Low vibration noise optimization method of driving motor, computer equipment and storage medium

Abstract

The invention relates to a low-vibration-noise optimization method for a driving motor, computer equipment and a storage medium, and the method comprises the steps: carrying out the structural parametric modeling of a motor through obtaining the structural parameters and geometric features of the motor, and obtaining a motor electromagnetic simulation model; setting constraint conditions according to a motor peak torque, a cogging torque and a back electromotive force harmonic distortion rate of the motor, and establishing a target function by taking motor order torque fluctuation, radial electromagnetic force of each section of a rotor, torque fluctuation of each section of the rotor, synthetic torque fluctuation and a matching degree of synthetic radial electromagnetic force density and synthetic torque fluctuation as to-be-optimized targets; setting a plurality of candidate electromagnetic design schemes, and for each electromagnetic design scheme, respectively calculating target function values of the motor electromagnetic simulation model under different working conditions under corresponding constraint conditions; determining a target scheme in the plurality of electromagnetic design schemes based on the target function value, and optimizing structural parameters of the driving motor based on the target scheme; and the electromagnetic scheme design with the optimal NVH performance is realized under the multi-dimensional constraint.

Description

Technical Field

[0001] This application relates to the field of electromagnetic optimization of electric motors, and in particular to a low-vibration and noise optimization method for drive motors, a computer device, and a storage medium. Background Technology

[0002] With the development of hybrid or pure electric vehicles, the topologies of motors used in automotive power drive systems are becoming more diverse and complex. In order to improve the overall performance of automobiles, such as power, economy, and ride comfort, the motors used in automobiles should not only meet the requirements of power, torque, and speed range, but also have low vibration and noise (NVH).

[0003] Traditional electromagnetic optimization schemes for motors often employ single-objective optimization processes, making it difficult to consider multiple key performance indicators simultaneously during the optimization process. This results in the final optimization solution not being the overall optimal electromagnetic design. For example, focusing on minimizing the total electromagnetic excitation force amplitude as the core optimization objective ignores the impact of this optimization strategy on other key electromagnetic performance parameters. This may adversely affect the motor's output torque fluctuations, efficiency, temperature rise, and other performance aspects, thereby limiting the improvement of overall system performance. Summary of the Invention

[0004] Based on this, it is necessary to provide a low-vibration noise optimization method, computer equipment, and storage medium for a drive motor that can achieve optimal NVH performance electromagnetic scheme under multi-dimensional constraints, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for optimizing the vibration and noise of a drive motor. The method includes:

[0006] Obtain the structural parameters and geometric characteristics of the motor;

[0007] Based on the structural parameters and geometric features, the motor is modeled using structural parameterization to obtain an electromagnetic simulation model of the motor.

[0008] Based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, constraints are set, and the motor order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between the composite radial electromagnetic force density and the composite torque fluctuation are used as optimization targets to establish an objective function.

[0009] Multiple candidate electromagnetic design schemes are set up, and for each electromagnetic design scheme, the objective function of the motor electromagnetic simulation model under different working conditions is calculated under the corresponding constraints.

[0010] Based on the value of the objective function, a target scheme is determined from multiple electromagnetic design schemes, and the structural parameters of the drive motor are optimized based on the target scheme.

[0011] In some embodiments, the motor is structurally parametrically modeled based on the structural parameters and geometric features to obtain an electromagnetic simulation model of the motor, including:

[0012] Based on the geometric features, a geometric model including a rotor structure and a stator structure is constructed, and corresponding material properties are configured for the geometric model.

[0013] The variable parameters of the geometric model are defined based on the structural parameters, and a variable name, default value, and value range are configured for each variable parameter.

[0014] In some embodiments, after defining variable parameters of the geometric model based on the structural parameters and configuring variable names, default values, and value ranges for each variable parameter, the method further includes:

[0015] An initial electromagnetic simulation model of the motor is constructed based on the set structural parameters, and simulation calculations are performed on the initial electromagnetic simulation model of the motor to obtain simulated motor performance data.

[0016] Compare the simulated motor performance data with the actual motor performance data;

[0017] If the simulated motor performance data deviates from the actual motor performance data or the deviation is outside a preset range, the material properties and / or variable parameters are adjusted so that the simulated motor performance data does not deviate from the actual motor performance data or the deviation is within a preset range.

[0018] In some embodiments, constraints are set based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, including:

[0019] The minimum allowable value of the peak torque of the motor, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate are set respectively, and the minimum allowable value of the peak torque of the motor, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate are used as the constraint conditions.

[0020] In some embodiments, the motor order torque fluctuation, the radial electromagnetic force of each rotor segment, the torque fluctuation of each rotor segment, the combined torque fluctuation, the degree of matching between the combined radial electromagnetic force density and the combined torque fluctuation are used as optimization targets to establish an objective function, including:

[0021] Set the target optimization percentage parameter corresponding to each of the aforementioned targets to be optimized;

[0022] For different working conditions, corresponding weight coefficients are assigned to each of the target optimization percentage parameters. Based on the weight coefficients, the target optimization percentage parameters are fused to obtain the objective function corresponding to different working conditions.

[0023] In some embodiments, multiple candidate electromagnetic design schemes are set. For each electromagnetic design scheme, after calculating the objective function value of the motor electromagnetic simulation model under different operating conditions and corresponding constraints, the method further includes:

[0024] Determine whether the value of the objective function satisfies the preset optimization objective;

[0025] If it is determined that the value of the objective function does not meet the optimization objective, the variable parameters of the motor electromagnetic simulation model are adjusted, and the simulation calculation is performed again until the value of the objective function meets the optimization objective.

[0026] In some embodiments, a target scheme is determined among multiple electromagnetic design schemes based on the value of the objective function, including:

[0027] Obtain the electromagnetic design schemes and their corresponding objective function values ​​under different operating conditions through simulation;

[0028] For each of the aforementioned operating conditions, based on the value of the objective function and the preset objective priority, an electromagnetic design scheme that is suitable for the current operating condition is extracted from the electromagnetic design scheme as the objective scheme.

[0029] Secondly, this application provides a low-vibration-noise optimization device for a drive motor, the device comprising:

[0030] The acquisition module is used to acquire the structural parameters and geometric features of the motor.

[0031] The modeling module is used to perform structural parametric modeling of the motor based on the structural parameters and geometric features to obtain an electromagnetic simulation model of the motor.

[0032] The configuration module is used to set constraints based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, and to establish an objective function with the motor's order torque fluctuation, rotor radial electromagnetic force in each segment, rotor torque fluctuation in each segment, composite torque fluctuation, and the degree of matching between the composite radial electromagnetic force density and the composite torque fluctuation as the optimization target.

[0033] The calculation module is used to set multiple candidate electromagnetic design schemes, and for each electromagnetic design scheme, calculate the value of the objective function of the motor electromagnetic simulation model under different working conditions and corresponding constraints.

[0034] The determination module is used to determine the target scheme from multiple electromagnetic design schemes based on the value of the objective function, and to optimize the structural parameters of the drive motor based on the target scheme.

[0035] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0036] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0037] The aforementioned low-noise optimization method, computer equipment, and storage medium for drive motors utilize structural parameterization modeling by extracting structural parameters and geometric features of the motor. Constraints are set based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate. An objective function is established based on the motor's order torque fluctuation, radial electromagnetic force in each rotor segment, torque fluctuation in each rotor segment, combined torque fluctuation, and the matching degree between the combined radial electromagnetic force density and the combined torque fluctuation. For each electromagnetic design scheme, the objective function value of the motor's electromagnetic simulation model under corresponding constraints is calculated for different operating conditions. Based on the objective function value, the target scheme is selected. This method combines electromagnetic NVH (noise, vibration, and harshness) analysis with performance analysis, reasonably setting multiple objectives for key indicators in NVH and performance analysis. This achieves global and effective optimization of the motor's stator and rotor structure, thereby realizing the electromagnetic scheme design with optimal NVH performance under multi-dimensional constraints. Furthermore, this application allows for optimization of the motor's electromagnetic performance in the early stages of development, helping to shorten the development cycle and reduce development costs. Attached Figure Description

[0038] Figure 1 This is a hardware structure block diagram of the terminal of a low vibration and noise optimization method for a drive motor according to an embodiment of this application;

[0039] Figure 2 This is a flowchart illustrating a low-vibration-noise optimization method for a drive motor in one embodiment.

[0040] Figure 3 This is a flowchart illustrating the structural parametric modeling process in one embodiment;

[0041] Figure 4 This is a flowchart illustrating a low-vibration-noise optimization method for a drive motor in another embodiment;

[0042] Figure 5 This is a partial structural diagram of the electromagnetic simulation model of the motor in one embodiment. Figure 1 ;

[0043] Figure 6 This is a partial structural diagram of the electromagnetic simulation model of the motor in one embodiment. Figure 2 ;

[0044] Figure 7 This is a structural block diagram of a low-vibration-noise optimization device for a drive motor in one embodiment;

[0045] Figure 8 This is a schematic diagram of the internal structure of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these” used in this application do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to these processes, methods, products, or devices. Words such as “connected,” “linked,” and “coupled” used in this application are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. Normally, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," "third," etc., used in this application are merely to distinguish similar objects and do not represent a specific order of objects.

[0048] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. For example, it can run on a terminal. Figure 1 This is a hardware structure block diagram of the terminal of a low-vibration noise optimization method for a drive motor according to an embodiment of this application. For example... Figure 1 As shown, a terminal may include one or more ( Figure 1Only one is shown in the diagram. A processor 101 and a memory 102 for storing data are also included. The processor 101 may be, but is not limited to, a microprocessor (MCU) or a programmable logic device (FPGA). The terminal may also include a transmission device 103 for communication functions and an input / output device 104. Those skilled in the art will understand that… Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown are illustrated.

[0049] The memory 102 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the low-noise optimization method for the drive motor in this embodiment. The processor 101 executes various functional applications and data processing by running the computer program stored in the memory 102, thereby implementing the above-described method. The memory 102 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 102 may further include memory remotely located relative to the processor 101, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0050] The transmission device 103 is used to receive or send data via a network. This network includes a wireless network provided by the terminal's communication provider. In one example, the transmission device 103 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 103 can be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0051] The design of motor electromagnetic schemes involves many dimensions. Traditional single-objective optimization processes for motors struggle to consider multiple important indicators during the optimization process, often resulting in suboptimal electromagnetic designs. Specifically, traditional low-vibration-noise optimization methods for motors have the following drawbacks:

[0052] (1) For the parametric modeling of motor geometry topology, only the shape change of motor geometry topology caused by the change of individual size parameters is considered, without considering the influence of the interrelationship between size parameters on motor NVH and performance design parameters;

[0053] (2) For the objective function of multi-objective optimization of motor, only the impact of parameter changes on a single objective is considered, without considering the impact of parameter changes on other key performance parameters;

[0054] (3) Simply examining the total electromagnetic force density and total torque fluctuations cannot avoid the motor's NVH problems;

[0055] (4) It is not possible to quickly and accurately optimize the NVH performance of the motor.

[0056] In one embodiment, such as Figure 2 The diagram shows a flowchart of a low-vibration-noise optimization method for a drive motor, which is then applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0057] Step S101: Obtain the structural parameters and geometric features of the motor;

[0058] The structural parameters include rotor skew angle, stator slot size, rotor slot opening position, rotor slot size, magnet size, magnet position and magnet angle. The geometric features include the rotor structure and stator structure of the motor.

[0059] The skew angle of a rotor is the angle between different segments of the rotor. The skew angle affects the interaction between the rotor and the stator, which in turn affects vibration and noise (referred to as "vibration noise"). Optimizing the skew angle can reduce electromagnetic vibration sources.

[0060] Stator slot dimensions, including the width, depth, and shape (such as circular, rectangular, or other special shapes), can reduce vibrations caused by electromagnetic forces by optimizing the stator slot dimensions.

[0061] Rotor slot location refers to the distribution of rotor slots within the rotor. Rotor slot dimensions include the slot width, depth, and shape. The location and dimensions of the rotor slots affect the interaction between the rotor and stator, directly impacting the overall NVH performance of the motor through torque fluctuations and electromagnetic force density.

[0062] The dimensions of the magnets include their length, width, and thickness. The magnet position refers to their installation location within the rotor or stator. The magnet angle refers to the angle between the magnets. The dimensions, position, and angle of the magnets affect the magnetic field distribution and electromagnetic performance of the motor, thus influencing its vibration and noise characteristics.

[0063] In this embodiment, by obtaining the above-mentioned structural parameters and geometric features, necessary data support is provided for the subsequent modeling, analysis and optimization process.

[0064] Step S102: Based on the structural parameters and geometric features, perform structural parameterization modeling of the motor to obtain the electromagnetic simulation model of the motor.

[0065] In this step, a geometric model including the rotor and stator structures can be constructed based on the geometric features, and corresponding material properties can be configured for the geometric model. Variable parameters of the geometric model are defined based on structural parameters, and variable names, default values, and value ranges are configured for each variable parameter. Through structural parametric modeling, the structural parameters and geometric features of the motor are transformed into variable parameters, allowing for flexible adjustment during simulation and optimization. For example, the following embodiment provides a specific process for structural parametric modeling:

[0066] Step 1, Determine the parameterized objects: Based on the structural parameters and geometric features obtained in step S101, determine the key components that need to be parameterized. Select professional modeling software suitable for motor electromagnetic simulation, ensuring that the tool supports parametric modeling and simulation functions.

[0067] Step 2, Construct a parametric model: Based on the geometric features, use modeling software to construct a 3D or 2D geometric model of the motor. Define key structural parameters as variable parameters to ensure that the geometric model can automatically update according to changes in these variable parameters. Key structural parameters can include rotor skew angle, stator slot dimensions, magnet dimensions, etc.

[0068] Step 3, Parametric settings: In the modeling software, set the variable name, default value, and value range for each variable parameter.

[0069] Step 4, Material Property Settings: Assign corresponding material properties to the materials (such as electromagnets, copper, magnets, etc.) of the rotor and stator structures.

[0070] Step S103: Based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, set constraints, and establish an objective function with the motor's order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between composite radial electromagnetic force density and composite torque fluctuation as the optimization objectives.

[0071] Regarding the constraints, the minimum allowable value of the motor peak torque, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate can be set separately, and these minimum allowable values ​​of the motor peak torque, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate can be used as constraints.

[0072] Motor peak torque constraint: By setting a minimum allowable value for the motor peak torque, we ensure that the motor peak torque will not fall below the minimum requirement value during the optimization process, and ultimately ensure that the motor peak torque meets the design requirements.

[0073] Cogging torque constraint: By setting the maximum allowable value of cogging torque, the design is optimized to reduce cogging torque, thereby reducing motor vibration and noise.

[0074] Back EMF harmonic distortion rate: By setting the maximum allowable value of the back EMF harmonic distortion rate, the design is optimized to reduce the harmonic distortion rate.

[0075] By setting corresponding constraints for each key performance indicator, we can ensure that the optimized design meets performance requirements and manufacturing feasibility.

[0076] Regarding the objective function, the following are the optimization objectives: motor order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the matching degree between composite radial electromagnetic force density and composite torque fluctuation. Target optimization percentage parameters are set for each of these objectives. For different operating conditions, corresponding weight coefficients are assigned to each target optimization percentage parameter. The objective functions for different operating conditions are obtained by fusing the target optimization percentage parameters according to the weight coefficients. The formula for calculating the objective function is as follows:

[0077] F=W1×A+W2×B+W3×C+W4×D+W5×E;

[0078] Where W1, W2, W3, W4, and W5 are weighting coefficients, and A, B, C, D, and E are objective optimization percentage parameters. The objective optimization percentage parameters can be solved through electromagnetic simulation, and then the objective optimization percentage parameters are substituted into the objective function to obtain the value of the objective function.

[0079] Here, different optimization percentage parameters refer to the degree to which the target value is optimized from its initial value to a set first threshold, for example: Where A0 is the initial value of the target to be optimized, and At is the first threshold.

[0080] Different operating conditions can refer to different motor speeds, and the weighting coefficients will differ for each condition. Considering the varying degrees of importance placed on each optimization objective under different operating conditions, the weighting coefficients for each objective are assigned differently. Under a given condition, the objective with the greater influence receives a larger weight. This arrangement allows for a balance between conflicting optimization objectives through weighting coefficients, improving the model's simulation results' relevance to actual operating conditions. For example, in a transmission project, the motor's order torque fluctuation is Q1 under the first operating condition and Q2 under the second. Neither of these indicators meets the requirements. However, since the first operating condition is frequently used and the second is rarely used, the weighting coefficient for the motor's order torque fluctuation is set relatively large under the first condition and relatively small under the second condition.

[0081] The specific objectives to be optimized are described below:

[0082] Motor order torque ripple: used to reflect the smoothness of motor torque; lower torque ripple corresponds to smoother operation.

[0083] Radial electromagnetic force in each section of the rotor: affects the vibration and noise of the motor. By optimizing the distribution of radial electromagnetic force in each section of the rotor, vibration and noise can be reduced.

[0084] Torque fluctuations in different sections of the rotor are closely related to the smoothness of motor operation.

[0085] Synthetic torque fluctuation: obtained by synthesizing the torque fluctuation of each segment of the rotor.

[0086] The degree of matching between the synthetic radial electromagnetic force density and the synthetic torque fluctuation: This comprehensively reflects the force and torque characteristics of the motor. By optimizing the matching relationship between the synthetic radial electromagnetic force density and the synthetic torque fluctuation, vibration and noise can be reduced.

[0087] In some cases, certain performance indicators can interact due to the motor's structure. For example, optimizing the radial electromagnetic force requires increasing the depth or width of the slots on the rotor surface, but larger rotor slots can lead to a decrease in motor torque. Therefore, this embodiment considers the interdependent performance indicators and treats them as optimization targets.

[0088] Step S104: Set up multiple candidate electromagnetic design schemes, and for each electromagnetic design scheme, calculate the objective function value of the motor electromagnetic simulation model under different working conditions and corresponding constraints.

[0089] Electromagnetic design scheme refers to the parameter configuration and structural layout scheme of the electromagnetic part in the drive motor, including stator / rotor slot shape, winding distribution, and magnetic circuit design.

[0090] In this step, based on each candidate electromagnetic design scheme, the motor electromagnetic simulation model is simulated under different operating conditions to calculate the value of the objective function under the corresponding constraints. Then, for a specific operating condition, one of the electromagnetic design schemes is selected as the objective scheme for that condition.

[0091] Furthermore, it can be determined whether the value of the objective function meets the preset optimization objective; if it is determined that the value of the objective function does not meet the optimization objective, the variable parameters of the motor electromagnetic simulation model are adjusted, and the simulation calculation is performed again until the value of the objective function meets the optimization objective.

[0092] Step S105: Determine the target scheme from multiple electromagnetic design schemes based on the value of the objective function, and optimize the structural parameters of the drive motor based on the target scheme.

[0093] Suppose that under a certain operating condition, model simulations of three electromagnetic design schemes were performed, and the values ​​of the three objective functions were obtained, as follows:

[0094] Electromagnetic design scheme 1: F1 = W1 × A1 + W2 × B1 + W3 × C1 + W4 × D1 + W5 × E1;

[0095] Electromagnetic design scheme 2: F2 = W1×A2 + W2×B2 + W3×C2 + W4×D2 + W5×E2;

[0096] Electromagnetic design scheme 3: F3 = W1×A3 + W2×B3 + W3×C3 + W4×D3 + W5×E3.

[0097] In some embodiments, the maximum value (F1, F2, F3) of the objective function of the electromagnetic design scheme can be directly taken, and the electromagnetic design scheme corresponding to the maximum value can be taken as the objective scheme.

[0098] In other embodiments, the target to be optimized corresponding to the highest target priority is first determined under this operating condition. Generally, the higher the weight coefficient, the higher the target priority. Assuming that W1, W2, W3, W4, and W5 decrease sequentially, the target to be optimized corresponding to the highest target priority is the target corresponding to A. The optimization percentage parameters A1, A2, and A3 of each target are compared with a set second threshold. Electromagnetic design schemes with parameters lower than the second threshold are filtered out. The maximum value of the objective function of the remaining electromagnetic design schemes is taken, and the electromagnetic design scheme corresponding to the maximum value is taken as the target scheme. Compared with the above method of directly finding the optimal solution through target priority in the objective function value of the electromagnetic design scheme, this method is more suitable for actual operating conditions.

[0099] Furthermore, all electromagnetic design schemes and their corresponding objective function values ​​can be compiled into a database or table for subsequent analysis and comparison. After selecting the optimal scheme, the NVH indicators should be verified to ensure they meet the requirements. Through these steps, a target scheme can be extracted from multiple electromagnetic design schemes, and its NVH performance can be evaluated to ensure it meets the preset requirements, thereby improving the NVH performance of the motor.

[0100] Traditional electromagnetic excitation source optimization methods, when designing electromagnetic excitation sources for motors, typically only use the relevant parameters affecting the total electromagnetic excitation as a single objective function, neglecting the impact on other performance aspects of the electromagnetic scheme after satisfying this objective.

[0101] In steps S101 to S105 above, structural parameterization modeling is performed by extracting the structural parameters and geometric features of the motor. Constraints are set based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate. An objective function is set based on the motor's order torque fluctuation, radial electromagnetic force in each rotor segment, torque fluctuation in each rotor segment, combined torque fluctuation, and the matching degree between the combined radial electromagnetic force density and the combined torque fluctuation. For each electromagnetic design scheme, the value of the objective function of the motor's electromagnetic simulation model under corresponding constraints is calculated for different operating conditions. Based on the value of the objective function, the target scheme is selected. The electromagnetic NVH (noise, vibration, and harshness) analysis of the motor is combined with performance analysis. Reasonable multi-objective settings are made for key indicators in NVH and performance analysis, achieving global and effective optimization of the motor's stator and rotor structure. This results in an electromagnetic scheme design with optimal NVH performance under multi-dimensional constraints. Moreover, this embodiment allows for optimization of the motor's electromagnetic performance in the early stages of development, helping to shorten the development cycle and reduce development costs.

[0102] In one embodiment, after step S102 above, an initial electromagnetic simulation model of the motor can be constructed according to the set structural parameters, and the initial electromagnetic simulation model of the motor can be simulated to obtain simulated motor performance data; the simulated motor performance data can be compared with the actual motor performance data; if there is a deviation between the simulated motor performance data and the actual motor performance data or the deviation is outside the preset range, the material properties and / or variable parameters can be adjusted so that there is no deviation between the simulated motor performance data and the actual motor performance data or the deviation is within the preset range.

[0103] In this embodiment, an initial electromagnetic simulation model of the motor can be constructed using known structural parameters, and simulation calculations can be performed to obtain simulated motor performance data including electromotive force, torque, and efficiency. The simulated motor performance data is then compared with the actual motor performance data to verify the accuracy of the model. If there is a deviation in the comparison results or the deviation is outside the preset range, the parameter settings and material properties are checked, and the deviation is reduced by adjusting the material properties and / or variable parameters. If there is no deviation between the simulated motor performance data and the actual motor performance data, or the deviation is within the preset range, the model is validated, and the final electromagnetic simulation model of the motor is obtained.

[0104] For example, Figure 3 A flowchart illustrating the structural parametric modeling process in this embodiment is provided, such as... Figure 3 As shown, the process includes the following steps:

[0105] Step S201, Determine the parameterized objects: Based on structural parameters and geometric features, determine the key components that need to be parameterized. Select professional modeling software suitable for motor electromagnetic simulation, ensuring that the tool supports parametric modeling and simulation functions.

[0106] Step S202, Construct a parametric model: Based on the geometric features, construct a three-dimensional or two-dimensional geometric model of the motor using modeling software. Define key structural parameters as variable parameters to ensure that the geometric model can automatically update according to changes in the variable parameters. Key structural parameters may include rotor skew angle, stator slot dimensions, magnet dimensions, etc.

[0107] Step S203, Parametric settings: In the modeling software, set the variable name, default value, and value range for each variable parameter.

[0108] Step S204, Material property setting: Assign corresponding material properties to the materials (such as electromagnets, copper, magnets, etc.) of the rotor and stator structures.

[0109] Step S205, Model Verification: Construct an initial model using known parameters and perform simulation calculations. Compare the simulated motor performance data with the actual motor performance data; if there is a deviation between the simulated and actual motor performance data, or if the deviation is outside the preset range, adjust the material properties and / or variable parameters to ensure that the simulated and actual motor performance data have no deviation or that the deviation is within the preset range.

[0110] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0111] In one embodiment, Figure 4 A flowchart illustrating another method for optimizing low vibration and noise in drive motors is provided, such as... Figure 4 As shown, the process includes the following steps:

[0112] Step S301: Obtain the structural parameters and geometric features of the motor.

[0113] Structural parameters include rotor skew angle, stator slot size, rotor slot opening position, rotor slot size, magnet size, magnet position and magnet angle. Geometric features include the rotor structure and stator structure of the motor.

[0114] Figure 5 This is a partial structural diagram of the electromagnetic simulation model of the motor in this embodiment. Figure 1 ,like Figure 5 As shown, the electromagnetic simulation model of this motor includes multiple parameters. Parameters ① to ⑦ together constitute the complete geometric characteristics of a set of magnets and magnet slots. Parameters ⑧ to ⑩ together constitute a pair of auxiliary slots. Through the combined effect of parameters ⑧, ⑨, and ⑩, the position and dimensional characteristics of a pair of auxiliary slots can be completely determined. The specific explanations of each parameter are as follows:

[0115] ① represents the polar angle parameter between the line connecting the center point of the magnet and the origin and the x-axis; ② represents the radial distance parameter between the center point of the magnet and the origin. The Cartesian coordinate system position of the center point of the magnet can be determined using parameters ① and ②.

[0116] ③ is the angle parameter of the magnet. The installation direction of the magnet can be determined by the included angle between two adjacent magnets.

[0117] ④ and ⑤ are the dimensional parameters of the magnet, used to control the thickness and length characteristics of the magnet, respectively;

[0118] ⑥ and ⑦ are the thickness parameters of the magnetic bridge. The geometric position of the magnetic steel groove can be located through ⑥ and ⑦.

[0119] ⑧ is the polar angle parameter between the line connecting the center point of the auxiliary groove and the origin and the x-axis, which can be used to determine the position of the auxiliary groove;

[0120] ⑨ and ⑩ are the dimensional parameters of the auxiliary groove, representing the width and depth characteristics of the auxiliary groove, respectively, and are used to define the geometry of the auxiliary groove.

[0121] Figure 6 This is a partial structural diagram of the electromagnetic simulation model of the motor in this embodiment. Figure 2 ,like Figure 6 As shown in the figure, the rotor skew stage angle parameter settings are illustrated. The motor rotor structure includes optimization a1 for the number of skew stage segments (arbitrary from 1 to 8 segments) and optimization a2 for the skew stage angle.

[0122] Step S302: Establish the electromagnetic simulation model of the motor.

[0123] Establish electromagnetic simulation models of motors under multiple operating conditions, parameterize the electromagnetic scheme of the assembly, and set constraints and output objective function files.

[0124] Step S303: Set up the electromagnetic simulation model execution script.

[0125] Set up script files for running the electromagnetic simulation model of the motor under different operating conditions, including setting optimization variables, submitting the model for calculation and constraint conditions, and post-processing the objective function result file.

[0126] Step S304: Establish a multi-objective optimization workflow.

[0127] Integrate the electromagnetic simulation model of the motor built in step S302 and the script file in step S303 into the workflow.

[0128] Step S305: Define the optimization variables, constraints, and objective function.

[0129] The value ranges of the corresponding optimization variables and constraints are set, and the objective function is defined. Specifically, the constraints are set based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate. The objective function is established with the motor's order torque fluctuation, the radial electromagnetic force of each rotor segment, the torque fluctuation of each rotor segment, the combined torque fluctuation, and the degree of matching between the combined radial electromagnetic force density and the combined torque fluctuation as the optimization objectives.

[0130] Step S306: Define the optimization space and set the optimization target.

[0131] The Design of Experiments (DOE) calculation for a multi-objective optimization model is performed based on the Latin hypercube sampling method. Within the design boundary, a multi-objective genetic algorithm (NSEA+) is used for optimization based on the response surface model to obtain the global multi-objective optimal solution that satisfies the constraints under the response surface model, thus confirming the optimal electromagnetic design scheme.

[0132] Step S307: Substitute the optimal solution value of the response surface obtained in step S306 into the actual workflow for verification to confirm the model accuracy and optimization effect.

[0133] In this embodiment, by defining the rotor in multiple segments, the electromagnetic scheme with good NVH (noise, vibration, and harshness) performance can be more accurately and specifically optimized during the motor design and optimization process. A genetic algorithm is used to achieve effective optimization in the global range, thereby achieving the design of an electromagnetic scheme with optimal NVH performance under multi-dimensional constraints.

[0134] In one embodiment, based on the same inventive concept as the method described above, a low-vibration noise optimization device for a drive motor is also provided in this embodiment. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. The terms "module," "unit," "subunit," etc., used below can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0135] Figure 7 This embodiment provides a low-vibration and noise optimization device for the drive motor, such as... Figure 7 As shown, the device includes:

[0136] The acquisition module is used to acquire the structural parameters and geometric features of the motor. The structural parameters include the rotor skew angle, stator slot size, rotor slot opening position, rotor slot size, magnet size, magnet position, and magnet angle. The geometric features include the rotor structure and stator structure of the motor.

[0137] The modeling module is used to perform structural parametric modeling of the motor based on structural parameters and geometric features, and obtain the electromagnetic simulation model of the motor.

[0138] The configuration module is used to set constraints based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, and to establish an objective function with the motor's order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between composite radial electromagnetic force density and composite torque fluctuation as the optimization targets.

[0139] The calculation module is used to set multiple candidate electromagnetic design schemes, and for each electromagnetic design scheme, calculate the value of the objective function of the motor electromagnetic simulation model under different working conditions and corresponding constraints.

[0140] The determination module is used to determine the target scheme from multiple electromagnetic design schemes based on the value of the objective function, and to optimize the structural parameters of the drive motor based on the target scheme.

[0141] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0142] Furthermore, in conjunction with the low-noise optimization method for the drive motor provided in the above embodiments, this embodiment can also provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any of the low-noise optimization methods for the drive motor described in the above embodiments.

[0143] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0144] Obtain the structural parameters and geometric features of the motor; the structural parameters include the rotor skew angle, stator slot size, rotor slot opening position, rotor slot size, magnet size, magnet position and magnet angle, and the geometric features include the rotor structure and stator structure of the motor;

[0145] Based on the structural parameters and geometric features, the motor is modeled using structural parameterization to obtain the electromagnetic simulation model of the motor.

[0146] Based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, constraints are set, and the motor's order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between composite radial electromagnetic force density and composite torque fluctuation are used as optimization objectives to establish an objective function.

[0147] Multiple candidate electromagnetic design schemes are set up, and for each electromagnetic design scheme, the objective function of the motor electromagnetic simulation model under different working conditions and corresponding constraints is calculated.

[0148] Based on the value of the objective function, the target scheme is determined from multiple electromagnetic design schemes, and the structural parameters of the drive motor are optimized based on the target scheme.

[0149] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0150] A geometric model containing rotor and stator structures is constructed based on geometric features, and corresponding material properties are configured for the geometric model.

[0151] The variable parameters of the geometric model are defined based on the structural parameters, and the variable name, default value and value range are configured for each variable parameter.

[0152] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0153] An initial electromagnetic simulation model of the motor is constructed based on the set structural parameters, and simulation calculations are performed on the initial electromagnetic simulation model of the motor to obtain simulated motor performance data.

[0154] Compare simulated motor performance data with actual motor performance data;

[0155] If the simulated motor performance data deviates from the actual motor performance data or the deviation is outside the preset range, the material properties and / or variable parameters are adjusted to ensure that the simulated motor performance data does not deviate from the actual motor performance data or the deviation is within the preset range.

[0156] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0157] Set the minimum allowable value of the motor peak torque, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate, and use these values ​​as constraints.

[0158] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0159] Set the target optimization percentage parameter for each target to be optimized;

[0160] For different working conditions, corresponding weight coefficients are assigned to the percentage parameters of each objective optimization. Based on the weight coefficients, the percentage parameters of each objective optimization are integrated to obtain the objective function corresponding to different working conditions.

[0161] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0162] Determine whether the value of the objective function meets the preset optimization objective;

[0163] If the value of the objective function does not meet the optimization objective, the variable parameters of the motor electromagnetic simulation model are adjusted, and the simulation calculation is repeated until the value of the objective function meets the optimization objective.

[0164] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0165] Obtain the electromagnetic design schemes and their corresponding objective function values ​​under different operating conditions through simulation;

[0166] For each working condition, based on the value of the objective function and the preset objective priority, an electromagnetic design scheme that is suitable for the current working condition is extracted from the electromagnetic design schemes as the objective scheme.

[0167] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 8 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a low-noise optimization method for driving a motor. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0168] Those skilled in the art will understand that Figure 8The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0169] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0170] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0171] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0172] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for optimizing the vibration and noise of a drive motor, characterized in that, include: Obtain the structural parameters and geometric characteristics of the motor; Based on the structural parameters and geometric features, the motor is structurally parametrically modeled to obtain an electromagnetic simulation model of the motor. Based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, constraints are set, and the motor order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between the composite radial electromagnetic force density and the composite torque fluctuation are used as optimization targets to establish an objective function. Multiple candidate electromagnetic design schemes are set up, and for each electromagnetic design scheme, the objective function of the motor electromagnetic simulation model under different working conditions is calculated under the corresponding constraints. Based on the value of the objective function, a target scheme is determined from multiple electromagnetic design schemes, and the structural parameters of the drive motor are optimized based on the target scheme.

2. The low vibration and noise optimization method for the drive motor according to claim 1, characterized in that, Based on the structural parameters and geometric features, the motor is structurally parametrically modeled to obtain an electromagnetic simulation model of the motor, including: Based on the geometric features, a geometric model including a rotor structure and a stator structure is constructed, and corresponding material properties are configured for the geometric model. The variable parameters of the geometric model are defined based on the structural parameters, and a variable name, default value, and value range are configured for each variable parameter.

3. The low vibration and noise optimization method for the drive motor according to claim 2, characterized in that, After defining the variable parameters of the geometric model based on the structural parameters, and configuring variable names, default values, and value ranges for each variable parameter, the method further includes: An initial electromagnetic simulation model of the motor is constructed based on the set structural parameters, and simulation calculations are performed on the initial electromagnetic simulation model of the motor to obtain simulated motor performance data. Compare the simulated motor performance data with the actual motor performance data; If the simulated motor performance data deviates from the actual motor performance data or the deviation is outside a preset range, the material properties and / or variable parameters are adjusted so that the simulated motor performance data does not deviate from the actual motor performance data or the deviation is within a preset range.

4. The low vibration and noise optimization method for the drive motor according to claim 1, characterized in that, Based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, constraints are set, including: The minimum allowable value of the peak torque of the motor, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate are set respectively, and the minimum allowable value of the peak torque of the motor, the maximum allowable value of the cogging torque, and the maximum allowable value of the back EMF harmonic distortion rate are used as the constraint conditions.

5. The low vibration and noise optimization method for the drive motor according to claim 1, characterized in that, The objective function is established using the motor order torque fluctuation, radial electromagnetic force of each rotor segment, torque fluctuation of each rotor segment, composite torque fluctuation, and the degree of matching between the composite radial electromagnetic force density and the composite torque fluctuation as optimization targets. This includes: Set the target optimization percentage parameter corresponding to each of the aforementioned targets to be optimized; For different working conditions, corresponding weight coefficients are assigned to each of the target optimization percentage parameters. Based on the weight coefficients, the target optimization percentage parameters are fused to obtain the objective function corresponding to different working conditions.

6. The low vibration and noise optimization method for the drive motor according to claim 1, characterized in that, After setting up multiple candidate electromagnetic design schemes, and calculating the objective function values ​​of the motor electromagnetic simulation model under different operating conditions and corresponding constraints for each electromagnetic design scheme, the method further includes: Determine whether the value of the objective function satisfies the preset optimization objective; If it is determined that the value of the objective function does not meet the optimization objective, the variable parameters of the motor electromagnetic simulation model are adjusted, and the simulation calculation is performed again until the value of the objective function meets the optimization objective.

7. The low vibration and noise optimization method for the drive motor according to claim 1, characterized in that, Determining the target scheme from multiple electromagnetic design schemes based on the value of the objective function includes: Obtain the electromagnetic design schemes and their corresponding objective function values ​​under different operating conditions through simulation; For each of the aforementioned operating conditions, based on the value of the objective function and the preset objective priority, an electromagnetic design scheme that is suitable for the current operating condition is extracted from the electromagnetic design scheme as the objective scheme.

8. A low-vibration and noise optimization device for a drive motor, characterized in that, The device includes: The acquisition module is used to acquire the structural parameters and geometric features of the motor. The modeling module is used to perform structural parametric modeling of the motor based on the structural parameters and geometric features to obtain an electromagnetic simulation model of the motor. The configuration module is used to set constraints based on the motor's peak torque, cogging torque, and back EMF harmonic distortion rate, and to establish an objective function with the motor's order torque fluctuation, rotor radial electromagnetic force in each segment, rotor torque fluctuation in each segment, composite torque fluctuation, and the degree of matching between the composite radial electromagnetic force density and the composite torque fluctuation as the optimization target. The calculation module is used to set multiple candidate electromagnetic design schemes, and for each electromagnetic design scheme, calculate the value of the objective function of the motor electromagnetic simulation model under different working conditions and corresponding constraints. The determination module is used to determine the target scheme from multiple electromagnetic design schemes based on the value of the objective function, and to optimize the structural parameters of the drive motor based on the target scheme.

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

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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