Magnetic weakening control strategy for mining permanent magnet driving motor based on dynamic parameter identification

Abstract

The invention belongs to an intelligent driving control technology of coal mining equipment, and provides a flux-weakening control strategy of a mining permanent magnet driving motor based on dynamic parameter identification in order to solve the problem that internal flux linkage parameters cannot be accurately observed after the motor enters a flux-weakening area in the operation process of the motor. The unscented Kalman filter is introduced to construct the permanent magnet flux linkage observer when the driving motor works in the weak magnetic area, the random distribution of a nonlinear system is accurately estimated, the linearization error of a traditional Kalman filter is avoided, more accurate state estimation is obtained, meanwhile, the self-adaptive technology is utilized, and the reliability of the system is improved. The observation noise of the permanent magnet flux linkage observer is identified and corrected, and the influence of interference on system operation is effectively suppressed.

Description

Technical Field

[0001] The present invention belongs to intelligent drive control technology for coal mining equipment, and specifically relates to a weak magnetic control strategy for a permanent magnet drive motor for mining based on dynamic parameter identification. Background Art

[0002] Mining battery powered vehicles are a major means of transportation required for coal mine production. Mining permanent magnet drive motors have become the first choice for mining battery powered vehicle motors due to their simple structure, small size and high power density. In order to ensure the stable operation of mining battery powered vehicles under extreme conditions such as high speed and climbing, weak magnetic control technology is widely used as an effective means. However, weak magnetic control technology has certain complexity and involves fine adjustment of many control parameters. In addition, the motor will inevitably be disturbed by a variety of complex factors during operation, such as internal temperature fluctuations, component wear and aging, and constant changes in the external environment. These interference factors will affect the stability of the internal parameters of the motor, cause parameter disturbances, and then lead to a mismatch between the control strategy and the actual state of the motor, and ultimately weaken the control performance of the motor. Given that advanced control algorithms have extremely high requirements for the accuracy of motor parameters, accurate identification of motor parameters has become a hot spot and frontier in the current research field.

[0003] At present, the field of flux identification of permanent magnet drive motors for mining mainly focuses on three technical paths: flux observation technology, model-based identification method and sensor identification method. Among them, flux observation technology is a traditional method. The motor output voltage and current data are input into the flux observation model to estimate the motor flux value. However, the accuracy of this method is easily affected by model construction errors and measurement errors. Therefore, in actual industrial applications, it is often necessary to introduce compensation mechanisms or perform calibration work to optimize its identification accuracy and the overall stability of the system. The sensor-based identification method directly relies on the flux sensor installed on the motor to measure and obtain the motor flux value in real time, thereby achieving accurate flux identification. Although this method is intuitive and accurate, it inevitably increases the cost investment and structural complexity of the system. The model-based identification method is highly favored in the flux identification of permanent magnet drive motors for mining due to its high accuracy and wide applicability. This method indirectly infers the motor flux information by constructing a detailed motor mathematical model and using the comparative analysis between the model and the actual measurement data. During the operation of the motor, multiple interference factors will cause disturbances in the internal parameters of the motor, which will lead to a decrease in the control performance of the motor and affect the response speed and stability of the entire control system. Therefore, in order to deal with this problem, a flux observer is designed to observe the change of the permanent magnet flux parameters of the motor in real time, so as to solve the problem of decreased control performance caused by inaccurate internal flux parameters of the motor. Summary of the invention

[0004] In order to solve at least one of the above technical problems existing in the prior art, the present invention provides a magnetic field weakening control strategy for a permanent magnet drive motor for mining based on dynamic parameter identification.

[0005] The present invention is implemented by the following technical solution: a weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification, comprising the following steps:

[0006] S1: real-time acquisition of the rotor angular frequency, three-phase stator current and DC bus voltage of the permanent magnet drive motor for mining, and pre-processing of the rotor angular frequency and the three-phase stator current to obtain the AC and DC axis current;

[0007] S2: Establish a maximum torque current ratio algorithm and a weak magnetic control algorithm, introduce an auxiliary function, and based on the auxiliary function and the maximum torque current ratio algorithm, obtain the constant torque zone current of the permanent magnet drive motor for mining when it works in the constant torque zone. When the permanent magnet drive motor for mining continues to work until the speed reaches the speed threshold of the constant torque zone, adjust the current AC and DC axis currents through the weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the permanent magnet drive motor for mining when it works in the weak magnetic zone.

[0008] S3: Calculate based on the AC and DC axis currents in the weak magnetic field area to obtain the AC and DC axis voltages, perform inverse Park transformation based on the AC and DC axis voltages to obtain AC and DC axis voltage instructions, obtain the action time of adjacent non-zero voltage vectors based on the AC and DC axis voltage vector instructions and use space vector pulse width modulation technology, and use the zero voltage vector to synthesize the reference voltage vector, and finally output the control pulse signal of the permanent magnet drive motor for mining;

[0009] S4: Establish a flux observer based on an adaptive unscented Kalman filter, and use the preprocessing results of the AC and DC axis currents, AC and DC axis voltages and rotor angular frequency in the weak magnetic field area as input signals of the flux observer. According to the processing results of the flux observer, the change of the permanent magnet flux when the permanent magnet drive motor for mining works in the weak magnetic field area is observed in real time.

[0010] Preferably, the auxiliary function is:

[0011]

[0012] In the formula, p n is the pole pair number, i d 、i q are the direct-axis current and quadrature-axis current, respectively, f is the permanent magnet flux, L d , L q are the direct-axis inductance and quadrature-axis inductance, λ is the Lagrange multiplier, i s is the current vector.

[0013] Preferably, step S2 is specifically as follows: using the Lagrange extremum method and auxiliary functions to obtain the partial derivative of the AC and DC axis currents to obtain the current in the constant torque zone; obtaining the maximum inverter voltage of the mine permanent magnet drive motor inverter, and making a difference based on the maximum inverter voltage and the DC bus voltage. When the maximum inverter voltage is equal to the DC bus voltage, the speed of the mine permanent magnet drive motor reaches the speed threshold in the constant torque zone, and adjusting the current AC and DC axis currents through the weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the mine permanent magnet drive motor working in the weak magnetic zone.

[0014] Preferably, the AC and DC axis currents in the weak magnetic region are:

[0015]

[0016] In the formula, ω e is the rotor speed of the permanent magnet drive motor for mining, u max is the maximum inverter voltage.

[0017] Preferably, step S3 further includes:

[0018] Determining the interval position of the reference voltage vector;

[0019] Acquire a carrier cycle of pulse width modulation, and determine the action time of the adjacent zero voltage vectors based on the interval position and the carrier cycle;

[0020] The driving pulse signal is determined according to the action time of adjacent zero voltage vectors.

[0021] Preferably, in step S4, a flux observer based on an adaptive unscented Kalman filter is established, comprising:

[0022] An adaptive matrix is ​​introduced to identify and correct the observation noise, and to determine whether the noise observation result is in a standard form. When the noise observation result is in a non-standard form, a nonlinear flux observer is established based on the non-standard form.

[0023] Preferably, in step S1, the three-phase stator current is preprocessed, including:

[0024] Using the Clarke transformation method, the three-phase stator current is transformed into coordinates to obtain current data in a stationary coordinate system;

[0025] The rotor position signal of the mining permanent magnet drive motor is obtained, and Park transformation is performed based on the rotor position signal and the current data in the stationary coordinate system to obtain the AC and DC axis currents.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present application introduces an unscented Kalman filter to construct a permanent magnet flux observer when the drive motor works in the weak magnetic field area, accurately estimates the random distribution of the nonlinear system, avoids the linearization error of the traditional Kalman filter, and obtains a more accurate state estimation. At the same time, adaptive technology is used to identify and correct the observation noise of the permanent magnet flux observer, effectively suppressing the influence of interference on the system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 It is a flow chart of a magnetic field weakening control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification provided by an embodiment of the present invention;

[0030] Figure 2 It is a vector control model of a permanent magnet synchronous motor for mining based on dynamic parameter identification of the present invention;

[0031] Figure 3 It is a simulation diagram of the motor flux parameter identification result in the example of the present invention;

[0032] Figure 4 It is a simulation diagram of the motor resistance parameter identification result in the example of the present invention;

[0033] Figure 5 It is a simulation diagram of the electromagnetic torque output by the motor in the example of the present invention. DETAILED DESCRIPTION

[0034] In conjunction with the drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments 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 implementation methods obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so that people familiar with this technology can understand and read them. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size should fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention. It should be noted that in this specification, relational terms such as first and second are only used to distinguish one entity from several other entities, and do not necessarily require or imply any actual relationship or order between these entities.

[0036] During the operation of the permanent magnet drive motor for mining, if the phase observation of the rotor flux is inaccurate, the excitation component and the torque component of the stator current cannot be completely decoupled, which may cause oscillation or even instability of the system. In the actual operation of the permanent magnet drive motor for mining, the weak magnetic zone is often caused by excessive load. If the flux observation is inaccurate at this time, it will affect the load capacity of the mining drive motor, and even burn the motor in serious cases. Therefore, the most critical link that determines the performance of the entire vector control system is the rotor flux observer. In order to solve the above problems, the present invention provides a weak magnetic control strategy for the permanent magnet drive motor for mining based on dynamic parameter identification. When the drive motor works in the weak magnetic zone, the flux observer constructed by the present application can accurately observe the change of the permanent magnet flux, so as to adjust the corresponding parameters in time and ensure the stable operation of the permanent magnet drive motor for mining.

[0037] like Figure 1 As shown, an embodiment of the present invention provides a magnetic field weakening control strategy for a permanent magnet drive motor for mining based on dynamic parameter identification, comprising the following steps:

[0038] S1: The rotor angular frequency, three-phase stator current and DC bus voltage of the permanent magnet drive motor for mining are collected in real time, and the rotor angular frequency and the three-phase stator current are preprocessed to obtain the AC and DC axis currents.

[0039] Optionally, the three-phase stator current is preprocessed, including: using the Clarke transformation method to perform coordinate transformation on the three-phase stator current to obtain current data in a stationary coordinate system; obtaining the rotor position signal of the mining permanent magnet drive motor, and performing Park transformation based on the rotor position signal and the current data in the stationary coordinate system to obtain the AC and DC axis currents.

[0040] In this embodiment, the mechanical angular frequency of the permanent magnet drive motor for mining is obtained in real time through the speed detection sensor, and the mechanical angular frequency is derived to obtain the rotor position signal of the permanent magnet drive motor for mining. At the same time, the three-phase stator current i of the permanent magnet drive motor for mining is collected in real time through the current collection device.a 、i b 、i c , and then the three-phase stator current i a 、i b 、i c Perform Clarke Transformation to obtain the current data i in the α-β stationary coordinate system α 、i β , and then according to the rotor position signal and the current data i in the stationary coordinate system α 、i β Perform Park's Transformation to obtain the direct and quadrature axis current i in the synchronous rotating coordinate system. d 、i q .

[0041] S2: Establish a maximum torque current ratio algorithm and a weak magnetic control algorithm, introduce an auxiliary function, and based on the auxiliary function and the maximum torque current ratio algorithm, obtain the constant torque zone current of the permanent magnet drive motor for mining working in the constant torque zone. When the permanent magnet drive motor for mining continues to work until the speed reaches the speed threshold of the constant torque zone, the current AC and DC axis currents are adjusted through the weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the permanent magnet drive motor for mining working in the weak magnetic zone.

[0042] In this embodiment, the torque formula is used as the objective function, the current constraint formula is used as the condition, and the auxiliary function is introduced:

[0043]

[0044] In the formula, is the torque formula, is the current constraint formula, p n is the pole pair number, i d 、i q are the direct-axis current and quadrature-axis current, respectively, f is the permanent magnet flux, L d , L q are the direct-axis inductance and quadrature-axis inductance, λ is the Lagrange multiplier, i s is the current vector.

[0045] Optionally, the Lagrange extremum method and auxiliary functions are used to obtain partial derivatives of the AC and DC axis currents to obtain the current in the constant torque region;

[0046] The maximum inverter voltage of the mine permanent magnet drive motor inverter is obtained, and the difference between the maximum inverter voltage and the DC bus voltage is made. When the maximum inverter voltage is equal to the DC bus voltage, the speed of the mine permanent magnet drive motor reaches the speed threshold in the constant torque zone. The current AC and DC axis currents are adjusted through a weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the mine permanent magnet drive motor working in the weak magnetic zone.

[0047] In this embodiment, the Lagrange extremum method is used to calculate i d 、i q Taking partial derivatives with λ, we get the following system of equations:

[0048]

[0049] After solving the equations, the dq axis current expression working in the constant torque region is obtained:

[0050]

[0051] When the mining permanent magnet drive motor continues to work in the constant torque area, it needs to enter the weak magnetic area. At this time, the maximum voltage of the inverter is equal to the DC bus voltage. At this time, the weak magnetic area AC and DC axis currents after entering the weak magnetic area are:

[0052]

[0053] In the formula, ω e is the rotor speed of the permanent magnet drive motor for mining, u max is the maximum inverter voltage.

[0054] S3: Calculate based on the AC and DC axis current in the weak magnetic field area to obtain the AC and DC axis voltage, perform inverse Park transform based on the AC and DC axis voltage to obtain the AC and DC axis voltage command, and based on the AC and DC axis voltage vector command and using space vector pulse width modulation technology, obtain the action time of adjacent non-zero voltage vectors, and use the zero voltage vector to synthesize the reference voltage vector, and finally output the control pulse signal of the permanent magnet drive motor for mining.

[0055] Optionally, it also includes: determining the interval position of the reference voltage vector; obtaining the carrier period of pulse width modulation, and determining the action time of the adjacent zero voltage vector based on the interval position and the carrier period; and determining the drive pulse signal according to the action time of the adjacent zero voltage vector.

[0056] In this embodiment, after the AC and DC axis currents pass through the PI controller, the AC and DC axis voltages are obtained, and then the AC and DC axis voltages are subjected to an inverse Park transform to obtain AC and DC axis voltage instructions in a stationary coordinate system.

[0057] In this embodiment, the reference voltage vector amplitude and phase voltage angular frequency of the mining permanent magnet drive motor working in the weak magnetic field area are obtained, and the components of the reference voltage in the two-phase stationary coordinate system are calculated based on the reference voltage vector amplitude and the phase voltage angular frequency, and then the interval position of the reference voltage vector is determined.

[0058] In this embodiment, when determining the interval position of the reference voltage vector, the basic non-zero vector voltage and the zero vector voltage of the adjacent interval are determined according to the current position of the reference voltage vector, and the basic non-zero vector voltage and the zero vector voltage are combined differently so that the average value after the combination is the same as the reference voltage vector, and then the action time of the reference voltage vector and the adjacent zero voltage vector is determined, thereby determining the drive pulse signal of the permanent magnet drive motor for mining during the action time.

[0059] S4: Establish a flux observer based on an adaptive unscented Kalman filter, and use the preprocessing results of the AC and DC axis currents, AC and DC axis voltages and rotor angular frequency in the weak magnetic field area as input signals of the flux observer. According to the processing results of the flux observer, the change of the permanent magnet flux when the permanent magnet drive motor for mining works in the weak magnetic field area is observed in real time.

[0060] Optionally, a flux observer based on an adaptive unscented Kalman filter is established, including: introducing an adaptive matrix to identify and correct observation noise, and judging whether the noise observation result is in a standard form; when the noise observation result is in a non-standard form, a nonlinear flux observer is established according to the non-standard form.

[0061] In this embodiment, before introducing the adaptive matrix to identify and correct the observation noise, it is necessary to calculate and update the estimated variance of the adaptive matrix. The variance formula is:

[0062]

[0063] Where n is the number of observation noises, is the optimal estimate at the current moment, It is the optimal estimate at the previous moment, and the T in the upper right corner indicates transposition.

[0064] The noise observation equation is:

[0065]

[0066] In the formula, E k is the identity matrix, v k is the system noise, g k is the variable when the Gaussian white noise expectation is 0, x k Estimate the system noise.

[0067] Taking the square root of both sides of the above equation to obtain the variance, we get the following equation:

[0068]

[0069] Where n is the number of observations, is the transpose of the identity matrix.

[0070] Compute the expected value of white noise and estimate the covariance matrix:

[0071]

[0072] Where tr is the trace of the matrix.

[0073] By updating the final estimated variance, the impact of state disturbance on the system is suppressed. The calculation formula is as follows:

[0074]

[0075] In the formula, Q k-1 is the noise covariance at the previous moment.

[0076] In this embodiment, in order to further improve the robustness of the unscented Kalman filter to the interference of system observation noise, an adaptive matrix is ​​introduced to identify and correct the system observation noise. The expression is as follows:

[0077]

[0078] Where C(k) is the adaptive matrix, ε is the rolling window, and y k For a given system observation, P yk is the estimated variance, S k is the noise variance matrix, and e(i) is the error between the reference value and the return value after passing through the unscented Kalman filter.

[0079] In this embodiment, the judgment function is defined as u(k), and the expression for judging whether the current noise observation is standard is:

[0080]

[0081] Where e(k) is the error between the reference value at time k and the return value after passing through the unscented Kalman filter, and C(k) -1 is the inverse matrix of the adaptive matrix.

[0082] When the noise observation result is in a non-standard form, the nonlinear flux observer is obtained by combining the voltage equation of the permanent magnet synchronous motor for mining:

[0083]

[0084] y(k)=Cx(k)+v(k)

[0085] In the formula,

[0086] In the formula, x=[i d i q ψ d ψ q ] are the AC and DC axis currents and flux linkages, where ψ d is the d-axis magnetic flux, ψ q is the q-axis magnetic flux; w=[u d / L u q / L] is the voltage equation of the permanent magnet synchronous motor for mining, L is the total inductance; y=[i d i q ]; v(k) is the system noise, ω is the rotor speed of the permanent magnet drive motor for mining, and R is the motor resistance.

[0087] An embodiment of the present invention provides a weak magnetic control strategy for a permanent magnet drive motor for mining based on dynamic parameter identification. By introducing an unscented Kalman filter, a permanent magnet flux observer is constructed when the drive motor works in a weak magnetic region, and the random distribution of the nonlinear system is accurately estimated, thereby avoiding the linearization error of the traditional Kalman filter and obtaining a more accurate state estimation. At the same time, adaptive technology is used to identify and correct the observation noise of the permanent magnet flux observer, thereby effectively suppressing the influence of interference on the operation of the system.

[0088] To further verify the effectiveness of the embodiments of the present application, the present application is constructed as follows Figure 2 The vector control model of the permanent magnet synchronous motor for mining shown in the figure is simulated and analyzed for verification. The speed command input by the model is converted into a current command. The current command is converted into a voltage command through the PI controller and coordinate transformation. The voltage command is passed through the space vector pulse width modulation module to obtain a duty cycle signal, which is input into the inverter module to control the motor. The simulation model of the flux observer of the adaptive unscented Kalman filter is established through the model reference adaptive module. In this simulation model, the flux parameter to be identified is an adjustable variable. The parameters to be identified are obtained through the adaptive regulation law that is derived theoretically or satisfies the stability theorem; the identification parameters obtained by the adaptive regulation law are substituted into the adjustable model, thereby adjusting the model parameters in real time. The specific model parameters are shown in Table 1 below.

[0089] Table 1

[0090] Motor parameters Numeric unit Pole pairs 4 - Motor resistance 0.958 Ω Stator inductance 0.0056 H Moment of Inertia 0.003 <![CDATA[kg·m 2 ]]> Permanent magnet flux amplitude 0.199 Wb Rated speed 1000 rpm DC bus voltage 300 V

[0091] like Figure 3 As shown in the figure, at 0.2s, the motor is suddenly loaded and disturbed by the outside world, the flux fluctuation is not large, and the calculation converges quickly.

[0092] like Figure 4 As shown in the figure, the identification results of the resistance parameters under load disturbance are basically close to the given results.

[0093] like Figure 5 As shown in the figure, the electromagnetic torque output of the motor has good stability when the load is suddenly added at 0.2s.

[0094] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A magnetic field weakening control strategy for a permanent magnet drive motor for mining based on dynamic parameter identification, characterized in that: The following steps are involved: S1: real-time acquisition of the rotor angular frequency, three-phase stator current and DC bus voltage of the permanent magnet drive motor for mining, and pre-processing of the rotor angular frequency and the three-phase stator current to obtain the AC and DC axis current; S2: Establish a maximum torque current ratio algorithm and a weak magnetic control algorithm, introduce an auxiliary function, and based on the auxiliary function and the maximum torque current ratio algorithm, obtain the constant torque zone current of the permanent magnet drive motor for mining when it works in the constant torque zone. When the permanent magnet drive motor for mining continues to work until the speed reaches the speed threshold of the constant torque zone, adjust the current AC and DC axis currents through the weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the permanent magnet drive motor for mining when it works in the weak magnetic zone. S3: Calculate based on the AC and DC axis currents in the weak magnetic field area to obtain the AC and DC axis voltages, perform inverse Park transformation based on the AC and DC axis voltages to obtain AC and DC axis voltage instructions, obtain the action time of adjacent non-zero voltage vectors based on the AC and DC axis voltage vector instructions and use space vector pulse width modulation technology, and use the zero voltage vector to synthesize the reference voltage vector, and finally output the control pulse signal of the permanent magnet drive motor for mining; S4: Establish a flux observer based on an adaptive unscented Kalman filter, and use the preprocessing results of the AC and DC axis currents, AC and DC axis voltages and rotor angular frequency in the weak magnetic field area as input signals of the flux observer. According to the processing results of the flux observer, the change of the permanent magnet flux when the permanent magnet drive motor for mining works in the weak magnetic field area is observed in real time.

2. The weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 1 is characterized in that: The auxiliary function in step S2 is: In the formula, p n is the pole pair number, i d 、i q are the direct-axis current and quadrature-axis current, respectively, f is the permanent magnet flux, L d , L q are the direct-axis inductance and quadrature-axis inductance, λ is the Lagrange multiplier, i s is the current vector.

3. The weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 1 is characterized in that: Step S2 is specifically: The Lagrange extremum method and auxiliary functions are used to obtain partial derivatives of the AC and DC axis currents to obtain the current in the constant torque zone; The maximum inverter voltage of the mine permanent magnet drive motor inverter is obtained, and the difference between the maximum inverter voltage and the DC bus voltage is made. When the maximum inverter voltage is equal to the DC bus voltage, the speed of the mine permanent magnet drive motor reaches the speed threshold in the constant torque zone. The current AC and DC axis currents are adjusted through a weak magnetic control algorithm to obtain the weak magnetic zone AC and DC axis currents of the mine permanent magnet drive motor working in the weak magnetic zone.

4. The weak magnetic field control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 3 is characterized in that: The AC and DC axis currents in the weak magnetic field region are: In the formula, ω e is the rotor speed of the permanent magnet drive motor for mining, u max is the maximum inverter voltage.

5. The weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 1 is characterized in that: Step S3 further includes: Determining the interval position of the reference voltage vector; Acquire a carrier cycle of pulse width modulation, and determine the action time of the adjacent zero voltage vectors based on the interval position and the carrier cycle; The driving pulse signal is determined according to the action time of adjacent zero voltage vectors.

6. The weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 1 is characterized in that: In step S4, a flux observer based on an adaptive unscented Kalman filter is established, including: An adaptive matrix is ​​introduced to identify and correct the observation noise, and to determine whether the noise observation result is in a standard form. When the noise observation result is in a non-standard form, a nonlinear flux observer is established based on the non-standard form.

7. The weak magnetic control strategy of a permanent magnet drive motor for mining based on dynamic parameter identification according to claim 1 is characterized in that: In step S1, the three-phase stator current is preprocessed, including: Using the Clarke transformation method, the three-phase stator current is transformed into coordinates to obtain current data in a stationary coordinate system; The rotor position signal of the mining permanent magnet drive motor is obtained, and Park transformation is performed based on the rotor position signal and the current data in the stationary coordinate system to obtain the AC and DC axis currents.

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