CN110995075B - Saturation model identification method, system, equipment and computer readable storage medium - Google Patents

Saturation model identification method, system, equipment and computer readable storage medium Download PDF

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CN110995075B
CN110995075B CN201911018908.4A CN201911018908A CN110995075B CN 110995075 B CN110995075 B CN 110995075B CN 201911018908 A CN201911018908 A CN 201911018908A CN 110995075 B CN110995075 B CN 110995075B
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axis
saturation
flux linkage
inductance
current
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CN110995075A (en
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孙鹏
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Shenzhen Inovance Technology Co Ltd
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Shenzhen Inovance Technology Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
    • H02P6/34—Modelling or simulation for control purposes
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
    • H02P23/14—Estimation or adaptation of motor parameters, e.g. rotor time constant, flux, speed, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/022—Synchronous motors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
    • H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/64—Electric machine technologies in electromobility

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  • Power Engineering (AREA)
  • Control Of Ac Motors In General (AREA)

Abstract

The invention provides a saturated model identification method, a system, equipment and a computer readable storage medium, wherein the saturated model identification method comprises the following steps: injecting first d-axis voltages of at least two periods into a stator winding of a synchronous motor to excite d-axis saturation characteristics of the synchronous motor, and acquiring d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents; injecting first q-axis voltages of at least two periods into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents. According to the embodiment of the invention, the d-axis voltage and the q-axis voltage are injected into the synchronous motor in a segmented way, so that the saturated model identification can be completed in a static off-line state, and the universality requirement is greatly improved under the condition of ensuring the accuracy.

Description

Saturation model identification method, system, equipment and computer readable storage medium
Technical Field
The present invention relates to the field of motor control, and more particularly, to a saturation model identification method, system, apparatus, and computer-readable storage medium.
Background
In the motor drive control system, the non-linear change of motor parameters along with different operation conditions caused by the characteristics of a motor body greatly limits the exertion of the optimal performance of a drive controller. In particular, for synchronous motors, the motor flux linkage current characteristics exhibit significant non-linear characteristics as the load changes, resulting in non-linear changes in motor inductance as the load changes.
The accuracy of the motor inductance parameter is very critical for both speed sensing control and speed sensorless control, and is particularly embodied in the following aspects:
(1) The deviation of the inductance parameter of the motor can cause the setting deviation of the parameter of the driving controller, and even can cause the control system to diverge and unstable operation under the condition that the nonlinear change of the inductance is obvious;
(2) Motor inductance parameter bias can affect MTPA (Maximum Torque Per Ampere, maximum torque to current ratio control performance, resulting in reduced system efficiency;
(3) The motor inductance parameter deviation can increase the torque observation deviation, influence the motor output effect and increase the control torque deviation:
(4) The motor inductance parameter deviation can cause the observer speed and angle observation deviation, the deviation can be fed back to a speed loop and a current loop, the deviation is aggravated, even the observer diverges, the controller is unstable, and the like, so that the influence is more obvious in speed-sensing-free control;
In a general motor driving control system, identification of inductance parameters of a synchronous motor needs to be executed before starting operation, and the traditional method needs to identify the AC-DC axis inductance of the synchronous motor in an off-line manner. The inductance obtained in the off-line identification process is a fixed value, and only represents the inductance value of the motor under a certain specific working condition, so that the actual inductance of the motor under different working conditions in the actual running process is difficult to be reflected truly.
In order to solve the problem that the off-line identification cannot truly reflect the actual inductance in the actual running process of the motor, various saturated model identification schemes have been proposed at present, and specifically include:
(1) The dynamic constant speed calibration test method needs to make the motor operate at a specific rotation speed, applies different current combinations to scan the working area through a current controller in a drag loading mode, and then calculates the flux linkage and the inductance under the current combination according to the flux linkage and the voltage equation of the motor. The method can ensure enough accuracy, but has complex process, needs additional loading test equipment, has limitation in most industrial field application, cannot achieve loading dynamic calibration test, and has poor universality.
(2) The dynamic acceleration and deceleration calibration test method is characterized in that a constant AC-DC axis current is set through a current loop, so that a motor is accelerated and then decelerated, and additional loading test equipment is not needed. And calculating flux linkage only through voltage and current data in the acceleration and deceleration process, and finally obtaining the flux linkage average value in the acceleration and deceleration engineering. The method has the same basic principle as the method, but does not need additional loading test equipment, and has simple process. However, the method also needs to be identified in a dynamic process, has poor applicability to occasions where dynamic identification cannot be carried out on various loads on an industrial site, and has long duration of the identification process.
(3) The method divides the motor flux linkage current relation into a non-saturated linear section and a saturated non-linear section, and the two ends of the non-saturated linear section are expressed by approximate relation. And acquiring voltage and current data through an alternating-direct axis voltage injection mode, so as to calculate and obtain a flux linkage, and determining fitting coefficients of a linear segment and a nonlinear segment in the segment model according to a specific coefficient fitting method (such as a least square method and the like). The accuracy of the method is to be improved, and the expression after the saturated model is segmented is not suitable for more synchronous motors, and the accuracy and the applicability are poor.
(4) The static flux linkage current fitting model identification method is characterized in that a flux linkage current relation is expressed by a complex polynomial, high-frequency pulse voltage is continuously injected into an alternating-direct axis, current response data are obtained, flux linkage data are obtained through calculation, flux linkage current polynomial fitting coefficients are determined by a specific fitting method, and finally a flux linkage-current expression is obtained, so that an inductance current expression can be obtained. Although static off-line identification of flux linkage and inductance can be realized, in order to ensure that the relation between flux linkage current and inductance current can accurately reflect the real characteristics of a motor, a polynomial expression is often very complex, and the coefficients of the polynomial are more. In order to fit a plurality of coefficients, the required calculation amount and data amount are more, the implementation space in the embedded system has a certain limitation, and the universality is not strong enough. More importantly, by adopting a continuous high-frequency pulse voltage injection method, when the flux linkage is obtained, the direct current bias or zero drift of flux linkage data can be caused by the phenomena of the initial value of integration, the direct current bias of voltage and current data and the zero drift, and the filter method has limited elimination effect, can further bring about identification deviation, and can also cause rotor shake and vibration.
(5) The method relies on high-frequency injection signals, and obtains flux linkage and inductance by extracting high-frequency current response information and utilizing a motor high-frequency digital model. However, the injected high-frequency signals can have adverse effects on the performances of noise, torque pulsation and the like in the online running process of the motor. In the speed-sensorless control, the injected high-frequency voltage is coupled in the speed-sensorless observation, so that the rotation speed and angle observation deviation is brought, and the stability of the observer is even affected when the rotation speed and angle observation deviation is serious, so that the system is unstable to operate.
Disclosure of Invention
Aiming at the problems that in the saturated model identification scheme, a dynamic constant-speed calibration test method is poor in universality, a dynamic acceleration and deceleration calibration test method is poor in applicability and long in duration, the accuracy and the applicability of a segmented approximate saturated model identification method are poor, the calculated amount and the data amount of a static flux linkage current fitting model identification method are large, direct current bias or zero drift exists in flux linkage data, and the online identification method causes unstable operation of a system, the saturated model identification method, the saturated model identification system, equipment and a computer readable storage medium are provided.
The technical scheme for solving the technical problems in the embodiment of the invention is to provide a saturation model identification method for acquiring saturation model parameters of a synchronous motor, wherein the saturation model parameters comprise self-saturation coefficients, and the method comprises the following steps:
Injecting first d-axis voltages of at least two periods into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first d-axis currents respectively generated by excitation of the first d-axis voltages of the at least two periods in the stator winding of the synchronous motor, and acquiring d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents;
injecting first q-axis voltages of at least two periods into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first q-axis currents respectively generated by the excitation of the first q-axis voltages of the at least two periods in the stator winding of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents.
The embodiment of the invention also provides a saturated model identification system, which is used for acquiring saturated model parameters of the synchronous motor, wherein the saturated model parameters comprise self-saturation coefficients, and the system comprises a first identification unit and a second identification unit, wherein:
The first identification unit is used for injecting first d-axis voltages of at least two periods into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, sampling at least two first d-axis currents respectively generated by excitation of the first d-axis voltages of the at least two periods in the stator winding of the synchronous motor, and acquiring d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents;
the second identification unit is used for injecting first q-axis voltages of at least two periods into the stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, sampling at least two first q-axis currents respectively generated by the excitation of the first q-axis voltages of the at least two periods in the stator winding of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents.
The embodiment of the invention also provides saturated model identification equipment, which comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor realizes the steps of the saturated model identification method when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the steps of the saturated model identification method when being executed by a processor.
According to the saturated model identification method, the saturated model identification system, the saturated model identification equipment and the computer readable storage medium, d-axis voltages of at least two periods and q-axis voltages of at least two periods are injected into the synchronous motor in a segmented mode, so that saturated model identification can be completed in a static off-line state, and the universality requirement is greatly improved under the condition of ensuring the accuracy.
The embodiment of the invention also adjusts the injection voltage set value according to different current states, thereby ensuring the current sampling accuracy, effectively reducing or avoiding rotor shake, and simultaneously eliminating accumulated errors introduced by continuous integration in the flux linkage solving process as far as possible.
Drawings
FIG. 1 is a flow chart of a saturated model identification method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a first d-axis voltage and a first d-axis current in a saturated model identification method according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a first d-axis voltage and a first d-axis current in a saturated pattern recognition method according to another embodiment of the invention;
FIG. 4 is a schematic diagram of a first d-axis voltage and a first d-axis current in a saturated pattern recognition method according to another embodiment of the invention;
FIG. 5 is a schematic flow chart of obtaining d-axis self-saturation inductance in the saturation model identification method according to the embodiment of the present invention;
FIG. 6 is a graph of obtaining d-axis self-saturation inductance in a saturation model identification method according to an embodiment of the present invention;
FIG. 7 is a schematic flow chart of obtaining a q-axis self-saturation inductance in the saturation model identification method according to the embodiment of the present invention;
FIG. 8 is a graph of the q-axis self-saturation inductance obtained in the saturation model identification method according to the embodiment of the present invention;
FIG. 9 is a schematic diagram of obtaining a d-axis inductance cross-coupling coefficient and a q-axis inductance cross-coupling coefficient in a saturated model identification method according to an embodiment of the present invention;
FIG. 10 is a schematic diagram of a second d-axis voltage, a second d-axis current, a second q-axis voltage, and a second q-axis current in a saturated model identification method according to an embodiment of the present invention;
FIG. 11 is a schematic diagram of a second d-axis voltage, a second d-axis current, a second q-axis voltage, and a second q-axis current in a saturated model identification method according to another embodiment of the invention;
FIG. 12 is a flow chart of obtaining d-axis self-saturation flux linkage in the saturation model identification method according to the embodiment of the present invention;
FIG. 13 is a schematic flow chart of acquiring q-axis self-saturation flux linkage in the saturation model identification method according to the embodiment of the present invention;
FIG. 14 is a schematic diagram of acquiring a d-axis flux linkage cross-coupling coefficient and a q-axis flux linkage cross-coupling coefficient in a saturated model identification method according to an embodiment of the present invention;
FIG. 15 is a schematic diagram of a saturated pattern recognition system according to an embodiment of the present invention;
fig. 16 is a schematic diagram of a saturated model recognition device according to an embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
According to the invention, the d-axis saturation characteristic and the q-axis saturation characteristic of the synchronous motor are excited at different times, so that the accuracy of current sampling is ensured, rotor shake can be effectively reduced or avoided, and accumulated errors introduced by continuous integration in the flux linkage solving process can be eliminated as much as possible, thereby improving the accuracy of saturated model identification and the universality of an identification method.
As shown in fig. 1, a saturated model identification method provided by an embodiment of the present invention is used for obtaining saturated model parameters of a synchronous motor, where the saturated model parameters include self-saturation coefficients (may include d-axis self-saturation coefficients and q-axis self-saturation coefficients in particular), and the saturated model identification method of the embodiment includes the following steps:
Step S11: injecting at least two periods of first d-axis voltage into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first d-axis currents respectively generated by the excitation of the at least two periods of first d-axis voltage in the stator winding of the synchronous motor, and acquiring d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents.
In this step, by injecting a first d-axis voltage into the stator windings of the synchronous machine, a current is generated in the synchronous machine windings sufficient to excite the saturation effect of the synchronous machine, i.e. a direct (d-axis) current (id) is generated in the rotational coordinate system in a direct (d-axis) direction sufficient to bring the synchronous machine into non-linear saturation. The first d-axis voltage needs to include a positive voltage and a negative voltage, and the voltage amplitude has no specific requirement, and only needs to be capable of exciting the current of the saturation effect of the synchronous motor. Also, the more the number of periods of the first d-axis voltage injected into the stator winding of the synchronous machine, the more accurate the obtained d-axis self-saturation coefficient, but the more the calculation amount and time consuming are increased.
The first d-axis voltage used in calculating the d-axis self-saturation coefficient may directly employ the voltage injected into the stator winding. To make the calculation structure more accurate, the first d-axis voltage may also be obtained by sampling the stator winding voltage. In order to ensure accurate subsequent identification and calculation, the first d-axis voltage (when obtained by a sampling mode) and the first d-axis current data acquisition may include links such as data delay calibration, zero drift calibration, nonlinear compensation calibration of an inverter, and the like.
Step S12: injecting first q-axis voltages of at least two periods into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first q-axis currents respectively generated by the excitation of the first q-axis voltages of at least two periods in the stator winding of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents.
Similarly, in step S11, the step generates a current in the windings of the synchronous machine sufficient to excite the saturation effect of the synchronous machine, i.e. a sufficient quadrature (q-axis) current (iq) in the rotating coordinate system, by injecting a first q-axis voltage into the stator windings of the synchronous machine to such an extent that the synchronous machine is in nonlinear saturation. The first q-axis voltage needs to include a positive voltage and a negative voltage, and the voltage amplitude has no specific requirement, and only needs to be capable of exciting the current of the saturation effect of the synchronous motor. Also, the more the number of periods of the first d-axis voltage injected into the stator winding of the synchronous machine, the more accurate the obtained d-axis self-saturation coefficient, but the more the calculation amount and time consuming are increased.
The first q-axis voltage used in calculating the q-axis self-saturation coefficient may directly employ the voltage injected into the stator winding. To make the calculation structure more accurate, the first q-axis voltage may also be obtained by sampling the stator winding voltage. In order to ensure accurate subsequent identification and calculation, the first q-axis voltage (when obtained by a sampling mode) and the first q-axis current data acquisition may include links such as data delay calibration, zero drift calibration, nonlinear compensation calibration of an inverter, and the like.
In the step S11, the first d-axis voltage is injected into the stator winding of the synchronous motor and the first d-axis current of the stator winding of the synchronous motor is sampled, and in the step S12, the first q-axis voltage is injected into the stator winding of the synchronous motor and the first q-axis current of the stator winding of the synchronous motor is sampled, which are performed at different times, and the execution sequence is not limited.
According to the saturation model identification method, d-axis voltages of at least two periods and q-axis voltages of at least two periods are injected into the synchronous motor in a segmented (i.e. different time periods), so that the saturation model identification can be completed in a static off-line state, and the universality requirement is greatly improved under the condition of ensuring the accuracy. Compared with the existing continuous pulse voltage injection identification method, the saturation model identification method has the advantages that the number of coefficients to be identified is small, complex polynomial fitting is not needed, operation is relatively small, the required storage space of a controller is low, and identification accuracy is high.
In one embodiment of the present invention, as shown in fig. 2, the first d-axis voltage 21 (the first q-axis voltage) may be a continuous positive and negative pulse equivalent voltage, which may cause a corresponding generation of a first d-axis current 22 (the first q-axis current) in the synchronous motor winding. To improve the accuracy of the identification, the number of pulse periods of the first d-axis voltage 21 (first q-axis voltage) injected to the stator winding of the synchronous motor may be increased.
In order to eliminate the accumulated error introduced by continuous integration during flux linkage calculation as much as possible, as shown in fig. 3, the first d-axis voltage 31 (first q-axis voltage) is a segmented positive and negative pulse equivalent voltage, which can correspondingly generate a first d-axis current 32 (first q-axis current) in the synchronous motor winding. That is, the first d-axis voltage (first q-axis voltage) of one period is divided into two parts: the portion that excites the positive first d-axis current 32 (first q-axis current) and the portion that excites the negative first d-axis current 32 (first q-axis current) are added with an interruption (i.e., zero voltage) of a preset duration in both portions, and the interruption duration can be adjusted as required.
In addition, when the first d-axis voltage and the first q-axis voltage are injected into the stator winding of the synchronous motor, the injection voltage set value can be adjusted according to different current states. Specifically, as shown in fig. 4, the first d-axis voltage 41 may be adjusted according to the first d-axis current 42 such that the voltage amplitude of the first d-axis voltage when the first d-axis current 42 is less than or equal to the preset amplitude is less than the voltage amplitude when the first d-axis current 42 is greater than the preset amplitude; and adjusting the first q-axis voltage according to the first q-axis current such that the voltage magnitude of the first q-axis voltage is less when the first q-axis current is less than or equal to the preset magnitude than when the first q-axis current is greater than the preset magnitude. The method has the advantages that the method adopts low-voltage injection when the excited current is smaller, and adopts high-voltage injection when the excited current is larger, so that on one hand, the accuracy of current sampling can be ensured, on the other hand, the influence of rotor jitter in the voltage injection process can be reduced as much as possible, and overcurrent or inaccurate current sampling in the identification process caused by too fast current rising of the small-inductance synchronous motor can be effectively avoided, and the universality of the identification method is improved.
In another embodiment of the present invention, the saturation model parameter includes a d-axis self-saturation inductance, and in this case, as shown in fig. 5, the d-axis self-saturation inductance may be obtained specifically in the above step S11 by:
step S111: according to the first d-axis voltage and the corresponding first d-axis current of each period, a first d-axis inductance at each sampling point of the first d-axis current is obtained (the first d-axis inductance can be a first d-axis inductance at part or all sampling points of the first d-axis current, and can be calculated in different manners according to different application occasions, and the following steps are the same), and in order to ensure the accuracy of the calculation of the first d-axis inductance, the steps can include necessary operations such as filtering, direct current bias, zero drift processing and the like.
Specifically, the d-axis self-saturation coefficient may specifically include a d-axis self-saturation inductance, as shown in fig. 6, if two periods of first d-axis voltages are injected into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, the step may be to obtain a first d-axis current of the stator winding during a first period of the first d-axis voltages being injected into the stator winding, and calculate the first d-axis inductance at each sampling point of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of the period (the first d-axis inductance during the period may be shown as a curve 61 in fig. 6); when the first d-axis voltage of the second period is injected into the stator winding, sampling to obtain a first d-axis current of the stator winding during the period, and calculating a first d-axis inductance at each sampling point of the first d-axis current according to the first d-axis voltage of the period and the corresponding first d-axis current (the first d-axis inductance during the period may be shown as a curve 62 in fig. 6).
Step S112: the first d-axis inductance average value at the plurality of preset current feature points 65 is obtained, where the first d-axis inductance average value is an average value or a weighted average value of the first d-axis inductances obtained at the preset current feature points according to the first d-axis voltage of at least two periods and the corresponding first d-axis current, respectively.
The number and the interval of the predetermined current feature points 65 are not limited, for example, the current feature points 65 may take the values of-In, -0.5In, -0.25In, 0, 0.25In, 0.5In, etc., respectively, where In is the rated current of the synchronous motor. In this step, at each preset current feature point 65, a first d-axis inductance of a first period (i.e., a point on the curve 61) and a first d-axis inductance of a second period (i.e., a point on the curve 62) are taken, and the ordinate of the two points is averaged or weighted to form a first d-axis inductance average at the preset current feature point 65. I.e. each preset current feature point 65 corresponds to a first d-axis inductance mean value.
Step S113: the d-axis self-saturating inductance is obtained by piecewise interpolation fitting (e.g., least squares, etc.) to the first d-axis inductance mean at a plurality of preset current feature points 65, as shown by curve 63 in fig. 6.
The q-axis self-saturation coefficient may specifically include a q-axis self-saturation inductance, and as shown in fig. 7, the step S12 may specifically obtain the q-axis self-saturation inductance by:
step S121: the first q-axis inductance at each sampling point of the first q-axis current is obtained according to the first q-axis voltage and the corresponding first q-axis current of each period (which may be calculated in different manners according to different applications), and this step may include necessary filtering, dc bias, zero-shift processing, etc. in order to ensure accuracy of the calculation of the first q-axis inductance.
Specifically, as shown in fig. 8, if two periods of first q-axis voltages are injected into the stator winding of the synchronous motor to excite the q-axis saturation characteristic of the synchronous motor, the step may be to sample and obtain a first q-axis current of the stator winding during the period when the first q-axis voltages of the first period are injected into the stator winding, and calculate a first q-axis inductance at each sampling point of the first q-axis current according to the first q-axis voltages of the period and the corresponding first q-axis currents (the first q-axis inductance during the period may be shown as a curve 81 in fig. 8); when the first q-axis voltage of the second period is injected into the stator winding, sampling is performed to obtain a first q-axis current of the stator winding during the period, and a first q-axis inductance at each sampling point of the first q-axis current is calculated according to the first q-axis voltage of the period and the corresponding first q-axis current (the first q-axis inductance during the period may be shown as a curve 82 in fig. 8).
Step S122: the first q-axis inductance means at a plurality of preset current feature points 85 are obtained, and the first q-axis inductance means is an average value or a weighted average value of the first q-axis inductances obtained at the preset current feature points according to the first q-axis voltage of at least two periods and the corresponding first q-axis currents, respectively.
In this step, at each preset current feature point 85, a first q-axis inductance of a first period (i.e., a point on the curve 81) and a first q-axis inductance of a second period (i.e., a point on the curve 82) are taken, and the ordinate of the two points is averaged or weighted to form a first q-axis inductance average at the preset current feature point 85. I.e. each preset current feature point 85 corresponds to a first q-axis inductance average value.
Step S123: the q-axis self-saturating inductance is obtained by piecewise interpolation fitting (e.g., least squares, etc.) to the first q-axis inductance mean at a plurality of preset current feature points 85, as shown by curve 83 in fig. 8.
In another embodiment of the present invention, the saturation model parameters may further include an inductance cross-coupling coefficient (specifically including a d-axis inductance cross-coupling coefficient and a q-axis inductance cross-coupling coefficient), as shown in fig. 9, and the corresponding saturation model identification method further includes, in addition to the steps shown in fig. 1:
Step S91: simultaneously injecting a second d-axis voltage and a second q-axis voltage into a stator winding of the synchronous motor to excite d-axis saturation characteristics and q-axis saturation characteristics of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor. The second d-axis voltage and the second q-axis voltage need to include a positive voltage and a negative voltage (in the same period), and the voltage amplitude is not specifically required, and only the current capable of exciting the saturation effect (i.e., the cross coupling characteristic of the d-axis and the q-axis) of the synchronous motor is needed.
In particular, in order to avoid the rotor of the synchronous motor from shaking during the injection of the second d-axis voltage and the second q-axis voltage into the stator winding as much as possible, as shown in fig. 10, the starting voltage directions of the second d-axis voltage 101 and the second q-axis voltage 103 are the same, and the stator winding is excited to generate the second d-axis current 102 and the second q-axis current 104, respectively, and the directions of the second d-axis voltage and the second q-axis voltage are opposite for at least a part of the period; alternatively, as shown in fig. 11, the starting voltage directions of the second d-axis voltage 111 and the second q-axis voltage 112 (which excite the stator windings to generate the second d-axis current 112 and the second q-axis current 114, respectively) are opposite, and (one period) at least for a part of the period, the directions of the second d-axis voltage 111 and the second q-axis voltage 113 are the same.
Step S92: a second d-axis inductance at each sampling point of the second d-axis current and a second q-axis inductance at each sampling point of the second q-axis current are calculated based on the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current (e.g., the second d-axis inductance may be the curve 64 shown in fig. 6 and the second q-axis inductance may be the curve 84 shown in fig. 8). To ensure accuracy of inductance calculation, this step may include necessary filtering, dc biasing, zero drift processing, etc.
Step S93: the second d-axis inductance at the plurality of preset current feature points 65 (the value at the corresponding preset current feature point 65 on the curve 64) is obtained, and the d-axis inductance cross-coupling coefficient (the d-axis inductance cross-coupling coefficient is a variable related to the d-axis current) is obtained by the identification fitting method according to the difference between the first d-axis inductance average value (from the curve 63) at the plurality of preset current feature points 65 and the second d-axis inductance (at the same preset feature point).
Step S94: the second q-axis inductance at the plurality of preset current feature points 85 (the value at the corresponding preset current feature point 85 on the curve 84) is obtained, and the q-axis inductance cross-coupling coefficient (the q-axis inductance cross-coupling coefficient is a variable related to the q-axis current) is obtained by the identification fitting method based on the difference between the first q-axis inductance average value (from the curve 63) at the plurality of preset current feature points 85 and the second q-axis inductance (at the same preset feature point).
In still another embodiment of the present invention, the d-axis sub-saturation coefficient may include a d-axis self-saturation flux linkage, and in this case, as shown in fig. 12, the d-axis self-saturation flux linkage may be obtained in the following manner in step S11:
step S114: according to the first d-axis voltage and the corresponding first d-axis current of each period, a first d-axis flux linkage at each sampling point of the first d-axis current is obtained (which can be calculated in different manners according to different application occasions), and in order to ensure the accuracy of the calculation of the first d-axis flux linkage, the steps can comprise necessary operations such as filtering, direct current bias, zero drift treatment and the like.
Specifically, if two periods of first d-axis voltage are injected into the stator winding of the synchronous motor to excite the d-axis saturation characteristic of the synchronous motor, the step can obtain a first d-axis current of the stator winding during the period by sampling when the first d-axis voltage of the first period is injected into the stator winding, and calculate a first d-axis flux linkage at each sampling point of the first d-axis current according to the first d-axis voltage of the period and the corresponding first d-axis current; and when the first d-axis voltage of the second period is injected into the stator winding, sampling to obtain a first d-axis current of the stator winding in the period, and calculating a first d-axis flux linkage at each sampling point of the first d-axis current according to the first d-axis voltage of the period and the corresponding first d-axis current.
Step S115: and acquiring first d-axis flux linkage average values at a plurality of preset current characteristic points, wherein the first d-axis flux linkage average values are average values or weighted average values of the first d-axis flux linkages acquired at the preset current characteristic points according to the first d-axis voltages of at least two periods and corresponding first d-axis currents respectively.
In the step, at each preset current characteristic point, taking a first d-axis flux linkage of a first period and a first d-axis flux linkage of a second period, and taking an average value or a weighted average value of the two points to form a first d-axis flux linkage average value at the preset current characteristic point. I.e. each preset current feature point corresponds to a first d-axis flux linkage mean value.
Step S116: the d-axis self-saturation flux linkage is obtained by performing piecewise interpolation fitting (e.g., least square method, etc.) on the first d-axis flux linkage mean value at a plurality of preset current feature points.
The q-axis self-saturation coefficient may include a q-axis self-saturation flux linkage, and as shown in fig. 13, the step S12 may specifically obtain the q-axis self-saturation flux linkage by:
step S124: the first q-axis flux linkage at each sampling point of the first q-axis current is obtained according to the first q-axis voltage and the corresponding first q-axis current of each period (which can be calculated in different manners according to different application occasions), and in order to ensure the accuracy of the calculation of the first q-axis flux linkage, the steps can comprise necessary filtering, direct current bias, zero drift processing and the like.
Specifically, if two periods of first q-axis voltages are injected into the stator winding of the synchronous motor to excite the q-axis saturation characteristic of the synchronous motor, the step may be to sample and obtain a first q-axis current of the stator winding during the period when the first q-axis voltages of the first periods are injected into the stator winding, and calculate a first q-axis flux linkage at each sampling point of the first q-axis current according to the first q-axis voltages of the periods and the corresponding first q-axis currents; when the first q-axis voltage of the second period is injected into the stator winding, sampling to obtain the first q-axis current of the stator winding in the period, and calculating the first q-axis flux linkage at each sampling point of the first q-axis current according to the first q-axis voltage of the period and the corresponding first q-axis current.
Step S125: the method comprises the steps of obtaining first q-axis flux linkage average values at a plurality of preset current characteristic points, wherein the first q-axis flux linkage average values are average values or weighted average values of first q-axis flux linkages obtained at the preset current characteristic points according to first q-axis voltages of at least two periods and corresponding first q-axis currents respectively.
In the step, at each preset current characteristic point, a first q-axis flux linkage of a first period and a first q-axis flux linkage of a second period are taken, and the values of the two points are averaged or weighted to form a first q-axis flux linkage average value at the preset current characteristic point. I.e. each preset current feature point corresponds to a first q-axis flux linkage mean value.
Step S126: the q-axis self-saturation flux linkage is obtained by piecewise interpolation fitting (e.g., least square method, etc.) to the first q-axis flux linkage mean at a plurality of preset current feature points.
In another embodiment of the present invention, the saturation model parameters may further include a d-axis flux linkage cross-coupling coefficient and a q-axis flux linkage cross-coupling coefficient, as shown in fig. 14, and the corresponding saturation model identification method further includes, in addition to the steps shown in fig. 1:
step S95: simultaneously injecting a second d-axis voltage and a second q-axis voltage into a stator winding of the synchronous motor to excite d-axis saturation characteristics and q-axis saturation characteristics of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor. The second d-axis voltage and the second q-axis voltage need to include a positive voltage and a negative voltage (in the same period), and the voltage amplitude is not specifically required, and only the current capable of exciting the saturation effect (i.e., the cross coupling characteristic of the d-axis and the q-axis) of the synchronous motor is needed.
Step S95: a second d-axis flux linkage at each sampling point of the second d-axis current and a second q-axis flux linkage at each sampling point of the second q-axis current are calculated from the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current. To ensure accuracy of flux linkage calculation, this step may include necessary filtering, dc biasing, zero drift processing, etc.
Step S96: the second d-axis flux linkage at the plurality of preset current feature points 65 is obtained, and the d-axis flux linkage cross-coupling coefficient (the d-axis flux linkage cross-coupling coefficient is a variable related to the d-axis current) is obtained through an identification fitting mode according to the difference value between the first d-axis flux linkage mean value and the second d-axis flux linkage at the plurality of preset feature points.
Step S97: a second q-axis flux linkage at a plurality of preset current feature points is obtained, and a q-axis flux linkage cross-coupling coefficient (the q-axis flux linkage cross-coupling coefficient is a variable related to q-axis current) is obtained by an identification fitting mode according to the difference value between the first q-axis flux linkage mean value and the second q-axis flux linkage at a plurality of feature points 85.
In addition, the saturation model identification method may further include a saturation model output step, so as to output the flux linkage obtained by the identification, parameters (d-axis inductance self-saturation coefficient, q-axis inductance self-saturation coefficient, d-axis flux linkage self-saturation coefficient, q-axis flux linkage self-saturation coefficient, d-axis inductance cross-coupling coefficient, q-axis inductance cross-coupling coefficient, d-axis flux linkage cross-coupling coefficient, q-axis flux linkage cross-coupling coefficient, and the like) in the inductance saturation model. Therefore, when the rear-stage module of the motor controller is applied, flux linkage and inductance corresponding to any d and q axis currents can be obtained through piecewise interpolation fitting operation.
As shown in fig. 15, the embodiment of the present invention further provides a saturation model identification system, which is used for obtaining a saturation model parameter of a synchronous motor, where the saturation model parameter includes a self-saturation coefficient. The saturated pattern recognition system of the present embodiment may be integrated into a motor controller driving a synchronous motor to operate, and include a first recognition unit 151 and a second recognition unit 152, and the first recognition unit 151 and the second recognition unit 152 may be formed of software on which the motor controller operates in combination.
The first identification unit 151 is configured to inject at least two periods of first d-axis voltages into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, sample at least two first d-axis currents respectively generated by excitation of the at least two periods of first d-axis voltages in the stator winding of the synchronous motor, and obtain a d-axis self-saturation coefficient of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents.
By injecting a first d-axis voltage into the stator winding of the synchronous motor, the first identification unit 151 generates a current in the synchronous motor winding sufficient to excite the saturation effect of the synchronous motor, that is, generates a direct-axis (d-axis) current (id) in a rotational coordinate system sufficient to enable the synchronous motor to be in nonlinear saturation. The first d-axis voltage needs to include a positive voltage and a negative voltage, and the voltage amplitude has no specific requirement, and only needs to be capable of exciting the current of the saturation effect of the synchronous motor. The first d-axis voltage used by the first identification unit 151 in calculating the d-axis self-saturation coefficient may directly employ the voltage injected into the stator winding. To make the calculation structure more accurate, the first d-axis voltage may also be obtained by sampling the stator winding voltage. In order to ensure accurate subsequent identification and calculation, the first d-axis voltage (when obtained by a sampling mode) and the first d-axis current data acquisition may include links such as data delay calibration, zero drift calibration, nonlinear compensation calibration of an inverter, and the like.
The second identification unit 152 is configured to inject at least two periods of first q-axis voltages into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, sample at least two first q-axis currents respectively generated by the excitation of the at least two periods of first q-axis voltages in the stator winding of the synchronous motor, and obtain q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents.
Similarly, the second identifying unit 152 generates a current in the windings of the synchronous motor sufficient to excite the saturation effect of the synchronous motor by injecting the first q-axis voltage into the stator windings of the synchronous motor, that is, generates a sufficiently large quadrature (q-axis) current (iq) in the quadrature (q-axis) in the rotating coordinate system to such an extent that the synchronous motor can be brought into nonlinear saturation. The first q-axis voltage needs to include a positive voltage and a negative voltage, and the voltage amplitude has no specific requirement, and only needs to be capable of exciting the current of the saturation effect of the synchronous motor. The first q-axis voltage used by the second identification unit 152 in calculating the q-axis self-saturation coefficient may directly employ the voltage injected into the stator winding. To make the calculation structure more accurate, the first q-axis voltage may also be obtained by sampling the stator winding voltage. In order to ensure accurate subsequent identification and calculation, the first q-axis voltage (when obtained by a sampling mode) and the first q-axis current data acquisition may include links such as data delay calibration, zero drift calibration, nonlinear compensation calibration of an inverter, and the like.
In another embodiment of the present invention, the self-saturation parameters include a d-axis self-saturation inductance and a q-axis self-saturation inductance, and accordingly, the first identification unit 151 includes a first inductance obtaining subunit, a first inductance average value obtaining subunit, and a first inductance interpolation fitting subunit. The first inductor acquisition subunit acquires first d-axis inductors at all sampling points of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period; the first inductance average value obtaining subunit is configured to obtain a first d-axis inductance average value at a plurality of preset current feature points, where the first d-axis inductance average value is an average value or a weighted average value of the first d-axis inductances obtained according to the first d-axis voltage of at least two periods and the corresponding first d-axis current respectively at the preset current feature points; the first inductance interpolation fitting subunit is used for obtaining d-axis self-saturation inductance through segment interpolation fitting on first d-axis inductance average values at a plurality of preset current characteristic points.
The second identifying unit 152 includes a second inductance obtaining subunit, a second inductance average obtaining subunit, and a second inductance interpolation fitting subunit. The second inductor acquisition subunit is used for acquiring first q-axis inductors at all sampling points of the first q-axis currents according to the first q-axis voltage and the corresponding first q-axis currents of each period; the second inductance average value obtaining subunit is used for obtaining first q-axis inductance average values at a plurality of preset current characteristic points, wherein the first q-axis inductance average values are average values or weighted average values of the first q-axis inductances obtained at the preset current characteristic points according to the first q-axis voltages of at least two periods and the corresponding first q-axis currents respectively; the second inductance interpolation fitting subunit is used for obtaining q-axis self-saturation inductance through segment interpolation fitting on the first q-axis inductance mean values at a plurality of preset current characteristic points.
In addition, the saturation model parameters include d-axis inductance cross-coupling coefficients and q-axis inductance cross-coupling coefficients, and accordingly, the saturation model identification system further includes a third identification unit. The third identification unit is used for simultaneously injecting a second d-axis voltage and a second q-axis voltage into the stator winding of the synchronous motor so as to excite the d-axis saturation characteristic and the q-axis saturation characteristic of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor; calculating a second d-axis inductance at each sampling point of the second d-axis current and a second q-axis inductance at each sampling point of the second q-axis current from the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current; acquiring second d-axis inductances at a plurality of preset current characteristic points, and acquiring d-axis inductance cross coupling coefficients in an identification fitting mode according to the difference value between the average value of the first d-axis inductances and the second d-axis inductances at the plurality of preset current characteristic points; and acquiring second q-axis inductances at a plurality of preset current characteristic points, and acquiring q-axis inductance cross coupling coefficients in an identification fitting mode according to the difference value between the average value of the first q-axis inductances and the second q-axis inductances at the plurality of preset current characteristic points.
In still another embodiment of the present invention, the self-saturation parameters include d-axis self-saturation flux and q-axis self-saturation flux, and accordingly, the first identification unit 151 may include a first flux linkage acquisition subunit, a first flux linkage mean value acquisition subunit, and a first flux linkage interpolation fitting subunit. The first flux linkage acquisition subunit is used for acquiring a first d-axis flux linkage at each sampling point of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period; the first flux linkage mean value obtaining subunit is used for obtaining first d-axis flux linkage mean values at a plurality of preset current characteristic points, wherein the first d-axis flux linkage mean values are average values or weighted average values of the first d-axis flux linkages obtained according to the first d-axis voltage of at least two periods and the corresponding first d-axis current at the preset current characteristic points respectively; the first flux linkage interpolation fitting subunit is used for obtaining the d-axis self-saturation flux linkage through piecewise interpolation fitting on the first d-axis flux linkage mean value at a plurality of preset current characteristic points.
Similarly, the second recognition unit 152 includes a second flux linkage acquisition subunit, a second flux linkage mean acquisition subunit, and a second flux linkage interpolation fit subunit. The second flux linkage acquisition subunit is used for acquiring a first q-axis flux linkage at each sampling point of the first q-axis current according to the first q-axis voltage and the corresponding first q-axis current of each period; the second flux linkage mean value obtaining subunit is used for obtaining first q-axis flux linkage mean values at a plurality of preset current characteristic points, wherein the first q-axis flux linkage mean values are average values or weighted average values of the first q-axis flux linkages obtained according to the first q-axis voltage of at least two periods and the corresponding first q-axis current at the preset current characteristic points respectively; the second flux linkage interpolation fitting subunit is used for obtaining the q-axis self-saturation flux linkage through piecewise interpolation fitting of the first q-axis flux linkage mean value at a plurality of preset current characteristic points.
In addition, the saturated model parameter includes a d-axis flux linkage cross-coupling coefficient and a q-axis flux linkage cross-coupling coefficient, and the saturated model identification system further includes a fourth identification unit. The fourth identification unit is used for simultaneously injecting a second d-axis voltage and a second q-axis voltage into the stator winding of the synchronous motor so as to excite the d-axis saturation characteristic and the q-axis saturation characteristic of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor; and calculating a second d-axis flux linkage at each sampling point of the second d-axis current and a second q-axis flux linkage at each sampling point of the second q-axis current based on the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current; acquiring second d-axis flux linkages at a plurality of preset current characteristic points, and acquiring d-axis flux linkage cross coupling coefficients in an identification fitting mode according to the difference value between the first d-axis flux linkage mean value and the second d-axis flux linkages at the plurality of preset current characteristic points; and acquiring second q-axis flux linkages at a plurality of preset current characteristic points, and acquiring q-axis flux linkage cross coupling coefficients in an identification fitting mode according to the difference value between the first q-axis flux linkage mean value and the second q-axis flux linkages at the plurality of characteristic points.
The saturated model identification system in this embodiment belongs to the same concept as the saturated model identification method in the corresponding embodiments in fig. 1-14, the specific implementation process is detailed in the corresponding method embodiment, and the technical features in the method embodiment are correspondingly applicable in the device embodiment, which is not repeated here.
The embodiment of the present invention further provides a saturated pattern-recognition device 16, where the device 16 may be a motor controller for driving a synchronous motor to operate, as shown in fig. 15, the saturated pattern-recognition device 16 includes a memory 161 and a processor 162, the memory 161 stores a computer program executable by the processor 162, and the processor 162 implements the steps of the saturated pattern-recognition method as described above when executing the computer program.
The saturated model identification device 16 in this embodiment belongs to the same concept as the saturated model identification method in the corresponding embodiments of fig. 1-14, the specific implementation process is detailed in the corresponding method embodiment, and the technical features in the method embodiment are all applicable in this device embodiment, and are not repeated here
The embodiment of the invention also provides a computer readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the saturated model identification method are realized. The computer readable storage medium in this embodiment belongs to the same concept as the saturation model identification method in the corresponding embodiments of fig. 1 to 14, and the specific implementation process is detailed in the corresponding method embodiment, and the technical features in the method embodiment are correspondingly applicable in the present device embodiment, which is not repeated herein.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional units and modules according to needs. The functional units and modules in the embodiment may be integrated in one processor, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed saturation model identification method, system and apparatus may be implemented in other manners. For example, the saturated model identification system embodiments described above are merely illustrative.
In addition, each functional unit in the embodiments of the present application may be integrated in one processor, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each method embodiment described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or interface switching device, recording medium, USB flash disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), electrical carrier wave signals, telecommunications signals, and software distribution media, among others, capable of carrying the computer program code. It should be noted that the computer readable medium may include content that is subject to appropriate increases and decreases as required by jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is not included as electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims (10)

1. A saturation model identification method for acquiring saturation model parameters of a synchronous motor, the saturation model parameters including self-saturation coefficients, the method comprising:
injecting at least two periodic first d-axis voltages into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first d-axis currents respectively generated by excitation of the at least two periodic first d-axis voltages in the stator winding of the synchronous motor, and acquiring d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents, wherein the first d-axis voltages comprise positive voltage and negative voltage, and the magnitudes of the first d-axis voltages are enough to excite currents of a synchronous motor saturation effect;
Injecting at least two periodic first q-axis voltages into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first q-axis currents respectively generated by the excitation of the at least two periodic first q-axis voltages in the stator winding of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents, wherein the first q-axis voltages comprise positive voltage and negative voltage, and the amplitude of the first q-axis voltages is enough to excite currents of a synchronous motor saturation effect.
2. The saturation model identification method according to claim 1, wherein the d-axis self-saturation coefficient includes a d-axis self-saturation inductance, the q-axis self-saturation coefficient includes a q-axis self-saturation inductance, the obtaining the d-axis self-saturation coefficient of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents includes:
acquiring a first d-axis inductance at each sampling point of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period;
acquiring a first d-axis inductance average value at a plurality of preset current characteristic points, wherein the first d-axis inductance average value is an average value or a weighted average value of first d-axis inductances acquired at the preset current characteristic points according to at least two periods of first d-axis voltage and corresponding first d-axis currents, and the plurality of preset current characteristic points correspond to different current values respectively;
Obtaining d-axis self-saturation inductance by carrying out piecewise interpolation fitting on the first d-axis inductance average value at a plurality of preset current characteristic points;
the obtaining q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents includes:
acquiring first q-axis inductances at all sampling points of the first q-axis current according to the first q-axis voltage and the corresponding first q-axis current of each period;
acquiring first q-axis inductance average values at a plurality of preset current characteristic points, wherein the first q-axis inductance average values are average values or weighted average values of first q-axis inductances acquired at the preset current characteristic points according to first q-axis voltages of at least two periods and corresponding first q-axis currents respectively;
and obtaining the q-axis self-saturation inductance by carrying out piecewise interpolation fitting on the first q-axis inductance average value at a plurality of preset current characteristic points.
3. The saturation model identification method of claim 2, wherein the saturation model parameters include inductance cross-coupling coefficients, the method comprising:
simultaneously injecting a second d-axis voltage and a second q-axis voltage into a stator winding of the synchronous motor to excite d-axis saturation characteristics and q-axis saturation characteristics of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor;
Calculating a second d-axis inductance at each sampling point of the second d-axis current and a second q-axis inductance at each sampling point of the second q-axis current from the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current;
acquiring a d-axis inductance cross coupling coefficient in an identification fitting mode according to the difference value between the first d-axis inductance mean value and the second d-axis inductance at the plurality of preset current characteristic points;
and obtaining the q-axis inductance cross coupling coefficient by an identification fitting mode according to the difference value between the first q-axis inductance mean value and the second q-axis inductance at the plurality of preset current characteristic points.
4. A saturation model identification method according to any one of claims 1-3, wherein the d-axis self-saturation coefficient comprises a d-axis self-saturation flux linkage, the q-axis self-saturation coefficient comprises a q-axis self-saturation flux linkage, the obtaining the d-axis self-saturation coefficient of the synchronous motor from the at least two first d-axis voltages and the at least two first d-axis currents comprises:
acquiring a first d-axis flux linkage at each sampling point of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period;
Acquiring a first d-axis flux linkage mean value at a plurality of preset current characteristic points, wherein the first d-axis flux linkage mean value is an average value or a weighted average value of a first d-axis flux linkage acquired according to a first d-axis voltage of at least two periods and corresponding first d-axis current at the preset current characteristic points, and the plurality of preset current characteristic points correspond to different current values respectively;
obtaining a d-axis self-saturation flux linkage by carrying out piecewise interpolation fitting on a first d-axis flux linkage mean value at a plurality of preset current characteristic points;
the obtaining q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents includes:
acquiring a first q-axis flux linkage at each sampling point of the first q-axis current according to the first q-axis voltage and the corresponding first q-axis current of each period;
acquiring first q-axis flux linkage average values at a plurality of preset current characteristic points, wherein the first q-axis flux linkage average values are average values or weighted average values of the first q-axis flux linkages acquired at the preset current characteristic points according to first q-axis voltages of at least two periods and corresponding first q-axis currents respectively;
And obtaining the q-axis self-saturation flux linkage by carrying out piecewise interpolation fitting on the first q-axis flux linkage mean value at a plurality of preset current characteristic points.
5. The saturation model identification method of claim 4, wherein the saturation model parameters include flux linkage cross-coupling coefficients, the method comprising:
simultaneously injecting a second d-axis voltage and a second q-axis voltage into a stator winding of the synchronous motor to excite d-axis saturation characteristics and q-axis saturation characteristics of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor;
calculating a second d-axis flux linkage at each sampling point of the second d-axis current and a second q-axis flux linkage at each sampling point of the second q-axis current from the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current;
acquiring a d-axis flux linkage cross coupling coefficient in an identification fitting mode according to the difference value between the first d-axis flux linkage mean value and the second d-axis flux linkage at the plurality of preset current characteristic points;
and obtaining the q-axis flux linkage cross coupling coefficient by an identification fitting mode according to the difference value between the first q-axis flux linkage mean value and the second q-axis flux linkage at the plurality of preset current characteristic points.
6. A saturated model identification system for obtaining saturated model parameters of a synchronous motor, the saturated model parameters comprising self-saturation coefficients, characterized in that the system comprises a first identification unit and a second identification unit, wherein:
the first identification unit is configured to inject at least two periods of first d-axis voltages into a stator winding of the synchronous motor to excite d-axis saturation characteristics of the synchronous motor, sample at least two first d-axis currents respectively generated by excitation of the at least two periods of first d-axis voltages in the stator winding of the synchronous motor, and obtain d-axis self-saturation coefficients of the synchronous motor according to the at least two first d-axis voltages and the at least two first d-axis currents, where the first d-axis voltages include positive voltages and negative voltages, and the magnitudes of the first d-axis voltages are sufficient to excite currents of a synchronous motor saturation effect;
the second identification unit is used for injecting first q-axis voltages of at least two periods into a stator winding of the synchronous motor to excite q-axis saturation characteristics of the synchronous motor, simultaneously sampling at least two first q-axis currents respectively generated by the excitation of the first q-axis voltages of the at least two periods in the stator winding of the synchronous motor, and acquiring q-axis self-saturation coefficients of the synchronous motor according to the at least two first q-axis voltages and the at least two first q-axis currents, wherein the first q-axis voltages comprise positive voltage and negative voltage, and the amplitude of the first q-axis voltages is enough to excite currents of a synchronous motor saturation effect.
7. The saturation model identification system of claim 6, wherein the saturation model parameters include d-axis self-saturation inductance, q-axis self-saturation inductance, d-axis inductance cross-coupling coefficient, and q-axis inductance cross-coupling coefficient;
the first identification unit comprises a first inductance acquisition subunit, a first inductance average value acquisition subunit and a first inductance interpolation fitting subunit, and the second identification unit comprises a second inductance acquisition subunit, a second inductance average value acquisition subunit and a second inductance interpolation fitting subunit;
the first inductor acquisition subunit is used for acquiring first d-axis inductors at all sampling points of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period;
the first inductance average value obtaining subunit is configured to obtain a first d-axis inductance average value at a plurality of preset current feature points, where the first d-axis inductance average value is an average value or a weighted average value of first d-axis inductances obtained according to a first d-axis voltage of at least two periods and a corresponding first d-axis current at the preset current feature points, and the plurality of preset current feature points correspond to different current values respectively;
The first inductance interpolation fitting subunit is used for obtaining d-axis self-saturation inductance by carrying out piecewise interpolation fitting on first d-axis inductance average values at a plurality of preset current characteristic points;
the second inductor acquisition subunit is used for acquiring first q-axis inductors at all sampling points of the first q-axis current according to the first q-axis voltage and the corresponding first q-axis current of each period;
the second inductance average value obtaining subunit is configured to obtain first q-axis inductance average values at a plurality of preset current feature points, where the first q-axis inductance average values are average values or weighted average values of first q-axis inductances obtained at the preset current feature points according to first q-axis voltages of at least two periods and corresponding first q-axis currents, respectively;
the second inductance interpolation fitting subunit is used for obtaining q-axis self-saturation inductance by carrying out piecewise interpolation fitting on the first q-axis inductance average values at a plurality of preset current characteristic points;
the saturation model identification system further comprises a third identification unit:
the third identification unit is used for simultaneously injecting a second d-axis voltage and a second q-axis voltage into the stator winding of the synchronous motor to excite the d-axis saturation characteristic and the q-axis saturation characteristic of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor; calculating a second d-axis inductance at each sampling point of the second d-axis current and a second q-axis inductance at each sampling point of the second q-axis current from the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current; acquiring a d-axis inductance cross coupling coefficient in an identification fitting mode according to the difference value between the first d-axis inductance mean value and the second d-axis inductance at the plurality of preset current characteristic points; and obtaining the q-axis inductance cross coupling coefficient by an identification fitting mode according to the difference value between the first q-axis inductance mean value and the second q-axis inductance at the preset current characteristic points.
8. The saturation model identification system of claim 6 or 7, wherein the saturation model parameters include d-axis self-saturation flux linkage, q-axis self-saturation flux linkage, d-axis flux linkage cross-coupling coefficient, and q-axis flux linkage cross-coupling coefficient;
the first identification unit comprises a first flux linkage acquisition subunit, a first flux linkage mean value acquisition subunit and a first flux linkage interpolation fitting subunit, and the second identification unit comprises a second flux linkage acquisition subunit, a second flux linkage mean value acquisition subunit and a second flux linkage interpolation fitting subunit;
the first flux linkage acquisition subunit is used for acquiring a first d-axis flux linkage at each sampling point of the first d-axis current according to the first d-axis voltage and the corresponding first d-axis current of each period;
the first flux linkage mean value obtaining subunit is configured to obtain first d-axis flux linkage mean values at a plurality of preset current feature points, where the first d-axis flux linkage mean values are average values or weighted average values of first d-axis flux linkages obtained at the preset current feature points according to first d-axis voltages of at least two periods and corresponding first d-axis currents, respectively;
the first flux linkage interpolation fitting subunit is used for obtaining a d-axis self-saturation flux linkage by carrying out piecewise interpolation fitting on a first d-axis flux linkage mean value at a plurality of preset current characteristic points;
The second flux linkage acquisition subunit is used for acquiring a first q-axis flux linkage at each sampling point of the first q-axis current according to the first q-axis voltage and the corresponding first q-axis current of each period;
the second flux linkage mean value obtaining subunit is configured to obtain first q-axis flux linkage mean values at a plurality of preset current feature points, where the first q-axis flux linkage mean values are average values or weighted average values of first q-axis flux linkages obtained at the preset current feature points according to first q-axis voltages of at least two periods and corresponding first q-axis currents, respectively;
the second flux linkage interpolation fitting subunit is used for obtaining a q-axis self-saturation flux linkage by carrying out piecewise interpolation fitting on first q-axis flux linkage mean values at a plurality of preset current characteristic points;
the saturated model identification system further comprises a fourth identification unit:
the fourth identification unit is used for simultaneously injecting a second d-axis voltage and a second q-axis voltage into the stator winding of the synchronous motor to excite the d-axis saturation characteristic and the q-axis saturation characteristic of the synchronous motor, and simultaneously sampling a second d-axis current and a second q-axis current of the stator winding of the synchronous motor; and calculating a second d-axis flux linkage at each sampling point of the second d-axis current and a second q-axis flux linkage at each sampling point of the second q-axis current based on the second d-axis voltage, the second d-axis current, the second q-axis voltage, and the second q-axis current; acquiring a d-axis flux linkage cross coupling coefficient in an identification fitting mode according to the difference value between the first d-axis flux linkage mean value and the second d-axis flux linkage at the plurality of preset current characteristic points; and acquiring the q-axis flux linkage cross coupling coefficient by an identification fitting mode according to the difference value between the first q-axis flux linkage mean value and the second q-axis flux linkage at the plurality of preset current characteristic points.
9. A saturated model identification device, characterized in that it comprises a memory and a processor, said memory having stored therein a computer program executable on said processor, said processor implementing the steps of the saturated model identification method according to any one of claims 1 to 5 when said computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the saturation model identification method according to any one of claims 1 to 5.
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