Dual three-phase permanent magnet synchronous generator rectification system and control method

Abstract

This invention discloses a control method for a dual three-phase permanent magnet synchronous generator (DTP-PMSG) rectifier system. By modeling the dual three-phase permanent magnet synchronous generator, vector control is performed on the DTP-PMSG rectifier system. A sliding mode observer based on an adaptive superspiral algorithm replaces the traditional sliding mode observer to estimate the motor back electromotive force and rotor position. This method suppresses the high-frequency chattering problem caused by the traditional sliding mode observer using a sign function as the control function, improving the observation accuracy of the rotor angle position. Furthermore, it ensures that the DC output provides stable DC power to the load. Simulation results verify the effectiveness of the proposed control scheme based on the adaptive superspiral algorithm sliding mode observer.

Description

Technical Field

[0001] This invention belongs to the technical field of dual three-phase permanent magnet synchronous generators, specifically relating to a control method for a dual three-phase permanent magnet synchronous generator rectifier system, and more particularly to a control method for a dual three-phase permanent magnet synchronous generator rectifier system based on an adaptive super-helical sliding mode observer. Background Technology

[0002] With the rapid development of science and technology in today's society, electric motors are widely used in production and daily life. Dual three-phase permanent magnet synchronous generators (DTP-PMSG) have advantages such as high power density, low torque ripple, and good fault tolerance. These advantages make them significantly superior in applications requiring high reliability and high power, such as wind power, ship propulsion, electric aircraft, and electric vehicles, gradually becoming an ideal upgrade solution for traditional permanent magnet synchronous generators.

[0003] The DTP-PMSG rectifier system can regulate the DC-side voltage and also improve the power factor of the AC-side generator. The system uses SVPWM technology to effectively reduce generator harmonic current. The rectifier system employs dual closed-loop control: the outer voltage loop obtains the reference value for the inner current loop through a PI controller, and then uses the control of the inner current loop and SVPWM technology to obtain the rectifier's switching signal, rectifying the 6-phase AC power into a stable DC output.

[0004] Sliding mode control of permanent magnet synchronous motors is sensorless control. This control method does not rely on mechanical encoders, but instead uses state estimation to indirectly calculate rotor position information. In sensorless control, the values ​​of motor voltage and current are first sampled, and the rotor position is obtained through formulas from the motor's mathematical model, replacing traditional mechanical position sensors with software algorithms.

[0005] Currently, sensorless control algorithms for electric motors can be divided into two main categories: one category utilizes the salient pole characteristics of the motor to identify the rotor position, which requires the injection of additional current or voltage signals, such as high-frequency square waves, high-frequency rotating signals, and high-frequency pulsating signals; the other category uses the back electromotive force or flux linkage of the motor to estimate the rotor position through a mathematical model of the motor, such as sliding mode observers, extended Kalman filters, and model reference adaptive algorithms. Sliding mode observer algorithms are widely used due to their fast dynamic response and strong robustness.

[0006] In order to ensure that the motor control system meets the stability conditions and that the observer converges at the sliding surface, the traditional SMO algorithm sets a large switching gain in the switching function, which can lead to system chattering and inaccurate rotor position estimation. Summary of the Invention

[0007] To address the issues of system chattering and inaccurate rotor position estimation, this application employs a control method for a dual three-phase permanent magnet synchronous generator rectifier system. By using the DTP-PMSG adaptive super-helical sliding mode control algorithm, chattering caused by the sign function in traditional SMO control is suppressed, while the accuracy of rotor position estimation is improved.

[0008] To address the above technical problems, this invention provides a control method for a dual three-phase permanent magnet synchronous generator rectifier system, comprising the following steps:

[0009] Step 1: Mathematical Modeling and Vector Control of DTP-PMSG

[0010] The working principle of the DTP-PMSG rectifier system is to use a prime mover coaxially connected to the generator as mechanical power to drive the generator to rotate and run. The alternating current output by the generator is converted into direct current through a fully controlled rectifier, and finally filtered by the bus capacitor to output stable electrical energy to the load.

[0011] The generator has two sets of windings, namely windings a, b, and c and windings d, e, and f. The neutral points of the two sets of windings are isolated from each other and are 30° out of phase.

[0012] The dual three-phase permanent magnet synchronous generator in the natural coordinate system is a high-order, nonlinear, and strongly coupled complex system. It is necessary to use vector space decomposition (VSD) transformation to simplify its analysis. The variables of DTP-PMSG in the natural coordinate system are mapped to three mutually orthogonal subspaces: α-β subspace, xy subspace and o1-o2 subspace.

[0013] According to the principle of constant amplitude, the static transformation matrix is:

[0014]

[0015] The α-β subspace corresponds to the first and second rows of the matrix and is called the fundamental subspace. The fundamental wave and the 12k±1 (k=1,2,…) harmonics in each variable of the dual three-phase permanent magnet synchronous generator are mapped to this subspace. The xy subspace corresponds to the third and fourth rows of the matrix and is called the harmonic subspace. The 6k±1 (k=1,3,5,…) harmonics are mapped in this subspace. The o1-o2 subspace corresponds to the last two rows of the matrix and is called the zero-sequence subspace. The 6k±3 (k=1,3,5,…) harmonics are mapped.

[0016] Further perform a rotational coordinate transformation on it, the transformation matrix is:

[0017]

[0018] Transforming the components of the α-β fundamental wavelet subspace into the dq rotating coordinate system using equation (2), we obtain the generator voltage equation as follows:

[0019]

[0020] In the formula, u d u q u x u y These represent the voltages along the d, q, x, and y axes, respectively; L d L q For d-axis and q-axis inductance; L z For stator leakage inductance; i d i q i x i y These represent the currents along the d, q, x, and y axes, respectively; R s ω is the stator resistance; e ψ is the electric angular velocity. f This refers to the flux linkage amplitude of the permanent magnet;

[0021] The electromagnetic torque equation of DTP-PMSG along the dq axis is:

[0022] T e =3p[ψ f i q +(L d -L d )i d i q (4)

[0023] In the formula, p is the number of pole pairs of the motor;

[0024] The active power output of the permanent magnet synchronous generator is:

[0025] P s =3(u d i d +u q i q (5)

[0026] Because of the surface-mounted permanent magnet synchronous motor L d =L q Therefore, the electromagnetic power output by the generator is:

[0027] P e =T e ω m =3ψ f ω e i q (6)

[0028] The DTP-PMSG rectifier system as a whole adopts id =0 control, with the given voltage as the outer control loop and the d-axis and q-axis currents as the inner control loop; the voltage loop PI controller controls the rectifier system based on the given voltage and the actual voltage values, and outputs a reference current. The reference voltage is obtained by passing the reference current through the inner loop PI controller. right Perform inverse Park transform to obtain Will The SVPWM algorithm outputs a switching signal to control the rectifier system to generate a stable DC voltage.

[0029] Step 2: SMO Control

[0030] The back electromotive force equation of the motor is related to the rotor position; therefore, the back electromotive force can be observed using a sliding mode observer to obtain information about the rotor position θ. The system sliding surface s is designed as follows:

[0031]

[0032] Among them, i α i β This is the actual value of the stator current. The observed value is the actual value when the sliding surface s = 0. The traditional sliding mode observer is constructed as shown in equation (8):

[0033]

[0034] In the formula, z α z β The sliding mode observer control law function is expressed as follows:

[0035]

[0036] Where h is the sliding mode gain coefficient, h > 0, and sgn(·) is the sign function; when h > max{m1,m2}, the stability requirement is met, where:

[0037]

[0038] and These are the differences between the observed and actual values ​​of the α and β axis currents, respectively.

[0039] When the system moves away from the sliding surface, the control law function is used to bring it back to the sliding surface and to make the system dynamically stable near the equilibrium point within a certain period of time. The value obtained by the formula contains high-order harmonics of the back electromotive force. After filtering by a low-pass filter, the estimated value of the back electromotive force is obtained. Then, the rotor position information can be obtained by using a phase-locked loop.

[0040] Step 3: SMO Control Based on Adaptive Superspiral Algorithm

[0041] An adaptive superhelical algorithm is used to replace the sign function of the traditional sliding mode observer, as follows:

[0042] 1. Control Law Design

[0043] Based on the design principles of the superhelical algorithm, the superhelical algorithm is given as follows:

[0044]

[0045] In the formula, x and y are control laws; K1 and K2 are sliding mode gains; m is the disturbance term; when m satisfies:

[0046] m≤a|s| 1 / 2 (12)

[0047] And K1 and K2 satisfy:

[0048]

[0049] Where a is an arbitrary constant that satisfies equation (12);

[0050] The superhelical algorithm is improved by incorporating adaptive control theory. The control law expression of the adaptive superhelical algorithm is as follows:

[0051]

[0052] in:

[0053]

[0054] In the formula, K(0)>0, γ, μ, η, δ, μ, α are all constants greater than 0 and δ≤|s|;

[0055] 2. Stability Analysis

[0056] To ensure the stable operation of the DTP-PMSG rectifier system, the adaptive superspiral algorithm is analyzed using the Lyapunov stability analysis method; the Lyapunov function is selected as follows:

[0057] V = ξ T Pξ (16)

[0058] in:

[0059]

[0060] Differentiating equation (16) yields:

[0061]

[0062] In the formula:

[0063]

[0064] Simplifying equation (19) yields:

[0065]

[0066] In the formula:

[0067]

[0068] When Q is a positive definite matrix, the system is guaranteed to be stable, therefore we can obtain:

[0069]

[0070] For the system to meet the stability condition, the control parameters need to meet the requirements of equation (22).

[0071] The technical solution further defined in this invention is:

[0072] In step one, the α-β subspace is related to electromechanical energy conversion, while the xy subspace and o1-o2 subspace are not related to electromechanical energy conversion.

[0073] The beneficial effects of this invention are:

[0074] This invention models a dual three-phase permanent magnet synchronous generator and performs vector control on a DTP-PMSG rectifier system. It replaces the traditional sliding mode observer with a sliding mode observer based on an adaptive superspiral algorithm to estimate the motor's back EMF and rotor position. This approach suppresses the high-frequency chattering problem caused by the traditional sliding mode observer using a sign function as the control function, improving the accuracy of rotor angle position observation. Furthermore, it ensures a stable DC power supply from the DC output to the load. Simulations verify the effectiveness of the proposed adaptive superspiral algorithm-based sliding mode observer control scheme. Detailed Implementation

[0075] Figure 1 Schematic diagram of the rectifier system of a dual three-phase permanent magnet synchronous generator;

[0076] Figure 2 Schematic diagram of the vector control framework of the DTP-PMSG rectifier system;

[0077] Figure 3 Schematic diagram of the sliding mode observer principle;

[0078] Figure 4 A schematic diagram of the back electromotive force observed by the adaptive superhelical algorithm;

[0079] Figure 5 A schematic diagram of the back electromotive force observed by a conventional sliding mode observer;

[0080] Figure 6 A schematic diagram showing the rotor position observed by a traditional sliding mode observer versus the actual error.

[0081] Figure 7 A schematic diagram showing the rotor position observed by the adaptive superhelical algorithm and the actual error.

[0082] Figure 8 A schematic diagram of the rectified voltage under the sliding mode observer of the adaptive superspiral algorithm.

[0083] Example

[0084] To further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and are not intended to limit the scope of the claims of the present invention.

[0085] Example 1:

[0086] This embodiment provides a control method for a dual three-phase permanent magnet synchronous generator rectifier system, including the following steps:

[0087] Step 1: Mathematical Modeling and Vector Control of DTP-PMSG

[0088] The working principle of the DTP-PMSG rectifier system is to use a prime mover coaxially connected to the generator as mechanical power to drive the generator to rotate. The alternating current output by the generator is converted into direct current through a fully controlled rectifier, and finally filtered by the bus capacitor to output stable electrical energy to the load.

[0089] System architecture diagram as follows Figure 1 As shown, the generator has two sets of windings, namely windings a, b, c and windings d, e, f. The neutral points of the two sets of windings are isolated from each other and are 30° out of phase.

[0090] The dual three-phase permanent magnet synchronous generator in the natural coordinate system is a high-order, nonlinear, and strongly coupled complex system, which requires the use of vector space decomposition (VSD) transformation to simplify its analysis.

[0091] The variables of DTP-PMSG in the natural coordinate system are mapped to three mutually orthogonal subspaces: α-β subspace, xy subspace and o1-o2 subspace.

[0092] Among them, the α-β subspace is related to electromechanical energy conversion, while the xy subspace and o1-o2 subspace are not related to electromechanical energy conversion. According to the principle of amplitude invariance, the static transformation matrix is:

[0093]

[0094] The α-β subspace corresponds to the first and second rows of the matrix and is called the fundamental subspace. The fundamental wave and the 12k±1 (k=1, 2, …) harmonics in each variable of the dual three-phase permanent magnet synchronous generator are mapped to this subspace. The xy subspace corresponds to the third and fourth rows of the matrix and is called the harmonic subspace. The 6k±1 (k=1, 3, 5, …) harmonics are mapped in this subspace. The o1-o2 subspace corresponds to the last two rows of the matrix and is called the zero-order subspace. The 6k±3 (k=1, 3, 5, …) harmonics are mapped in this subspace.

[0095] Further perform a rotational coordinate transformation on it, the transformation matrix is:

[0096]

[0097] Transforming the components of the α-β fundamental wavelet subspace into the dq rotating coordinate system using equation (2), we obtain the generator voltage equation as follows:

[0098]

[0099] In the formula, u d u q u x u y These represent the voltages along the d, q, x, and y axes, respectively; L d L q For d-axis and q-axis inductance; L z For stator leakage inductance; i d i q i x i y These represent the currents along the d, q, x, and y axes, respectively; R s ω is the stator resistance; e ψ is the electric angular velocity. f The flux linkage amplitude of the permanent magnet is given. The electromagnetic torque equation of the DTP-PMSG along the dq axis is:

[0100] T e =3p[ψ f i q +(L d -L d )i d i q (4)

[0101] In the formula, p is the number of pole pairs of the motor.

[0102] The active power output of the permanent magnet synchronous generator is

[0103] P s =3(u d i d +u q iq (5)

[0104] Because of the surface-mounted permanent magnet synchronous motor L d =L q Therefore, the electromagnetic power output by the generator is...

[0105] P e =T e ω m =3ψ f ω e i q (6)

[0106] The DTP-PMSG rectifier system as a whole adopts i d =0 control, with the given voltage as the outer control loop and the d-axis and q-axis currents as the inner control loop, the control framework is as follows: Figure 2 As shown. The voltage loop PI controller controls the rectifier system based on the given voltage and the actual voltage value, and outputs a reference current. The reference voltage is obtained by passing the reference current through the inner loop PI controller. right Perform inverse Park transform to obtain Will The SVPWM algorithm outputs a switching signal to control the rectifier system to generate a stable DC voltage.

[0107] Step 2: SMO Control Strategy

[0108] The back electromotive force (EMF) equation of the motor is related to the rotor position; therefore, the back EMF can be observed using a sliding mode observer to obtain information about the rotor position θ. The system's sliding surface s is designed.

[0109]

[0110] Among them, i α i β This is the actual value of the stator current. The observed value is the back electromotive force when the sliding surface s = 0. The traditional sliding mode observer is constructed as shown in equation (8).

[0111]

[0112] In the formula, z α z β Let be the control law function of the sliding mode observer, with the expression:

[0113]

[0114] Where h is the sliding mode gain coefficient, h > 0, and sgn(·) is the sign function. Stability is satisfied when h > max{m1, m2}, where...

[0115]

[0116] and These represent the differences between the observed and actual values ​​of the α and β axis currents, respectively. When the system moves far from the sliding surface, a control law function is used to bring it back towards the sliding surface, and the system is dynamically stabilized near the equilibrium point within a certain time. The values ​​obtained from the formula contain high-order harmonics of the back electromotive force (EMF). After filtering with a low-pass filter, an estimated value of the back EMF is obtained. Then, a phase-locked loop (PLL) is used to obtain the rotor position information. The principle framework of the sliding mode observer is as follows: Figure 3 As shown.

[0117] Step 3: SMO Control Based on Adaptive Superspiral Algorithm

[0118] Traditional Sliding Mode Observer (SMO) control is a special type of nonlinear control system, characterized by its switching properties that cause the system's "structure" to change constantly, resulting in discontinuous control. When implementing SMO control, it is crucial to carefully select the sliding surface function and sliding gain. This requires ensuring the observer's convergence speed while avoiding excessive chattering in the observed rotor speed and position information due to a large sliding gain. Traditional SMO observers using a sign function as the switching function exhibit significant chattering amplitude after the system state leaves the sliding surface, affecting observation accuracy and negatively impacting voltage stability. To improve the observation accuracy of rotor speed and position information and enhance DC voltage stability, this paper employs an adaptive superspiral algorithm to replace the sign function of the traditional SMO observer.

[0119] 1. Control Law Design

[0120] Based on the design principles of the superhelical algorithm, the superhelical algorithm is given as follows:

[0121]

[0122] In the formula, x and y are control laws; K1 and K2 are sliding mode gains; m is the disturbance term; when m satisfies:

[0123] m≤a|s| 1 / 2 (12)

[0124] And K1 and K2 satisfy:

[0125]

[0126] Where a is an arbitrary constant that satisfies equation (12).

[0127] The superhelical algorithm is improved by incorporating adaptive control theory. The control law expression of the adaptive superhelical algorithm is as follows:

[0128]

[0129] in:

[0130]

[0131] In the formula, K(0)>0, γ, μ, η, δ, μ, α are all constants greater than 0 and δ≤|s|.

[0132] 2. Stability Analysis

[0133] To ensure the stable operation of the DTP-PMSG rectifier system, the adaptive superspiral algorithm is analyzed using the Lyapunov stability analysis method. The Lyapunov function is selected as follows:

[0134] V = ξ T Pξ (16)

[0135] in:

[0136]

[0137] Differentiating equation (16) yields:

[0138]

[0139] In the formula:

[0140]

[0141] Simplifying equation (19) yields:

[0142]

[0143] In the formula:

[0144]

[0145] When Q is a positive definite matrix, the system is guaranteed to be stable, therefore we can obtain:

[0146]

[0147] For the system to meet the stability condition, the control parameters need to meet the requirements of equation (22).

[0148] 3. Simulation verification

[0149] To verify the effectiveness of the proposed adaptive helical sliding mode observer-based control strategy, our research group conducted simulations based on a surface-mounted dual three-phase permanent magnet synchronous generator (DTP-PMSG). A simulation model of the DTP-PMSG was built using the MATLAB / Simulink platform. Simulation analyses were performed on the rectifier system using both a traditional sliding mode observer and a sliding mode observer based on the adaptive superhelical algorithm. The simulation parameters are shown in Table 1.

[0150] Table 1. DTP-PMSG Simulation Parameters

[0151] Parameter name Parameter value <![CDATA[Stator resistance R s (Ω)]]> 1.3 <![CDATA[d-axis main self-inductance L d (mH)]]> 12 <![CDATA[q-axis main self-inductance L q (mH)]]> 12 <![CDATA[Stator leakage inductance L z (mH)]]> 5 <![CDATA[Permanent magnet flux linkage ψ f (Wb)]]> 0.063 Extreme number p 4 Rated speed n (rpm) 2000 <![CDATA[DC bus voltage U dc (V)]]> 500

[0152] The motor speed was set to a constant 2000 rpm. At 0 s, the rectifier system was started with a load and the DC bus voltage was stably output at 500V. The back electromotive force and rotor position estimation curves observed by the sliding mode observer based on the adaptive super spiral algorithm are shown in the figure.

[0153] contrast Figure 6 and Figure 7 It can be seen that the rotor angle estimated by the sliding mode observer based on the adaptive superhelical algorithm has a smaller estimation error than that of the traditional sliding mode observer, and the angle error is controlled within 10° after stable operation.

[0154] Using an adaptive superspiral algorithm-based sliding mode observer, the dual three-phase permanent magnet synchronous generator rectifier system operates stably, outputting 500V. The results are as follows: Figure 8 As shown.

[0155] The comparison results show that the back EMF estimated by the traditional sliding mode observer has high-frequency chattering, while the adaptive superspiral algorithm can significantly reduce the chattering problem of the back EMF observation.

[0156] This embodiment models a dual three-phase permanent magnet synchronous generator and performs vector control on the DTP-PMSG rectifier system. A sliding mode observer based on an adaptive superspiral algorithm replaces the traditional sliding mode observer to estimate the motor back EMF and rotor position. This approach suppresses the high-frequency chattering problem caused by the traditional sliding mode observer using a sign function as the control function, improving the accuracy of rotor angle position observation. Furthermore, it ensures a stable DC power supply from the DC output to the load. Simulations verify the effectiveness of the proposed adaptive superspiral algorithm-based sliding mode observer control scheme.

[0157] The above embodiments are merely illustrative of the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solutions based on the technical concept proposed in this invention shall fall within the scope of protection of this invention.

Claims

1. A control method for a dual three-phase permanent magnet synchronous generator rectifier system, characterized in that, Includes the following steps: Step 1: Mathematical Modeling and Vector Control of DTP-PMSG The working principle of the DTP-PMSG rectifier system is to use a prime mover coaxially connected to the generator as mechanical power to drive the generator to rotate and run. The alternating current output by the generator is converted into direct current through a fully controlled rectifier, and finally filtered by the bus capacitor to output stable electrical energy to the load. The generator has two sets of windings, namely windings a, b, and c and windings d, e, and f. The neutral points of the two sets of windings are isolated from each other and are 30° out of phase. The dual three-phase permanent magnet synchronous generator in the natural coordinate system is a high-order, nonlinear, and strongly coupled complex system. It is necessary to use vector space decomposition (VSD) transformation to simplify its analysis. The variables of DTP-PMSG in the natural coordinate system are mapped to three mutually orthogonal subspaces: α-β subspace, xy subspace and o1-o2 subspace. According to the principle of constant amplitude, the static transformation matrix is: The α-β subspace corresponds to the first and second rows of the matrix and is called the fundamental subspace. The fundamental wave and the 12k±1 (k=1,2,…) harmonics in each variable of the dual three-phase permanent magnet synchronous generator are mapped to this subspace. The xy subspace corresponds to the third and fourth rows of the matrix and is called the harmonic subspace. The 6k±1 (k=1,3,5,…) harmonics are mapped in this subspace. The o1-o2 subspace corresponds to the last two rows of the matrix and is called the zero-sequence subspace. The 6k±3 (k=1,3,5,…) harmonics are mapped. Further perform a rotational coordinate transformation on it, the transformation matrix is: Transforming the components of the α-β fundamental wavelet subspace into the dq rotating coordinate system using equation (2), we obtain the generator voltage equation as follows: In the formula, u d u q u x u y These represent the voltages along the d, q, x, and y axes, respectively; L d L q For d-axis and q-axis inductance; L z For stator leakage inductance; i d i q i x i y These represent the currents along the d, q, x, and y axes, respectively; R s ω is the stator resistance; e ψ is the electric angular velocity. f This refers to the flux linkage amplitude of the permanent magnet; The electromagnetic torque equation of DTP-PMSG along the dq axis is: T e =3p[ψ f and q +(L d -L d )i d and q ] (4) In the formula, p is the number of pole pairs of the motor; The active power output of the permanent magnet synchronous generator is: P s =3(in d and d +in q and q ) (5) Because of the surface-mounted permanent magnet synchronous motor L d =L q Therefore, the electromagnetic power output by the generator is: P e =T e ω m =3ψ f ω e i q (6) The DTP-PMSG rectifier system as a whole adopts i d =0 control, with the given voltage as the outer control loop and the d-axis and q-axis currents as the inner control loop; The voltage loop PI controller controls the rectifier system based on the given voltage and the actual voltage value, and outputs a reference current. The reference voltage is obtained by passing the reference current through the inner loop PI controller. right Perform inverse Park transform to obtain Will The SVPWM algorithm outputs a switching signal to control the rectifier system to generate a stable DC voltage. Step 2: SMO Control The back electromotive force equation of the motor is related to the rotor position; therefore, the back electromotive force can be observed using a sliding mode observer to obtain information about the rotor position θ. The system sliding surface s is designed as follows: Among them, i α i β This is the actual value of the stator current. The observed value is the actual value when the sliding surface s = 0. The traditional sliding mode observer is constructed as shown in equation (8): In the formula, z α z β The sliding mode observer control law function is expressed as follows: Where h is the sliding mode gain coefficient, h>0, and sgn(·) is the sign function; when h>max{m1, m2}, the stability requirement is met, where: and These are the differences between the observed and actual values ​​of the α and β axis currents, respectively. When the system moves away from the sliding surface, the control law function is used to bring it back to the sliding surface and to make the system dynamically stable near the equilibrium point within a certain period of time. The value obtained by the formula contains high-order harmonics of the back electromotive force. After filtering by a low-pass filter, the estimated value of the back electromotive force is obtained. Then, the rotor position information can be obtained by using a phase-locked loop. Step 3: SMO Control Based on Adaptive Superspiral Algorithm An adaptive superhelical algorithm is used to replace the sign function of the traditional sliding mode observer, as follows:

1. Control Law Design Based on the design principles of the superhelical algorithm, the superhelical algorithm is given as follows: In the formula, x and y are control laws; K1 and K2 are sliding mode gains; m is the disturbance term; when m satisfies: m≤a|s| 1 / 2 (12) And K1 and K2 satisfy: Where a is an arbitrary constant that satisfies equation (12); The superhelical algorithm is improved by incorporating adaptive control theory. The control law expression of the adaptive superhelical algorithm is as follows: in: In the formula, K(0)>0, γ, μ, η, δ, μ, α are all constants greater than 0 and δ≤|s|; 2. Stability Analysis To ensure the stable operation of the DTP-PMSG rectifier system, the adaptive superspiral algorithm is analyzed using the Lyapunov stability analysis method; the Lyapunov function is selected as follows: V=ξ T Px (16) in: Differentiating equation (16) yields: In the formula: Simplifying equation (19) yields: In the formula: When Q is a positive definite matrix, the system is guaranteed to be stable, therefore we can obtain: For the system to meet the stability condition, the control parameters need to meet the requirements of equation (22).

2. The control method for the dual three-phase permanent magnet synchronous generator rectifier system according to claim 1, characterized in that: In step one, the α-β subspace is related to electromechanical energy conversion, while the xy subspace and o1-o2 subspace are not related to electromechanical energy conversion.

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