An online parameter identification method for dual three-phase permanent magnet synchronous motors

Abstract

A method for online parameter identification of a dual three-phase permanent magnet synchronous motor relates to the technical field of motor control. The present invention is intended to solve the problem of poor accuracy of identification results of online multi-parameter identification methods for motors. The present invention performs four-dimensional current vector control on the motor and records the mechanical angular velocity in steady state; injects sinusoidal current into the dq plane and z1z2 plane respectively, and after reaching steady state, uses a second-order generalized integrator and an orthogonal signal generator to extract the sinusoidal signal and calculate its differential signal, uses a recursive least squares method to solve the dq plane identification equation and the z1z2 plane identification equation respectively, and obtains the dq plane and z1z2 plane resistance and inductance parameters; injects DC current into the d-axis, uses a low-pass filter to obtain the DC component of the dq axis voltage and current feedback value, solves the flux linkage identification equation, and obtains the permanent magnet flux linkage.

Description

Technical Field

[0001] The invention belongs to the technical field of motor control. Background Art

[0002] In the field of motor control, high-performance current control strategies, sensorless position control strategies, and motor condition monitoring strategies all require accurate motor parameters. Offline parameter identification methods, especially parameter self-learning methods, are very effective for obtaining motor parameters. However, offline parameter identification methods struggle to account for the effects of temperature on motor resistance and permanent magnet flux. In contrast, online parameter identification methods utilize existing sensor data from the drive to continuously monitor motor parameter changes, ensuring accurate and reliable parameter determination.

[0003] Core issues in online multi-parameter identification include under-rank identification equations, algorithm convergence, and identification accuracy. To address under-rank identification equations, a fast-slow dual solver approach can be used to reduce the number of parameters to be identified and achieve full rank. Alternatively, full rank identification equations can be achieved by designing additional excitations. The former approach does not require signal injection, but for some motor systems with unique motor parameters, this approach can sometimes suffer from slow convergence or pathological convergence. In contrast, the latter approach, while requiring voltage or current injection, can accurately and quickly converge to the parameter values, offering greater applicability. The accuracy of the identification results is another key concern. Sampling and quantization noise, inverter nonlinearities, and back-EMF harmonics are the primary sources of identification error. Simple combined numerical solution methods and inverter nonlinearity compensation strategies not only fail to completely eliminate these error sources but also complicate the implementation of the identification strategy. Summary of the Invention

[0004] The present invention aims to solve the problem of poor accuracy of identification results of an online multi-parameter identification method for a motor, and now provides an online parameter identification method for a dual three-phase permanent magnet synchronous motor.

[0005] A method for online parameter identification of a dual three-phase permanent magnet synchronous motor, comprising:

[0006] Perform four-dimensional current vector control on the dual three-phase permanent magnet synchronous motor and record the mechanical angular velocity ω when the dual three-phase permanent magnet synchronous motor reaches steady state during online operation m0 ;

[0007] Injecting sinusoidal currents into the dq plane and the z1z2 plane, respectively, and after the current response reaches a steady state, using a second-order generalized integrator and an orthogonal signal generator to extract the sinusoidal signal and calculate its differential signal, and using a recursive least squares method to solve the dq plane identification equation and the z1z2 plane identification equation composed of the sinusoidal signal and the differential signal, respectively, to obtain the dq plane resistance, dq plane d-axis inductance, dq plane q-axis inductance, z1z2 plane resistance, and z1z2 plane inductance;

[0008] A DC current is injected into the d-axis, and a low-pass filter is used to obtain the DC components of the dq-axis voltage feedback value and the dq-axis current feedback value. The flux linkage identification equation composed of the DC component, the dq plane resistance, the dq plane d-axis inductance, and the dq plane q-axis inductance is solved to obtain the permanent magnet flux linkage.

[0009] Furthermore, the above-mentioned four-dimensional current vector control of the dual three-phase permanent magnet synchronous motor includes:

[0010] Performing vector space decoupling transformation on the phase current of the dual three-phase permanent magnet synchronous motor to obtain α-axis, β-axis, x-axis and y-axis current feedback values;

[0011] Performing rotational coordinate transformation on the α-axis, β-axis, x-axis and y-axis current feedback values respectively to obtain d-axis, q-axis, z1-axis and z2-axis current feedback values;

[0012] The d-axis, q-axis, z1-axis and z2-axis current instructions and current feedback values are passed through the PI regulator to output the voltage instructions of each axis. The voltage instructions are subjected to vector space decoupling inverse transformation, rotating coordinate transformation and zero-sequence injection modulation strategy to obtain the switching signal of the inverter. The switching signal is applied to the inverter to complete the four-dimensional current vector control of the dual three-phase permanent magnet synchronous motor.

[0013] Furthermore, the above-mentioned sinusoidal current is injected into the dq plane and the z1z2 plane respectively, and after the current response reaches a steady state, a second-order generalized integrator and an orthogonal signal generator are used to extract the sinusoidal signal and calculate its differential signal, and the recursive least squares method is used to solve the dq plane identification equation and the z1z2 plane identification equation composed of the sinusoidal signal and the differential signal respectively to obtain the dq plane resistance, dq plane d-axis inductance, dq plane q-axis inductance, z1z2 plane resistance and z1z2 plane inductance, including:

[0014] Set the amplitude to And the frequency is ω dq =6pω m0 The d and q axis sinusoidal current are respectively superimposed on the d-axis and q-axis current instructions of the dual three-phase permanent magnet synchronous motor. When the current response reaches a steady state, a second-order generalized integrator is used to extract the 6th harmonic component in the d-axis and q-axis voltage instructions and current feedback values. An orthogonal signal generator is used to calculate the differential of the 6th harmonic component in the d-axis and q-axis current feedback values. A recursive least squares method is used to solve the identification equation composed of the 6th harmonic component and its differential in the d-axis and q-axis current feedback values to obtain the dq plane resistance, dq plane d-axis inductance and dq plane q-axis inductance, wherein p is the pole pair number of the dual three-phase permanent magnet synchronous motor, and I N is the rated current of the dual three-phase permanent magnet synchronous motor;

[0015] Set the amplitude to And the frequency is ω z =3pω m0 The z1 and z2 axis sinusoidal currents The three harmonic components in the voltage instructions and current feedback values of the z1 and z2 axes are respectively superimposed on the dual three-phase permanent magnet synchronous motor. When the current response reaches a steady state, a second-order generalized integrator is used to extract the three harmonic components in the voltage instructions and current feedback values of the z1 and z2 axes. An orthogonal signal generator is used to calculate the differentials of the three harmonic components in the current feedback values of the z1 and z2 axes. The recursive least squares method is used to solve the identification equation composed of the three harmonic components and their differentials in the current feedback values of the z1 and z2 axes to obtain the z1z2 plane resistance and z1z2 plane inductance.

[0016] Furthermore, the DC current injected into the d-axis has an amplitude of

[0017] Furthermore, the d and q axis sinusoidal currents injected into the dq plane The expression is as follows:

[0018]

[0019] The z1 and z2 axis sinusoidal currents injected into the z1z2 plane The expression is as follows:

[0020]

[0021] Furthermore, for a sinusoidal signal v with a frequency of ω1, the digital form of the second-order generalized integrator is:

[0022]

[0023] For a sinusoidal signal v with a frequency of ω1, the digital form of the orthogonal signal generator is:

[0024]

[0025] Where D(·) represents the output of the second-order generalized integrator, Q(·) represents the output of the orthogonal signal generator, and T s is the system sampling period, K GI is the proportional coefficient of the second-order generalized integrator and the orthogonal signal generator.

[0026] Furthermore, the identification equation composed of the sixth harmonic component and its differential in the d-axis and q-axis current feedback values is:

[0027]

[0028] in, and are the voltage instructions for the d-axis and q-axis respectively, and Respectively represent the input and The output of the second-order generalized integrator, R s is the dq plane resistance to be identified, i d and i q are the current feedback values of the d-axis and q-axis respectively, L d and L q are the d-axis and q-axis inductances to be identified, Q[D(i d )] and Q[D(i q )] are respectively input as D(i d ) and D(i q ) is the output result of the orthogonal signal generator, and ω dq Q[D(i d )] and ω dq Q[D(i q )] represent the differential of the d-axis and q-axis current feedback values, D(i d ) and D(i q ) represent the input i d and i q The output of the second-order generalized integrator when .

[0029] Furthermore, the above-mentioned recursive least squares method is used to solve the identification equation composed of the sixth harmonic component and its differential in the d-axis and q-axis current feedback values, which is expressed as:

[0030]

[0031] Where y(t) represents the output vector, H(t) represents the signal vector, and θ(t) represents the parameter vector.

[0032] Furthermore, the identification equation composed of the third harmonic component and its differential in the z1-axis and z2-axis current feedback values is:

[0033]

[0034] in, and are the voltage instructions for the z1 axis and z2 axis respectively, and Respectively represent the input and The output of the second-order generalized integrator, R sz is the z1z2 plane resistor to be identified, i z1 and i z2 are the current feedback values of the z1 axis and z2 axis respectively, L zis the z1z2 plane inductor to be identified, Q[D(i z1 )] and Q[D(i z2 )] are respectively input as D(i z1 ) and D(i z2 ) is the output result of the orthogonal signal generator, and ω z Q[D(i z1 )] and ω z Q[D(i z2 )] represent the differential of the current feedback value of the z1 axis and the z2 axis respectively, D(i z1 ) and D(i z2 ) are input as i z1 and i z2 The output of the second-order generalized integrator when .

[0035] Furthermore, the above-mentioned recursive least squares method is used to solve the identification equation composed of the third harmonic component and its differential in the z1 and z2 axis current feedback values, which is expressed as:

[0036]

[0037] Where y(t) represents the output vector, H(t) represents the signal vector, and θ(t) represents the parameter vector.

[0038] The online parameter identification method for a dual three-phase permanent magnet synchronous motor described in the present invention achieves the following beneficial effects through the above-mentioned method:

[0039] The online parameter identification method does not require an integrated inverter nonlinearity compensation strategy, but it can eliminate the effects of inverter nonlinearity and back-EMF harmonics, achieving higher accuracy. The parameter solution process includes signal pre-cleaning using a second-order generalized integrator and a quadrature signal generator, and a parameter solution based on RLS. This reduces the impact of sampling and quantization noise on the identification results, making the identification more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Flowchart of the online parameter identification method for dual three-phase permanent magnet synchronous motor;

[0041] Figure 2 This is the principle block diagram of the online parameter identification method for dual three-phase permanent magnet synchronous motors;

[0042] Figure 3 Implement block diagram for signal pre-cleaning and parameter solution;

[0043] Figure 4 This is the current response waveform when a sinusoidal current is injected;

[0044] Figure 5 This is the result diagram of online parameter identification. DETAILED DESCRIPTION

[0045] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other in the absence of conflict.

[0046] Considering the iron loss and AC loss of the dual three-phase permanent magnet synchronous motor, the dq plane resistance R of the dual three-phase permanent magnet synchronous motor is s With z1z2 plane resistor R sz Ignoring the non-ideal back EMF, the mathematical model of the dual three-phase permanent magnet synchronous motor in the VSD decoupling framework is:

[0047]

[0048] Where u d is the d-axis voltage feedback value, u q is the q-axis voltage feedback value, u z1 is the voltage feedback value of z1 axis, u z2 is the voltage feedback value of the z2 axis, i d is the d-axis current feedback value, i q is the q-axis current feedback value, i z1 is the z1 axis current feedback value, i z2 is the z2 axis current feedback value, ω e is the electrical angular velocity, ω e =pω m , p is the number of pole pairs of the motor, ω m is the mechanical angular velocity of the motor, and t is the time. The parameter to be identified is the dq plane resistance R s , dq plane d-axis inductance L d , dq plane q-axis inductance L q 、z1z2 plane resistor R sz 、z1z2 planar inductor L z and permanent magnet flux ψ f .

[0049] Reference Figure 1 Specifically describing this embodiment, the online parameter identification method for a dual three-phase permanent magnet synchronous motor based on sinusoidal current injection includes: a sinusoidal current injection step, a signal cleaning step using a second-order generalizer and an orthogonal signal generator, and a flux linkage identification step that eliminates the nonlinear effects of the inverter using a resistance-inductance identification equation based on a sinusoidal signal. The details are as follows:

[0050] Step 1: Control the dual three-phase permanent magnet synchronous motor. During the online operation of the motor, monitor the motor speed and dq axis current to determine whether the motor has reached a steady state, and record the mechanical angular velocity ω of the motor during steady-state operation. m0 .

[0051] The control method for the dual three-phase permanent magnet synchronous motor is the four-dimensional current vector control method, specifically:

[0052] Perform vector space decoupling transformation on the motor phase current to obtain the current feedback values of the α-axis, β-axis, x-axis and y-axis. Vector space decoupling transformation matrix T VSD for:

[0053]

[0054] Perform rotation coordinate transformation on the α-axis current, β-axis current, x-axis current and y-axis current respectively to obtain the d-axis current feedback value i d , q-axis current feedback value i q , z1 axis current feedback value i z1 and z2 axis current feedback value i z2 .

[0055] The rotation coordinate transformation matrix Park(θ e )for:

[0056]

[0057] Where θ e It is the angle between the d-axis and the A-phase axis.

[0058] d-axis, q-axis, z1-axis, z2-axis current commands and the current feedback value i d 、i q 、i z1 、i z2 Output voltage instructions for each axis through PI regulator The voltage command is transformed into the switching signal of the inverter through vector space decoupling inverse transformation, rotating coordinate transformation and zero-sequence injection modulation strategy; the switching signal is applied to the inverter to complete the four-dimensional current vector control of the dual three-phase permanent magnet synchronous motor.

[0059] Step 2: Identify the dq plane resistance and inductance parameters

[0060] The frequency is ω dq Sinusoidal current and D and q axis current instructions superimposed on the motor dq plane and In the d-axis and q-axis current instructions are obtained and

[0061] The sinusoidal current and The expressions are as follows:

[0062]

[0063] in, is the amplitude of the current injected into the dq plane.

[0064] Since the injection of sinusoidal current into the dq plane will produce torque fluctuations, in order to reduce the impact of the injected current on the motor operation, the dq plane current injection amplitude is preferably I N is the rated current of the motor. The dq plane voltage equation contains the fundamental component and the 12th component. In order to stay away from these two frequencies, the frequency of the injected current ω dq The preferred 6th harmonic frequency ω dq =6pω m0 , p is the number of pole pairs of the motor.

[0065] When the current response reaches a steady state, the dq plane voltage and current contain a DC component, a 6th harmonic component, and a 12th harmonic component. For a sinusoidal signal v with a frequency of ω1, a second-order generalized integrator can filter out noise and extract the sinusoidal signal v with a frequency of ω1 without phase shift. The filtered signal is D(v). This embodiment uses a second-order generalized integrator to extract the 6th harmonic component from the d and q axis voltage commands and current feedback values. D(i d ),D(i q ). The digital form of the above second-order generalized integrator (SOGI) is:

[0066]

[0067] The quadrature signal generator can filter out noise and accurately shift the phase of the sinusoidal signal by 90 degrees. This embodiment uses the quadrature signal generator to calculate the sixth harmonic component D (i d ) and D(i q )'s differential ω dq Q[D(i d )] and ω dq Q[D(i q )].

[0068] The differential of the sinusoidal signal v is denoted as ω1Q[D(v)], and the digital form of the quadrature signal generator (QSG) is:

[0069]

[0070] In the above formula, Q(·) represents the output of the orthogonal signal generator, D(·) represents the output of the second-order generalized integrator, and T s is the system sampling period, K GI is the proportional coefficient of the second-order generalized integrator and the orthogonal signal generator, preferably

[0071] Substituting the results of the second-order generalized integral and orthogonal differential into the mathematical model of the dual three-phase permanent magnet synchronous motor in the VSD decoupling framework, the identification equation consisting only of the sixth harmonic component is obtained:

[0072]

[0073] Use the recursive least squares method to solve the parameter R in the identification equation s 、L d 、L q .

[0074] The recursive least squares expression is as follows:

[0075]

[0076] Where P(t) is the covariance matrix, H(t) is the signal vector, y(t) is the output vector, and θ(t) is the parameter vector. is the identified parameter vector, and ε(t) is the estimation error.

[0077] Then the resistance and inductance parameter solution equation obtained using the recursive least squares method is:

[0078]

[0079] Step 3: Identify the resistance and inductance parameters of the z1z2 plane

[0080] The frequency is ω z Sinusoidal current and The z1 and z2 axis current instructions superimposed on the motor z1z2 plane and Get the current instructions of the z1 axis and z2 axis and

[0081] The sinusoidal current and The expressions are as follows:

[0082]

[0083] in, is the amplitude of the current injected into the z1z2 plane.

[0084] Since the injection of sinusoidal current into the z1z2 plane will produce torque fluctuations, in order to reduce the impact of the injected current on the motor operation, the current injection amplitude of the z1z2 plane is preferably The voltage equation of the z1z2 plane is mainly composed of the sixth harmonic component. In order to stay away from this frequency, the injection frequency ω z The preferred third harmonic frequency ω z =3pω m0 .

[0085] After the current response reaches a steady state, the voltage and current of the z1 axis and the z2 axis contain the third harmonic component and the sixth harmonic component. A second-order generalized integrator is used to extract the frequency ω in the z1 and z2 axis command voltage and current feedback values. z The third harmonic component D(i z1 ),D(i z2 ) Use the orthogonal signal generator to calculate the third harmonic component D(i z1 ) and D(i z2 )'s differential ω z Q[D(i z1 )] and ω z Q[D(i z2 )]. Substituting the results of the second-order generalized integral and orthogonal differential into the mathematical model of the dual three-phase permanent magnet synchronous motor in the VSD decoupling framework, the identification equation consisting only of the third harmonic component is obtained:

[0086]

[0087] Use the recursive least squares method to solve the parameter R in the identification equation sz and L z .

[0088] The resistance and inductance parameter solution equation obtained using the recursive least squares method is:

[0089]

[0090] Step 4: Identify the permanent magnet flux

[0091] The parameter identification of the z1z2 plane requires that the motor operates under a non-zero d-axis current. In this embodiment, a DC current is injected into the d-axis current command.

[0092] Considering the nonlinearity of the inverter, a low-pass filter is used to filter out the high-frequency noise of the dq axis voltage and dq axis current, and their DC components are obtained as

[0093]

[0094] in, and are the voltage errors of the inverter nonlinearity on the d-axis and q-axis respectively, and:

[0095]

[0096] ΔU is the terminal voltage error saturation value caused by dead time and device voltage drop, γ is the angle between the dq plane current vector and the d axis,

[0097] Will and Substitution and Eliminating the voltage error in the formula, the identification equation of permanent magnet flux is obtained:

[0098]

[0099] At this point, the parameter identification is completed. The resistance-inductance parameters and flux linkage identification are not affected by the inverter nonlinearity and back-electromotive force higher harmonics, and the results are accurate.

[0100] The principles of this implementation are as follows:

[0101] According to the harmonic mapping mechanism of the VSD, the inverter nonlinearity and higher harmonics of the back EMF of a dual three-phase permanent magnet synchronous motor are mapped to different planes through VSD coordinate transformation. The fundamental component and the 11th and 13th harmonic components of the voltage and current are mapped to the DC component and the 12th harmonic component in the dq plane, while the 5th and 7th harmonic components of the voltage and current are mapped to the 6th harmonic component in the z1z2 plane. Harmonics in the dq and z1z2 planes can affect the accuracy of online parameter identification. To this end, the present invention proposes a parameter identification method based on sinusoidal current injection. A 6th-order sinusoidal current is injected into the dq plane, and then a second-order generalized integrator and a quadrature signal generator are used to accurately extract the 6th-order voltage and current for parameter solution. A 3rd-order sinusoidal current is injected into the z1z2 plane, and a second-order generalized integrator and a quadrature signal generator are used to accurately extract the 3rd-order voltage and current for parameter solution. This method avoids the influence of inverter nonlinearity and higher harmonics of the back EMF on the resistance and inductance parameter identification. For the identification of flux parameters, this paper adopts the d-axis DC current injection method. Under the operating condition of d-axis DC injection, the voltage error introduced by the inverter nonlinearity in the d-axis and the voltage error introduced in the q-axis are related to the current amplitude of the dq axis. Using this characteristic, this paper uses the identification equation for calculating the permanent magnet flux parameters to eliminate the effect of the inverter nonlinearity on ψ fThe parameter identification method is not affected by the nonlinearity of the inverter and the back EMF harmonics. In terms of parameter solution, the present invention uses a second-order generalized integrator and an orthogonal signal generator for signal cleaning, and uses RLS to eliminate the influence of white noise, which minimizes the impact of sampling and quantization errors on the identification results, ultimately achieving accurate parameter self-learning.

[0102] The effect of this embodiment is illustrated by taking a six-phase inverter based on SiC MOSFET and a dual three-phase permanent magnet synchronous motor drive system as an example. The inverter nonlinear identification flow chart is as follows: Figure 1 As shown. Constructing four-dimensional current vector control as Figure 2 The signal cleaning and parameter solving methods are shown in Figure 3 The current waveform during the identification process is shown as Figure 4 The parameter identification results are shown in Figure 5 The identification results can converge to the true value quickly and stably, which proves the effectiveness of parameter identification.

[0103] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. A method for online parameter identification of a dual three-phase permanent magnet synchronous motor, characterized in that: include: Perform four-dimensional current vector control on the dual three-phase permanent magnet synchronous motor and record the mechanical angular velocity ω when the dual three-phase permanent magnet synchronous motor reaches steady state during online operation m0 ; Injecting sinusoidal currents into the dq plane and the z1z2 plane, respectively, and after the current response reaches a steady state, using a second-order generalized integrator and an orthogonal signal generator to extract the sinusoidal signal and calculate its differential signal, and using a recursive least squares method to solve the dq plane identification equation and the z1z2 plane identification equation composed of the sinusoidal signal and the differential signal, respectively, to obtain the dq plane resistance, dq plane d-axis inductance, dq plane q-axis inductance, z1z2 plane resistance, and z1z2 plane inductance; injecting a DC current into the d-axis, obtaining the DC components of the dq-axis voltage feedback value and the dq-axis current feedback value using a low-pass filter, and solving a flux linkage identification equation consisting of the DC component, the dq-plane resistance, the dq-plane d-axis inductance, and the dq-plane q-axis inductance to obtain the permanent magnet flux linkage; The method injects sinusoidal currents into the dq plane and the z1z2 plane respectively, and after the current response reaches a steady state, uses a second-order generalized integrator and an orthogonal signal generator to extract the sinusoidal signal and calculate its differential signal, and uses a recursive least squares method to solve the dq plane identification equation and the z1z2 plane identification equation composed of the sinusoidal signal and the differential signal respectively to obtain the dq plane resistance, dq plane d-axis inductance, dq plane q-axis inductance, z1z2 plane resistance, and z1z2 plane inductance, including: Set the amplitude to And the frequency is ω dq =6pω m0 The d and q axis sinusoidal current are respectively superimposed on the d-axis and q-axis current instructions of the dual three-phase permanent magnet synchronous motor. When the current response reaches a steady state, a second-order generalized integrator is used to extract the 6th harmonic component in the d-axis and q-axis voltage instructions and current feedback values. An orthogonal signal generator is used to calculate the differential of the 6th harmonic component in the d-axis and q-axis current feedback values. A recursive least squares method is used to solve the identification equation composed of the 6th harmonic component and its differential in the d-axis and q-axis current feedback values to obtain the dq plane resistance, dq plane d-axis inductance and dq plane q-axis inductance, wherein p is the pole pair number of the dual three-phase permanent magnet synchronous motor, and I N is the rated current of the dual three-phase permanent magnet synchronous motor; Set the amplitude to And the frequency is ω z =3pω m0 The z1 and z2 axis sinusoidal currents The three harmonic components in the voltage instructions and current feedback values of the z1 and z2 axes are respectively superimposed on the dual three-phase permanent magnet synchronous motor. When the current response reaches a steady state, a second-order generalized integrator is used to extract the three harmonic components in the voltage instructions and current feedback values of the z1 and z2 axes. An orthogonal signal generator is used to calculate the differentials of the three harmonic components in the current feedback values of the z1 and z2 axes. The recursive least squares method is used to solve the identification equation composed of the three harmonic components and their differentials in the current feedback values of the z1 and z2 axes to obtain the z1z2 plane resistance and z1z2 plane inductance.

2. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: The four-dimensional current vector control of the dual three-phase permanent magnet synchronous motor includes: Performing vector space decoupling transformation on the phase current of the dual three-phase permanent magnet synchronous motor to obtain α-axis, β-axis, x-axis and y-axis current feedback values; Performing rotational coordinate transformation on the α-axis, β-axis, x-axis and y-axis current feedback values respectively to obtain d-axis, q-axis, z1-axis and z2-axis current feedback values; The d-axis, q-axis, z1-axis and z2-axis current instructions and current feedback values are passed through the PI regulator to output the voltage instructions of each axis. The voltage instructions are subjected to vector space decoupling inverse transformation, rotating coordinate transformation and zero-sequence injection modulation strategy to obtain the switching signal of the inverter. The switching signal is applied to the inverter to complete the four-dimensional current vector control of the dual three-phase permanent magnet synchronous motor.

3. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: The DC current injected into the d-axis has an amplitude of 4. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: The d and q axis sinusoidal currents injected into the dq plane The expression is as follows: The z1 and z2 axis sinusoidal currents injected into the z1z2 plane The expression is as follows:

5. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: For a sinusoidal signal v with a frequency of ω1, the digital form of the second-order generalized integrator is: For a sinusoidal signal v with a frequency of ω1, the digital form of the orthogonal signal generator is: Where D(·) represents the output of the second-order generalized integrator, Q(·) represents the output of the orthogonal signal generator, and T s is the system sampling period, K GI is the proportional coefficient of the second-order generalized integrator and the orthogonal signal generator.

6. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: The identification equation composed of the sixth harmonic component and its differential in the d-axis and q-axis current feedback values is: in, and are the voltage instructions for the d-axis and q-axis respectively, and Respectively represent the input and The output of the second-order generalized integrator, R s is the dq plane resistance to be identified, i d and i q are the current feedback values of the d-axis and q-axis respectively, L d and L q are the d-axis and q-axis inductances to be identified, Q[D(i d )] and Q[D(i q )] are respectively input as D(i d ) and D(i q ) is the output result of the orthogonal signal generator, and ω dq Q[D(i d )] and ω dq Q[D(i q )] represent the differential of the d-axis and q-axis current feedback values, D(i d ) and D(i q ) represent the input i d and i q The output of the second-order generalized integrator when .

7. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 6, characterized in that: The recursive least squares method is used to solve the identification equation composed of the sixth harmonic component and its differential in the d-axis and q-axis current feedback values, which is expressed as: Where y(t) represents the output vector, H(t) represents the signal vector, and θ(t) represents the parameter vector.

8. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 1, characterized in that: The identification equation composed of the third harmonic component and its differential in the z1 and z2 axis current feedback values is: in, and are the voltage instructions for the z1 axis and z2 axis respectively, and Respectively represent the input and The output of the second-order generalized integrator, R sz is the z1z2 plane resistor to be identified, i z1 and i z2 are the current feedback values of the z1 axis and z2 axis respectively, L z is the z1z2 plane inductor to be identified, Q[D(i z1 )] and Q[D(i z2 )] are respectively input as D(i z1 ) and D(i z2 ) is the output result of the orthogonal signal generator, and ω z Q[D(i z1 )] and ω z Q[D(i z2 )] represent the differential of the current feedback value of the z1 axis and the z2 axis respectively, D(i z1 ) and D(i z2 ) are input as i z1 and i z2 The output of the second-order generalized integrator when .

9. The method for online parameter identification of a dual three-phase permanent magnet synchronous motor according to claim 8, characterized in that: The recursive least squares method is used to solve the identification equation composed of the third harmonic component and its differential in the z1 and z2 axis current feedback values, which is expressed as: Where y(t) represents the output vector, H(t) represents the signal vector, and θ(t) represents the parameter vector.

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