An imbalance control method for a flywheel energy storage active magnetic levitation bearing system

Abstract

This invention relates to an unbalance control method for an active magnetic levitation bearing system for flywheel energy storage. The method involves placing displacement sensors around the rotor and connecting these sensors to a controller via an adaptive notch filter with a frequency estimation unit. The steps include: establishing a model of the active magnetic levitation bearing system containing the unbalanced mass and deriving the component expressions of the unbalanced force in the x and y directions; determining the transfer function of the adaptive notch filter and extracting the same-frequency vibration signal from the rotor displacement signal using the adaptive notch filter; estimating the rotor speed using the output signal of the adaptive notch filter and determining the expression for the estimated speed; and feeding back the unbalanced same-frequency quantity obtained after passing through the adaptive notch filter with the frequency estimation unit to the active magnetic levitation bearing system to eliminate the same-frequency current and achieve automatic rotor balancing. This invention achieves automatic balancing of the magnetic levitation flywheel without the need for an external speed sensor.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of magnetic suspension rotor vibration suppression, in particular to an unbalance control method for a flywheel energy storage active magnetic bearing system. BACKGROUND

[0002] Flywheel energy storage mainly stores energy through high-speed rotation, and how to reduce bearing mechanical friction loss is a key problem to ensure the good performance of flywheel energy storage. Due to the advantages of active magnetic bearing such as no mechanical friction, no need for lubrication, controllable electromagnetic force, etc., it is more and more widely used in the field of high-speed spindle, high-speed motor and flywheel energy storage and other high-speed rotating machinery. The uneven rotor material, part processing and assembly error and other reasons will cause the rotor mass imbalance, and the excitation force caused by the eccentric mass will cause the rotor to vibrate at the same frequency as the speed. If this vibration is not eliminated or reduced, the control accuracy of the magnetic suspension rotor will be seriously affected, and even the system may be damaged. Due to the change of the working condition of the active magnetic bearing system and the limitation of the correction accuracy, the rotor still has residual unbalance after applying the traditional on-site dynamic balancing technology. Therefore, it is necessary to select a reasonable algorithm to suppress the unbalance vibration by using the adjustable stiffness and damping characteristics of the active magnetic bearing.

[0003] At present, many scholars have studied the suppression algorithm for unbalanced vibration, and the main methods are as follows: the first method is unbalance compensation, the main idea of which is to extract the same frequency vibration signal in the rotor displacement signal, calculate a force equal in size and opposite in direction to the unbalanced force, and offset each other, aiming to achieve "zero displacement control", improve the rotation accuracy of the rotor and constrain the rotation of the rotor around the geometric axis. The commonly used control methods at present mainly include influence coefficient method, model identification based method, etc., but this method is easy to cause the saturation of the power amplifier circuit at high speed, and the reaction force will be transmitted to the base to produce vibration, so this method is suitable for occasions with high requirements for rotor displacement accuracy. The second method is automatic balancing, the main idea of which is to directly offset or filter out the same frequency component in the displacement sensor output signal, so that the controller does not respond to the same frequency vibration signal, and the rotor rotates around the inertia axis, aiming to achieve "zero current or zero bearing force control". The commonly used methods at present include LMS algorithm, generalized notch filter, etc. This method can avoid the saturation of the power amplifier circuit, so it is the best choice for high-speed rotor vibration suppression.

[0004] However, the above methods all need the angular velocity feedback of the rotor to be realized, and the traditional scheme usually obtains it by a Hall speed sensor, an optical encoder and the like. However, the angular velocity sensor has some limitations in many applications, including limited mechanical size, low reliability and cost limitations, and once the angular velocity sensor has a large error or fails, the control system will not be able to obtain an accurate speed signal, so it is necessary to estimate the actual speed of the rotor. For the angular velocity estimation problem of the magnetic suspension bearing rotor, Lee et al. proposed to differentiate the angular position to estimate the rotor speed, but this method is easy to introduce noise. Zhang et al. obtained the speed signal by Hilbert spectrum analysis of the high frequency component in the rotor displacement signal, which although improves the accuracy, but the frequency component is unstable at low speed. Liu et al. constructed a BP neural network speed measurement model according to the existing displacement signal and speed signal, but this method excessively depends on the initial displacement and speed data of the rotor, and has a large amount of calculation. SUMMARY

[0005] The application provides a flywheel energy storage active magnetic suspension bearing system imbalance control method, which can overcome the shortcomings of the existing imbalance vibration suppression algorithm of the magnetic suspension flywheel energy storage system.

[0006] The technical scheme adopted by the application to solve the technical problem is: an active magnetic suspension bearing system imbalance control method is provided, a displacement sensor is arranged around a rotor, the displacement sensor is connected to a controller through an adaptive notch filter with a frequency estimation unit, and the method comprises the following steps:

[0007] (1) an active magnetic suspension bearing system model containing an imbalance mass is established, and expressions of x and y direction components of the imbalance force are derived;

[0008] (2) a transfer function of the adaptive notch filter is determined, and a same frequency vibration signal in the rotor displacement signal is extracted through the adaptive notch filter;

[0009] (3) the speed of the rotor is estimated through the output signal of the adaptive notch filter, and an expression of the estimated speed is determined;

[0010] (4) the imbalance same frequency quantity obtained after passing through the adaptive notch filter with the frequency estimation unit is fed back to the active magnetic suspension bearing system to eliminate the same frequency current and realize automatic balancing of the rotor.

[0011] The active magnetic suspension bearing system model in the step (1) is: wherein, and are coordinates of a geometric center C of the rotor in a fixed coordinate system O-xy, and are coordinates of a mass center G of the rotor in the fixed coordinate system O-xy, eccentricity of the rotor, rotation angle of the rotor.

[0012] The expression of the components of the unbalance force in the x and y directions in step (1) is: wherein, and are the components of the unbalance force in the x and y directions, respectively, and are the angular velocity and the angular acceleration of the rotor, respectively, is the mass of the rotor.

[0013] The two-phase transfer function of the adaptive notch filter in step (2) is: Let when the gain of the adaptive notch filter is not zero, then: wherein, and are the two-phase transfer function of the adaptive notch filter, respectively, and are the two-phase output signals of the adaptive notch filter, respectively, is the Laplace operator, is the center frequency of the adaptive notch filter, represents the actual rotor speed, is a minimum value of the rotor speed.

[0014] When the estimated rotor speed is the center frequency of the adaptive notch filter in step (2), the output signal will completely track the input rotor displacement signal v, and the output signal is a quadrature signal with the same amplitude absolute value as the output signal , and at this time the unbalance vibration quantity with the same frequency as the rotor speed is extracted.

[0015] In step (3), the rotor speed is estimated by wherein, and represent the value of the output signal and the value of the output signal , respectively.

[0016] The controller makes the estimated rotor speed infinitely close to the center frequency of the adaptive notch filter by integral closed-loop control, and the expression of the integral closed-loop control is: wherein, is the gain coefficient of the integral closed-loop control, ​is Laplace operator.

[0017] The transfer function of the adaptive notch filter with the frequency estimation unit is expressed as: .

[0018] The transfer function expression from the unbalance disturbance to the control current is: where, , , , , are the transfer functions of the displacement sensor, the rotor, the controller and the power amplifier respectively.

[0019] Advantages

[0020] Compared with the prior art, the present application has the following advantages and positive effects: the present application does not need an additional rotating speed sensor, and can monitor the rotating speed of the flywheel by means of a simple frequency estimation unit, thereby realizing automatic balancing of the magnetic suspension flywheel, and the whole method has low calculation amount and clear and simple parameter design. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a sectional view of the structure of the flywheel energy storage active magnetic suspension bearing system;

[0022] Figure 2 is a schematic diagram of the unbalanced mass in the flywheel energy storage active magnetic suspension bearing system;

[0023] Figure 3 is a control block diagram of the embodiment of the present application;

[0024] Figure 4 is a block diagram of the adaptive notch filter in the embodiment of the present application;

[0025] Figure 5 is a block diagram of the frequency estimation unit in the embodiment of the present application;

[0026] Figure 6 is a block diagram of the controller in the embodiment of the present application;

[0027] Figure 7 is a diagram of the displacement trajectory and the frequency estimation trajectory of the upper end of the rotor before and after compensation under the condition of a signal-to-noise ratio of 10 dB. DETAILED DESCRIPTION

[0028] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0029] The embodiments of the present invention relate to an imbalance control method for an active magnetic levitation bearing system. This method can be applied to a flywheel energy storage active magnetic levitation bearing system, and its structure is as follows: Figure 1 As shown, it includes: a magnetically levitated flywheel rotor 4, and a radial displacement sensor 1 and an axial displacement sensor 5 disposed on the side of the magnetically levitated flywheel rotor 4. Both the radial displacement sensor 1 and the axial displacement sensor 5 are connected to the magnetic levitation control unit 3. The output terminal of the magnetic levitation control unit 3 is connected to a power amplifier 2, and the power amplifier 2 applies an amplified control current to the magnetically levitated flywheel rotor 4. Figure 3 The diagram shown is a control block diagram of the imbalance control method in this embodiment. The magnetic levitation control unit 3 used in this embodiment includes an adaptive notch filter with a frequency estimation unit and a controller connected to each other. The imbalance control specifically includes the following steps:

[0030] Step 1: Establish a model of the flywheel energy storage active magnetic levitation bearing system containing unbalanced mass, and derive the component expressions of the unbalanced force in the x and y directions. For example... Figure 2 As shown, in the flywheel energy storage active magnetic levitation bearing system, due to the existence of mass imbalance, the rotor geometric center C and the center of mass G do not coincide. The coordinates of the rotor geometric center C in the fixed coordinate system O-xy are (x... c y c The coordinates of the centroid G in the fixed coordinate system O-xy are (x g y g ), where Ω is the rotor speed, from which we can obtain the coordinate relationship between the rotor's center of mass and centroid, and the component equations of the unbalanced force in the x and y directions:

[0031]

[0032]

[0033] in, The eccentricity of the flywheel rotor. The rotation angle of the flywheel rotor. and These are the components of the unbalanced force in the x and y directions, respectively. and These are the rotational angular velocity and rotational angular acceleration of the flywheel rotor, respectively. Let be the mass of the flywheel rotor.

[0034] Step 2, determine the transfer function of the adaptive notch filter, and extract the same frequency vibration signal in the flywheel rotor displacement signal through the adaptive notch filter.

[0035] Figure 4 is the block diagram of the adaptive notch filter in the embodiment, and the two-phase transfer function is: Let When the gain of the adaptive notch filter is not zero, then: wherein, and represent the two-phase transfer function of the adaptive notch filter, and are the two-phase output signals of the adaptive notch filter, is the Laplace operator, is the center frequency of the adaptive notch filter, represents the actual rotor speed, is a minimum value of the rotor speed.

[0036] When the estimated rotor speed is the center frequency of the adaptive notch filter , the output signal will completely track the input flywheel rotor displacement signal v, and the output signal is the orthogonal signal with the same amplitude absolute value as the output signal , and at this time the unbalanced vibration quantity with the same frequency as the rotor speed is extracted.

[0037] Step 3, estimate the rotor speed of the flywheel through the output signal of the adaptive notch filter, and determine the expression of the estimated rotor speed. In this step, the rotor speed of the flywheel is estimated by a frequency estimation unit, and the structure of the frequency estimation unit is as shown in Figure 5 , which estimates the rotor speed of the flywheel through , wherein, and represent the value of the output signal and the value of the output signal , respectively.

[0038] The controller in the embodiment adopts integral closed-loop control, and through the integral closed-loop control, the estimated rotor speed is infinitely close to the center frequency of the adaptive notch filter , and the integral closed-loop control expression is: , wherein, is the gain coefficient of the integral closed-loop control, is the Laplace operator.

[0039] The final implementation of the rotor speed estimation value in the embodiment is:​ wherein, is a constant positive convergence factor.

[0040] The transfer function from the monitored rotor displacement signal v to the error signal e' (i.e. the transfer function of the adaptive notch filter with frequency estimation unit) is expressed as: The transfer function from the unbalance disturbance to the control current is expressed as: wherein, , , , , are the transfer functions of the displacement sensor, the rigid rotor, the controller and the power amplifier, respectively.

[0041] Step 4: The unbalance disturbance to the control current is zero when the frequency estimation unit correctly identifies the rotor frequency, and the same frequency vibration signal extracted by the adaptive notch filter with frequency estimation unit is fed back to the original active magnetic bearing flywheel energy storage system to eliminate the same frequency current and achieve automatic balancing of the rotor.

[0042] Figure 7 are the displacement trajectories and frequency estimation trajectories of the rotor upper end before and after compensation under the condition of signal-to-noise ratio of 10 dB. By comparison, it can be seen that the method of the present embodiment can better suppress the unbalanced vibration, and the method of the present embodiment does not need an additional speed sensor, but relies on a simple frequency estimation unit to monitor the flywheel speed, thereby achieving automatic balancing of the magnetic suspension flywheel. The whole method has low calculation amount and clear and simple parameter design.

Claims

1. A method of unbalance control for an active magnetic bearing system, characterized by, A displacement sensor is arranged on the periphery of the rotor, and the displacement sensor is connected to a controller through an adaptive notch filter with a frequency estimation unit, comprising the following steps: (1) establishing a model of the active magnetic suspension bearing system containing unbalanced mass, and deducing the component expression of the unbalanced force in x and y directions; (2) Determine the transfer function of the adaptive notch filter, and extract the same-frequency vibration signal from the rotor displacement signal through the adaptive notch filter; when the estimated rotational speed is the center frequency of the adaptive notch filter. At that time, the output signal of the adaptive notch filter The output signal will completely track the input rotor displacement signal v. To be consistent with the output signal Orthogonal signals with equal absolute amplitudes are used to extract unbalanced vibrations that are at the same frequency as the rotational speed. (3) estimating the rotational speed of the rotor by the output signal of the adaptive notch filter and determining an expression of the estimated rotational speed; wherein the estimating is performed by estimating the rotational speed of the rotor, wherein for estimating the rotational speed, and represent the value of the output signal and the value of the output signal respectively, is the gain of the adaptive notch filter; the controller makes the estimated rotational speed unlimitedly close to the center frequency of the adaptive notch filter by integral closed loop control, and the expression of the integral closed loop control is: wherein is the gain coefficient of the integral closed loop control, is the Laplace operator; (4) the unbalance homochromatic quantity after adaptive notch filter with frequency estimation unit is fed back to the active magnetic suspension bearing system to eliminate homochromatic current and realize automatic balancing of the rotor; the transfer function of the adaptive notch filter with frequency estimation unit is represented as: .

2. The active magnetic bearing system imbalance control method of claim 1, wherein, The model of the active magnetic suspension bearing system in step (1) is: wherein, and is the coordinate of the geometric center C of the rotor in the fixed coordinate system O-xy, and is the coordinate of the center of mass G of the rotor in the fixed coordinate system O-xy, is the eccentricity of the rotor, is the rotation angle of the rotor.

3. The active magnetic bearing system imbalance control method of claim 2, wherein, The component expressions of the unbalance force in x, y direction in step (1) are: wherein, and are the components of the unbalance force in x, y direction, respectively, and are the angular velocity and angular acceleration of the rotation of the rotor, respectively, is the mass of the rotor.

4. The active magnetic bearing system imbalance control method of claim 1, wherein, The two-phase transfer function of the adaptive notch filter in step (2) is: Let When the gain of the adaptive notch filter is not zero, then: wherein, and denote the two-phase transfer function of the adaptive notch filter, and are the two-phase output signals of the adaptive notch filter, denotes the actual rotor speed, is a minimum value of the rotor speed.​ 5. The active magnetic bearing system imbalance control method of claim 1, wherein, The active magnetic levitation bearing system is protected from unbalanced disturbances. To control current The transfer function expression is: ,in, , , , , These are the transfer functions of the displacement sensor, rotor, controller, and power amplifier, respectively.

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