Small VAWT sensorless control method based on improved nonlinear double-loop ADRC

Abstract

The invention discloses a small VAWT sensorless control method based on an improved nonlinear double-loop ADRC. The response real-time performance and the operation stability of a small vertical axis fan under the complex condition of parameter change can be improved. Improved nonlinear ADRC controllers are designed in a rotating speed loop and a current loop, an improved new-fal function is used for replacing an original fal function, LSEFCR is designed to reduce nonlinear second-order ESO parameter adjustment complexity and enhance system dynamic characteristics, adaptive filtering is added on the basis of an original sliding-mode observer, a normalized feedforward PLL is used for obtaining rotor speed and position information, and the speed and position information of a rotor can be obtained. The motor response speed is effectively improved, the control error is reduced, and the overall stability of the system is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of fan control, and in particular relates to a small VAWT sensorless control method based on improved nonlinear dual-loop ADRC. Background Art

[0002] Small vertical axis wind turbines (VAWT) have the advantages of simple structure, high wind energy utilization, and no need for yaw devices. Therefore, compared with large wind power generation systems, they have wider application prospects in harsh environments.

[0003] The wind drives the blades of the wind turbine, which converts wind energy into electrical energy through the generator and adjusts the motor speed according to the wind speed. As an important component of energy conversion, permanent magnet synchronous motors (PMSM) are currently used in the field of wind power generation. The traditional PI control is used as the drive control strategy for this motor. However, this control strategy has many shortcomings. Its working principle is to control through error feedback and then eliminate the error. When encountering disturbances, there is obvious hysteresis. When responding quickly, it is easy to produce obvious overshoot. Therefore, the control effect is not good for multi-coupled complex nonlinear systems such as wind power generation.

[0004] Therefore, researchers have introduced more nonlinear control strategies, among which Active Disturbance Rejection Control (ADRC) is suitable for wind power generation systems because of its stronger robustness, adaptability and dynamic response capabilities. For example, the literature [Zhu Keke, Ruan Lin. Permanent magnet direct-drive wind turbine active disturbance rejection technology and its position sensorless control strategy [J]. Acta Energiae Solaris Sinica, 2022, 43 (10): 266-274] adopts a linear ADRC control strategy, which simplifies the parameter setting process but weakens the algorithm's ability to suppress high-frequency noise. The literature [Liu Chunqiang, Luo Guangzhao, Tu Wencong et al. Dual-loop servo system based on active disturbance rejection control [J]. Proceedings of the CSEE, 2017, 37: 7032-7039+7095] uses nonlinear ADRC control in the speed loop to enhance the robustness of the system, but the parameter setting process of this control strategy is cumbersome and requires high hardware processing capabilities, which is insufficient for harsh scenarios such as wind turbine applications.

[0005] It can be seen from this that when wind power generation is applied to harsh scenarios, in order to reduce the subsequent operation and maintenance costs of the equipment, sensorless control should be combined to improve system stability. Summary of the invention

[0006] In view of the above, the present invention provides a small VAWT sensorless control method based on improved nonlinear dual-loop ADRC, which can improve the real-time response and operation stability of small vertical axis fans under complex conditions of parameter changes, and is simple, practical, safe and reliable.

[0007] A sensorless control method for a small VAWT based on an improved nonlinear dual-loop ADRC comprises the following steps:

[0008] (1) Collect the three-phase stator current of VAWT and calculate the stator current i of α and β axes through coordinate transformation α and i β , stator voltage u α and u β And the stator current i of the dq axis d and i q ;

[0009] (2) According to the stator current i α and i β And the stator voltage u α and u β The extended back electromotive force E of the αβ axis is calculated by the sliding mode observer α and E β , and design an adaptive filter for E α and E β Perform filtering;

[0010] (3) According to the extended back electromotive force e after filtering α and e β The rotor position observation value of VAWT is obtained through PLL (phase-locked loop) feedforward compensation and speed observations

[0011] (4) Design a speed loop anti-disturbance control controller based on the second-order ESO (Extended State Observer), LSEFCR (linear state error feedback control rate) and new-fal function to control the speed error and obtain the q-axis current reference value i q * ;

[0012] (5) Design a current loop anti-disturbance controller based on second-order ESO, LSEFCR and new-fal function to control the current error of the dq axis and obtain the stator voltage command value u of the dq axis d * and u q *, thereby controlling the VAWT.

[0013] Furthermore, the transfer function expression of the adaptive filter in step (2) is as follows:

[0014]

[0015] Where: k is the adaptive coefficient (k>0), s is the Laplace operator, ω e is the actual speed of the VAWT.

[0016] Furthermore, the expression of the speed loop anti-disturbance control in step (4) is as follows:

[0017]

[0018] in: is the estimated value of the rotation speed, is the disturbance estimate, and They are and The first derivative of e is the actual speed of VAWT, e1 is the error between the estimated speed and the actual speed, u0 is the output of LSEFCR, h(e1,δ1) and h(e1,δ2) are the new-fal functions about the error e1, β1 and β2 are the correction gains (β1>0, β2>0), J is the moment of inertia of VAWT, p n is the pole pair number of VAWT, ψ f is the permanent magnet flux linkage of VAWT, k p is the gain coefficient, ω e * is the speed reference value of VAWT.

[0019] Furthermore, the expressions of the new-fal functions h(e1, δ1) and h(e1, δ2) are as follows:

[0020]

[0021] Among them: δ1 and δ2 are given constants.

[0022] Furthermore, the expression of the current loop anti-disturbance control in step (5) is as follows:

[0023]

[0024] in: is the estimated value of d-axis current, is the estimated value of the d-axis disturbance, and They are and The first derivative of is the estimated value of q-axis current, is the estimated value of the q-axis disturbance, and They are and The first derivative of 1d is the error between the estimated d-axis current and the actual d-axis current, e 1q is the error between the estimated q-axis current and the actual q-axis current, u 0d and u 0q is the output of LSEFCR, h(e 1d ,δ 1d ) and h(e 1d ,δ 2d ) is about the error e 1d The new-fal function, h(e 1q ,δ 1q ) and h(e 1q ,δ 2q ) is about the error e 1q The new-fal function, β 1d , β 2d , β 1q , β 2q is the correction gain (β 1d >0,β 2d >0,β 1q >0,β 2q >0), J is the moment of inertia of VAWT, p n is the pole pair number of VAWT, ψ f is the permanent magnet flux linkage of VAWT, k pd and k pq is the gain coefficient, i d * is the d-axis current reference value and i d * =0,u d and u q are the d-axis stator voltage and the q-axis stator voltage respectively.

[0025] Furthermore, the new-fal function h(e 1d ,δ 1d ) and h(e 1d ,δ 2d ) and h(e 1q ,δ 1q ) and h(e 1q ,δ 2q ) is as follows:

[0026]

[0027] Where: 1d , δ 2d , δ 1q and δ 2q are all given constants.

[0028] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the above-mentioned small VAWT sensorless control method based on improved nonlinear dual-loop ADRC.

[0029] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program is used to implement the above-mentioned small VAWT sensorless control method based on improved nonlinear dual-loop ADRC.

[0030] The present invention applies an improved nonlinear dual-loop ADRC small VAWT sensorless control method, designs improved nonlinear ADRC controllers in both the speed loop and the current loop, uses an improved new-fal function to replace the original fal function, designs LSEFCR to reduce the complexity of nonlinear second-order ESO parameter adjustment, enhances the dynamic characteristics of the system, adds adaptive filtering on the basis of the original sliding mode observer, adopts normalized feedforward PLL to obtain rotor speed and position information, effectively improves the motor response speed, reduces the control error, and improves the overall stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a block diagram of a small VAWT sensorless control system based on an improved nonlinear dual-loop ADRC according to the present invention.

[0032] Figure 2 This is the block diagram of the improved speed loop anti-disturbance controller.

[0033] Figure 3 The block diagram of the improved d-axis current loop anti-disturbance controller.

[0034] Figure 4 The block diagram of the improved q-axis current loop anti-disturbance controller.

[0035] Figure 5 This is the equivalent block diagram of the PLL.

[0036] Figure 6 It is a schematic diagram of the speed tracking motor without improved ADRC sensorless control.

[0037] Figure 7 Schematic diagram of the improved ADRC sensorless control tracking motor speed.

[0038] Figure 8 Schematic diagram of the speed error of the motor tracked without improved ADRC sensorless control.

[0039] Fig. 9 Schematic diagram of the speed error of the improved ADRC sensorless control tracking motor.

[0040] Fig.10 It is a schematic diagram of the position of the motor without improved ADRC sensorless control tracking.

[0041] Fig.11 Schematic diagram of the position of the improved ADRC sensorless control tracking motor.

[0042] Fig.12 Schematic diagram of position error of the motor tracked by sensorless control without improved ADRC.

[0043] Fig.13 Schematic diagram of the position error of the improved ADRC sensorless control tracking motor. DETAILED DESCRIPTION

[0044] In order to describe the present invention more specifically, the technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0045] The present invention is based on a small VAWT sensorless control method based on an improved nonlinear dual-loop ADRC, comprising the following steps:

[0046] (1) Based on aerodynamic knowledge and Betz theory, the mechanical power P that a wind turbine can obtain under ideal conditions is m for:

[0047]

[0048] Where: ρ0 is air density, r is blade radius, v is wind speed, C p is the wind energy utilization rate.

[0049] C p The expression is:

[0050]

[0051] In the above formula: λ is the tip speed ratio, ω r is the wind turbine angular velocity, and β is the pitch angle. For a fixed pitch angle, there is an optimal tip speed ratio λ0, which can obtain the maximum wind energy utilization coefficient C pmax , so that the fan output power is maximized.

[0052] (2) Decouple the motor excitation component and torque component, control them separately, and simplify the motor mathematical model to obtain the electromagnetic torque equation:

[0053]

[0054] For SPMSM, due to the direct-axis inductance L d and L q are equal, so the electromagnetic torque equation can be further simplified as:

[0055]

[0056] Where: T e is the electromagnetic torque of the motor, P n is the number of pole pairs of the permanent magnet, ψ f is the permanent magnet flux.

[0057] Due to the fan angular velocity ω r and the motor angular velocity ω m The same, so the mechanical torque T m for:

[0058]

[0059] The mechanical motion equation of the wind turbine is:

[0060]

[0061] Where: J is the moment of inertia, B is the damping coefficient.

[0062] Based on the electromagnetic torque equation and the mechanical motion equation, the speed estimation equation can be obtained as follows:

[0063]

[0064] Where: make is the disturbance f.

[0065] Because e =p n ω m , take z1=ω e , z2=f, design a second-order ESO to observe the state variables and disturbances in real time, and the following expanded equation can be obtained:

[0066]

[0067] Where: e1 is the difference between the estimated speed and the actual speed, is the estimated value of the rotation speed, is the disturbance estimate, and They are and The first-order derivative of , β1 and β2 are correction gains, β1>0, β2>0.

[0068] Since the speed loop of the wind turbine can be regarded as a first-order controlled system, the design is as follows: Figure 2 The first-order ADRC shown in the figure is used for control, but since the fal function used in the traditional ADRC has poor smoothness, an improved nonlinear smooth function is designed to replace it, and this function is named new-fal function.

[0069] The traditional fal function is as follows:

[0070]

[0071] The designed new-fal is:

[0072]

[0073] The improved second-order ESO is as follows:

[0074]

[0075] In order to reduce the complexity of nonlinear second-order ESO parameter adjustment and enhance the system dynamic characteristics, LSEFCR is designed as follows:

[0076]

[0077] Where: K p is the controller gain coefficient, u0 is the controller output, ω e * is the reference input speed, is the estimated value of the speed.

[0078] Finally, the q-axis current reference value i is calculated by the following formula q * :

[0079]

[0080] (3) According to the basic structure and working principle of SPMSM, the stator voltage equation in dq axis coordinates is established.

[0081] Since the air gap magnetic field of SPMSM is uniform and the inductance of the AC and DC axes is basically the same, i d =0 double closed-loop vector control method. Assuming that the three-phase stator winding of the motor is symmetrical, the waveform of the induced back electromotive force on the stator side is a standard sine wave when the motor rotates, and ignoring the core saturation, the stator voltage equation of the SPMSM in the two-phase rotating coordinate system is as follows:

[0082]

[0083] Where: u d 、u q 、id 、i q are the voltage and current components in the dq coordinate system, R is the stator resistance, L d and L q is the stator dq axis inductance, ω e is the electrical angular velocity, ψ f is the permanent magnet flux.

[0084] Similar to the above speed loop ADRC design, the improved nonlinear ADRC is applied to the current loop as follows: Figure 3 and Figure 4 As shown; therefore, the expression of the current loop anti-disturbance controller is as follows:

[0085]

[0086] in: is the estimated value of d-axis current, is the estimated value of the d-axis disturbance, and They are and The first derivative of is the estimated value of q-axis current, is the estimated value of the q-axis disturbance, and They are and The first derivative of 1d is the error between the estimated d-axis current and the actual d-axis current, e 1q is the error between the estimated q-axis current and the actual q-axis current, u 0d and u 0q is the output of LSEFCR, h(e 1d ,δ 1d ) and h(e 1d ,δ 2d ) is about the error e 1d The new-fal function, h(e 1q ,δ 1q ) and h(e 1q ,δ 2q ) is about the error e 1q The new-fal function, β 1d , β 2d , β 1q , β 2q is the correction gain (β 1d >0,β 2d >0,β 1q >0,β 2q >0), k pd and k pq is the gain coefficient, i d* is the d-axis current reference value and i d * =0,u d and u q are the d-axis stator voltage and the q-axis stator voltage respectively.

[0087] (4) The mathematical model of SPMSM in the α-β two-phase stationary coordinate system is:

[0088]

[0089] Where: L s is the stator inductance, u α with u β is the stator voltage corresponding to the α-β axis, i α with i β is the stator current corresponding to the α-β axis, E α With E β They are the extended back electromotive force in the α-β coordinate system, R is the stator phase resistance, and L is the stator phase inductance.

[0090] And E α With E β There is the following equation:

[0091]

[0092] Where: θ e is the rotor position angle.

[0093] The second-order SMO is constructed as:

[0094]

[0095] Where: and for i α with i β The superscripts used below have the same meaning.

[0096] Design the following sliding surface:

[0097]

[0098] Sliding mode control law V α With V β for:

[0099]

[0100] Where: k is the sliding mode gain coefficient, k>0, and sign is the sign function.

[0101] Subtracting the above equation, we get the current error equation:

[0102]

[0103] Where: for i α 、i β The error between the estimated value and the actual value of , the superscripts appearing below have the same meaning.

[0104] When the sliding surface converges, the equivalent control principle shows that the estimated value of the extended back electromotive force is: E α =V α , E β =V β , and obtain the extended back electromotive force of the discontinuous high-frequency signal.

[0105] Since the conventional low-pass filter has a fixed gain, when the motor runs at different speeds, the estimated back electromotive force amplitude attenuates and the phase lags, and the observation effect of the sliding mode observer is poor. Therefore, an adaptive filter is designed to obtain the required signal:

[0106]

[0107] Where: e α 、e β is the back electromotive force after filtering, k is the adaptive coefficient, k>0, ω e is the electrical angular velocity.

[0108] After filtering, the signal phase delay and amplitude change are caused, and the phase compensation of the rotor position angle is required. The position angle after compensation is:

[0109]

[0110] Where: are the rotor position and speed observation values ​​respectively.

[0111] In order to improve the smoothness of the estimated back electromotive force waveform, an adaptive law is designed. Simplify the control model, assume that the flux amplitude does not change, and the speed change rate is very small and can be ignored, then we can get:

[0112]

[0113] Then, the following adaptive law is designed based on the above formula:

[0114]

[0115] Where: ρ is the adaptive parameter, ρ>0.

[0116] After obtaining the back electromotive force observation value, the error is normalized and the following Figure 5 The PLL feedforward compensation shown above obtains the rotor position and speed. The PLL error is:

[0117]

[0118] when When Approximately but After the error signal is normalized, the coefficient This improves the stability of the PLL when the speed changes, and increases the convergence speed through feedforward compensation.

[0119] (5) The final improved nonlinear dual-loop ADRC sensorless control method is used to achieve high-precision control of small vertical axis fans.

[0120] In this embodiment, the simulated wind turbine generator parameters are shown in Table 1:

[0121] Table 1

[0122]

[0123] The small vertical axis fan adopts Figure 1 The small VAWT sensorless control system based on the improved nonlinear dual-loop ADRC is shown in FIG. Figure 6 to Figure 13 It can be seen that the improved nonlinear dual-loop ADRC sensorless control can quickly follow the motor speed without obvious overshoot, while the speed error is significantly reduced, the rotor position estimation accuracy is improved, and the stability of the motor during operation is improved, which proves the accuracy and reliability of the control method of the present invention.

[0124] From the above simulation results, it can be seen that the small VAWT sensorless control method based on the improved nonlinear dual-loop ADRC of the present invention can make the motor speed respond quickly without obvious overshoot, and the speed error and position error are significantly reduced compared with those before improvement; at the same time, this method has high observation accuracy and is not easily affected by external disturbances, which helps to improve the dynamic performance and stability of the system.

[0125] The above description of the embodiments is to facilitate the understanding and application of the present invention by those skilled in the art. It is obvious that those skilled in the art can easily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without creative work. Therefore, the present invention is not limited to the above embodiments. Improvements and modifications made by those skilled in the art to the present invention based on the disclosure of the present invention should be within the protection scope of the present invention.

Claims

1. A sensorless control method for a small VAWT based on an improved nonlinear dual-loop ADRC comprises the following steps: (1) Collect the three-phase stator current of VAWT and calculate the stator current i of α and β axes through coordinate transformation α and i β , stator voltage u α and u β And the stator current i of the dq axis d and i q ; (2) According to the stator current i α and i β And the stator voltage u α and u β The extended back electromotive force E of the αβ axis is calculated by the sliding mode observer α and E β , and design an adaptive filter for E α and E β Perform filtering; (3) According to the extended back electromotive force e after filtering α and e β The rotor position observation value of VAWT is obtained through PLL feedforward compensation. and speed observations (4) Design a speed loop anti-disturbance controller based on second-order ESO, LSEFCR and new-fal function to control the speed error and obtain the q-axis current reference value i q * ; (5) Design a current loop anti-disturbance controller based on second-order ESO, LSEFCR and new-fal function to control the current error of the dq axis and obtain the stator voltage command value u of the dq axis d * and u q * , thereby controlling the VAWT.

2. The small VAWT sensorless control method according to claim 1, characterized in that: The transfer function expression of the adaptive filter in step (2) is as follows: Where: k is the adaptive coefficient, s is the Laplace operator, ω e is the actual speed of the VAWT.

3. The small VAWT sensorless control method according to claim 1, characterized in that: The expression of the speed loop anti-disturbance control in step (4) is as follows: in: is the estimated value of the rotation speed, is the disturbance estimate, and They are and The first derivative of e is the actual speed of VAWT, e1 is the error between the estimated speed and the actual speed, u0 is the output of LSEFCR, h(e1,δ1) and h(e1,δ2) are the new-fal functions about the error e1, β1 and β2 are the correction gains, J is the moment of inertia of VAWT, p n is the pole pair number of VAWT, ψ f is the permanent magnet flux linkage of VAWT, k p is the gain coefficient, ω e * is the speed reference value of VAWT.

4. The small VAWT sensorless control method according to claim 3, characterized in that: The expressions of the new-fal functions h(e1, δ1) and h(e1, δ2) are as follows: Among them: δ1 and δ2 are given constants.

5. The small VAWT sensorless control method according to claim 1, characterized in that: The expression of the current loop anti-disturbance control in step (5) is as follows: in: is the estimated value of d-axis current, is the estimated value of the d-axis disturbance, and They are and The first derivative of is the estimated value of q-axis current, is the estimated value of the q-axis disturbance, and They are and The first derivative of 1d is the error between the estimated d-axis current and the actual d-axis current, e 1q is the error between the estimated current on the q-axis and the actual current on the q-axis, u 0d and u 0q is the output of LSEFCR, h(e 1d ,δ 1d ) and h(e 1d ,δ 2d ) is about the error e 1d The new-fal function, h(e 1q ,δ 1q ) and h(e 1q ,δ 2q ) is about the error e 1q The new-fal function, β 1d , β 2d , β 1q , β 2q To correct the gain, J is the moment of inertia of VAWT, p n is the pole pair number of VAWT, ψ f is the permanent magnet flux linkage of VAWT, k pd and k pq is the gain coefficient, i d * is the d-axis current reference value and i d * =0,u d and u q are the d-axis stator voltage and the q-axis stator voltage respectively.

6. The small VAWT sensorless control method according to claim 5, characterized in that: The new-fal function h(e 1d ,δ 1d ) and h(e 1d ,δ 2d ) and h(e 1q ,δ 1q ) and h(e 1q ,δ 2q ) is as follows: Where: 1d , δ 2d , δ 1q and δ 2q are all given constants.

7. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: The processor is used to execute the computer program to implement the small VAWT sensorless control method based on improved nonlinear dual-loop ADRC as claimed in any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the computer program can realize the small VAWT sensorless control method based on improved nonlinear dual-loop ADRC according to any one of claims 1 to 6.

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