtered phase angle, and enable the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation; Determine whether the objective function is a convex function based on the Hessian matrix eigenvalue of the objective function; A threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is modified according to a time-varying characteristic of a target motor control system parameter; The obtaining of the objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the objective function value; By eliminating the influence of hysteresis and cross saturation of current sampling in the target motor on the position estimation, the estimation accuracy of the monitoring estimation algorithm is compensated; The preset envelope extraction scheme is established according to the peak holding circuit principle of the target motor; the method of obtaining the phase angle of the two-phase current envelope of the target motor by using the preset envelope extraction scheme includes: extracting the low-frequency component associated with the motor speed in the high-frequency current response of the target motor by using the preset envelope extraction scheme, determining the two-phase current envelope of the target motor for the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​by an inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor; The phase angle is filtered through a phase-locked loop observer; Among them, the objective function is designed with the estimated speed and rotor position as independent variables. The Hessian matrix eigenvalue of the objective function is used to determine that when the objective function is a convex function, the global minimum occurs when the estimated value is equal to the true value. The operation status is determined by monitoring the estimation algorithm through real-time calculation of the objective function. When the objective function value exceeds the set threshold, erroneous convergence of the position estimation occurs. The position estimation is corrected to make the target motor re-enter a stable state.

2. The method according to claim 1, characterized in that The determining the influence of the high-frequency signal injection on the electromagnetic field of the target motor includes: Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established; Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor; The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor; The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established; Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting a high frequency signal of a preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected; The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

3. The method according to claim 1, characterized in that: The step of determining the property parameters of the target motor includes: Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis; Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor; The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size; determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor; Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state; The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

4. The method according to claim 1, characterized in that The voltage compensation of the target motor when the high-frequency signal is injected includes: Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model; In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model; Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

5. A system for optimizing the performance of a motor, characterized in that: The system comprises: A first optimization module is used to establish an air gap magnetic field distribution model for a target motor, determine the influence of high-frequency signal injection on the electromagnetic field of the target motor based on the air gap magnetic field distribution model, and determine a high-frequency signal suitable for injection into the target motor and property parameters of the target motor based on the influence of the high-frequency signal injection on the electromagnetic field of the target motor; A second optimization module is used for adjusting the target motor by the attribute parameters and injecting a high-frequency signal suitable for injecting into the target motor, performing voltage compensation on the target motor when the high-frequency signal is injected, determining a rotor position of the target motor based on the high-frequency signal injected into the target motor, and performing closed-loop control on the target motor through a control system based on the rotor position; A third optimization module is used to inject the high-frequency signal suitable for injecting into the target motor into the target motor, and adjust the target motor according to the attribute parameters to optimize the electromagnetic performance of the target motor, optimize the control performance of the target motor through the voltage compensation and closed-loop control, and optimize the performance of the target motor by optimizing the control performance and electromagnetic performance of the target motor; Perform closed-loop control of the target motor, including: After the high-frequency signal is injected into the target motor, the fault feature quantity of the target motor is extracted by a preset convex optimization extraction scheme; Based on the extracted fault feature quantity, and taking the speed and rotor position estimated by the monitoring prediction algorithm of the target motor as independent variables, an objective function is established. If the objective function is a convex function, the independent variables are input into the objective function as input values, so as to prompt the objective function to perform solution calculation and obtain the objective function value of the objective function; When a target function value in any time unit exceeds a preset threshold, determining a rotor position estimated by a monitoring prediction algorithm of the target motor at this time, and performing a rotor position correction on a control system of the target motor based on the estimated rotor position; After the control system of the target motor is modified, the phase angle of the two-phase current envelope of the target motor is obtained by using a preset envelope extraction scheme, and the phase angle is filtered; Determine the rotor position based on the filtered phase angle, and enable the control system to perform closed-loop control on the target motor based on the rotor position to improve the stability of the target motor operation; Determine whether the objective function is a convex function based on the Hessian matrix eigenvalue of the objective function; A threshold is set based on an estimation error of a monitoring estimation algorithm, and the threshold is modified according to a time-varying characteristic of a target motor control system parameter; The obtaining of the objective function value of the objective function includes: calculating the operation status of the target motor monitoring estimation algorithm in real time through the objective function to obtain the objective function value; By eliminating the influence of hysteresis and cross saturation of current sampling in the target motor on the position estimation, the estimation accuracy of the monitoring estimation algorithm is compensated; The preset envelope extraction scheme is established according to the peak holding circuit principle of the target motor; the method of obtaining the phase angle of the two-phase current envelope of the target motor by using the preset envelope extraction scheme includes: extracting the low-frequency component associated with the motor speed in the high-frequency current response of the target motor by using the preset envelope extraction scheme, determining the two-phase current envelope of the target motor for the low-frequency component, normalizing the two-phase current envelope, determining the sine and cosine values ​​of the two-phase current envelope, and calculating the sine and cosine values ​​by an inverse tangent function to obtain the phase angle of the two-phase current envelope of the target motor; The phase angle is filtered through a phase-locked loop observer; Among them, the objective function is designed with the estimated speed and rotor position as independent variables. The Hessian matrix eigenvalue of the objective function is used to determine that when the objective function is a convex function, the global minimum occurs when the estimated value is equal to the true value. The operation status is determined by monitoring the estimation algorithm through real-time calculation of the objective function. When the objective function value exceeds the set threshold, erroneous convergence of the position estimation occurs. The position estimation is corrected to make the target motor re-enter a stable state.

6. The system according to claim 5, characterized in that The determining the influence of the high-frequency signal injection on the electromagnetic field of the target motor includes: Based on the influencing parameters of the air gap magnetic field harmonics affecting the target motor, a magnetomotive force spatial distribution model under three-phase sinusoidal alternating current excitation associated with the target motor is established; Determine the air gap magnetic field distribution of the target motor based on Maxwell space electromagnetic field analysis, and establish a Maxwell magnetic field analytical model based on the determined air gap magnetic field distribution of the target motor; The magnetomotive force spatial distribution model and the Maxwell magnetic field analytical model are integrated, and the cogging effect and the magnetic saturation effect are combined in the integration process to establish an air gap magnetic field distribution model of the target motor; The output results of the air gap magnetic field distribution model are verified using sample data. If the accuracy of the results during the verification process reaches a threshold value or above, the verification is completed, and a mapping relationship between the harmonic amplitude-frequency characteristics of the high-frequency signal and the equivalent air gap magnetic resistance of the target motor is established; Prompting the air gap magnetic field distribution model to perform simulation operation based on the mapping relationship, and injecting a high frequency signal of a preset frequency band during the simulation operation to output a simulation signal of the air gap magnetic field harmonics of the target motor after the high frequency signal of the preset frequency band is injected; The influence of high-frequency signal injection on the electromagnetic field of the target motor is determined according to the simulation signal.

7. The system according to claim 5, characterized in that The step of determining the property parameters of the target motor includes: Determining an initial motor size of a target motor to be controlled based on electromagnetic analysis; Determining amplitude-frequency characteristics of an injection signal suitable for the target motor based on a pre-established initial motor control model associated with the target motor; The amplitude-frequency characteristics are calculated based on a pre-established air gap magnetic field distribution model to obtain a calculation result, and the initial motor size is adjusted according to the calculation result to obtain an adjusted motor size; determining a bulk parameter of the target motor according to an adjusted motor size of the target motor and a limiting factor of the target motor; Based on the intrinsic parameters of the target motor, the parameters and control strategy of the initial motor control model are adjusted to obtain the adjusted motor control model, and simulation operation is performed on the adjusted motor control model to determine whether the adjusted motor control model can meet the control performance requirements of the motor and whether the motor reaches a deep magnetic saturation state. If the adjusted motor control model can meet the control performance requirements of the motor and the motor reaches a deep magnetic saturation state; The intrinsic parameters of the target motor and the adjusted motor control model are used as attribute parameters of the target motor.

8. The system according to claim 5, characterized in that The voltage compensation of the target motor when the high-frequency signal is injected includes: Acquiring electrical parameters of the target motor, establishing a discrete prediction model of the target motor based on the electrical parameters, and determining the current polarity of the target motor in a zero current region according to the discrete prediction model; In the case of injecting a high-frequency signal into a target motor, determining influencing factors affecting a voltage error of the target motor, establishing a voltage error model of the target motor based on the influencing factors, and determining a voltage error curve of the target motor in the case of injecting a high-frequency signal according to the voltage error model; Based on the current polarity of the target motor in the zero current region and the voltage error curve when a high-frequency signal is injected, the voltage value that needs to be compensated for the target motor when a high-frequency signal is injected is determined, and based on the voltage value, voltage compensation is performed on the target motor when a high-frequency signal is injected.

9. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 4 is implemented.

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