A vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle

Abstract

The application provides a vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle, comprising the following steps: establishing a mathematical model of the permanent magnet synchronous motor in different coordinate systems; constructing a torque and flux observer to obtain an electromagnetic torque estimation value and a stator flux estimation value; obtaining an electromagnetic torque reference value through speed loop control, and obtaining a stator flux reference value based on the electromagnetic torque reference value and by introducing a cloud drift optimization algorithm; obtaining a discrete system, constructing a cost function, and obtaining a reference voltage vector by solving; performing inverse coordinate conversion on the reference voltage vector, adopting hybrid random space vector pulse width modulation, generating a three-phase pulse width modulation signal, and sending the three-phase pulse width modulation signal into an inverter to drive the permanent magnet synchronous motor, so as to realize vibration noise suppression of the permanent magnet synchronous motor. The application can effectively suppress vibration noise and improve the control performance and operation stability of the permanent magnet synchronous motor.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of electric vehicles, in particular to a vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle. BACKGROUND

[0002] The permanent magnet synchronous motor is widely applied to electric vehicle driving systems due to high efficiency, high power density and excellent dynamic performance. Traditional permanent magnet synchronous motor control methods mainly include vector control and direct torque control.

[0003] The vector control has higher steady-state accuracy but slower dynamic response, and the direct torque control has fast response speed but is prone to torque pulsation and flux linkage fluctuation, which leads to vibration noise, thereby affecting the control performance and operation stability of the permanent magnet synchronous motor. SUMMARY

[0004] Therefore, the application provides a vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle, so as to effectively suppress vibration noise and improve the control performance and operation stability of the permanent magnet synchronous motor.

[0005] A vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle comprises the following steps.

[0006] In step S1, parameter information of the permanent magnet synchronous motor is collected in real time, and then a permanent magnet synchronous motor mathematical model in different coordinate systems is established through coordinate transformation.

[0007] In step S2, a torque and flux observer is constructed based on the permanent magnet synchronous motor mathematical model, so as to obtain an electromagnetic torque estimation value and a stator flux estimation value.

[0008] In step S3, an electromagnetic torque reference value is obtained through speed loop control, and a stator flux reference value is obtained based on the electromagnetic torque reference value by introducing a cloud drift optimization algorithm.

[0009] In step S4, a discrete system is obtained based on the permanent magnet synchronous motor mathematical model, and then a cost function is constructed based on the electromagnetic torque estimation value and the electromagnetic torque reference value and the stator flux estimation value and the stator flux reference value, and a reference voltage vector is obtained by solving the cost function.

[0010] In step S5, the reference voltage vector is inversely coordinate-converted, and a hybrid random space vector pulse width modulation is adopted to generate a three-phase pulse width modulation signal, and the three-phase pulse width modulation signal is sent to an inverter to drive the permanent magnet synchronous motor, so as to suppress vibration noise of the permanent magnet synchronous motor.

[0011] The vibration noise suppression method for the permanent magnet synchronous motor of the electric vehicle has the following beneficial effects.

[0012] (1) Considering that the traditional direct torque control utilizes hysteresis comparison control torque and flux linkage, which can cause electromagnetic torque and stator flux linkage to fluctuate obviously, the application constructs a cost function based on the electromagnetic torque estimated value and the electromagnetic torque reference value, and the stator flux linkage estimated value and the stator flux linkage reference value, and obtains the reference voltage vector by solving the cost function, so as to realize the model predictive control instead of the traditional hysteresis control, and reduce the torque and flux linkage ripple.

[0013] (2) Considering that the inverter switching frequency fluctuation is large in the traditional direct torque control, which affects the control accuracy and operation stability, the application adopts the hybrid random space vector pulse width modulation technology to replace the switching table part in the traditional direct torque control, so as to improve the system control accuracy.

[0014] (3) Considering that the stator flux linkage reference value will change dynamically with the motor operating condition, the application introduces the cloud drift optimization algorithm to realize the adaptive adjustment of the reference stator flux linkage, and improves the dynamic performance of the motor.

[0015] (4) Considering that the traditional speed loop control is sensitive to the change of system parameters, which can reduce the robustness of the system, the application proposes an improved approach law to improve the response speed and reduce the chattering, so as to improve the control performance of the speed loop.

[0016] (5) The application can effectively suppress the motor vibration noise, reduce the torque ripple and fluctuation, improve the control performance and operation stability of the permanent magnet synchronous motor, and make the electric vehicle have smaller vibration noise under complex working conditions. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 The flowchart of the electric vehicle permanent magnet synchronous motor vibration noise suppression method provided by the embodiment of the application is shown in the figure.

[0018] Figure 2 The speed comparison chart of the application and the traditional control method under specific working conditions is shown in the figure.

[0019] Figure 3 The torque comparison chart of the application and the traditional control method under specific working conditions is shown in the figure. DETAILED DESCRIPTION

[0020] The embodiments of the application will be described in detail below, and the examples of the embodiments are shown in the drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are intended to explain the embodiments of the application, and cannot be understood as limiting the application.

[0021] Please refer to Figure 1The embodiment of the application provides a vibration noise suppression method for a permanent magnet synchronous motor of an electric vehicle, comprising steps S1 to S5:

[0022] In step S1, parameter information of the permanent magnet synchronous motor is collected in real time, and then a mathematical model of the permanent magnet synchronous motor in different coordinate systems is established through coordinate transformation.

[0023] The parameter information at least comprises stator current and stator voltage. The parameter information of the permanent magnet synchronous motor satisfies the following formula:

[0024]

[0025]

[0026] Wherein, is a stator voltage vector, , , , are A-phase stator voltage, B-phase stator voltage and C-phase stator voltage respectively, denotes transposition, is a stator current vector, , , , are A-phase stator current, B-phase stator current and C-phase stator current respectively, is a stator resistance, is a stator flux linkage vector, , , , are A-phase stator flux linkage, B-phase stator flux linkage and C-phase stator flux linkage respectively, denotes time, denotes differentiation, is an inductance matrix, is a flux linkage generated by a rotor permanent magnet;

[0027] In step S1, a mathematical model of the permanent magnet synchronous motor in a two-phase static coordinate system and a mathematical model of the permanent magnet synchronous motor in a two-phase rotating coordinate system are established through coordinate transformation.

[0028] The stator voltage expression in the two-phase static coordinate system is as follows:

[0029]

[0030]

[0031] Wherein, , are components of the stator voltage on two-phase static coordinate axes, , are the components of the stator current on the two-phase stationary coordinate axes, , are the components of the stator flux linkage on the two-phase stationary coordinate axes;

[0032] The expression of the stator flux linkage in the two-phase stationary coordinate system is:

[0033]

[0034]

[0035]

[0036] The expression of the stator voltage in the two-phase rotating coordinate system is:

[0037]

[0038]

[0039] wherein, , are the components of the stator voltage on the two-phase rotating coordinate axes, , are the components of the stator current on the two-phase rotating coordinate axes, , are the components of the stator flux linkage on the two-phase rotating coordinate axes, is the electrical angular velocity;

[0040] The expression of the stator flux linkage in the two-phase rotating coordinate system is:

[0041]

[0042]

[0043] wherein, , are the components of the stator inductance on the two-phase rotating coordinate axes.

[0044] Step S2, based on the mathematical model of the permanent magnet synchronous motor, a torque and flux linkage observer is constructed, so as to obtain an electromagnetic torque estimation value and a stator flux linkage estimation value.

[0045] wherein, step S2 specifically comprises:

[0046] Based on the mathematical model of the permanent magnet synchronous motor in the two-phase stationary coordinate system, the expression of the stator flux linkage observation model is obtained:

[0047]

[0048]

[0049]

[0050] wherein, , is the stator back EMF on two-phase stationary coordinate axis, is the stator back EMF of permanent magnet synchronous motor, is the imaginary unit;

[0051] Since the ideal integrator has cumulative error or integral drift problem, the direct current bias in the electromotive force cannot be eliminated, which will lead to inaccurate flux linkage observation, therefore, the application constructs a joint filter, and the transfer function expression thereof is:

[0052]

[0053] wherein, is the Laplace operator, is the cut-off frequency of the filter;

[0054] Further, compensation control is introduced, and the compensation amount is defined as , and the expression is:

[0055]

[0056] The stator flux linkage observation expression based on the voltage model is:

[0057]

[0058] wherein, is the stator flux linkage estimation value based on the voltage model;

[0059] The stator flux linkage observation expression based on the current model is:

[0060]

[0061] wherein, is the stator flux linkage estimation value based on the current model;

[0062] The stator flux linkage observation expression based on the voltage model and the stator flux linkage observation expression based on the current model are fused to obtain the following formula:

[0063]

[0064] wherein, is the stator flux linkage estimation value, is the high-pass filtering weight, is the low-pass filtering weight, , is the stator flux linkage estimation value on two-phase stationary coordinate axis;

[0065] According to the observed stator flux linkage estimation value, an electromagnetic torque estimation value is calculated through an electromagnetic torque equation in a two-phase static coordinate system, and the expression is:

[0066]

[0067] Wherein, is the electromagnetic torque estimation value, is the number of pole pairs.

[0068] Step S3, an electromagnetic torque reference value is obtained through speed loop control, and a stator flux linkage reference value is obtained based on the electromagnetic torque reference value by introducing a cloud drift optimization algorithm.

[0069] Wherein, step S3 specifically includes:

[0070] In the speed loop control, the speed error is defined as:

[0071]

[0072] Wherein, is the reference speed, is the mechanical angular velocity;

[0073] The mechanical motion expression of the permanent magnet synchronous motor is:

[0074]

[0075] Wherein, is the moment of inertia, is the electromagnetic torque, is the load torque, is the damping coefficient;

[0076] The derivative of the speed error expression is obtained, and the mechanical motion expression of the permanent magnet synchronous motor is obtained:

[0077]

[0078] Wherein, is the first derivative of is the first derivative of is the first derivative of is the first derivative of is the first derivative of is the first derivative of

[0079] The sliding mode surface is defined as:

[0080]

[0081] Wherein, , are state variables, , , , , , are constants, and , , ;

[0082] Further derivation obtains:

[0083]

[0084] wherein, is the first derivative of , is the second derivative of , is the first derivative of , is the first derivative of ;

[0085] In order to improve the response speed and slow down the chattering, the improved approach law is defined as:

[0086]

[0087]

[0088] wherein, , , are to-be-designed parameters, , are approach law parameters, is a hyperbolic tangent function, is a saturation function, is a natural constant;

[0089] Let , and the simultaneous equations can obtain:

[0090]

[0091] wherein, is an electromagnetic torque reference value;

[0092] Considering that too many to-be-designed parameters in the speed loop controller result in difficulty in algorithm implementation, therefore, the improved meloidogyne optimization algorithm is adopted to perform adaptive optimization on the parameters in , and the optimal solution is found, so that the electromagnetic torque reference value is obtained;

[0093] wherein, the improved meloidogyne optimization algorithm is adopted to perform adaptive optimization on the parameters in The parameters in the adaptive optimization, specifically including:

[0094] Determine the optimization parameter matrix of the improved harvester ant optimization algorithm Wherein:

[0095] ;

[0096] Initialize the number of harvester ants, and perform adaptive optimization through the fitness function to find the optimal solution, end the iteration, complete the optimization processing, and the fitness function in the adaptive optimization process The expression is:

[0097]

[0098] Wherein, The absolute error of the speed at the moment .

[0099] After obtaining the electromagnetic torque reference value , the expression of the stator flux reference value is obtained by combining the electromagnetic torque equation in the two-phase stationary coordinate system:

[0100]

[0101]

[0102]

[0103] Wherein, , The components of the stator flux reference value on the two-phase stationary coordinate axes, The spatial position angle corresponding to the stator flux reference value, The amplitude of the stator flux reference value;

[0104] The cloud drift optimization algorithm is introduced to dynamically update the stator flux reference value. First, randomly initialize the cloud in the search space. For each cloud, its location is a candidate solution of the stator flux reference value. Second, call the fitness function of the cloud drift optimization algorithm to calculate each cloud. During the calculation process, each cloud is assigned a dynamic weight according to the fitness value of other clouds. The dynamic weight expression of the cloud is:

[0105]

[0106] Wherein, The dynamic weight of the first cloud, The random component coefficient, The distance component coefficient, The number of initialized clouds;

[0107] Further, the cloud moves to the optimal solution, and the position update equation is:

[0108]

[0109] wherein, is the position of the first cloud at the time t, is the position of the first cloud at the time t, is the velocity of the first cloud at the time t; is the position of the first cloud at the time t, is the position of the first cloud at the time t, is the velocity of the first cloud at the time t; is the position of the first cloud at the time t, is the position of the first cloud at the time t, is the velocity of the first cloud at the time t;

[0110] Finally, diversity is achieved through random motion of the cloud in the search space, and the algorithm is prevented from prematurely falling into convergence through a random disturbance mechanism. After the above steps, the position of the optimal solution is determined, and the stator flux reference value is obtained .

[0111] Step S4, based on the mathematical model of the permanent magnet synchronous motor to obtain a discrete system, and then based on the electromagnetic torque estimation value and the electromagnetic torque reference value, and the stator flux estimation value and the stator flux reference value to construct a cost function, by solving the cost function, the reference voltage vector is obtained.

[0112] Wherein, step S4 specifically includes:

[0113] Based on the mathematical model of the permanent magnet synchronous motor in the two-phase rotating coordinate system established in S1, the flux differential equation is obtained, and the expression is:

[0114]

[0115]

[0116] Further, the continuous system expression is obtained:

[0117]

[0118]

[0119]

[0120] wherein, is the derivative matrix of the system state variable, is the system state variable matrix, is the control variable matrix, is the state variable weight matrix, is the control variable weight matrix;

[0121] Further establishing a discrete system, the expression is:

[0122]

[0123]

[0124]

[0125]

[0126]

[0127] in, for The state variable matrix at time t, for The state variable matrix at time t, for Control variable matrix at all times for Output variable matrix at all times. The weight matrix is ​​a discretized state variable. The control variable weight matrix is ​​a discretized matrix. The output variable weight matrix is ​​a discretized matrix. It is the identity matrix. Sampling time;

[0128] A cost function is constructed based on the estimated and reference values ​​of electromagnetic torque, as well as the estimated and reference values ​​of stator flux linkage. The expression is:

[0129] ;

[0130] in, This is the stator flux linkage weighting coefficient. This is the electromagnetic torque weighting coefficient. For the smoothing factor weights, For the stator flux reference value in Discrete values ​​at time points, For the stator flux linkage estimate in Discrete values ​​at time points, For the electromagnetic torque reference value in Discrete values ​​at time points, For the electromagnetic torque estimate in Discrete values ​​at time points, To control the increment of quantity Discrete values ​​at time points;

[0131] By analyzing the cost function The reference voltage vector is obtained by solving the problem.

[0132] Step S5, the reference voltage vector is inversely coordinate-converted, and a hybrid random space vector pulse width modulation is adopted to generate a three-phase pulse width modulation signal, the three-phase pulse width modulation signal is sent into an inverter to drive the permanent magnet synchronous motor, and vibration noise suppression of the permanent magnet synchronous motor is realized.

[0133] The step S5 specifically comprises:

[0134] The reference voltage vector is inversely coordinate-converted to obtain a reference voltage vector in a two-phase static coordinate system, taking an example of an expected voltage vector in a third sector in a voltage space vector, vector synthesis is performed according to the volt-second balance principle to obtain:

[0135]

[0136]

[0137] wherein, is the expected voltage vector, , represents two adjacent non-zero voltage vectors in the third sector in the voltage space vector, is a zero voltage vector, represents in an action time of a pulse width modulation period, represents in an action time of a pulse width modulation period, represents in an action time of a pulse width modulation period;

[0138] Then, a hybrid random space vector pulse width modulation is adopted to generate a three-phase pulse width modulation signal, on the basis of a traditional space vector pulse width modulation technology, a hybrid random strategy is introduced, and a pulse width modulation period value and a zero vector action time in the pulse width modulation period are randomly changed, and a hybrid coefficient expression is:

[0139]

[0140] wherein, is the hybrid coefficient, is a random change amount of a carrier frequency, is a random change coefficient of the zero vector;

[0141] The action time of each vector in the hybrid random strategy space vector pulse width modulation is:

[0142]

[0143]

[0144]

[0145] wherein, is a direct current bus voltage.

[0146] Finally, the three-phase pulse width modulation signal is sent to the inverter to drive the permanent magnet synchronous motor, so as to realize vibration noise suppression of the permanent magnet synchronous motor. Specifically, according to the action time of each vector, the modulation signal of the vector control is determined, the modulation signal generated by the triangular carrier signal and the space vector pulse width modulation is compared, the pulse signal required by the inverter is generated, and the permanent magnet synchronous motor is driven, so as to realize vibration noise suppression of the motor.

[0147] Figure 2 and Figure 3 are respectively the comparison diagram of the speed and torque of the electric vehicle permanent magnet synchronous motor vibration noise suppression method proposed by the application under specific working conditions, and Figure 2 It can be seen that compared with the traditional control method, the speed can converge to the stable value faster; and Figure 3 It can be seen that compared with the electromagnetic torque obtained by the traditional control method, the pulse of the application is smaller. Therefore, the electric vehicle permanent magnet synchronous motor vibration noise suppression method proposed by the application can stabilize the error to a small value in terms of speed and torque, suppress the motor vibration noise, reduce the torque ripple and fluctuation, improve the control accuracy, and meet the design purpose of the application.

[0148] In summary, the electric vehicle permanent magnet synchronous motor vibration noise suppression method according to the above embodiment has the following beneficial effects:

[0149] (1) Considering that the traditional direct torque control utilizes hysteresis comparison to control torque and flux linkage, which will cause significant fluctuations in electromagnetic torque and stator flux linkage, the application constructs a cost function based on electromagnetic torque estimation value and electromagnetic torque reference value, as well as stator flux linkage estimation value and stator flux linkage reference value, and obtains a reference voltage vector by solving the cost function, which realizes model predictive control instead of traditional hysteresis control, and can reduce torque and flux linkage ripple.

[0150] (2) Considering that the inverter switching frequency fluctuation is large in the traditional direct torque control, which affects the control accuracy and running stability, the application uses hybrid random space vector pulse width modulation technology to replace the switching table part in the traditional direct torque control, which can improve the system control accuracy.

[0151] (3) Considering that the stator flux linkage reference value will dynamically change with the motor operating conditions, the application introduces a cloud drift optimization algorithm to realize adaptive adjustment of the reference stator flux linkage, which improves the dynamic performance of the motor.

[0152] (4) Considering that the traditional speed loop control is sensitive to system parameter changes, which will lead to the decrease of system robustness, the application proposes an improved approach law to improve the response speed and slow down the chattering, thereby improving the control performance of the speed loop.

[0153] (5) The application can effectively suppress motor vibration noise, reduce torque ripple and fluctuation, improve the control performance and operation stability of the permanent magnet synchronous motor, and make the electric vehicle have smaller vibration noise under complex working conditions.

[0154] The above-mentioned embodiments only express several embodiments of the application, and the description is more specific and detailed, but it cannot be understood as the limitation of the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the application, some modifications and improvements can be made, which belong to the protection scope of the application. Therefore, the protection scope of the patent of the application should be subject to the appended claims.

Claims

1. A vibration noise suppression method for an electric vehicle permanent magnet synchronous motor, characterized by, The application relates to a vibration noise suppression method for a permanent magnet synchronous motor. The method comprises the following steps: Step S1, collecting parameter information of the permanent magnet synchronous motor in real time, and then establishing a permanent magnet synchronous motor mathematical model in different coordinate systems through coordinate transformation; Step S2, constructing a torque and flux observer based on the permanent magnet synchronous motor mathematical model, so as to obtain an electromagnetic torque estimation value and a stator flux estimation value; Step S3, obtaining an electromagnetic torque reference value through speed loop control, and obtaining a stator flux reference value based on the electromagnetic torque reference value and introducing a cloud drift optimization algorithm; Step S4, obtaining a discrete system based on the permanent magnet synchronous motor mathematical model, and then constructing a cost function based on the electromagnetic torque estimation value and the electromagnetic torque reference value and the stator flux estimation value and the stator flux reference value, and obtaining a reference voltage vector by solving the cost function; Step S5, performing inverse coordinate conversion on the reference voltage vector, adopting hybrid random space vector pulse width modulation to generate a three-phase pulse width modulation signal, and sending the three-phase pulse width modulation signal into an inverter to drive the permanent magnet synchronous motor, so that vibration noise suppression of the permanent magnet synchronous motor is realized. wherein is a stator voltage vector, , , , is an A-phase stator voltage, a B-phase stator voltage, a C-phase stator voltage, respectively, denotes a transpose, is a stator current vector, , , , is an A-phase stator current, a B-phase stator current, a C-phase stator current, respectively, is a stator resistance, is a stator flux vector, , , , is an A-phase stator flux, a B-phase stator flux, a C-phase stator flux, respectively, denotes time, denotes a differential, is an inductance matrix, is a flux generated by a rotor permanent magnet; In step S1, the parameter information of the permanent magnet synchronous motor satisfies the following formula: In step S1, permanent magnet synchronous motor mathematical models in a two-phase static coordinate system and a two-phase rotating coordinate system are established through coordinate transformation; wherein , are the components of the stator voltage on the two-phase stationary coordinate axes, , are the components of the stator current on the two-phase stationary coordinate axes, , are the components of the stator flux linkage on the two-phase stationary coordinate axes; The stator voltage expression in the two-phase static coordinate system is as follows: The stator flux expression in the two-phase static coordinate system is as follows: wherein , is the component of the stator voltage on the two-phase rotating coordinate axis, , is the component of the stator current on the two-phase rotating coordinate axis, , is the component of the stator flux on the two-phase rotating coordinate axis, is the electrical angular velocity; The stator voltage expression in the two-phase rotating coordinate system is as follows: wherein , are components of the stator inductance on the two-phase rotating coordinate axes.

2. The vibration noise suppression method for electric vehicle permanent magnet synchronous motor according to claim 1, characterized in that, The stator flux expression in the two-phase rotating coordinate system is as follows: Step S2 specifically comprises the following steps: wherein , is the stator back EMF in two-phase stationary coordinates, is the stator back EMF of the permanent magnet synchronous motor, is the imaginary unit; Based on the permanent magnet synchronous motor mathematical model in the two-phase static coordinate system, the expression of the stator flux observation model is obtained as follows: wherein is the Laplacian operator, is the cut-off frequency of the filter; Compensation control is introduced, and the compensation amount is defined , and the expression is A joint filter is constructed, and the transfer function expression of the joint filter is as follows: wherein, is the stator flux linkage estimate based on the voltage model; The stator flux observation expression based on the voltage model is as follows: wherein, is a stator flux linkage estimate based on a current model; The stator flux observation expression based on the current model is as follows: wherein is a stator flux linkage estimate, is a high pass filter weight, is a low pass filter weight, , is a stator flux linkage estimate in two-phase stationary coordinate axes; The stator flux observation expression based on the voltage model and the stator flux observation expression based on the current model are fused, and the following formula is obtained: wherein is an electromagnetic torque estimate, is the number of pole pairs.

3. The vibration noise suppression method for electric vehicle permanent magnet synchronous motor according to claim 2, characterized in that, According to the observed stator flux estimation value, the electromagnetic torque estimation value is calculated through the electromagnetic torque equation in the two-phase static coordinate system, and the expression is as follows: In the speed loop control, the speed error is defined as: e = ωref - ω wherein is the reference rotational speed, is the mechanical angular velocity; Step S3 specifically comprises the following steps: wherein, is the moment of inertia, is the electromagnetic torque, is the load torque, is the damping coefficient; The mechanical motion expression of the permanent magnet synchronous motor is as follows: wherein is the first derivative of is the first derivative of is the first derivative of Defining a sliding surface is: wherein , is a state variable, , , , , , are constants, and , , ; The expression of the speed error is derived, and the mechanical motion expression of the permanent magnet synchronous motor is obtained as follows: wherein is the first derivative of is the second derivative of is the first derivative of is the first derivative of Defining improved approach law is: wherein , , is a parameter to be designed, , is a parameter of the approaching law, is a hyperbolic tangent function, is a saturation function, is a natural constant; Let , the simultaneous equations can be obtained: wherein is the electromagnetic torque reference value; Adopting the improved melolontha optimization algorithm to perform adaptive optimization on the parameters in , find the optimal solution, and thus obtain the electromagnetic torque reference value ; After obtaining the electromagnetic torque reference value Then, the expression of the stator flux linkage reference value is obtained by combining the electromagnetic torque equation in the two-phase stationary coordinate system. wherein, , is a component of the stator flux reference value on the two-phase stationary coordinate axis, is a spatial position angle corresponding to the stator flux reference value, is a magnitude of the stator flux reference value; Further derivation is performed, and the following formula is obtained: wherein, is the dynamic weight of the th cloud, is the random component coefficient, is the distance component coefficient, is the number of initialized clouds; The cloud drift optimization algorithm is introduced to dynamically update the stator flux reference value. Firstly, the cloud is randomly initialized in the search space, and the position of each cloud is a candidate solution of the stator flux reference value; secondly, the fitness function of the cloud drift optimization algorithm is called to calculate each cloud, and in the calculation process, each cloud is assigned a dynamic weight according to the fitness values of other clouds, and the dynamic weight expression of the cloud is as follows: wherein, is the position of the nth cloud at time t, is the velocity of the nth cloud at time t, is the position of the nth cloud at time t, is the velocity of the nth cloud at time t, is the velocity of the nth cloud at time t,​​​​ Finally, the position of the optimal solution is determined by the random motion of the cloud in the search space, so as to obtain the stator flux linkage reference value .

4. The vibration noise suppression method for electric vehicle permanent magnet synchronous motor according to claim 3, characterized in that, In step S3, an improved dung beetle optimization algorithm is used to... The parameters in the data are adaptively optimized, specifically including: Determining an improved optimization parameter matrix for a dung beetle optimization algorithm wherein: ； Initialize the number of ants, and through the fitness function, find the optimal solution, end iteration, complete optimization processing, fitness function in adaptive optimization process The expression is: wherein is absolute error of the rotational speed at the moment.

5. The vibration noise suppression method for electric vehicle permanent magnet synchronous motor according to claim 4, characterized in that, Further, the cloud moves to the optimal solution, and the position updating equation is as follows: Step S4 specifically comprises the following steps: Based on the permanent magnet synchronous motor mathematical model in the two-phase rotating coordinate system established in S1, the flux differential equation is obtained, and the expression is as follows: wherein, is a system state variable derivative matrix, is a system state variable matrix, is a control variable matrix, is a state variable weight matrix, is a control variable weight matrix; Further, the continuous system expression is obtained as follows: wherein is the state variable matrix at time instant is the state variable matrix at time instant is the control variable matrix at time instant is the output variable matrix at time instant is the discretized state variable weight matrix, is the discretized control variable weight matrix, is the discretized output variable weight matrix, is the identity matrix, is the sampling time; A cost function is constructed based on the electromagnetic torque estimate and the electromagnetic torque reference value, and the stator flux linkage estimate and the stator flux linkage reference value , the expression being: ; in, This is the stator flux linkage weighting coefficient. This is the electromagnetic torque weighting coefficient. For the smoothing factor weights, For the stator flux reference value in Discrete values ​​at time points, For the stator flux linkage estimate in Discrete values ​​at time points, For the electromagnetic torque reference value in Discrete values ​​at time points, For the electromagnetic torque estimate in Discrete values ​​at time points, To control the increment of quantity Discrete values ​​at time points; The reference voltage vector is obtained by solving the cost function with respect to the reference voltage vector.

6. The vibration noise suppression method for electric vehicle permanent magnet synchronous motor according to claim 5, characterized in that, Further, the discrete system is established, and the expression is as follows: Step S5 specifically comprises the following steps: First, the reference voltage vector is inversely coordinate-converted to obtain a reference voltage vector in a two-phase stationary coordinate system, and then a hybrid random space vector pulse width modulation is adopted to generate a three-phase pulse width modulation signal, in which the following formula is met: wherein is a mixing coefficient, is a random variation of the carrier frequency, is a random variation coefficient of the zero vector; Finally, the three-phase pulse width modulation signal is sent to an inverter to drive the permanent magnet synchronous motor, so as to realize vibration noise suppression of the permanent magnet synchronous motor.

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