A low-noise motor optimization method for vehicles based on multi-parameter variable fusion

Abstract

The application provides a low-noise motor optimization method based on multi-parameter variable fusion, and the specific process is as follows: taking motor back electromotive force variation and minimum slot torque as an optimization objective function; taking motor rotor magnetic pole circular arc wrap angle as an optimization variable, and multiple iterations of the magnetic pole circular arc wrap angle are carried out in a set range, the magnetic pole circular arc wrap angle corresponding to the minimum objective function is taken as an optimal parameter of the motor, and low-noise motor optimization is realized; the magnetic pole circular arc wrap angle is proportional to the magnetic pole circular arc length. In the method, the magnetic pole circular arc wrap angle is taken as an optimization object, and the optimization design can be quickly and effectively completed, and the low-noise motor for vehicles can be developed.

Description

Technical Field

[0001] This invention belongs to the field of low vibration and noise motor optimization design technology for passenger vehicles, and specifically relates to a low noise vehicle motor optimization method based on multi-parameter variable fusion. Background Technology

[0002] The noise generated by the motors of new energy vehicles during operation is a superposition of aerodynamic noise, electromagnetic noise, and mechanical noise, with electromagnetic noise accounting for a significant portion. Currently, the noise control effect of permanent magnet synchronous motors is not effective. The main reason for this is that motor manufacturers and automobile manufacturers have not adopted appropriate vibration and noise control methods and means, and have not taken effective optimization design methods for the main noise source of the motor—electromagnetic noise. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and to solve the problem of excessive electromagnetic excitation vibration and noise in motors. It proposes a low-noise automotive motor optimization method based on multi-parameter variable fusion. By using this method to optimize the key parameters of the motor, the electromagnetic excitation vibration and noise of the motor can be effectively reduced.

[0004] The technical solution for implementing the present invention is as follows:

[0005] A low-noise automotive motor optimization method based on multi-parameter variable fusion, the specific process of which is as follows:

[0006] Minimize the change in back electromotive force and cogging torque of the motor as the optimization objective function;

[0007] The magnetic pole arc wrap angle of the motor rotor is used as an optimization variable. The magnetic pole arc wrap angle is iterated multiple times within a set range. The magnetic pole arc wrap angle corresponding to the minimum objective function is taken as the optimal parameter of the motor to achieve optimization of low-noise automotive motors. The magnetic pole arc wrap angle is proportional to the magnetic pole arc length.

[0008] Furthermore, the radius of curvature of the rotor magnetic poles of the motor described in this invention is:

[0009]

[0010] Where, α i The radius of the magnetic pole circle is i = 1, 2, ..., p, where p is the number of pole pairs; R is the rotor radius; e is the pole eccentricity; S i It represents the length of the magnetic pole arc.

[0011] Furthermore, when optimizing the magnetic pole arc encirclement angle, the present invention needs to satisfy the following optimization conditions:

[0012]

[0013] Furthermore, the optimization variables described in this invention also include the permanent magnet slot width and the permanent magnet thickness.

[0014] Furthermore, the constraints described in this invention also include:

[0015]

[0016] Where ΔP is the variation in the rated power of the motor; b c0 and Δb C These are the reference values ​​for the permanent magnet slot width and their variations; b T0 and Δb T These are the reference values ​​for the thickness of the permanent magnet and their variations.

[0017] Furthermore, the objective function of this invention is:

[0018] Objective function:

[0019] Min Z=ηΔe+ζT (2)

[0020] Where Δe is the change in back EMF of the motor, T is the cogging torque, and η and ζ are the weighting coefficients for the change in back EMF and the cogging torque of the motor, respectively.

[0021] Beneficial effects

[0022] First, since the magnetic pole arc wrap angle, which is proportional to the length of the magnetic pole arc, can greatly affect the noise of the vehicle motor, the method of this invention sets it as the optimization object, which can quickly and effectively complete the optimization design and develop a low-noise vehicle motor.

[0023] Second, the method of the present invention optimizes the length of the magnetic pole arc within a certain feasible constraint range, ensuring that the optimization result can meet the actual needs of motor design.

[0024] Third, the method of the present invention further incorporates the permanent magnet slot width and permanent magnet thickness as optimization variables and sets optimization conditions for these optimization variables. The inclusion of the parameters affecting the noise of the vehicle motor as optimization variables can effectively reduce the noise of the vehicle motor.

[0025] Fourth, the objective function designed in the method of the present invention is equipped with weighting coefficients. By adjusting the size of the weighting coefficients, the focus of optimization in the objective function can be adjusted. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the circular arc encirclement angle of the motor rotor magnetic poles according to an embodiment of the present invention;

[0027] Figure 2 A parametric electromagnetic model of a permanent magnet synchronous motor;

[0028] Figure 3 Finite element mesh generation for electromagnetics of electric motors;

[0029] Figure 4 A design process for optimizing low-noise motors based on multi-parameter variable fusion;

[0030] Figure 5 Comparison of vibration acceleration test results for the original motor and the developed low-noise motor;

[0031] Figure 6 Comparison of A-weighted sound pressure level test results for the original motor and the developed low-noise motor;

[0032] Among them, 1-stator core; 2-armature winding; 3-line permanent magnet; 4-V-shaped permanent magnet; 5-rotor core. Detailed Implementation

[0033] The embodiments of the method of the present invention will be described in detail below with reference to the accompanying drawings.

[0034] It should be noted that, in the absence of conflict, the following embodiments and features can be combined with each other; and, based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0035] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using other structures and / or functionalities besides one or more of the aspects set forth herein.

[0036] This application provides a low-noise automotive motor optimization method based on multi-parameter variable fusion, the specific process of which is as follows:

[0037] Minimize the change in back electromotive force and cogging torque of the motor as the optimization objective function;

[0038] The magnetic pole arc wrap angle of the motor rotor is used as an optimization variable. The magnetic pole arc wrap angle is iterated multiple times within a set range. The magnetic pole arc wrap angle corresponding to the minimum objective function is taken as the optimal parameter of the motor to achieve optimization of low-noise automotive motors. The magnetic pole arc wrap angle is proportional to the magnetic pole arc length.

[0039] In this embodiment, the applicant discovered through numerous experiments that parameters such as the length of the magnetic pole arc can greatly affect the noise of the vehicle motor. Therefore, a magnetic pole arc wrap angle proportional to the length of the magnetic pole arc was defined and used as the optimization object, which can quickly and effectively complete the optimization design.

[0040] In another embodiment of this application, the radius of curvature of the motor rotor magnetic poles is determined as follows:

[0041]

[0042] Where, α i The radius of the magnetic pole circle is i = 1, 2, ..., p, where p is the number of pole pairs; R is the rotor radius; e is the pole eccentricity; S i It represents the length of the magnetic pole arc.

[0043] In this embodiment of the application, based on the fact that the magnetic pole arc wrap angle of the motor rotor is proportional to the magnetic pole arc length, it is further constrained to be inversely proportional to (Re). Through a large number of experiments, it was found that the magnetic pole arc wrap angle determined according to formula (1) is strongly correlated with the motor noise. Therefore, by optimizing the magnetic pole arc wrap angle in formula (1), the motor optimization can be completed quickly and effectively.

[0044] In another embodiment of this application, when optimizing the magnetic pole arc wrap angle, the following optimization conditions need to be met:

[0045]

[0046] The embodiments of this application optimize the length of the magnetic pole arc within certain feasible constraints, ensuring that the optimization result can meet the actual needs of motor design.

[0047] In another embodiment of this application, the optimization variables also include the permanent magnet slot width and the permanent magnet thickness.

[0048] In this embodiment, in addition to using the original magnetic pole arc wrap angle as an optimization variable, the permanent magnet slot width and permanent magnet thickness, which have a significant impact on motor noise, are further used as optimization variables. Through optimized design, the noise of the motor can be effectively reduced.

[0049] In another embodiment of this application, the constraints also include:

[0050]

[0051] Where ΔP is the variation in the rated power of the motor; b c0 and Δb C These are the reference values ​​for the permanent magnet slot width and their variations; b T0 and Δb TThese are the reference values ​​for the thickness of the permanent magnet and their variations.

[0052] In this embodiment, when the two parameters of permanent magnet slot width and permanent magnet thickness are included as optimization variables, the change in the parameters between two consecutive iterations is used as a constraint condition to achieve parameter optimization.

[0053] In another embodiment of this application, the objective function is:

[0054] Objective function:

[0055] Min Z=ηΔe+ζT (2)

[0056] Where Δe is the change in back EMF of the motor, T is the cogging torque, and η and ζ are the weighting coefficients for the change in back EMF and the cogging torque of the motor, respectively.

[0057] In the embodiments of this application, weighting coefficients are designed on the objective function. By adjusting the size of the weighting coefficients, the focus of optimization in the objective function can be adjusted.

[0058] Based on the above embodiments of this application, such as Figure 4 As shown below, the optimization method for low-noise automotive motors based on multi-parameter variable fusion will be explained in detail:

[0059] Step 1: Input the initial parameters of the motor, including geometric parameters and material property parameters, so that the motor can be simulated in the relevant software.

[0060] Step 2: Divide the rotor into several equal parts according to the number of pole pairs p, such as... Figure 1 As shown (e - rotor pole eccentricity; b) T - Thickness of the permanent magnet; b C - Spat width of permanent magnet poles; S i - Length of the i-th magnetic pole arc); and calculate the rotor magnetic pole arc wrap angle according to the following formula:

[0061]

[0062] Where: α i The radius of the magnetic pole circle is i = 1, 2, ..., p, where p is the number of pole pairs; R is the rotor radius; e is the pole eccentricity; S i S1 represents the arc length of the magnetic poles, which is calculated based on the actual arc length corresponding to each pair of magnetic poles arranged along the rotor circumference. When the p pairs of magnetic poles of the motor are uniformly arranged along the rotor surface: S1 = S2 = S i =S p ,i=1,2,…,p;If for some reason the p pairs of magnetic poles of the motor are not uniformly arranged along the rotor surface: S1≠S2≠S i ≠Sp If i = 1, 2, ..., p, then we need to calculate p α values ​​according to formula (1). i .

[0063] Step 3: Use MAXWELL 2D software to build a parametric model of the motor, such as... Figure 2 As shown;

[0064] Step 4: Set the region for the parametric model of the motor and perform the corresponding finite element mesh generation, see [link to step 4]. Figure 3 ;

[0065] Step 5: Perform electromagnetic simulation of the motor using the MAXWEILL software module;

[0066] Step Six: Based on the research on the vibration and noise mechanism of the motor, parameters that significantly affect motor vibration and noise, such as the magnetic pole arc wrap angle, permanent magnet slot width, and permanent magnet thickness, are used as optimization variables. The objective function is to minimize the variation in motor back electromotive force Δe and cogging torque T. The optimization mathematical model is as follows:

[0067] Objective function:

[0068] Min Z=ηΔe+ζT (2)

[0069] Where: Δe is the change in back EMF of the motor, T is the cogging torque; η and ζ are the weighting coefficients for the change in back EMF and the cogging torque of the motor, respectively.

[0070] Constraints:

[0071]

[0072] Where ΔP is the variation in the rated power of the motor; b c0 and Δb c These are the reference values ​​for the permanent magnet slot width and their variations (the difference between two adjacent values); b T0 and Δb T These are the reference values ​​for the thickness of the permanent magnet and their variations; α i Let i be the arc of the magnetic pole, i = 1, 2, ..., p, where p is the number of magnetic pole pairs;

[0073] Step 7: Calculate the motor performance parameters using the corresponding modules of MAXWELL software, plot the corresponding curves, calculate the motor cogging torque T and the motor back electromotive force e, and calculate the variation Δe based on the motor back electromotive force.

[0074] Step 8: Combine the Latin hypersolution method with the second-order central composite algorithm, and solve the optimization model using the MATLAB software platform.

[0075] Step 9: If the accuracy of the solution meets the requirements, the calculation is considered converged; if the accuracy does not meet the requirements, the calculation is not converged. New variable parameters need to be selected, and steps 3 to 8 need to be repeated to start the next iteration calculation.

[0076] Step 10: After successfully solving the problem in the previous step, obtain the optimal solution and output the optimal parameters: magnetic pole arc encirclement angle α. i * Permanent magnet slot width b c * and the thickness b of the permanent magnet T * The design of a low-noise motor was completed.

[0077] Bench test:

[0078] The optimal parameter, magnetic pole arc encirclement angle α, obtained according to the embodiments of this application, will be used. i * Permanent magnet slot width b c * and the thickness b of the permanent magnet T * The designed finite element model of the motor was imported into ANSYS Workbench software, and the motor vibration harmonic response was calculated.

[0079] Then import the vibration response calculation results into LMS Virtual.Lab and use its corresponding modules to perform motor acoustic calculations;

[0080] Draw up the machining drawings for the low-noise motor and develop a prototype of the low-noise motor;

[0081] Conduct NVH verification tests on the motor bench.

[0082] Figure 5 This is a comparison of vibration test results between the original motor and the newly developed low-noise motor. Figure 6 This paper compares the noise test results of the original motor and the newly developed low-noise motor. The bench test results show that the new motor developed based on this invention patent has an average reduction of more than 27% in the effective value of vibration response under 34 driving conditions, and a reduction of more than 6 dBA in the A-weighted total sound pressure level.

[0083] Through the above effective research, the amplitude of higher harmonics in the radial force of the motor's electromagnetic field was reduced, and torque pulsation and cogging torque were weakened, thereby reducing motor vibration and noise and improving the NVH characteristics of new energy passenger vehicles. This completes / realizes the challenging task of optimizing the design and development of low-noise motors for vehicles based on multi-parameter variable fusion.

[0084] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A low-noise motor optimization method for vehicles based on multi-parameter variable fusion, characterized in that, The specific process is: Minimizing motor back electromotive force variation and cogging torque as an optimization objective function; Taking the motor rotor magnetic pole circular arc wrap angle as an optimization variable, the magnetic pole circular arc wrap angle is iterated multiple times in a set range, the magnetic pole circular arc wrap angle corresponding to the minimum target function is taken as an optimal parameter of the motor, and low-noise motor optimization for vehicles is realized; the magnetic pole circular arc wrap angle is proportional to the magnetic pole circular arc length; The motor rotor magnetic pole circular arc wrap angle is: wherein α i is the magnetic pole circular arc wrap angle, i = 1, 2, …, p, p is the number of magnetic pole pairs; R is the rotor radius; e is the magnetic pole eccentricity; S i is the magnetic pole circular arc length; The target function is: Objective function: Min Z=ηΔe+ζT Wherein, Δe is the motor back electromotive force variation, T is the cogging torque; η and ζ are the weighting coefficients of the motor back electromotive force variation and the motor cogging torque respectively.

2. The multi-parameter variable fusion based low noise motor optimization method for vehicle according to claim 1, characterized in that, When optimizing the magnetic pole circular arc wrap angle, the following optimization conditions need to be met:

3. The multi-parameter variable fusion based low noise motor optimization method for vehicle according to claim 1, characterized in that, The optimization variable also includes the permanent magnet slot width and the permanent magnet thickness.

4. The multi-parameter variable fusion based low noise motor optimization method for vehicle according to claim 3, characterized in that, The constraint condition also includes: wherein ΔP is a motor rated power variation amount; b c0 and Δb C are a permanent magnet slot width reference value and a variation amount thereof, respectively; b T0 and Δb T are a permanent magnet thickness reference value and a variation amount thereof, respectively.

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