Motor parameter identification method and system based on multiple synchronous rotation coordinate conversion filters

Abstract

The invention discloses a motor parameter identification method and system based on multiple synchronous rotation coordinate conversion filters, and the method comprises the steps: taking the voltage and current of a motor under an alpha-beta axis and the position estimation information fed back by an orthogonal phase-locked loop as the input of a sliding-mode observer, thereby obtaining a back electromotive force observation value; the sliding mode algorithm adopts a switching function to suppress high-frequency buffeting in the back electromotive force, then harmonic disturbance in the back electromotive force is filtered out by adopting a multiple synchronous rotating coordinate system conversion filter, and a fundamental component of the back electromotive force passes through an orthogonal phase-locked loop to obtain rotor estimation speed and position information. The filter based on the multiple synchronous rotating coordinate system conversion can be applied to a motor sensorless control system, fifth and seventh harmonics in estimated counter electromotive force are eliminated, a good harmonic suppression effect is achieved, therefore, motor position information can be accurately obtained in real time, and the control performance of a motor driving system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of permanent magnet synchronous motor control, and in particular to a motor parameter identification method and system based on a multiple synchronous rotating coordinate conversion filter. BACKGROUND

[0002] To promote the quality and efficiency of the power industry, broaden the industrial chain of efficient and energy-saving electrical equipment, and accelerate the demand-side substitution of fossil energy. Permanent magnet synchronous motor (PMSM) is widely used in important fields such as aerospace and automotive transportation due to its simple structure, high power density, and other characteristics. With the development of advanced rare earth materials, the development of power electronics technology, and the improvement of motor control algorithms, the development and research of PMSM and its driving system meet the fundamental requirements of energy transformation in the current era.

[0003] The PMSM driving system mainly consists of the motor body, power electronic converter and controller. Regardless of the control algorithm, the accurate position information of the rotor needs to be obtained in real time to ensure the high-performance control of the PMSM, which is usually detected by a mechanical position sensor installed on the shaft of the motor. However, this type of mechanical position sensor has relatively harsh operating conditions and is easily affected, which seriously reduces the reliability of the PMSM driving system. In order to overcome these problems, sensorless control technology is used to control the PMSM. However, there are still many problems to be solved in the sensorless control technology of PMSM, such as harmonic suppression, high-precision, and high-robustness rotor position observation technology, which is still the mainstream direction of research by domestic and foreign scholars.

[0004] When the motor operates at medium and high speed, the back electromotive force or flux linkage of the motor needs to be observed by relying on the fundamental frequency model method, and the position information is extracted by processing the back electromotive force or flux linkage. The existing methods mainly include: model reference adaptive observation method, extended Kalman filter observation method, state observer observation method, disturbance observer observation method, and sliding mode observer observation method, etc. Among them, the sliding mode observation method is not sensitive to internal and external parameter disturbances of the system, so the system has strong robustness. However, due to the use of discontinuous control function and the inertia and hysteresis of the system, high-frequency chattering will exist in the output state variable, which will affect the estimation accuracy. In addition, due to the dead-time effect of the inverter, the actual voltage deviates from the reference voltage, which will produce a dead-time voltage. The dead-time voltage injected into the motor will cause harmonic components in the voltage and current, which will lead to high-order harmonics in the observed back electromotive force or flux linkage. When the position information is extracted by arctangent or PLL, high-order harmonics and DC bias will cause inaccurate position angle calculation.

[0005] From the above, there are still many problems in the above-mentioned prior art to be solved, and further exploration of feasible technology is needed, for example, the nonlinearity of the inverter and the magnetic field spatial harmonic will also lead to the distortion of the observed back electromotive force, wherein the dead time, the power device tube voltage drop is an important reason for the nonlinearity of the inverter, and the dead zone voltage generated by the dead zone effect of the inverter is injected into the motor, which will cause harmonic components in voltage and current; the magnetic bias of the permanent magnet and the rotor eccentricity will cause uneven distribution of the magnetic field space, and generate low-order harmonics (such as 3 times and 5 times), which will cause the observed back electromotive force to have harmonics, and further cause position estimation error. SUMMARY

[0006] The present application aims to solve the technical problem of position estimation error caused by the nonlinearity of the inverter and the magnetic field spatial harmonic leading to the distortion of the observed back electromotive force, and for this purpose, the present application provides a motor parameter identification method based on a multiple synchronous rotating coordinate conversion filter. In the present application, an improved multiple synchronous rotating coordinate conversion filter is introduced between the sliding mode observer and the quadrature phase-locked loop, which eliminates the fifth and seventh harmonics in the estimated back electromotive force, and has good harmonic suppression effect. The present application overcomes the problem of phase lag of the traditional sliding mode observer, increases the accuracy of signal estimation, improves the reliability of permanent magnet synchronous motor control, and has higher system stability and dynamic response. Especially for position, the position observation harmonic suppression effect is good.

[0007] Therefore, the present application provides the following technical scheme:

[0008] On the one hand, the present application provides a motor parameter identification method based on a multiple synchronous rotating coordinate conversion filter, comprising the following steps:

[0009] Step 1: sampling the motor drive system to obtain stator voltage and current components in two-phase static coordinate system , and then obtaining the back electromotive force estimation value based on the sliding mode observer;

[0010] Step 2: inputting the back electromotive force estimation value into a multiple synchronous rotating coordinate conversion filter to obtain a filtered fundamental back electromotive force; the multiple synchronous rotating coordinate conversion filter adopts a multi-harmonic observer cross feedback network based on SRFT (Synchronous Rotating Frame Transformation);

[0011] Step 3: inputting the filtered fundamental back electromotive force into a quadrature phase-locked loop, and normalizing to obtain the speed and the rotor position . ​

[0012] Further optionally, the multiple synchronous rotating coordinate system conversion filter filters the fundamental wave, the negative sequence fifth-order harmonic wave and the positive sequence seventh-order harmonic wave, and the corresponding orders are +1, -5 and +7, respectively.

[0013] The mathematical model of the SRFT-based multi-harmonic observer cross feedback network is represented as:

[0014]

[0015] In the formula, E1, E5 and E7 are the back electromotive force components corresponding to the orders +1, -5 and +7 after negative feedback, respectively. In the formula, E1, E5 and E7 are the back electromotive force components corresponding to the orders +1, -5 and +7 after negative feedback, respectively. In the formula, G1, G5 and G7 are transfer functions corresponding to the orders +1, -5 and +7, respectively. In the formula, E1, E5 and E7 are the back electromotive force components corresponding to the orders +1, -5 and +7 after negative feedback, respectively.

[0016] Further optionally, the multiple synchronous rotating coordinate system conversion filter filters the fundamental wave, the negative sequence fifth-order harmonic wave and the positive sequence seventh-order harmonic wave, and the corresponding orders are +1, -5 and +7, respectively.

[0017] In the formula, each cycle period is processed as follows:

[0018] The coordinate conversion matrix of the corresponding resonant frequency is calculated for each order, and the back electromotive force component of each order after negative feedback is converted to the synchronous rotating coordinate system and then low-pass filtered to obtain a direct current component.

[0019] The direct current component is inversely converted in the synchronous rotating coordinate system and used for negative feedback.

[0020] The back electromotive force component estimation value of each order in the stationary coordinate system after inverse conversion is fed back to other orders and then enters the next cycle period.

[0021] The negative feedback is to subtract the current back electromotive force component estimation value of other orders from the back electromotive force estimation value of the corresponding order, thereby obtaining the back electromotive force component of each order after negative feedback, which participates in the back electromotive force component estimation of the current order in the next cycle period.

[0022] Further optionally, the formula of the coordinate conversion matrix is as follows:

[0023]

[0024] In the formula, h is the position estimation value of the corresponding order, and θ is the rotor position. In the formula, h is the position estimation value of the corresponding order, and θ is the rotor position. In the formula, h is the position estimation value of the corresponding order, and θ is the rotor position. In the formula, h is the position estimation value of the corresponding order, and θ is the rotor position.

[0025] ​Further optionally, the overall transfer function of the multiple synchronous rotating coordinate system conversion filter is:

[0026]

[0027] In the formula, is the fundamental back-EMF, respectively, the transfer functions corresponding to the +1, -5, +7 orders, s is the Laplace variable, representing the complex frequency domain;

[0028]

[0029] In the formula, the rotational speed observation value corresponding to the order h , the parameter , the coefficient , is the cut-off frequency of the LPF, is the rotational speed estimation value, corresponds to .

[0030] Further optionally, the back-EMF estimation value when composed of the fundamental, negative sequence fifth order, and positive sequence seventh order harmonics, is represented by the mathematical model as:

[0031]

[0032] In the formula, represents the fundamental amplitude and the harmonic amplitude of the back-EMF component corresponding to the fundamental and the h order harmonic, the h order harmonic corresponding to the negative sequence fifth order and the positive sequence seventh order harmonic; is the initial phase of the back-EMF component corresponding to the fundamental and the h order harmonic; t is time, respectively, the fundamental rotational speed estimation value and the h order harmonic rotational speed estimation value.

[0033] In the second aspect, the motor control method based on the above motor parameter identification method provided by the technical scheme of the present application comprises:

[0034] The rotational speed estimation value and the rotor position estimation value are obtained by using the steps 1-3.

[0035] The rotational speed estimation value and the rotor position estimation value are used for IPMSM vector control, and finally, a PWM driving signal is obtained, which controls the on-off of the inverter switch tube to obtain an inverter voltage to drive the IPMSM, so as to realize the IPMSM position sensorless control.

[0036] In three aspects, the control system based on the above-mentioned motor parameter identification method provided by the technical solution of the present invention includes at least: a sliding mode observer (SMO), a multi-synchronous rotating coordinate system transformation filter, an orthogonal phase-locked loop (PLL), a sampling and processing module, an inner current loop, an outer speed loop, a speed loop PI regulator, an inner current loop PI regulator, and an SVPWM modulation module.

[0037] The sampling and processing module is used to sample the stator voltage in the two-phase stationary coordinate system of the motor drive system. and current components And transmit it to the sliding mode observer (SMO);

[0038] The sliding mode observer (SMO) is used to obtain the back electromotive force estimate. And transmit it to the multi-synchronous rotating coordinate system transformation filter;

[0039] The multi-synchronous rotating coordinate system transformation filter estimates the back electromotive force. Filtering is performed to obtain the filtered fundamental back electromotive force, which is then transmitted to the quadrature phase-locked loop.

[0040] The orthogonal phase-locked loop is used to calculate the speed estimate. and rotor position estimate and connected to the outer rotation speed ring;

[0041] The outer speed loop, the speed loop PI regulator, the inner current loop, the inner current loop PI regulator, and the SVPWM modulation module are connected in sequence to finally generate an inverter voltage to drive the IPMSM, which is then input to the motor.

[0042] The present invention provides a PMSM drive system including the above-mentioned control system, characterized in that it includes at least a control system, a permanent magnet synchronous motor body, and an inverter.

[0043] The control system generates a PWM drive signal to control the switching of the inverter transistors, thereby obtaining an inverter voltage to drive the IPMSM, which acts on the permanent magnet synchronous motor body.

[0044] In five aspects, the present invention provides a computer-readable storage medium storing a computer program, which is invoked by a processor to implement the following:

[0045] The steps of the motor parameter identification method based on the above-mentioned multi-synchronous rotating coordinate transformation filter or the steps of the above-mentioned motor control method.

[0046] Beneficial effects

[0047] The improved multiple synchronous rotating coordinate conversion filter is introduced between the sliding mode observer and the quadrature phase-locked loop, five seventh harmonics in the estimated back electromotive force are eliminated, and good harmonic suppression effect is obtained.

[0048] In order to verify the feasibility, the on-machine test system of the IPMSM of 1.5kw is carried out, including a magnetic powder brake torque for providing a load, the actual speed and position are measured through a mechanical shaft connection (PENON-K3808 G) with an incremental encoder, and the estimated accuracy is only used for comparison. The sensorless control is realized by using a DSP (32-bit TMS 320 F2808), the sampling frequency is 10 kHz, the discretization error of the linear interpolation MSRFT digital delay can be ignored, and the steady state and dynamic test are carried out, and it can be known from the figure that the phase estimation accuracy is improved, the phase lag problem is overcome, the signal estimation accuracy is increased, the permanent magnet synchronous motor control reliability is improved, and the system stability and dynamic response performance are higher. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 The structure block diagram of the control system of the motor parameter identification method disclosed in the application based on the multiple synchronous rotating coordinate conversion filter is shown in the figure;

[0050] Figure 2 The structure block diagram of the position observer based on the SMO and the multiple synchronous rotating coordinate conversion filter of the embodiment of the application is shown in the figure;

[0051] Figure 3 The structure of the harmonic observer based on the multiple synchronous rotating coordinate conversion filter of the embodiment of the application is shown in the figure;

[0052] Figure 4 The Bode diagram of the SRFT harmonic observer based on the embodiment of the application is shown in the figure;

[0053] Figure 5 The Bode diagram of the harmonic observer based on the multiple synchronous rotating coordinate conversion filter of the embodiment of the application is shown in the figure;

[0054] Figure 6 The Nyquist diagram of the SRFT harmonic observer based on the embodiment of the application is shown in the figure;

[0055] Figure 7 The estimated back electromotive force waveform diagram and the FFT analysis result of the harmonic observer based on the multiple synchronous rotating coordinate conversion filter of the embodiment of the application are shown in the figure. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application. The technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other.

[0057] It should be noted that although the functional modules are divided in the device schematic diagram, and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a manner different from the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification and claims and the above drawings are used to distinguish similar objects, and do not necessarily describe a specific order or sequence.

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0059] The application provides a motor parameter identification method based on multiple synchronous rotating coordinate conversion filter, which belongs to a position sensorless control method, and does not need to install a mechanical position sensor; and for the chattering phenomenon introduced by the sliding mode observer, the multiple synchronous rotating coordinate system conversion filter constructed in the technical solution of the application can accurately eliminate the harmonic component in the back electromotive force, without the need for additional compensation measures, thereby reducing the complexity of the IPMSM position sensorless control system, and realizing the elimination of the back electromotive force harmonic at a low switching frequency, and improving the rotor position estimation accuracy. The technical solution of the application is described in detail taking a permanent magnet synchronous motor as an example, and specific details are described below.

[0060] The estimation method and the control method provided by the technical solution of the application both need to use a sliding mode observer and a multiple synchronous rotating coordinate system conversion filter, therefore, the principle thereof is first described as follows:

[0061] Sliding mode observer:

[0062] The permanent magnet synchronous motor is sampled to obtain at least real-time stator current, and the real-time stator current is subjected to coordinate transformation to obtain the stator current in the two-phase stationary coordinate system, and the stator current estimation value is obtained by using the voltage equation .

[0063] Among them, the voltage equation of PMSM in the two-phase stationary coordinate system (αβ coordinate system) is:

[0064]

[0065] where, is the stator voltage, is the axis component, axis component; is the stator current, is the axis component, axis component; is the back EMF axis component, axis component; is the axis component, axis component; is the dq-axis inductance, is the stator resistance, is the rotational speed, is the rotor position, is the flux of the rotor magnet, denotes the differential operator.

[0066] where:

[0067]

[0068] where, is the extended back EMF amplitude.

[0069] The back EMF calculation process is to input the stator current and stator voltage in the two-phase stationary coordinate system, as well as the rotational speed observation value estimated by the quadrature phase-locked loop, into the sliding mode observer to obtain the back EMF observation value. The sliding mode observer voltage equation based on the extended back EMF for estimating the rotor position can be obtained:

[0070]

[0071] The stator current estimation value is added, is the axis component of the stator current estimation value, axis component; the back EMF observation value , is the axis component of the back EMF observation value, axis component; the rotational speed estimation value ; wherein the control function of the sliding mode observer is defined as: , denotes the sliding mode gain. To maintain system stability, it is necessary to satisfy:

[0072]

[0073]

[0074] wherein, is the stator current estimation error, the axis component, the axis component; A, B are self-defined coefficient matrix symbols.

[0075] It should be understood that the stator current observation value obtained based on the sliding mode observer is more and more close to the actual value of the stator current, and when the stator current observation value converges to the actual value of the stator current (the current observation value approaches the sliding mode surface), the back-EMF obtained at this time is regarded as the final back-EMF observation value and is used for subsequent position estimation. It should be understood that the data when not converging can also be transmitted to the subsequent filter, and the difference lies in that it is not used for directly estimating the position corresponding to the current time.

[0076] It should also be understood that the sliding mode observer described above is selected by taking the permanent magnet synchronous motor as an example in the embodiment of the application, and in other feasible embodiments, the sliding mode observer capable of observing the back-EMF is also within the protection scope of the application based on the change of the motor type and the motor model.

[0077] The harmonics in the back-EMF are analyzed, which include negative sequence fifth-order, positive sequence seventh-order harmonics and high-order harmonics. Considering the low-pass characteristics of the sliding mode observer SMO (Sliding Mode Observer) and the phase-locked loop PLL (Phase-Locked Loop), the high-frequency noise is ignored, and the back-EMF is rewritten as:

[0078]

[0079] wherein, denotes the fundamental amplitude and the harmonic amplitude corresponding to the back-EMF component of the fundamental and the h-order harmonic, and the subscript h denotes the harmonic order, corresponding to the negative sequence fifth-order, positive sequence seventh-order harmonics; is the initial phase corresponding to the back-EMF component of the fundamental and the h-order harmonic; t is time, respectively, are the fundamental speed estimation value and the h-order harmonic speed estimation value; the two kinds of harmonics will prevent the error from converging to zero, which means that the position estimation will deviate from the actual position to a certain extent, and the sensorless control performance is reduced.

[0080] The position signal error of the PLL is normalized to obtain:

[0081]

[0082]

[0083] wherein, is the position estimation value, is the phase estimation value corresponding to the fundamental and the harmonic, All are self-defined parameter symbols. From the above formula, it is known that the position estimation error is expected to be zero, but the two harmonics will prevent the error from converging to zero, meaning that the position estimation will deviate from the actual position to a certain extent, reducing the sensorless control performance.

[0084] Due to the influence of the nonlinearity of the inverter and the spatial harmonics of the magnetic field, the estimated back electromotive force is distorted, so the technical scheme of the present application introduces a multiple synchronous rotating coordinate system conversion filter, i.e. a filter module, for inputting the back electromotive force observation value into the constructed multiple synchronous rotating coordinate system conversion filter to obtain the filtered fundamental back electromotive force.

[0085] The multiple synchronous rotating coordinate system conversion filter:

[0086] Figure 3 The harmonic observer structure based on the multiple synchronous rotating coordinate system conversion filter of the embodiment of the present application, wherein a cross feedback network is used. In this embodiment, the harmonic order h = 1, -5, 7 is preferred. This is because the -5 and 7th harmonics are dominant, and need to be filtered out. Based on the above formula, those skilled in the art can understand that the filter can filter out the specified harmonic components to obtain the fundamental back electromotive force component. Specifically: the back electromotive force observation value is input into the multiple synchronous rotating coordinate system conversion filter, and the filter is divided into three orders, +1, -5, and +7, and each order only has a harmonic frequency that changes with the order. A cross feedback network based on the SRFT multiple harmonic observer is used, each observer observes the fundamental or harmonic at its own frequency, and the cross feedback network is a feasible structure that cooperates to adjust the parameters at different frequencies, so that the fundamental component can be obtained even under severely distorted back electromotive force, and multiple harmonic components can be eliminated. Among them, the cross feedback network based on the SRFT multiple harmonic observer is as follows:

[0087]

[0088] is the corresponding back electromotive force component of the corresponding h order after negative feedback, is the back electromotive force estimation value of the h order. are the transfer functions corresponding to +1, -5, and +7 orders respectively, h = +1, -5, and +7.

[0089] Mechanism of each order synchronous rotating coordinate system conversion filter: first, it is converted to direct current through coordinate transformation, and the expression is:

[0090]

[0091]

[0092] Among them,​ is the position estimation value corresponding to the order h, is the coordinate conversion matrix corresponding to the order h, is the h-th fundamental or harmonic component of the counter electromotive force in the synchronous rotating coordinate system, is the axis component, is the axis component; the harmonic of the negative sequence fifth and the positive sequence seventh can be extracted by the above formula and the low-pass filter as follows: is the h-th fundamental or harmonic component of the counter electromotive force in the synchronous rotating coordinate system,

[0093]

[0094] wherein, is the low-pass filter cutoff frequency, the direct current signal is extracted, the low-pass filter is input to filter out high-order, the signal corresponding to the order is extracted, and finally the coordinate is converted back to the corresponding order frequency, which is convenient for negative feedback afterwards, and the expression is as follows:

[0095]

[0096] wherein, is the estimated counter electromotive force component of the frequency h order in the stationary coordinate system, and the extracted harmonic is negatively fed back to other shaft systems for elimination.

[0097] As can be seen from the above, the multiple synchronous rotating coordinate system conversion filter realizes harmonic filtering through multiple cycles of circulation;

[0098] wherein, the processing process of each cycle is:

[0099] The coordinate conversion matrix of the corresponding resonant frequency is calculated for each order, and the counter electromotive force component of each order after negative feedback is converted to the synchronous rotating coordinate system based on the coordinate conversion matrix, and then the direct current component obtained after low-pass filtering is obtained;

[0100] The direct current component is inversely converted in the synchronous rotating coordinate system, which is used for negative feedback;

[0101] The counter electromotive force component estimation value of each order in the stationary coordinate system after inverse conversion is negatively fed back to other orders, and then enters the next cycle.

[0102] Based on the above reasoning, the multiple synchronous rotating coordinate system conversion filter is described from the overall perspective.

[0103] Single-order SRFT transfer function:

[0104]

[0105] In the formula, the rotational speed observation value corresponding to the order h , parameters , coefficients , is where the cut-off frequency of the LPF, its Bode diagram is as Figure 4 , it can be seen that the SRFT has a band-pass characteristic at , which can suppress the undesired components of other frequencies. According to the formula, the . corresponds to , the extracted harmonic signal of each order is input to other orders for filtering, and the final harmonic filtering is achieved through multiple cycles, obtaining the target fundamental signal, therefore, the overall transfer function is:

[0106]

[0107] Substituting the single-order transfer function into the equation can obtain:

[0108]

[0109] where the user-defined parameter satisfies:

[0110]

[0111] The overall Bode diagram is as Figure 5 , it can be seen from the figure that the proposed multiple synchronous rotating coordinate system conversion filter can eliminate the fifth and seventh harmonics to convert the observation signal into the required filtered waveform, ensuring the accuracy of the estimation and realizing the position sensorless position estimation. Simplifying can obtain:

[0112]

[0113] Regarding the structure as a negative feedback system, the open-loop transfer function is obtained:

[0114]

[0115] where the user-defined parameter :

[0116] .

[0117] The Nyquist diagram is drawn as Figure 6 , it can be seen that the frequency does not affect the stability of the system, and the system is always stable, that is, the system has good stability and response speed. It should be understood that according to the above technical means, the observation back-EMF filtered by the multiple synchronous rotating coordinate system conversion filter eliminates the fifth and seventh harmonics in the estimated back-EMF, and has good harmonic suppression effect.

[0118] Based on this, the motor parameter identification method based on the multiple synchronous rotating coordinate conversion filter provided by the embodiment of the application comprises the following steps:

[0119] Step 1: sampling the motor drive system to obtain stator voltage and current components in a two-phase static coordinate system , and then obtaining back electromotive force estimation value based on a sliding mode observer .

[0120] Step 2: inputting the back electromotive force estimation value into a multiple synchronous rotating coordinate conversion filter to obtain a filtered fundamental back electromotive force; the multiple synchronous rotating coordinate conversion filter adopts a multi-harmonic observer cross feedback network based on SRFT

[0121] Step 3: inputting the filtered fundamental back electromotive force into a quadrature phase-locked loop to obtain speed and rotor position .

[0122] In addition, the motor control method based on the motor parameter identification method comprises:

[0123] First, the speed estimation value and the rotor position estimation value are obtained by using the method of steps 1-3;

[0124] Second, the speed estimation value and the rotor position estimation value are used for IPMSM vector control, and finally a PWM driving signal is obtained, the PWM driving signal controls the on-off of the inverter switch tube to obtain the inverter voltage to drive the IPMSM, and the IPMSM position sensorless control is realized.

[0125] The permanent magnet synchronous motor position estimation method of the multiple synchronous rotating coordinate conversion filter disclosed in the application mainly comprises a sliding mode observer, a multiple synchronous rotating coordinate conversion filter and a quadrature phase-locked loop. According to the dSPACE experiment platform development process and the corresponding matching hardware, the platform mainly comprises an inverter rectifier circuit, a dSPACE system and a driving motor. After the motor control algorithm is built by using MATLAB / Simulink, it is compiled and downloaded to the dSPACE for implementation, and the control board connected with the dSPACE is used for power supply of each power supply, various hardware protection and the like. The optical encoder at the end of the motor rotating shaft is used to obtain the rotor position signal, but is only used for comparative analysis in the experiment and does not participate in the actual control of the motor. The magnetic powder brake linked with the motor coaxially provides a load torque for the motor. The stator voltage inputted by the sensor is inputted into the sliding mode observer, and the estimated stator current is obtained according to the voltage equation above​ , respectively, the actual stator current , the current difference is obtained by difference The back electromotive force is obtained by a sliding mode gain observer , input into a multiple synchronous rotating coordinate system conversion filter, the filter is divided into three orders, respectively, +1, -5, +7, and each order only has a resonant frequency that changes with the order, a multi-harmonic observer cross feedback network based on SRFT is used, each observer observes the respective fundamental wave or harmonic, and the cross feedback network is a feasible structure that cooperates to adjust parameters at different frequencies, and each order is first subjected to coordinate conversion of the corresponding resonant frequency , a direct current signal is extracted, input into a low-pass filter for high-order filtering, and a signal of the corresponding order is extracted, which is subjected to negative sign processing, and finally inverse coordinate conversion The extracted compensation signal of the corresponding order frequency is obtained Input into other orders for filtering, due to the limited extraction capability, the desired accuracy cannot be achieved at one time, and through multiple cycles of circulation, the final harmonic filtering is achieved, and the target fundamental wave signal is obtained The target fundamental wave signal is input into a quadrature phase-locked loop, normalized and processed by a quadrature transformation PI regulator to obtain the speed , and the rotor position is obtained by integration The estimated speed and position need to be input into the sliding mode observer and the multiple synchronous rotating coordinate system conversion filter for closed-loop estimation.

[0126] Therefore, the application overcomes the phase lag problem of the traditional sliding mode observer, increases the signal estimation accuracy, improves the permanent magnet synchronous motor control reliability, and has higher system stability and dynamic response. Figure 7 The estimated back electromotive force waveform and FFT analysis result of the harmonic observer based on the multiple synchronous rotating coordinate system conversion filter of the embodiment of the application can be seen, and it can be seen that after using the filter of the application, the back electromotive force waveform is obviously smoothed, close to a standard sine wave, and the FFT analysis result can be seen that the fifth and seventh harmonics are obviously reduced, achieving a good filtering effect.

[0127] In some embodiments, as shown in Figure 1 and 2 , the control system applying the motor parameter identification method at least includes: a sliding mode observer SMO, a multiple synchronous rotating coordinate system conversion filter, a quadrature phase-locked loop PLL, a sampling and processing module, a current inner loop, a speed outer loop, a speed loop PI regulator, a current inner loop PI regulator, and an SVPWM modulation module.

[0128] The sampling and processing module is configured to sample the motor driving system to obtain stator voltage and current components in a two-phase static coordinate system and transmit the stator voltage and current components to a sliding mode observer (SMO) The SMO is configured to obtain an estimated back electromotive force (EMF) value and transmit the estimated back EMF value to a multiple synchronous rotating coordinate transformation filter The multiple synchronous rotating coordinate transformation filter is configured to filter the estimated back EMF value to obtain a filtered fundamental back EMF value and transmit the filtered fundamental back EMF value to a quadrature phase detector (QPD) The QPD is configured to calculate a speed estimation value and a rotor position estimation value The speed outer loop, a speed loop PI regulator, a current inner loop, a current inner loop PI regulator, the SVPWM modulation module, and the IPMSM are sequentially connected to generate an inverter voltage driven IPMSM, which is input to the motor.

[0129] In some embodiments, the PMSM driving system provided by the technical solution of the present application comprises a control system, a permanent magnet synchronous motor (PMSM) and an inverter.

[0130] In some embodiments, the computer readable storage medium provided by the technical solution of the present application stores a computer program, which is called by a processor to implement:

[0131] the steps of the motor parameter identification method based on the multiple synchronous rotating coordinate transformation filter or the steps of the motor control method.

[0132] The process of implementing the motor parameter identification method based on the multiple synchronous rotating coordinate transformation filter comprises:

[0133] Step 1: sampling the motor driving system to obtain stator voltage and current components in a two-phase static coordinate system and obtaining an estimated back electromotive force (EMF) value based on a sliding mode observer (SMO) .

[0134] Step 2: inputting the estimated back EMF value to a multiple synchronous rotating coordinate transformation filter to obtain a filtered fundamental back EMF value The multiple synchronous rotating coordinate transformation filter adopts a multiple harmonic observer cross feedback network based on a synchronous reference frame transformation (SRFT)

[0135] Step 3: inputting the filtered fundamental back EMF value to a quadrature phase detector (QPD) to obtain a speed estimation value and a rotor position estimation value and rotor position .

[0136] The process of implementing the motor control method is as follows:

[0137] Step 1: Sampling the motor drive system to obtain stator voltage components in two-phase static coordinate system and current components , and then obtaining back-EMF estimation value based on a sliding mode observer.

[0138] Step 2: inputting the back-EMF estimation value into a multiple synchronous rotating coordinate system conversion filter to obtain filtered fundamental back-EMF; the multiple synchronous rotating coordinate system conversion filter adopts a cross feedback network of a multi-harmonic observer based on SRFT;

[0139] Step 3: inputting the filtered fundamental back-EMF into a quadrature phase-locked loop to obtain speed and rotor position through normalization processing.

[0140] Step 4: using the speed estimation value and the rotor position estimation value for IPMSM vector control to finally obtain a PWM driving signal, which controls the on-off of the inverter switch tube to obtain an inverter voltage to drive the IPMSM, thereby realizing IPMSM position sensorless control.

[0141] The specific implementation process of each step is described in the foregoing method.

[0142] The readable storage medium is a computer readable storage medium, which can be an internal storage unit of the software and hardware device in any of the foregoing embodiments, such as a hard disk or a memory of the controller. The readable storage medium can also be an external storage device of the controller, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the readable storage medium can include both the internal storage unit and the external storage device of the controller. The readable storage medium is used to store the computer program and other programs and data required by the controller. The readable storage medium can also be used to temporarily store data that has been output or will be output.

[0143] Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art, or the whole or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned readable storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0144] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer usable program code. The present application is produced by referring to the flowcharts and the instructions executed by the processor of the method, device (system), and computer program product according to the embodiments of the present application to realize the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams. These computer program instructions can also be stored in a computer readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable memory produce a manufactured product including instruction devices that realize the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams. These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer implemented process, so that the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one or more flows of the flowcharts and / or one or more blocks of the block diagrams.

[0145] It should be emphasized that the examples described in the present application are illustrative rather than limiting, and therefore the present application is not limited to the examples described in the specific embodiments, and any other embodiments derived by those skilled in the art from the technical solutions of the present application without departing from the purpose and scope of the present application, whether modified or replaced, also belong to the protection scope of the present application.

Claims

1. A motor parameter identification method based on multiple synchronous rotating coordinate conversion filter, characterized in that: The method comprises the following steps: Step 1: Sample the motor drive system to obtain stator voltage components in two-phase stationary coordinate system and current components , and then obtain back electromotive force estimation value based on a sliding mode observer ; Step 2: the back EMF estimation value is filtered An input multiple synchronous rotating coordinate system conversion filter is used to obtain a filtered fundamental back EMF, and the multiple synchronous rotating coordinate system conversion filter adopts a multiple harmonic observer cross feedback network based on SRFT. Step 3: The filtered fundamental back-EMF input is fed into a quadrature phase-locked loop, and the normalized processing obtains the rotating speed and the rotor position .

2. The method of claim 1, wherein: The multiple synchronous rotating coordinate system conversion filter filters the fundamental wave, negative sequence fifth-order and positive sequence seventh-order harmonics, and the corresponding orders are +1, -5 and +7; The mathematical model of the SRFT-based multi-harmonic observer cross feedback network is represented as: wherein, are the back EMF components of the +1, -5, +7 order after negative feedback, respectively, are the transfer functions of the +1, -5, +7 order, respectively, are the estimated values of the back EMF components of the +1, -5, +7 order in the two-phase stationary coordinate system, respectively.

3. The method of claim 1, wherein: The multiple synchronous rotating coordinate system conversion filter filters the harmonics through multiple cycles; The processing procedure of each cycle is as follows: The coordinate conversion matrix of the corresponding resonant frequency is calculated for each order, the back electromotive force component of each order after negative feedback is converted to the synchronous rotating coordinate system based on the coordinate conversion matrix, and the direct current component is obtained through low-pass filtering; The direct current component is inversely converted in the synchronous rotating coordinate system and used for negative feedback; The back electromotive force component estimation value of each order in the stationary coordinate system after inverse conversion is extracted and fed back to other orders, and then enters the next cycle; The negative feedback is to subtract the back electromotive force estimation value of other orders Subtracting the current back electromotive force component estimation value of other orders, thereby obtaining the back electromotive force component of each order after negative feedback, participating in the estimation of the back electromotive force component of the current order in the next cycle.

4. The method of claim 3, wherein: The formula of the coordinate conversion matrix is as follows: wherein, is a position estimate for the corresponding order h, is a rotor position; is a coordinate transformation matrix for the corresponding resonance frequency.

5. The method of claim 1, wherein: The overall transfer function of the multiple synchronous rotating coordinate system conversion filter is as follows: In the formula, is the fundamental back electromotive force, are the transfer functions corresponding to the +1, -5, +7 orders, respectively, and s is the Laplace variable, representing the complex frequency domain. In the formula, the order h corresponds to the rotational speed observation value , the parameter , the coefficient , is the cut-off frequency of the LPF, is the rotational speed estimate value, corresponds .

6. The method of claim 1, wherein: the back emf estimate When the fundamental, negative-sequence fifth, and positive-sequence seventh harmonics are used, the corresponding mathematical model is represented as: In the formula, denote the fundamental wave amplitude and the harmonic amplitude corresponding to the back-EMF component of the fundamental wave and the h-order harmonic, and the h-order harmonic corresponds to the negative sequence fifth-order and the positive sequence seventh-order harmonic; is the initial phase of the back-EMF component of the fundamental wave and the h-order harmonic; t is time, are the estimated values of the fundamental wave speed and the h-order harmonic speed, respectively.

7. A motor control method based on the motor parameter identification method of any one of claims 1-6, characterized in that: The method comprises the following steps: The rotational speed estimate is obtained in the manner of steps 1-3 and the rotor position estimate ; The rotational speed estimation value And the rotor position estimation value For IPMSM vector control, ultimately get PWM drive signal, the PWM drive signal control inverter switch tube on-off get inverter voltage drive IPMSM, realize IPMSM sensorless control.

8. A control system based on the method of parameter identification of an electrical machine according to any one of claims 1 to 6, characterized in that: At least comprising: The SMO, the multiple synchronous rotating coordinate system conversion filter, the PLL, the sampling and processing module, the current inner loop, the speed outer loop, the speed loop PI regulator, the current inner loop PI regulator, the SVPWM modulation module; The sampling and processing module is configured to sample the motor driving system to obtain stator voltage components in a two-phase static coordinate system and current components and transmit the stator voltage components and the current components to the sliding mode observer SMO. A sliding mode observer SMO is used to obtain back electromotive force estimates and transmitted to a multiple synchronous rotating coordinate system conversion filter; The multiple synchronous rotating coordinate system conversion filter is used for back electromotive force estimation value The fundamental back electromotive force is filtered to obtain a filtered fundamental back electromotive force, and the filtered fundamental back electromotive force is transmitted to a quadrature phase-locked loop. The quadrature phase locked loop is used to calculate a rotational speed estimate and a rotor position estimate and is connected to the rotational speed outer loop; The speed outer loop, the speed loop PI regulator, the current inner loop, the current inner loop PI regulator and the SVPWM modulation module are sequentially connected, and finally generate the inverter voltage driving IPMSM, and the inverter voltage driving IPMSM inputs the motor.

9. A PMSM drive system comprising the control system of claim 8, characterized by: At least comprising a control system, a permanent magnet synchronous motor and an inverter; The control system generates a PWM driving signal to control the on-off of the inverter switching tube, and then obtains the inverter voltage driving IPMSM, which acts on the permanent magnet synchronous motor.

10. A computer-readable storage medium, characterized in that: The computer program is stored and called by a processor to implement the following steps: The steps of the motor parameter identification method based on the multiple synchronous rotating coordinate conversion filter according to any one of claims 1-6 or the steps of the motor control method according to claim 7.

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