Improved ephemera algorithm for optimizing electromagnetic vibration noise of permanent magnet synchronous motor and its system

Abstract

The present invention provides an improved ephemera algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method and system, which relates to the technical field of motor optimization. The method includes establishing a permanent magnet synchronous motor analytical model, analyzing the electromagnetic vibration noise characteristics of the permanent magnet synchronous motor; determining the design variables, constraints and optimization targets of the permanent magnet synchronous motor; improving the traditional ephemera search algorithm, introducing Circle chaos mapping, cosine weight factor and Cauchy mutation strategy into the traditional ephemera search algorithm, obtaining an improved ephemera algorithm, and using the improved ephemera algorithm to perform optimization calculation on the permanent magnet synchronous motor analytical model to obtain the optimal motor performance parameters that meet the constraints and objective functions. The present invention can make the generated population position more uniform and the range more extensive, perform disturbance mutation operations at the optimal solution position to obtain a new solution, improve the defect of the algorithm falling into a local area, increase the possibility of making it jump out of the local optimum, and improve the algorithm optimization accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of motor optimization, and in particular to an improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method and system. Background Art

[0002] Built-in permanent magnet synchronous motors are easier to design into motors with small size, light weight, high efficiency, and high speed range. They are mainly used in electric vehicle drive systems. Although built-in permanent magnet stepper motors have many advantages, their equivalent air gap length is small, and they usually produce more radial electromagnetic harmonic components and higher harmonic amplitudes, which can easily excite the corresponding stator mode, causing more serious vibration and thus noise. Therefore, it is necessary to improve the motor noise by changing the stator modal frequency and electromagnetic force from the perspective of the stator and rotor structure of the motor.

[0003] Because the design problem of permanent magnet synchronous motor has the characteristics of multi-objective, multi-variable, nonlinear, etc., it is difficult for traditional optimization algorithms to complete the global optimization design. The swarm intelligence optimization algorithm proposed in recent years mainly simulates the group behavior of insects, animal flocks, bird flocks and fish schools. These groups search for food in a certain cooperative way. Each member of the group constantly changes the search direction by learning from its own experience and the experience of other members. The mayfly algorithm is an optimization algorithm proposed based on the flight and reproduction of mayflies. The movement of females and males provides the algorithm with local search capabilities, while mating and reproduction provide global search capabilities. The algorithm has strong local search capabilities but poor stability and is prone to fall into local optimality. Therefore, it is necessary to propose a new optimization method to prevent the algorithm from falling into local optimality. Summary of the invention

[0004] To this end, an embodiment of the present invention provides an improved method and system for optimizing the electromagnetic vibration noise of a permanent magnet synchronous motor using an improved mayfly algorithm, which solves the uneven population position produced by the existing algorithm, performs a disturbance mutation operation at the optimal solution position to obtain a new solution, improves the defect of the algorithm falling into a local area, increases the possibility of making it jump out of the local optimum, and improves the algorithm's optimization accuracy, thereby optimizing the motor noise.

[0005] In order to solve the above problems, an embodiment of the present invention provides an improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method, the method comprising:

[0006] S1: Establish an analytical model of permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of permanent magnet synchronous motor;

[0007] S2: Based on the analytical model of permanent magnet synchronous motor, determine the design variables, constraints and optimization objectives of the permanent magnet synchronous motor;

[0008] S3: Perform optimization calculation on the analytical model of permanent magnet synchronous motor, take the stator and rotor structural parameters of permanent magnet synchronous motor as optimization variables, take the output torque, torque pulsation, radial force wave of specific order frequency, multi-frequency electromagnetic vibration and material price of permanent magnet synchronous motor electromagnetic as optimization targets, perform multi-physics field and multi-target vibration and noise optimization on permanent magnet synchronous motor, and obtain the optimal motor performance parameters that meet the constraints and objective functions.

[0009] Preferably, a method for establishing an analytical model of a permanent magnet synchronous motor and analyzing the electromagnetic vibration noise characteristics of the permanent magnet synchronous motor is as follows:

[0010] S11: Establish an equivalent magnetic circuit model of the permanent magnet synchronous motor, calculate the air gap magnetic field of the permanent magnet synchronous motor under specified working conditions, calculate the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor according to the Maxwell stress tensor equation, and convert it into the radial electromagnetic force wave on the stator core teeth through the stator core tooth modulation equation. After two-dimensional Fourier decomposition, it is sent to the vibration transfer function as input to obtain the air gap magnetic flux density and electromagnetic force wave of the permanent magnet synchronous motor;

[0011] S12: Use the modal superposition method to obtain the harmonic response of the stator electromagnetic vibration noise displacement, velocity and acceleration;

[0012] S13: Calculate the noise sound pressure and obtain the noise sound pressure level by taking the decibel logarithm method.

[0013] Preferably, the calculation analytical expressions of the air gap flux density and electromagnetic force wave of the permanent magnet synchronous motor are:

[0014]

[0015] B g (θ,t)=[f pm,g (θ,t)+f arm,g (θ,t)]Λ 0 ·λ sat (θ,t)·λ dq (θ,t)·λ bri (θ,t)·λ slot (θ,t)

[0016] Among them, p r (θ,t) is the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor, p t (θ,t) is the tangential electromagnetic force wave in the air gap of the permanent magnet synchronous motor, B g (θ,t) is the air gap flux density of the permanent magnet synchronous motor, B r (θ,t) is the radial flux density of the air gap, B t (θ,t) is the air gap tangential flux density, μ 0 is the vacuum magnetic permeability, θ is the electrical angle, t is the time, f pm,g(θ, t) is the magnetomotive force of the permanent magnet in the air gap, f arm,g (θ,t) is the magnetomotive force of the armature winding in the air gap, Λ 0 is the uniform permeability of the air gap when slotting is not considered, λsat(θ,t) is the relative permeability ratio of the air gap caused by the magnetic circuit saturation effect, λ dq (θ,t) is the relative air gap permeability ratio caused by rotor salient poles, λ bri (θ,t) is the relative air gap permeability ratio caused by the rotor magnetic bridge, λ slot(θ,t) is the relative air gap permeability ratio caused by stator slotting.

[0017] Preferably, the determining of the design variables, constraints and optimization objectives of the permanent magnet synchronous motor based on the permanent magnet synchronous motor analytical model specifically includes:

[0018] The design variables include slot height, slot width, permanent magnet width, permanent magnet thickness, pole arc coefficient, and magnetic steel angle;

[0019] The constraints are expressed as follows:

[0020]

[0021] Among them, x 1 , x 2 , …, x n represents the design variable of permanent magnet synchronous motor; g 1 (x), g 2 (x), …, g m (x) represents the constraint function of various technical performance indicators of the permanent magnet synchronous motor; m is the number of constraint functions;

[0022] The optimization objective is expressed as follows:

[0023] f(x) = f(x) 1 ,x 2 ,…,x n )

[0024] Among them, x 1 , x 2 , …, x n represents the design variables of the permanent magnet synchronous motor; f(x) represents the objective function in the optimization design of the permanent magnet synchronous motor.

[0025] Preferably, the step S3 specifically includes:

[0026] S31: Use Circle chaotic mapping to randomly initialize the mayfly population and divide the initial population into male and female groups;

[0027] S32: Calculate and sort the fitness values ​​of the mayfly individuals, i.e., the variables to be optimized, to find the individual optimal values ​​and the global optimal values;

[0028] S33: According to the male mayfly speed update formula, the female mayfly speed update formula, and the male and female mayfly position movement formula, the speed and position of the mayfly individual are updated respectively, and the updated fitness is evaluated;

[0029] S34: Arrange the male and female individuals according to their fitness from best to worst, and mate the male and female individuals of the same level to produce offspring mayflies;

[0030] S35: Randomly divide the offspring into females and males, sort all the mayfly individuals in the space according to their fitness values, and select excellent individuals with the same number as the initial population;

[0031] S36: Determine whether the iteration end condition is met. If so, exit the loop and output the optimal solution to obtain the optimal variables to be optimized for the electromagnetic vibration noise of the permanent magnet synchronous motor and the optimal motor performance parameters. Otherwise, return to step S32.

[0032] Preferably, the mayfly population is randomly initialized using Circle chaos mapping, wherein the expression of Circle chaos mapping is:

[0033]

[0034] Among them, x i is the position of the i-th mayfly, mod is the remainder function;

[0035] Introducing random variables into the original Circle chaos map expression, the improved expression is:

[0036]

[0037] Among them, N T is the number of particles in the chaotic sequence, and rand(0,1) is a random number between [0,1].

[0038] Preferably, male and female individuals of the same level are mated to produce offspring mayflies, and the production formula is as follows:

[0039] offspring 1 =L·xm+(1-L)xf

[0040] offspring 2 =(1-L)·xm+Lxf

[0041] Among them, offspring is the offspring mayfly, L is a random number with a value range of (0,1); xm is the male mayfly, xf is the female mayfly, and the two individuals generated are symmetrical about the center of the female pair.

[0042] Preferably, the updating of the speed and position of the individual mayflies according to the male mayfly speed update formula, the female mayfly speed update formula, and the male and female mayfly position movement formulas specifically includes:

[0043] The male mayfly speed update formula is:

[0044]

[0045] in, represents the speed of the jth dimension of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever been to, gbest is the best global position, and a 1 、a 2 is a constant, usually 2, r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current position and gbest; e is a natural constant; d is a constant, generally 0, 1; r is a random number in [-1, 1]; if the individual is the best individual in the group, use the above formula to move, and other individuals use the following formula to move;

[0046] The female mayfly speed update formula is:

[0047]

[0048] Among them, xm is the position of the male individual paired with the female individual, xf is the position of the female individual, and r mf is the position between the two mayflies; fl is a constant and is generally taken as 0 or 1; r is a random number in [-1,1]; when the female individual is worse than the male individual, the upper formula of the formula is used; when the female individual is better than the male individual, the lower formula of the formula is used;

[0049] The movement formula of male and female mayflies is:

[0050]

[0051] in, Represents the position of the jth dimension of the i-th individual in the n-th generation population.

[0052] Preferably, the inertia coefficient is added to the male mayfly speed update formula, and the Cauchy variation is introduced into the target position update method, which specifically includes:

[0053] The inertia coefficient is added to the male mayfly speed update formula, and the inertia coefficient is a cosine weight factor, that is:

[0054]

[0055] The improved male mayfly speed update formula is:

[0056]

[0057] Among them, ω(n) is the inertia coefficient, which is used to make it possible to jump out of the local optimum; represents the j-dimensional velocity of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever been to, and gbest is the global best position; a 1 、a 2 is a constant, generally taking the value as 2; r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current location and gbest, e is a natural constant; d is a constant, generally 0, 1; r is a random number in [-1, 1];

[0058] The Cauchy mutation strategy is introduced into the target position update method, and the improved position movement formula is:

[0059]

[0060] Among them, cauchy(0,1) is the standard Cauchy distribution, is the position of the jth dimension of the i-th individual at time t+1, X best is the global optimal position, is the point multiplication operation.

[0061] The embodiment of the present invention further provides an improved ephemera algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization system, which is used to implement the improved ephemera algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method described above, and the system includes:

[0062] The module for establishing the analytical model of permanent magnet synchronous motor is used to establish the analytical model of permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of permanent magnet synchronous motor;

[0063] A permanent magnet synchronous motor determination module is used to determine the design variables, constraints and optimization objectives of the permanent magnet synchronous motor based on the permanent magnet synchronous motor analytical model;

[0064] The permanent magnet synchronous motor optimization module is used to perform optimal calculations on the permanent magnet synchronous motor analytical model. It takes the stator and rotor structural parameters of the permanent magnet synchronous motor as optimization variables, and the electromagnetic output torque, torque pulsation, radial force waves of specific order frequencies, multi-frequency electromagnetic vibrations and material prices of the permanent magnet synchronous motor as optimization targets. It performs multi-physics field and multi-target vibration and noise optimization on the permanent magnet synchronous motor to obtain the optimal motor performance parameters that meet the constraints and objective functions.

[0065] It can be seen from the above technical solutions that the present invention has the following advantages:

[0066] The present invention proposes an improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method and system, by establishing a permanent magnet synchronous motor electromagnetic-structural resonance-acoustic multi-physics field coupling analytical model, saving more computing time compared to the finite element method. Based on the traditional mayfly search algorithm, improvements are made, and Circle chaos mapping, cosine weight factor and Cauchy mutation strategy are introduced into the traditional mayfly search algorithm to obtain an improved mayfly algorithm, and the improved mayfly algorithm is used to perform optimization calculations on the permanent magnet synchronous motor to obtain the most suitable motor parameters that meet the constraints and objective functions. The present invention can make the generated population position more uniform and the range more extensive, perform perturbation mutation operations at the optimal solution position to obtain a new solution, improve the defect of the algorithm falling into the local area, increase the possibility of it jumping out of the local optimum, and improve the algorithm optimization accuracy, thereby realizing the optimization of the electromagnetic vibration noise of the permanent magnet synchronous motor and strengthening the research on the motor performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the implementation cases of the present invention or the technical solutions in the prior art, the following is a brief description of the drawings required for use in the embodiments. By referring to the drawings, the features and advantages of the present invention will be more clearly understood. The drawings are schematic and should not be understood as limiting the present invention in any way. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0068] Figure 1 It is a flow chart of an improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method provided in an embodiment;

[0069] Figure 2 The block diagram is a permanent magnet synchronous motor electromagnetic vibration noise optimization system according to an improved mayfly algorithm provided in an embodiment. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Embodiment 1

[0072] like Figure 1As shown, an embodiment of the present invention proposes an improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method, the method comprising:

[0073] S1: Establish an analytical model of permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of permanent magnet synchronous motor;

[0074] S2: Based on the analytical model of permanent magnet synchronous motor, determine the design variables, constraints and optimization objectives of the permanent magnet synchronous motor;

[0075] S3: Perform optimization calculation on the analytical model of permanent magnet synchronous motor, take the stator and rotor structural parameters of permanent magnet synchronous motor as optimization variables, take the output torque, torque pulsation, radial force wave of specific order frequency, multi-frequency electromagnetic vibration and material price of permanent magnet synchronous motor electromagnetic as optimization targets, perform multi-physics field and multi-target vibration and noise optimization on permanent magnet synchronous motor, and obtain the optimal motor performance parameters that meet the constraints and objective functions.

[0076] The present invention proposes an improved mayfly algorithm for optimizing electromagnetic vibration noise of permanent magnet synchronous motors. By establishing an analytical model of electromagnetic-structural resonance-acoustic multi-physical field coupling of permanent magnet synchronous motors, more computing time is saved compared to the finite element method. Based on the traditional mayfly search algorithm, improvements are made, and Circle chaos mapping, cosine weight factor and Cauchy mutation strategy are introduced into the traditional mayfly search algorithm to obtain an improved mayfly algorithm, and the improved mayfly algorithm is used to perform optimization calculations on permanent magnet synchronous motors to obtain the most suitable motor parameters that meet the constraints and objective functions. The present invention can make the generated population positions more uniform and the range more extensive, perform perturbation mutation operations at the optimal solution position to obtain new solutions, improve the defects of the algorithm falling into local areas, increase the possibility of making it jump out of the local optimum, and improve the optimization accuracy of the algorithm, thereby realizing the optimization of the electromagnetic vibration noise of the permanent magnet synchronous motor and strengthening the research on motor performance.

[0077] Furthermore, in step S1, an analytical model of a permanent magnet synchronous motor is established to analyze the electromagnetic vibration noise characteristics of the permanent magnet synchronous motor. First, an equivalent magnetic circuit model of the permanent magnet synchronous motor is established to calculate the air gap magnetic field of the permanent magnet synchronous motor under specified working conditions, and the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor is calculated according to the Maxwell stress tensor equation, and converted into the radial electromagnetic force wave received by the stator core teeth through the stator core tooth modulation equation, and sent to the vibration transfer function as input after two-dimensional Fourier decomposition to obtain the air gap magnetic flux density and electromagnetic force wave of the permanent magnet synchronous motor.

[0078] Specifically, in the equivalent magnetic circuit model of the permanent magnet synchronous motor, the permanent magnet is equivalent to the magnetic flux source, and its expression is:

[0079]

[0080] Among them, Br is the remanent magnetic density of the permanent magnet, w pm is the width of the permanent magnet, l ef is the effective axial length of the motor.

[0081] Permanent magnet equivalent magnetic resistance R pm 、Top magnetic isolation bridge R br1 , the equivalent magnetic resistance R of the bottom magnetic bridge br2 And the air gap equivalent magnetic resistance R g The analytical expression of is:

[0082]

[0083] Among them, μ r , μ 0 are the relative magnetic permeability of permanent magnet and the magnetic permeability of vacuum, μ r (H) is the relative magnetic permeability of the rotor magnetic bridge when it is in magnetic saturation, which needs to be iteratively obtained based on the BH curve of the ferromagnetic material. br 、w br are the length and width of the magnetic isolation bridge, δ is the air gap thickness, α pm is the permanent magnet pole arc coefficient, and τ is the rotor pole pitch.

[0084] From the above, we can know that the magnetic flux amplitude Φ in the air gap g and the permanent magnet magnetomotive force amplitude F pm,g for:

[0085]

[0086] Armature equivalent magnetomotive force F a1 、F a2 、F a3 、F a4 、F a5 ,…,F aj The calculation expression is:

[0087]

[0088] Where N is the number of conductors per slot, I aj is the current in the jth slot, Q s is the total number of stator slots.

[0089] Stator tooth equivalent magnetic resistance R tj and stator yoke equivalent magnetic resistance R yj The calculation expression is:

[0090]

[0091] Among them, h t 、w t are the height and width of a stator tooth, hy 、w y are the thickness and width of the stator yoke corresponding to one tooth, μ r (H) is the relative magnetic permeability of each stator tooth or yoke.

[0092] Usually, the square value of the tangential magnetic flux in the air gap of the motor is much smaller than the square value of the radial magnetic flux. Therefore, the calculation expressions of the radial electromagnetic force wave and the tangential electromagnetic force wave in the air gap of the permanent magnet synchronous motor can be simplified as follows:

[0093]

[0094] Air gap magnetic flux density B of permanent magnet synchronous motor g The expression of (θ,t) is:

[0095] B g (θ,t)=[f pm,g (θ,t)+f arm,g (θ,t)]Λ 0 ·λ sat (θ,t)·λ dq (θ,t)·λ bri (θ,t)·λ slot (θ,t)

[0096] Among them, p r (θ,t) is the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor, p t (θ,t) is the tangential electromagnetic force wave in the air gap of the permanent magnet synchronous motor, B r (θ,t) is the radial flux density of the air gap, B t (θ,t) is the air gap tangential flux density, μ 0 is the vacuum magnetic permeability, θ is the electrical angle, t is the time, f pm,g (θ, t) is the magnetomotive force of the permanent magnet in the air gap, f arm,g (θ,t) is the magnetomotive force of the armature winding in the air gap, Λ 0 is the uniform permeability of the air gap when slotting is not considered, λsat(θ,t) is the relative permeability ratio of the air gap caused by the magnetic circuit saturation effect, λ dq (θ,t) is the relative air gap permeability ratio caused by rotor salient poles, λ bri (θ,t) is the relative air gap permeability ratio caused by the rotor magnetic bridge, λ slot(θ,t) is the relative air gap permeability ratio caused by stator slotting.

[0097] Then, the modal superposition method is used to obtain the harmonic response of the stator electromagnetic vibration noise displacement, velocity and acceleration. The displacement frequency response of the multi-degree-of-freedom system can be expressed as:

[0098]

[0099] Where P v (ω) is the external v-th order exciting force, H D,y (ω) is the displacement transfer function corresponding to the vth-order mode of the system.

[0100] Finally, the noise sound pressure is calculated and the noise sound pressure level is obtained by taking the decibel logarithm method.

[0101] In the sound field, the sound pressure level is generally used to judge the size of the noise amplitude, and the radius R from the center point of the motor c The sound pressure at is:

[0102]

[0103] In the formula, S Rc L is the sound field radiation surface area at a radius Rc from the motor center point, sh is the motor housing shaft length, ρ 0 is the air density, c 0 is the speed of sound, ERP sum is the sound field radiation power on the motor surface.

[0104] After obtaining the noise sound pressure, the noise sound pressure level is obtained by taking the decibel logarithm method:

[0105]

[0106] Among them, P 0 is the reference sound pressure.

[0107] Furthermore, in step S2, based on the analytical model of the permanent magnet synchronous motor, the design variables, constraints and optimization objectives of the permanent magnet synchronous motor are determined.

[0108] Specifically, the stator and rotor structural parameters are substituted into the equivalent magnetic circuit model of the permanent magnet synchronous motor. The design variables to be optimized for the permanent magnet synchronous motor include slot height, slot width, permanent magnet width, permanent magnet thickness, pole arc coefficient, magnetic steel angle, etc., which are respectively expressed as: x 1 , x 2 , …, x n The various technical performance indicators of the motor are functions of these design variables. These technical performance indicators are treated as constraints in the optimal design of the motor and can be expressed as follows:

[0109]

[0110] Where m is the number of constraint functions.

[0111] The objective function in motor optimization design can be expressed as a function of the design variables:

[0112] f(x) = f(x) 1 ,x2 ,…,x n ).

[0113] Furthermore, in step S3, based on the traditional mayfly search algorithm, improvements are made by introducing Circle chaos mapping, cosine weight factor and Cauchy mutation strategy into the traditional mayfly search algorithm to obtain an improved mayfly algorithm. The improved mayfly algorithm is used to perform optimization calculation on the analytical model of the permanent magnet synchronous motor, with the stator and rotor structural parameters of the permanent magnet synchronous motor as optimization variables, and the output torque, torque pulsation, radial force wave of a specific order frequency, multi-frequency electromagnetic vibration and material price of the permanent magnet synchronous motor as optimization targets, and the permanent magnet synchronous motor is optimized for multi-physics field and multi-target vibration noise, and the optimal motor performance parameters that meet the constraints and objective functions are obtained.

[0114] Specifically, the position of each mayfly in the search space represents a feasible solution to the problem. The position and velocity of the i-th male mayfly in the D-dimensional space can be expressed as:

[0115] xi=(xi 1 ,xi 2 ,…,xi d ) T

[0116] vi=(vi 1 ,vi 2 ,…,vi d ) T

[0117] S31: Use Circle chaos mapping to randomly initialize the mayfly population and divide the initial population into male and female groups. The expression of Circle chaos mapping is:

[0118]

[0119] Among them, x i is the position of the i-th mayfly, mod is the remainder function;

[0120] Introducing random variables into the original Circle chaos map expression, the improved expression is:

[0121]

[0122] Among them, N T is the number of particles in the chaotic sequence, and rand(0,1) is a random number between [0,1].

[0123] S32: Calculate and sort the fitness values ​​of the mayfly individuals, i.e., the variables to be optimized, to find the individual optimal values ​​and the global optimal values.

[0124] S33: According to the male mayfly speed update formula, the female mayfly speed update formula, and the male and female mayfly position movement formula, the speed and position of the mayfly individual are updated respectively, and the updated fitness is evaluated.

[0125] The male mayfly speed update formula is:

[0126]

[0127] in, represents the speed of the jth dimension of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever been to, gbest is the best global position, and a 1 、a 2 is a constant, generally taking the value as 2; r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current position and gbest, e is a natural constant, d is a constant, generally 0, 1; r is a random number in [-1, 1]; if the individual is the best individual in the group, use the above formula to move, and other individuals use the following formula to move. ij , gbest ij are the individual optimal value and the global optimal value respectively, and their expressions are as follows:

[0128]

[0129] Among them, f represents the fitness calculation formula.

[0130] The female mayfly speed update formula is:

[0131]

[0132] Among them, xm is the position of the male individual paired with the female individual, xf is the position of the female individual, and r mf is the position between the two mayflies, fl is a constant generally taking a value of 0 or 1; r is a random number in [-1,1]; when the female individual is worse than the male individual, use the upper formula of the formula; when the female individual is better than the male individual, use the lower formula of the formula.

[0133] The movement formula of male and female mayflies is:

[0134]

[0135] in, Represents the position of the jth dimension of the i-th individual in the n-th generation population.

[0136] In addition, in order to better improve the algorithm's optimization and solving ability, the inertia coefficient is added to the male mayfly speed update formula. The inertia coefficient is a cosine weight factor, that is:

[0137]

[0138] The improved male mayfly speed update formula is:

[0139]

[0140] Among them, ω(n) is the inertia coefficient, which is used to make it possible to jump out of the local optimum; represents the j-dimensional velocity of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever been to, and gbest is the global best position; a 1 、a 2 is a constant, generally taking the value as 2; r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current position and gbest, e is a natural constant, d is a constant, generally taking values ​​of 0 or 1; r is a random number in the range of [-1,1].

[0141] The Cauchy mutation strategy is introduced into the target position update method to give full play to the perturbation ability of the Cauchy operator, so that the global optimization performance of the algorithm is improved. The improved position movement formula is:

[0142]

[0143] Among them, cauchy(0,1) is the standard Cauchy distribution, is the position of the jth dimension of the i-th individual at time t+1, X best is the global optimal position, is the point multiplication operation.

[0144] In the Cauchy mutation strategy, the Cauchy mutation operator is used to perform perturbation mutation operations at the optimal solution position to obtain a new solution, which improves the defect of the algorithm falling into the local area.

[0145] S34: The male and female individuals are arranged from best to worst according to their fitness, and the male and female individuals of the same level are mated to produce offspring mayflies. The production formula is as follows:

[0146] offspring 1 =L·xm+(1-L)xf

[0147] offspring 2 =(1-L)·xm+Lxf

[0148] Among them, offspring is the offspring mayfly, L is a random number with a value range of (0,1); xm is the male mayfly, xf is the female mayfly, and the two individuals generated are symmetrical about the center of the female pair.

[0149] S35: Randomly divide the offspring into females and males, sort all the mayfly individuals in the space according to their fitness values, and select excellent individuals with the same number as the initial population;

[0150] S36: Determine whether the iteration end condition is met. If so, exit the loop and output the optimal solution to obtain the optimal variables to be optimized for the electromagnetic vibration noise of the permanent magnet synchronous motor and the optimal motor performance parameters. Otherwise, return to step S32.

[0151] Embodiment 2

[0152] like Figure 2 As shown, the present invention provides a permanent magnet synchronous motor electromagnetic vibration noise optimization system based on an improved mayfly algorithm, the system comprising:

[0153] A permanent magnet synchronous motor analytical model building module 10 is used to build an analytical model of the permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of the permanent magnet synchronous motor;

[0154] A permanent magnet synchronous motor determination module 20 is used to determine the design variables, constraints and optimization targets of the permanent magnet synchronous motor based on the permanent magnet synchronous motor analytical model;

[0155] The permanent magnet synchronous motor optimization module 30 is used to perform optimal calculations on the permanent magnet synchronous motor analytical model, taking the stator and rotor structural parameters of the permanent magnet synchronous motor as optimization variables, and the electromagnetic output torque, torque pulsation, radial force waves of specific order frequencies, multi-frequency electromagnetic vibrations and material prices of the permanent magnet synchronous motor as optimization targets, and performing multi-physical field and multi-target vibration and noise optimization on the permanent magnet synchronous motor to obtain the optimal motor performance parameters that meet the constraints and objective functions.

[0156] An improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization system of the present embodiment is used to implement the aforementioned improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method. Therefore, the specific implementation method of the improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization system can be seen in the embodiment part of the improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method mentioned above. For example, the permanent magnet synchronous motor analytical model establishment module 10, the permanent magnet synchronous motor determination module 20, and the permanent magnet synchronous motor optimization module 30 are respectively used to implement steps S1, S2, and S3 in the above-mentioned improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method. Therefore, its specific implementation method can refer to the description of the corresponding various parts of the embodiment. In order to avoid redundancy, it will not be repeated here.

[0157] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

[0158] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0159] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0160] 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 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in 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.

[0161] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. An improved ephemera algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method, characterized in that: include: S1: Establish an analytical model of permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of permanent magnet synchronous motor; S2: Based on the analytical model of permanent magnet synchronous motor, determine the design variables, constraints and optimization objectives of the permanent magnet synchronous motor; S3: Perform optimization calculation on the analytical model of permanent magnet synchronous motor, take the stator and rotor structural parameters of permanent magnet synchronous motor as optimization variables, take the output torque, torque pulsation, radial force wave of specific order frequency, multi-frequency electromagnetic vibration and material price of permanent magnet synchronous motor electromagnetic as optimization targets, perform multi-physics field and multi-target vibration and noise optimization on permanent magnet synchronous motor, and obtain the optimal motor performance parameters that meet the constraints and objective functions; Wherein step S3 comprises: S31: Use Circle chaotic mapping to randomly initialize the mayfly population and divide the initial population into male and female groups; S32: Calculate and sort the fitness values ​​of the mayfly individuals, i.e., the variables to be optimized, to find the individual optimal values ​​and the global optimal values; S33: According to the male mayfly speed update formula, the female mayfly speed update formula, and the male and female mayfly position movement formula, the speed and position of the mayfly individual are updated respectively, and the updated fitness is evaluated; S34: Arrange the male and female individuals according to their fitness from best to worst, and mate the male and female individuals of the same level to produce offspring mayflies; S35: Randomly divide the offspring into females and males, sort all the mayfly individuals in the space according to their fitness values, and select excellent individuals with the same number as the initial population; S36: Determine whether the iteration end condition is met, if so, exit the loop and output the optimal solution, obtain the optimal variable to be optimized for the electromagnetic vibration noise of the permanent magnet synchronous motor, and obtain the optimal motor performance parameters, otherwise return to step S32; The inertia coefficient is added to the speed update formula of male mayflies, and the Cauchy variation is introduced into the target position update method, which includes: The inertia coefficient is added to the male mayfly speed update formula, and the inertia coefficient is a cosine weight factor, that is: The improved male mayfly speed update formula is: Among them, ω(n) is the inertia coefficient, which is used to make it possible to jump out of the local optimum; represents the j-dimensional velocity of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever been to, gbest is the global best position; a1 and a2 are constants; r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current position and gbest, and e is a natural constant; The Cauchy mutation strategy is introduced into the target position update method, and the improved position movement formula is: Among them, cauchy(0,1) is the standard Cauchy distribution, is the position of the jth dimension of the i-th individual at time t+1, X best is the global optimal position, and ⊕ is the point multiplication operation.

2. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 1 is characterized in that: The method of establishing the analytical model of permanent magnet synchronous motor and analyzing the electromagnetic vibration noise characteristics of permanent magnet synchronous motor is as follows: S11: Establish an equivalent magnetic circuit model of the permanent magnet synchronous motor, calculate the air gap magnetic field of the permanent magnet synchronous motor under specified working conditions, calculate the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor according to the Maxwell stress tensor equation, and convert it into the radial electromagnetic force wave on the stator core teeth through the stator core tooth modulation equation. After two-dimensional Fourier decomposition, it is sent to the vibration transfer function as input to obtain the air gap magnetic flux density and electromagnetic force wave of the permanent magnet synchronous motor; S12: Use the modal superposition method to obtain the harmonic response of the stator electromagnetic vibration noise displacement, velocity and acceleration; S13: Calculate the noise sound pressure and obtain the noise sound pressure level by taking the decibel logarithm method.

3. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 2 is characterized in that: The calculation analytical expressions of the air gap flux density and electromagnetic force wave of the permanent magnet synchronous motor are as follows: B g (θ,t)=[f pm,g (θ,t)+f arm,g (θ,t)]Λ0·λ sat (θ,t)·λ dq (θ,t)·λ bri (θ,t)·λ slot (θ,t) Among them, p r (θ,t) is the radial electromagnetic force wave in the air gap of the permanent magnet synchronous motor, p t (θ,t) is the tangential electromagnetic force wave in the air gap of the permanent magnet synchronous motor, B g (θ,t) is the air gap flux density of the permanent magnet synchronous motor, B r (θ,t) is the radial flux density of the air gap, B t (θ, t) is the air gap tangential magnetic flux density, μ0 is the vacuum magnetic permeability, θ is the electrical angle, t is the time, f pm,g (θ, t) is the magnetomotive force of the permanent magnet in the air gap, f arm,g (θ, t) is the magnetomotive force of the armature winding in the air gap, Λ0 is the uniform permeability of the air gap when slotting is not considered, λsat(θ, t) is the relative permeability ratio of the air gap caused by the magnetic circuit saturation effect, λ dq (θ,t) is the relative air gap permeability ratio caused by the rotor salient poles, λ bri (θ,t) is the relative air gap permeability ratio caused by the rotor magnetic bridge, λ slot(θ,t) is the relative air gap permeability ratio caused by stator slotting.

4. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 1 is characterized in that: The determination of the design variables, constraints and optimization objectives of the permanent magnet synchronous motor based on the permanent magnet synchronous motor analytical model specifically includes: The design variables include slot height, slot width, permanent magnet width, permanent magnet thickness, pole arc coefficient, and magnetic steel angle; The constraints are expressed as follows: where x1, x2, …, x n represents the design variables of the permanent magnet synchronous motor; g1(x), g2(x), …, g m (x) represents the constraint function of various technical performance indicators of the permanent magnet synchronous motor; m is the number of constraint functions; The optimization objective is expressed as follows: f(x)=f(x1,x2,…,x n ) Among them, x1, x2, …, x n represents the design variable of the permanent magnet synchronous motor; f(x) represents the objective function in the optimization design of the permanent magnet synchronous motor.

5. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 1 is characterized in that: The method of randomly initializing the mayfly population using Circle chaotic mapping is: The mayfly population is randomly initialized using the Circle chaos map, where the expression of the Circle chaos map is: Among them, x i is the position of the i-th mayfly, mod is the remainder function; Introducing random variables into the original Circle chaos map expression, the improved expression is: Among them, N T is the number of particles in the chaotic sequence, and rand(0,1) is a random number between [0,1].

6. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 1 is characterized in that: Male and female individuals of the same level mate to produce offspring mayflies, and the production formula is as follows: offspring1=L·xm+(1-L)xf offspring2=(1-L)·xm+Lxf Among them, offspring is the offspring mayfly, L is a random number with a value range of (0,1); xm is the male mayfly, xf is the female mayfly, and the two individuals generated are symmetrical about the center of the female pair.

7. The improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization method according to claim 1 is characterized in that: The updating of the speed and position of the individual mayflies according to the male mayfly speed updating formula, the female mayfly speed updating formula, and the male and female mayfly position movement formulas specifically includes: The male mayfly speed update formula is: in, represents the j-dimensional velocity of the ith individual in the n+1th generation population, pbest is the best position that the individual has ever reached, gbest is the global best position; a1 and a2 are constants; r p is the Euclidean distance between the current position and pbest, r g is the Euclidean distance between the current position and gbest; e is a natural constant; d is a constant; r is a random number in [-1,1]; if the individual is the best individual in the group, use the above formula to move, and other individuals use the following formula to move; The female mayfly speed update formula is: Among them, xm is the position of the male individual paired with the female individual, xf is the position of the female individual, and r mf is the position between the two mayflies; fl is a constant; r is a random number in [-1,1]; when the female individual is worse than the male individual, the upper formula of the formula is used; when the female individual is better than the male individual, the lower formula of the formula is used; The movement formula of male and female mayflies is: in, Represents the position of the jth dimension of the i-th individual in the n-th generation population.

8. An improved mayfly algorithm permanent magnet synchronous motor electromagnetic vibration noise optimization system, characterized in that: The method for optimizing electromagnetic vibration noise of a permanent magnet synchronous motor using an improved mayfly algorithm according to any one of claims 1 to 7 comprises: The module for establishing the analytical model of permanent magnet synchronous motor is used to establish the analytical model of permanent magnet synchronous motor and analyze the electromagnetic vibration and noise characteristics of permanent magnet synchronous motor; A permanent magnet synchronous motor determination module is used to determine the design variables, constraints and optimization objectives of the permanent magnet synchronous motor based on the permanent magnet synchronous motor analytical model; The permanent magnet synchronous motor optimization module is used to perform optimal calculations on the permanent magnet synchronous motor analytical model. It takes the stator and rotor structural parameters of the permanent magnet synchronous motor as optimization variables, and the electromagnetic output torque, torque pulsation, radial force waves of specific order frequencies, multi-frequency electromagnetic vibrations and material prices of the permanent magnet synchronous motor as optimization targets. It performs multi-physics field and multi-target vibration and noise optimization on the permanent magnet synchronous motor to obtain the optimal motor performance parameters that meet the constraints and objective functions.

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