Motor parameter identification method, motor parameter analysis method, vehicle and storage medium

Abstract

The application discloses a motor parameter identification method, a motor parameter analysis method, a vehicle and a storage medium, relates to the technical field of electronics, and aims to improve the efficiency of motor parameter identification. The method comprises the following steps: constructing an observation matrix based on motor output signals in a preset time period; the observation matrix is used to reflect the relationship between the motor output signals and the motor state; and the motor parameters are identified based on the observation matrix.

Description

Technical Field

[0001] This application relates to the field of electronic technology, and in particular to a method for identifying motor parameters, a method for analyzing motor parameters, a vehicle, and a storage medium. Background Technology

[0002] Motor parameter identification plays a crucial role in optimizing motor performance. Accurate motor parameters help optimize motor control strategies, enabling the motor to better adapt to changes in environment or operating conditions, thereby improving motor performance.

[0003] Existing motor parameter identification technologies mainly fall into two categories: offline identification and online identification. Offline identification yields high accuracy but struggles to reflect the dynamic changes in motor parameters under actual operating conditions. Therefore, online identification methods are generally used when real-time optimization of motor control strategies is required. However, existing online identification algorithms are complex and have long response times, impacting the efficiency of motor parameter identification. Summary of the Invention

[0004] The purpose of this application is to provide a method for identifying motor parameters, a method for analyzing motor parameters, a vehicle, and a storage medium, with the aim of improving the efficiency of motor parameter identification.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] In a first aspect, this application provides a method for identifying motor parameters, applied to a motor control device. The method includes: constructing an observation matrix based on the motor output signal within a preset time period; the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state; and identifying motor parameters based on the observation matrix.

[0007] The motor parameter identification method provided in this application can construct an observation matrix reflecting the relationship between the motor output signal and the motor state, and can perform motor parameter identification based on the observation matrix. By constructing the observation matrix, the motor output signal is converted into a form suitable for linear regression analysis, reducing the algorithm complexity in the motor parameter identification process, thereby reducing the response delay of motor parameter identification and improving the efficiency of motor parameter identification.

[0008] One possible implementation is that the observation matrix includes at least one of the following: a first observation matrix, which reflects the relationship between the motor output signal and the motor state in the direct axis direction; and a second observation matrix, which reflects the relationship between the motor output signal and the motor state in the quadrature axis direction.

[0009] Another possible implementation involves a first observation matrix comprising a first output matrix and a first state matrix; the motor output signals comprising direct-axis current, quadrature-axis current, direct-axis voltage, and motor speed; constructing the observation matrix based on the motor output signals within a preset time period, including: determining the first output matrix based on the direct-axis current and a first modulation parameter; the first modulation parameter being determined based on the identification time and a first integration interval; the first integration interval being determined based on the preset time period; and determining the first state matrix based on the direct-axis current, quadrature-axis current, direct-axis voltage, motor speed, and the first modulation parameter.

[0010] Another possible implementation is that the elements in the first output matrix are determined based on the integration result of the first integral object within the first integration interval; wherein the first integral object is the product of the direct-axis current and the first derivative; the first derivative is the derivative of the first modulation parameter with respect to the time variable.

[0011] Another possible implementation is that the first state matrix includes a first element, a second element, and a third element; the first element is determined based on the integration result of a second integral object within a first integration interval; wherein the second integral object is the product of the direct-axis current and the first modulation parameter; the second element is determined based on the integration result of a third integral object within a first integration interval; wherein the third integral object is the product of the quadrature-axis current, the motor speed, and the first modulation parameter; the third element is determined based on the integration result of a fourth integral object within a first integration interval; wherein the fourth integral object is the product of the direct-axis voltage and the first modulation parameter.

[0012] Another possible implementation involves a second observation matrix comprising a second output matrix and a second state matrix; the motor output signals include: direct-axis current, quadrature-axis current, quadrature-axis voltage, and motor speed; constructing the observation matrix based on the output signals includes: determining the second output matrix based on the quadrature-axis current and the second modulation parameter; determining the second modulation parameter based on the identification time and the second integration interval; determining the second integration interval based on a preset time period; and determining the second state matrix based on the direct-axis current, quadrature-axis current, quadrature-axis voltage, motor speed, and the second modulation parameter.

[0013] Another possible implementation is that the elements in the second output matrix are determined based on the integration result of the fifth integral object within the second integration interval; wherein the fifth integral object is the product of the cross-axis current and the second derivative; the second derivative is the derivative of the second modulation parameter with respect to the time variable.

[0014] Another possible implementation involves a second state matrix comprising a fourth, fifth, sixth, and seventh element. The fourth element is determined based on the integration result of the sixth integral object within the second integration interval; wherein the sixth integral object is the product of the direct-axis current, motor speed, and the second modulation parameter. The fifth element is determined based on the integration result of the seventh integral object within the second integration interval; wherein the seventh integral object is the product of the quadrature-axis current and the second modulation parameter. The sixth element is determined based on the integration result of the eighth integral object within the second integration interval; wherein the eighth integral object is the product of the quadrature-axis voltage and the second modulation parameter. The seventh element is determined based on the integration result of the ninth integral object within the second integration interval; wherein the ninth integral object is the product of the motor speed and the second modulation parameter.

[0015] Another possible implementation involves identifying motor parameters based on an observation matrix, including: determining a parameter matrix based on a first observation matrix and / or a second observation matrix, the parameter matrix including at least one parameter vector used to determine predicted values ​​of motor parameters; and determining motor parameters based on at least one parameter vector in the parameter matrix.

[0016] Another possible implementation involves determining the parameter matrix based on the first observation matrix and / or the second observation matrix, including: determining the parameter matrix using the least squares method based on the first observation matrix and / or the second observation matrix.

[0017] Another possible implementation is that the parameter matrix includes at least one of the following: a first parameter matrix, which is obtained by solving a first parameter estimation equation based on a first observation matrix; and a second parameter matrix, which is obtained by solving a second parameter estimation equation based on a second observation matrix.

[0018] Another possible implementation is that the motor parameters include at least one of the following: a first motor parameter, which is determined based on at least one parameter vector in a first parameter matrix; and a second motor parameter, which is determined based on at least one parameter vector in a second parameter matrix.

[0019] Another possible implementation is that the first motor parameters include at least one of the following: a first direct-axis inductance parameter, a first quadrature-axis inductance parameter, and a first resistance parameter; and / or, the second motor parameters include at least one of the following: a second direct-axis inductance parameter, a second quadrature-axis inductance parameter, a second resistance parameter, and a flux linkage parameter.

[0020] Another possible implementation is that the motor parameters are determined based on the first motor parameters, the weights corresponding to the first motor parameters, the second motor parameters, and the weights corresponding to the second motor parameters.

[0021] Another possible implementation is that, in the case where the motor output signal includes direct-axis current and quadrature-axis current, the direct-axis current and the quadrature-axis current are obtained based on the motor's three-phase current through Clarke transformation and Park transformation.

[0022] Another possible implementation, before constructing the observation matrix based on the motor output signal within a preset time period, further includes: in response to a received vehicle control command, acquiring the motor output signal within the preset time period.

[0023] Another possible implementation method, based on the observation matrix, after identifying the motor parameters, further includes: sending the motor parameters to the vehicle controller, so that the vehicle controller can send the motor parameters to the cloud platform when it determines that preset conditions are met; wherein, the cloud platform is used to perform parameter analysis of the motor based on the motor parameters.

[0024] Another possible implementation method includes at least one of the following preset conditions: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0025] Another possible implementation method includes: receiving a control adjustment command; the control adjustment command is issued by the cloud platform when it determines that the motor parameters are inconsistent with the nominal parameters; and adjusting the motor control parameters in response to the control adjustment command.

[0026] Secondly, this application provides a motor parameter analysis method for a vehicle controller, comprising: receiving motor parameters sent by a motor control device; the motor parameters are obtained by identifying motor parameters based on an observation matrix; the observation matrix is ​​constructed based on the motor output signal within a preset time period, and the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state; and, when a preset condition is met, sending the motor parameters to a cloud platform so that the cloud platform can perform motor parameter analysis based on the motor parameters.

[0027] The motor parameter analysis method provided in this application can send motor parameters to the cloud platform when it is determined that the motor is in an abnormal working state, so that the cloud platform can respond in a timely manner to motor faults caused by changes in motor parameters, thereby enhancing the reliability and safety of the motor.

[0028] One possible implementation method includes at least one of the following preset conditions: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0029] Thirdly, this application provides a motor parameter analysis method for a cloud platform, comprising: receiving motor parameters sent by a vehicle controller; the motor parameters are obtained by identifying motor parameters based on an observation matrix; the observation matrix is ​​constructed based on the motor output signal within a preset time period, and the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state; and performing motor parameter analysis based on the motor parameters.

[0030] The motor parameter analysis method provided in this application can obtain motor parameters sent by the vehicle controller and perform motor parameter analysis based on the motor parameters. This not only improves the accuracy and efficiency of motor parameter analysis, but also enhances the reliability and safety of the motor.

[0031] One possible implementation involves analyzing the motor parameters based on the motor parameters, including: sending a control adjustment command to the motor when it is determined that the motor parameters are inconsistent with the nominal parameters; the control adjustment command is used to instruct the motor to adjust the motor's control parameters.

[0032] Fourthly, this application provides a motor control device for performing the method described in the first method above.

[0033] Fifthly, this application provides a vehicle controller for performing the second method described above.

[0034] Sixthly, this application provides a cloud platform for performing the method described in the third method above.

[0035] In a seventh aspect, this application provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; and when the processor is configured to execute the instructions, causing the electronic device to implement the methods of the first, second, or third aspects described above.

[0036] Eighthly, this application provides an in-vehicle system, which includes a motor control device as described in the fourth aspect above, a vehicle controller as described in the fifth aspect above, and a communication device; the communication device is used to send the motor parameters output by the vehicle controller as described in the fifth aspect to the cloud platform as described in the sixth aspect above, so that the cloud platform as described in the sixth aspect can execute the motor parameter analysis method as described in the third aspect above.

[0037] Ninthly, this application provides a vehicle that includes a motor control device as described in the fourth aspect above, or a vehicle controller as described in the fifth aspect above, or an electronic device as described in the seventh aspect above, or an in-vehicle system as described in the eighth aspect above.

[0038] In a tenth aspect, this application provides a computer-readable storage medium comprising: computer software instructions; which, when executed in an electronic device, cause the electronic device to implement the methods of the first, second, or third aspects described above.

[0039] In one aspect, this application provides a computer program product comprising a computer program; when the computer program is run in an electronic device, it causes the electronic device to implement the methods of the first, second, or third aspects described above.

[0040] The beneficial effects of aspects four through eleven above are described in the corresponding descriptions of aspects one, two, or three, and will not be repeated here. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A schematic diagram illustrating the application environment of the motor parameter identification method provided in this application;

[0043] Figure 2 A flowchart illustrating a motor parameter identification method provided in an embodiment of this application;

[0044] Figure 3 A flowchart illustrating another motor parameter identification method provided in this application embodiment;

[0045] Figure 4 A flowchart illustrating a motor parameter analysis method provided in this application embodiment;

[0046] Figure 5 A flowchart illustrating another motor parameter analysis method provided in this application embodiment;

[0047] Figure 6 A flowchart illustrating another motor parameter identification method provided in this application embodiment;

[0048] Figure 7 A schematic diagram of a motor control system provided in an embodiment of this application;

[0049] Figure 8 This is a schematic diagram of the composition of a motor parameter identification device provided in an embodiment of this application;

[0050] Figure 9This is a schematic diagram of the composition of a motor parameter analysis device provided in an embodiment of this application;

[0051] Figure 10 This is a schematic diagram of another motor parameter analysis device provided in an embodiment of this application;

[0052] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0053] Reference numerals: motor (101), sensing device (102), motor control device (103), vehicle controller (104), cloud platform (105), motor parameter identification device (600), identification module (601), communication module (602), motor parameter analysis device (700), communication module (701), motor parameter analysis device (800), communication module (801), analysis module (802), electronic device (900), memory (901), processor (902), communication interface (903), bus (904). Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and for simplification, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0056] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0057] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0058] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0059] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0060] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0061] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0062] Motor parameter identification plays a crucial role in optimizing motor performance. Accurate motor parameters help optimize motor control strategies, enabling the motor to better adapt to changes in environment or operating conditions, thereby improving motor performance. Especially in new energy vehicles, motor parameter identification not only optimizes motor control strategies, allowing the electric drive system of electric vehicles to better match the needs of the vehicle, but also helps the vehicle's inverter implement safety measures such as overload protection and overheat protection to prevent accidental motor damage.

[0063] Existing motor parameter identification technologies mainly fall into two categories: offline identification and online identification. Offline identification yields high accuracy but struggles to reflect the dynamic changes in motor parameters under actual operating conditions. Therefore, online identification methods are generally used when real-time optimization of motor control strategies is required. However, existing online identification algorithms are complex and have long response times, impacting the efficiency of motor parameter identification.

[0064] To address the aforementioned technical problems, this application provides a motor parameter identification method. This method constructs an observation matrix reflecting the relationship between the motor output signal and the motor state, and identifies motor parameters based on this observation matrix. The motor parameter identification method provided in this application, by constructing the observation matrix, transforms the motor output signal into a form suitable for linear regression analysis, reducing the algorithm complexity during motor parameter identification, thereby reducing the response delay and improving the efficiency of motor parameter identification.

[0065] The embodiments provided in this application will now be described in detail with reference to the accompanying drawings.

[0066] The motor parameter identification method provided in this application can be applied to, for example... Figure 1 The application environment shown. For example... Figure 1 As shown, the application environment includes: motor 101, sensing device 102, motor control device 103, vehicle controller 104, and cloud platform 105.

[0067] In some embodiments, when the motor 101 is located inside the vehicle, the motor 101 is used to provide the driving force required for the vehicle to move. Exemplarily, the motor 101 may be a permanent magnet synchronous motor (PMSM), a DC motor, an AC induction motor (IM), or a switched reluctance motor (SRM), etc.

[0068] In some embodiments, the sensing device 102 is used to detect dynamic operating parameters generated by the motor 101 during operation. The dynamic operating parameters of the motor 101 include at least one of three-phase voltage, three-phase current and motor speed.

[0069] For example, the sensing device 102 may include at least one of a current sensor, a voltage sensor, and a speed and position sensor.

[0070] In some embodiments, the motor control device 103 is used to control the operation of the motor 101. For example, the motor control device 103 may be a motor control unit (MCU).

[0071] In some embodiments, the motor control device 103 is further configured to perform motor parameter identification. For example, the motor control device 103 can acquire the motor output signal within a preset time period; construct an observation matrix based on the output signal and modulation parameters; and perform motor parameter identification based on the observation matrix.

[0072] Therefore, the motor control device 103 can integrate a processor or processing unit with computing capabilities, such as a microcontroller unit (MCU), system on chip (SoC), digital signal processor (DSP), field-programmable gate array (FPGA), etc.

[0073] As one possible implementation, the motor output signal includes at least one of direct-axis current, quadrature-axis current, direct-axis voltage, quadrature-axis voltage, and motor speed.

[0074] The motor speed can be sent from the sensor 102 to the motor control device 103. The acquisition of the direct-axis current and quadrature-axis current requires the sensor 102 to send the three-phase current and three-phase voltage to the motor control device 103, and the motor control device 103 to perform Clarke transformation and Park transformation on the three-phase current to obtain the direct-axis current and quadrature-axis current.

[0075] In some embodiments, the motor control device 103 can also send motor parameters to the vehicle controller 104, so that the vehicle controller 104 can send motor parameters to the cloud platform 105 when it determines that preset conditions are met; wherein, the cloud platform 105 is used to perform parameter analysis of the motor based on the motor parameters.

[0076] In some embodiments, the vehicle controller 104 is used to coordinate and manage the operation of various subsystems in the vehicle. For example, the vehicle controller 104 can send vehicle control commands to the motor control device 103, so that the motor control device 103 can identify motor parameters and / or adjust the output power and speed of the motor.

[0077] In some embodiments, the vehicle controller 104 can acquire motor parameters sent by the motor control device 103; the vehicle controller 104 can also send motor parameters to the cloud platform 105 when it is determined that preset conditions are met, so that the cloud platform 105 can perform parameter analysis of the motor based on the motor parameters.

[0078] In some embodiments, the cloud platform 105 is used to provide remote monitoring and management services for vehicles, and can communicate with vehicles via vehicle-to-cloud communication. For example, the cloud platform 105 may be a server cluster consisting of multiple servers, a single server, a computer, or a processor or processing chip within a server or computer, etc. This application embodiment does not limit the specific device form of the cloud platform 105. Figure 1 The example shown is a single server on the China-Israel cloud platform 105.

[0079] In some embodiments, the cloud platform 105 can receive motor parameters sent by the vehicle controller 104; it can also perform parameter analysis of the motor based on the motor parameters.

[0080] It should be noted that the system architecture described in the embodiments of this application is for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and does not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of system architecture, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0081] See Figure 2 This is a flowchart illustrating a motor parameter identification method provided in an embodiment of this application. Figure 2 As shown, this embodiment takes a permanent magnet synchronous motor as an example to illustrate the motor parameter identification method provided in this application. The motor parameter identification method provided in this application can be implemented by the above-mentioned motor control device, specifically including the following steps S201 to S202.

[0082] S201. Construct an observation matrix based on the motor output signal within a preset time period.

[0083] The observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state.

[0084] In some embodiments, the motor output signal includes the motor speed and at least one of the following in the synchronous rotating (d-quadrature, DQ) coordinate system: direct-axis (d-axis) current, quadrature-axis (q-axis) current, direct-axis voltage, and quadrature-axis voltage.

[0085] It should be noted that the motor's state can be determined by observing the motor's output signal.

[0086] Taking a permanent magnet synchronous motor as an example, in a synchronous rotating coordinate system, the direct-axis voltage of a permanent magnet synchronous motor can reflect the resistance voltage drop, inductance voltage drop, and mutual inductance voltage drop on the direct axis and the quadrature-axis voltage drop.

[0087] Among them, the resistance voltage drop represents the voltage change caused by the stator resistance of the motor, which is related to the motor's resistance parameters and direct-axis current; the inductance voltage drop represents the voltage change caused by the rate of change of the direct-axis current, reflecting the change in the energy stored in the direct-axis inductance of the motor, which is related to the direct-axis inductance parameters and the rate of change of the direct-axis current; the mutual inductance voltage drop represents the change in direct-axis voltage caused by the change in the magnetic field generated by the quadrature-axis current, which is related to the motor speed, quadrature-axis inductance parameters, and quadrature-axis current.

[0088] The quadrature-axis voltage of a permanent magnet synchronous motor can reflect the resistance voltage drop, inductance voltage drop, mutual inductance voltage drop, and back electromotive force on the quadrature axis.

[0089] Among them, the resistance voltage drop represents the voltage change caused by the stator resistance of the motor, which is related to the motor's resistance parameters and quadrature-axis current; the inductance voltage drop represents the voltage change caused by the rate of change of the quadrature-axis current, reflecting the change in the energy stored in the quadrature-axis inductance of the motor, which is related to the motor's quadrature-axis inductance parameters and the rate of change of the quadrature-axis current; the mutual inductance voltage drop represents the quadrature-axis voltage change caused by the change in the magnetic field generated by the direct-axis current, which is related to the motor speed, direct-axis inductance parameters, and direct-axis current; and the back electromotive force represents the induced voltage generated by the combined action of the permanent magnet flux linkage and the rotor rotation, which is related to the motor speed and the permanent magnet flux linkage parameters.

[0090] Therefore, an observation matrix can be constructed based on the relationship between the motor output signal and the motor parameters reflecting the motor state. For example, observation matrices can be constructed based on the relationship between the output signal reflected by the direct-axis voltage and the motor state, and the relationship between the output signal reflected by the quadrature-axis voltage and the motor state, respectively.

[0091] Based on this, the observation matrix may include at least one of a first observation matrix and a second observation matrix. The first observation matrix reflects the relationship between the motor output signal and the motor state in the direct axis direction; the second observation matrix reflects the relationship between the motor output signal and the motor state in the quadrature axis direction.

[0092] It is understandable that constructing the first and second observation matrices can comprehensively reflect the relationship between the motor output signal and the motor state in the synchronous rotating coordinate system. This relationship can be transformed into a form suitable for linear regression analysis, which helps improve the efficiency of motor parameter identification.

[0093] In some embodiments, a first observation matrix can be constructed based on the relationship between the motor output signal and the motor state in the direct axis direction of the synchronous rotating coordinate system.

[0094] Taking a permanent magnet synchronous motor as an example, the direct-axis voltage equation of a permanent magnet synchronous motor in a synchronous rotating coordinate system can reflect the relationship between the motor output signal and the motor state in the direct-axis direction.

[0095] Therefore, the elements for constructing the first observation matrix can be determined based on the analysis of the direct-axis voltage equation and the first modulation parameters of the permanent magnet synchronous motor in the synchronous rotating coordinate system. The first modulation parameters are determined based on the identification time and the first integration interval; the first integration interval is determined based on a preset time period.

[0096] The direct-axis voltage equation of the permanent magnet synchronous motor in the synchronous rotating coordinate system is as follows (1).

[0097]

[0098] Among them, u d Represents the direct-axis voltage, R s Indicates the resistance parameter, i d Represents the direct-axis current, ω e L represents the motor speed. q Indicates the quadrature axis inductance parameter, i q This represents the quadrature-axis current.

[0099] It should be noted that since formula (1) includes the rate of change of the direct-axis current, i.e., the derivative of the direct-axis current, the process of obtaining the derivative of the direct-axis current by analyzing the motor output signal may generate noise. In order to reduce the influence of noise that may be generated during signal analysis, an integral analysis method can be used to calculate the integral of the motor output signal within a preset time period. Furthermore, by introducing the first modulation parameter and multiplying it with the motor output signal, the derivative analysis of the unknown signal to be detected, the direct-axis current, can be transformed into a derivative analysis of the known first modulation parameter based on the integration by parts method.

[0100] As one possible implementation, based on the analysis of the direct-axis voltage equation and the first modulation parameter of the permanent magnet synchronous motor in the synchronous rotating coordinate system, the specific process of determining the elements of the first observation matrix includes the following steps A1-A4.

[0101] A1. Introduce the first modulation parameter g into formula (1). m (t), multiply both sides of formula (1) by the first modulation parameter to obtain the following formula (2):

[0102]

[0103] Among them, g m (t) represents the first modulation parameter, u d (t) represents the direct-axis voltage, R s Indicates the resistance parameter, i d(t) represents the direct-axis current, L d L represents the direct-axis inductance parameter. q ω represents the quadrature axis inductance parameter. e (t) represents the motor speed, i q (t) represents the quadrature-axis current, and t represents the current time.

[0104] A2. Using the integral analysis method, we integrate both sides of formula (2) from time T before the current time to the current time, and obtain the following formula (3):

[0105]

[0106] Where tT in the first integration interval represents the time T before the current time, t represents the current time, and g m (τ) represents the first modulation parameter, g m (τ)=(t-τ) m (tT-τ), u d (τ) represents the direct-axis voltage, R s Indicates the resistance parameter, i d (τ) represents the direct-axis current, ω e (τ) represents the motor speed, L d L represents the direct-axis inductance parameter. q Indicates the quadrature axis inductance parameter, i q (τ) represents the quadrature-axis current.

[0107] A3. Using the integration by parts method, the derivative of formula (3) with respect to the direct-axis current is transformed into the derivative with respect to the first modulation parameter g. m Differentiating (τ), we obtain the following formula (4):

[0108]

[0109] It should be noted that, due to g m (τ)=(t-τ) m (tT-τ), g m (τ)i d (τ) is 0 at τ = t and τ = Tt, therefore It can be directly omitted in formula (4)

[0110] A4. After phase shifting and normalization of the above formula (4), we obtain formula (5):

[0111]

[0112] It is understandable that, given that the motor output signal includes direct-axis current, quadrature-axis current, direct-axis voltage, and motor speed, based on the analysis of the known first modulation parameter and the motor output signal within a preset time period, the following elements are included in formula (5): the integral of the product of the direct-axis current and the derivative of the first modulation parameter with respect to the time variable within the preset time period, the integral of the product of the direct-axis current and the first modulation parameter within the preset time period, the integral of the product of the quadrature-axis current, the motor speed, and the first modulation parameter within the preset time period, and the integral of the product of the direct-axis voltage and the first modulation parameter within the preset time period.

[0113] Therefore, the known elements in formula (5) can be used as the elements for constructing the first observation matrix. To facilitate linear algebraic analysis, the elements for constructing the first observation matrix can be divided into two groups, which are used to construct the first output matrix and the first state matrix included in the first observation matrix, respectively.

[0114] In some embodiments, the first observation matrix includes a first output matrix and a first state matrix, and the above step S201 can be specifically implemented as the following steps S2011-S2012.

[0115] S2011. Determine the first output matrix based on the direct-axis current and the first modulation parameters.

[0116] The first modulation parameter is determined based on the identification time and the first integration interval; the first integration interval is determined based on a preset time period.

[0117] For example, the elements in the first output matrix are determined based on the integration result of the first integration object within the first integration interval; wherein, the first integration object is the product of the direct-axis current and the first derivative; the first derivative is the derivative of the first modulation parameter with respect to the time variable.

[0118] As one possible implementation, the first output matrix can be represented by the following formula (6).

[0119]

[0120] Where Y(t) represents the first output matrix, tT in the first integration interval represents the time T before the current time, and t represents the current time. These represent the first modulation parameter g when m takes the values ​​1, 2, and 3, respectively. m (τ) derivative with respect to the time variable, i f (τ) represents the direct-axis current.

[0121] S2012. Determine the first state matrix based on the direct-axis current, quadrature-axis current, direct-axis voltage, motor speed, and the first modulation parameter.

[0122] For example, the first state matrix includes a first element, a second element, and a third element; the first element is determined based on the integration result of a second integral object within a first integration interval; wherein the second integral object is the product of the direct-axis current and the first modulation parameter; the second element is determined based on the integration result of a third integral object within a first integration interval; wherein the third integral object is the product of the quadrature-axis current, the motor speed, and the first modulation parameter; the third element is determined based on the integration result of a fourth integral object within a first integration interval; wherein the fourth integral object is the product of the direct-axis voltage and the first modulation parameter.

[0123] As one possible implementation, the first column of the first state matrix is ​​composed of the first element, the second column of the first state matrix is ​​composed of the second element, and the third column of the first state matrix is ​​composed of the first element. The first state matrix can be represented by the following formula (7).

[0124]

[0125] Where Φ(t) represents the first state matrix, tT in the first integration interval represents the time T before the current time, t represents the current time, and g1(τ), g2(τ), and g3(τ) represent the first modulation parameters g when m takes the values ​​1, 2, and 3, respectively. m (τ), i d (τ) represents the direct-axis current, i ωq (τ)=ω e (τ)i q (τ), i ωq (τ) represents the product of the quadrature-axis current and the motor speed, u d (t) represents the direct-axis voltage.

[0126] As can be seen from steps S2011-S2012 above, dividing the elements of the first observation matrix into two groups, which are used to construct the first output matrix and the first state matrix included in the first observation matrix, can convert the relationship reflected between direct-axis current, quadrature-axis current, direct-axis voltage, and motor speed into a linear algebraic form. Constructing the first output matrix and the first state matrix can intuitively reflect the relationship between the motor output signal and the motor state in the direct-axis direction, which is helpful for motor parameter identification.

[0127] In some embodiments, a second observation matrix can be constructed based on the relationship between the motor output signal and the motor state in the cross-axis direction of the synchronous rotating coordinate system.

[0128] Taking permanent magnet synchronous motor as an example, the quadrature axis voltage equation of permanent magnet synchronous motor in synchronous rotating coordinate system can reflect the relationship between the motor output signal and the motor state in the quadrature axis direction.

[0129] Therefore, the elements for constructing the second observation matrix can be determined based on the analysis of the quadrature-axis voltage equation and the second modulation parameter of the permanent magnet synchronous motor in the synchronous rotating coordinate system.

[0130] The quadrature-axis voltage equation of the permanent magnet synchronous motor in the synchronous rotating coordinate system is as follows (8).

[0131]

[0132] Among them, u q R represents the quadrature-axis voltage. s Indicates the resistance parameter, i q Represents the quadrature-axis current, ω e L represents the motor speed. d Indicates the quadrature axis inductance parameter, i d Represents direct-axis current, Ψ f This represents the flux linkage parameter.

[0133] It should be noted that since formula (8) includes the rate of change of the quadrature-axis current, i.e., the derivative of the quadrature-axis current, the process of obtaining the derivative of the quadrature-axis current by analyzing the motor output signal may generate noise. In order to reduce the influence of noise that may be generated during signal analysis, an integral analysis method can be used to calculate the integral of the motor output signal within a preset time period. Furthermore, by introducing a second modulation parameter and multiplying it with the motor output signal, the derivative analysis of the unknown signal to be detected, the quadrature-axis current, can be transformed into a derivative analysis of the known second modulation parameter based on the integration by parts method.

[0134] As one possible implementation, based on the analysis of the quadrature-axis voltage equation and the second modulation parameter of the permanent magnet synchronous motor in the synchronous rotating coordinate system, the specific process of determining the elements of the second observation matrix includes the following steps B1-B4.

[0135] B1. Introduce the second modulation parameter f in formula (8). m (t), multiply both sides of formula (1) by the second modulation parameter to obtain the following formula (9):

[0136]

[0137] Among them, f m (t) represents the second modulation parameter, u q (t) represents the quadrature-axis voltage, R s Indicates the resistance parameter, i q (t) represents the quadrature-axis current, L q L represents the quadrature axis inductance parameter. d Indicates the direct-axis inductance parameter, i d (t) represents the direct-axis current, ω e (t) represents the motor speed, Ψf represents the flux linkage parameter, and t represents the current time.

[0138] B2. Using the integral analysis method, we integrate both sides of formula (9) from time T before the current time to the current time, and obtain the following formula (10):

[0139]

[0140] In the second integration interval, tT represents the time T before the current time, t represents the current time, and f m (τ) represents the second modulation parameter, f m (τ)=(t-τ) m (tT-τ), u q (τ) represents the quadrature-axis voltage, R s Indicates the resistance parameter, i q (τ) represents the quadrature-axis current, L q L represents the quadrature axis inductance parameter. d Indicates the direct-axis inductance parameter, i d (τ) represents the direct-axis current, ω e (τ) represents the motor speed, Ψ f This represents the flux linkage parameter.

[0141] B3. Using the integration by parts method, the derivative of the quadrature-axis current in formula (10) is transformed into the derivative of the second modulation parameter f. m Differentiating (τ), we obtain the following formula (11):

[0142]

[0143] It should be noted that, due to f m (τ)i q (τ) is 0 at τ = t and τ = Tt, therefore This can be directly omitted in formula (11)

[0144] B4. After phase shifting and normalization of the above formula (11), we obtain formula (12):

[0145]

[0146] It is understandable that, given that the motor output signal includes direct-axis current, quadrature-axis current, quadrature-axis voltage, and motor speed, based on the analysis of the known second modulation parameter and the motor output signal within a preset time period, the following elements are included in formula (12): the integral of the product of quadrature-axis current and the second modulation parameter within a preset time period, the integral of the product of direct-axis current and motor speed with the second modulation parameter within a preset time period, the integral of the product of quadrature-axis current and the second modulation parameter within a preset time period, the integral of the product of quadrature-axis voltage and the second modulation parameter within a preset time period, and the integral of the product of motor speed and the second modulation parameter within a preset time period.

[0147] Therefore, the known elements in formula (12) can be used as elements to construct the second observation matrix. To facilitate linear algebraic analysis, the elements for constructing the second observation matrix can be divided into two groups, which are used to construct the second output matrix and the second state matrix included in the second observation matrix, respectively.

[0148] In some embodiments, the second observation matrix includes a second output matrix and a second state matrix, and the above step S201 can be specifically implemented as the following steps S2013-S2014.

[0149] S2013. Determine the second output matrix based on the quadrature axis current and the second modulation parameters.

[0150] For example, the elements in the second output matrix are determined based on the integration result of the fifth integral object within the second integration interval; wherein the fifth integral object is the product of the cross-axis current and the second derivative; the second derivative is the derivative of the second modulation parameter with respect to the time variable.

[0151] As one possible implementation, the second output matrix can be expressed as formula (13).

[0152]

[0153] Where M(t) represents the second output matrix, tT in the second integration interval represents the time T before the current time, and t represents the current time. These represent the second modulation parameter f when m takes the values ​​1, 2, 3, and 4, respectively. m (τ) derivative with respect to the time variable, i q (τ) represents the quadrature-axis current.

[0154] S2014. Based on the direct-axis current, quadrature-axis current, quadrature-axis voltage, motor speed, and second modulation parameters, determine the second state matrix.

[0155] For example, the second state matrix includes a fourth element, a fifth element, a sixth element, and a seventh element; the fourth element is determined based on the integration result of the sixth integral object within the second integration interval; wherein, the sixth integral object is the product of the direct-axis current, the motor speed, and the second modulation parameter; the fifth element is determined based on the integration result of the seventh integral object within the second integration interval; wherein, the seventh integral object is the product of the quadrature-axis current and the second modulation parameter; the sixth element is determined based on the integration result of the eighth integral object within the second integration interval; wherein, the eighth integral object is the product of the quadrature-axis voltage and the second modulation parameter; the seventh element is determined based on the integration result of the ninth integral object within the second integration interval; wherein, the ninth integral object is the product of the motor speed and the second modulation parameter.

[0156] As one possible implementation, the first column of the second state matrix is ​​composed of the fourth element, the second column is composed of the fifth element, the third column is composed of the sixth element, and the fourth column is composed of the seventh element. The second state matrix can be represented by the following formula (14).

[0157]

[0158] Where λ(t) represents the second state matrix, tT in the second integration interval represents the time T before the current time, t represents the current time, and f1(τ), f2(τ), f3(τ), and f4(τ) represent the second modulation parameters f when m takes the values ​​1, 2, 3, and 4, respectively. m (τ), i ωd (τ)=ω e (τ)i d (τ), i ωd (τ) represents the product of the direct-axis current and the motor speed, i q (τ) represents the quadrature-axis current, u q (t) represents the quadrature-axis voltage, ω e (τ) represents the motor speed.

[0159] It should be noted that the first integration interval and the second integration interval are the integration intervals used when constructing the first observation matrix and the second observation matrix, respectively. At the same identification time, the values ​​of the first integration interval and the second integration interval are the same.

[0160] As can be seen from steps S2013-S2014 above, the elements in formula (12) that can be determined based on the analysis of the known second modulation parameters and motor output signal can be used as elements for constructing the second output matrix and the second state matrix. This can convert the relationship between direct-axis current, quadrature-axis current, quadrature-axis voltage, and motor speed into a form that can be analyzed using linear algebra. Constructing the second output matrix and the second state matrix can intuitively reflect the relationship between the motor output signal and the motor state in the direct-axis direction, which helps to reduce the complexity of the algorithm in the motor parameter identification process.

[0161] S202. Identify motor parameters based on the observation matrix.

[0162] The motor parameters include at least one of the following: inductance parameters, resistance parameters, and flux linkage parameters. The inductance parameters include direct-axis inductance parameters and quadrature-axis inductance parameters.

[0163] In some embodiments, motor parameter identification can be based on linear analysis of the observation matrix. For example... Figure 3 As shown, the above step S202 can be specifically implemented as the following steps S2021-S2022.

[0164] S2021. Determine a parameter matrix based on a first observation matrix and / or a second observation matrix. The parameter matrix includes at least one parameter vector, which is used to determine the predicted values ​​of the motor parameters.

[0165] It should be noted that the observation matrix can reflect the relationship between the motor output signal and the motor state, that is, the relationship between the motor output signal and the motor parameters. Furthermore, under conditions where there are no significant temperature changes in the motor environment, no mechanical deformation of the internal motor structure, or the motor is not affected by a strong magnetic field, the values ​​of the motor parameters can remain stable for a short period of time.

[0166] Based on this, the observation matrix can be regarded as a linear model, and the motor parameters can be determined by analyzing the linear model.

[0167] In some embodiments, since the least squares method provides a systematic approach to estimate the parameters of a linear model, minimizing the sum of squared errors between the model's predicted values ​​and the actual observed values, the least squares method can be used to construct parameter estimation equations based on the observation matrix. By solving these equations, the motor parameters can be identified. Therefore, the above-described determination of the parameter matrix based on the first and / or second observation matrix can be implemented as follows: determining the parameter matrix using the least squares method based on the first and / or second observation matrices.

[0168] For example, when the observation matrix includes a first observation matrix, which includes a first output matrix and a first state matrix, the parameter estimation equation includes a first parameter estimation equation, which is constructed based on the first observation matrix. The first parameter estimation equation can be expressed as the following formula (15).

[0169] α=(Φ T Φ) -1 Φ T Y formula (15)

[0170] Where α represents the solution to the first parameter estimation equation, i.e., the first parameter matrix, Φ represents the first output matrix, and Y represents the first state matrix.

[0171] When the observation matrix includes a second observation matrix, and the second observation matrix includes a second output matrix and a second state matrix, the parameter estimation equation includes a second parameter estimation equation, which is constructed based on the second observation matrix. The second parameter estimation equation can be expressed as the following formula (16).

[0172] β=(λ T λ) -1 λ T M formula (16)

[0173] Where β represents the solution to the second parameter estimation equation, i.e., the second parameter matrix, λ represents the second output matrix, and M represents the second state matrix.

[0174] Understandably, the parameter estimation equations constructed based on the observation matrix can reflect the relationship between the output signal and the motor parameters. Solving the parameter estimation equations can yield the parameter matrix, which includes a parameter vector composed of the motor parameters.

[0175] S2022. Determine the motor parameters based on at least one parameter vector in the parameter matrix.

[0176] As one possible implementation, when the observation matrix includes a first observation matrix and a second observation matrix, the parameter matrix includes a first parameter matrix and a second parameter matrix.

[0177] The first parameter matrix is ​​obtained by solving the first parameter estimation equation based on the first observation matrix, and the second parameter matrix is ​​obtained by solving the second parameter estimation equation based on the second observation matrix.

[0178] The first observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state in the direct axis direction, and the second observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state in the quadrature axis direction.

[0179] For example, when the first output matrix is ​​represented by formula (6) and the first state matrix is ​​represented by formula (7), the first parameter matrix can be represented by formula (15); when the second output matrix is ​​represented by formula (13) and the second state matrix is ​​represented by formula (14), the second parameter matrix can be represented by formula (16).

[0180] As can be seen from steps S2021-S2022 above, identifying motor parameters based on the parameter estimation strategy can reduce the algorithm complexity during the motor parameter identification process, thereby reducing the response latency of motor parameter identification. This not only improves the efficiency of motor parameter identification but also helps optimize the motor control strategy, achieving more efficient motor management.

[0181] In some embodiments, the motor parameters include at least one of the following: first motor parameters and second motor parameters; wherein the first motor parameters are determined based on at least one parameter vector in the first parameter matrix; and the second motor parameters are determined based on at least one parameter vector in the second parameter matrix.

[0182] For example, the first motor parameters include at least one of the following: a first direct-axis inductance parameter, a first quadrature-axis inductance parameter, and a first resistance parameter; and / or, the second motor parameters include at least one of the following: a second direct-axis inductance parameter, a second quadrature-axis inductance parameter, a second resistance parameter, and a flux linkage parameter.

[0183] As one possible implementation, when the parameter matrix is ​​determined based on the first observation and the second observation matrix, that is, when the parameter matrix includes the first parameter matrix and the second parameter matrix, the above step S2022 can be specifically implemented as the following steps C1-C3.

[0184] C1. Determine the parameters of the first motor based on at least one parameter vector in the first parameter matrix.

[0185] It is understandable that since the first output matrix and the first state matrix are constructed based on the known elements in formula (5), when the first output matrix is ​​represented by formula (6) and the first state matrix is ​​represented by formula (7), the parameter vectors included in the first parameter matrix obtained based on formula (15) correspond one-to-one with the coefficients of the elements used to construct the first observation matrix in formula (5).

[0186] The first parameter matrix is ​​in the form of In this case, based on the correspondence between the elements in the first output matrix and the first state matrix and the elements included in formula (15), we can obtain Among them, R s L represents the resistance parameter. q L represents the quadrature axis inductance parameter. dThis represents the parameters of the direct-axis inductance.

[0187] Based on this, the parameters of the first motor can be expressed as formulas (17)-(19).

[0188]

[0189] Among them, L d1 α represents the first-axis inductance parameter, and α3 represents the parameter vector in the third row of the first parameter matrix.

[0190]

[0191] Among them, L q1 Let α1 represent the first cross-axis inductance parameter, α2 represent the parameter vector in the second row of the first parameter matrix, and α3 represent the parameter vector in the third row of the first parameter matrix.

[0192]

[0193] Among them, R s1 Let α1 represent the parameter vector in the first row of the first parameter matrix, and α3 represent the parameter vector in the third row of the first parameter matrix.

[0194] C2. Determine the parameters of the second motor based on at least one parameter vector in the second parameter matrix.

[0195] It is understandable that since the second output matrix and the second state matrix are constructed based on the known elements in formula (12), when the first output matrix is ​​represented by formula (13) and the first state matrix is ​​represented by formula (14), the parameter vectors included in the first parameter matrix obtained based on formula (16) correspond one-to-one with the coefficients of the elements used to construct the first observation matrix in formula (12).

[0196] The second parameter matrix is ​​in the form of In this case, based on the correspondence between the elements in the second output matrix and the second state matrix and the elements included in formula (16), we can obtain Among them, R s L represents the resistance parameter. q L represents the quadrature axis inductance parameter. d Ψ represents the direct-axis inductance parameter. f This represents the flux linkage parameter.

[0197] Based on this, the parameters of the second motor can be expressed as formulas (20)-(23).

[0198]

[0199] Among them, Lq2 β3 represents the parameter of the second cross-axis inductance, and β3 represents the parameter vector in the third row of the second parameter matrix.

[0200]

[0201] Among them, L d2 Let β1 represent the parameter vector in the first row of the second parameter matrix, and β3 represent the parameter vector in the third row of the second parameter matrix.

[0202]

[0203] Among them, R s2 β1 represents the second resistance parameter, β2 represents the parameter vector in the second row of the second parameter matrix, and β3 represents the parameter vector in the third row of the second parameter matrix.

[0204]

[0205] Where, ψ f β3 represents the flux linkage parameter in the second motor parameters, β4 represents the parameter vector in the third row of the second parameter matrix, and β3 represents the parameter vector in the fourth row of the second parameter matrix.

[0206] C3. Based on the first motor parameters, the weights corresponding to the first motor parameters, the second motor parameters, and the weights corresponding to the second motor parameters, the motor parameters are obtained.

[0207] For example, when the motor parameters include inductance parameters, flux linkage parameters and resistance parameters, the flux linkage parameter in the motor parameters can be determined based on the flux linkage parameter in the second motor parameters; the inductance parameter and resistance parameter in the motor parameters can be determined based on the following formulas (24)-(26).

[0208] L d =ξ1L d1 +(1-ξ1)L d2 Formula (24)

[0209] Among them, L d L represents the direct-axis inductance parameter. d1 L represents the first-axis inductance parameter. d2 Let ξ1 represent the weight corresponding to the first direct-axis inductance parameter, and (1-ξ1) represent the weight corresponding to the second direct-axis inductance parameter. The value range of ξ1 is 0≤ξ1≤1.

[0210] L q =ξ2L r1 +(1-ξ2)L q2 Formula (25)

[0211] Among them, Lq L represents the quadrature axis inductance parameter. q1 L represents the parameter of the first quadrature axis inductance. q2 Let ξ2 represent the weight corresponding to the first cross-axis inductance parameter, and (1-ξ2) represent the weight corresponding to the second cross-axis inductance parameter. The value range of ξ2 is 0≤ξ2≤1.

[0212] R s =ξ3R s1 +(1-ξ3)R s2 Formula (26)

[0213] Among them, R s R represents the resistance parameter. s1 R represents the first resistance parameter. s2 Let ξ3 represent the weight corresponding to the first resistance parameter, and (1-ξ3) represent the weight corresponding to the second resistance parameter. The value range of ξ3 is 0≤ξ3≤1.

[0214] It should be noted that the weights corresponding to the first motor parameter and the second motor parameter include: the weights corresponding to the first direct-axis inductance parameter, the second direct-axis inductance parameter, the first quadrature-axis inductance parameter, the second quadrature-axis inductance parameter, the first resistance parameter, and the second resistance parameter. The weights corresponding to the first motor parameter and the second motor parameter can be determined through motor calibration tests.

[0215] In some embodiments, in order to reduce the error of the motor parameter identification result, in step C3 above, the weights corresponding to the first direct-axis inductance parameter, the first quadrature-axis inductance parameter, and the first resistance parameter are all 0.5.

[0216] As can be seen from the above steps C1-C3, determining the motor parameters based on the first motor parameters and the second motor parameters can simultaneously identify the motor parameters based on the relationship between the motor output signal and the motor state in the direct axis direction and the relationship between the motor output signal and the motor state in the quadrature axis direction. This not only improves the reliability of the motor parameter identification results, but also helps to optimize the motor control strategy, thereby improving the motor's operating performance.

[0217] As another possible implementation, when the parameter matrix is ​​determined based on the first observation matrix, that is, when the parameter matrix includes the first parameter matrix, step S2022 can be implemented as steps D1-D2 as follows.

[0218] D1. Determine the parameters of the first motor based on at least one parameter vector in the first parameter matrix.

[0219] In some embodiments, the implementation method of determining the first motor parameters based on at least one parameter vector in the first parameter matrix can be referred to the description in step C1 above, and will not be repeated here.

[0220] D2. Obtain motor parameters based on the first motor parameters.

[0221] In some embodiments, the first motor parameters include a first direct-axis inductance parameter, a first quadrature-axis inductance parameter, and a first resistance parameter. When the motor parameters include inductance and resistance parameters, the direct-axis inductance parameter is the first direct-axis inductance parameter, the quadrature-axis inductance parameter is the first quadrature-axis inductance parameter, and the resistance parameter is the first resistance parameter.

[0222] For example, the first direct-axis inductance parameter can be determined based on formula (17), the first quadrature-axis inductance parameter can be determined based on formula (18), and the first resistance parameter can be determined based on formula (19).

[0223] As another possible implementation, when the parameter matrix is ​​determined based on the second observation matrix, that is, when the parameter matrix includes the second parameter matrix, step S2022 can be implemented as steps E1-E2 as follows.

[0224] E1. Determine the parameters of the second motor based on at least one parameter vector in the second parameter matrix.

[0225] In some embodiments, the implementation method of determining the second motor parameters based on at least one parameter vector in the second parameter matrix can be referred to the description in step C2 above, and will not be repeated here.

[0226] E2. Obtain motor parameters based on the second motor parameters.

[0227] In some embodiments, the second motor parameters include a second direct-axis inductance parameter, a second quadrature-axis inductance parameter, a second resistance parameter, and a flux linkage parameter. When the motor parameters include inductance, resistance, and flux linkage, the direct-axis inductance parameter is the second direct-axis inductance parameter, the quadrature-axis inductance parameter is the second quadrature-axis inductance parameter, the resistance parameter is the second resistance parameter, and the flux linkage parameter of the motor parameters is the flux linkage parameter in the second motor parameters.

[0228] For example, the second direct-axis inductance parameter can be determined based on formula (21), the second quadrature-axis inductance parameter can be determined based on formula (20), the second resistance parameter can be determined based on formula (22), and the flux linkage parameter in the second motor parameter can be determined based on formula (23).

[0229] The technical solutions provided by the above embodiments bring at least the following beneficial effects: The solutions provided by the embodiments of this application can construct an observation matrix that reflects the relationship between the motor output signal and the motor state, and can perform motor parameter identification based on the observation matrix. By constructing the observation matrix, the motor output signal is converted into a form suitable for linear regression analysis, reducing the algorithm complexity in the motor parameter identification process, thereby reducing the response delay of motor parameter identification and improving the efficiency of motor parameter identification.

[0230] In some embodiments, in order to accurately evaluate the performance of the motor under actual operating conditions, parameter evaluation needs to be performed when the motor is in operation. Before step S201 above, the motor parameter identification method provided in this application further includes: in response to a received vehicle control command, acquiring the motor output signal within a preset time period.

[0231] In some embodiments, the motor output signal collected within a preset segment is stored in the built-in memory of the motor control device.

[0232] One possible implementation is that the vehicle control command is sent from the vehicle control unit (VCU) to the motor control device, and the vehicle control command is used to control the motor.

[0233] Understandably, when the motor control device receives control commands from the vehicle, it acquires the motor output signal, enabling the motor parameter identification process to be completed while the motor is running. Performing parameter identification while the motor is running not only improves the accuracy of the identification results but also allows for a more accurate assessment of the motor's performance under actual operating conditions. This helps optimize the motor control strategy and improve motor performance.

[0234] It should be noted that since the direct-axis current and quadrature-axis current of the motor are defined in a synchronous rotating coordinate system, they cannot be directly obtained through sensor detection. Therefore, the direct-axis current and quadrature-axis current of the motor can be obtained by transforming the three-phase current in a three-phase stationary coordinate system, which can be directly obtained.

[0235] For example, when the motor output signal includes direct-axis current, quadrature-axis current, direct-axis voltage, and quadrature-axis voltage, the motor output signal within a preset time period can be obtained, which can be implemented as follows: steps F1-F2.

[0236] F1: Obtain the three-phase current of the motor.

[0237] One possible approach is to obtain the motor's three-phase current from the motor's three-phase inverter.

[0238] As another possible implementation, the three-phase current of the motor can be obtained from a three-phase current sensor.

[0239] F2. Perform Clarke and Park transformations on the three-phase currents of the motor to obtain the direct-axis current and quadrature-axis current.

[0240] Understandably, the Clarke transformation can convert three-phase currents in a three-phase stationary coordinate system to a two-phase stationary coordinate system (α-β coordinate system); the Park transformation can convert the α-axis and β-axis currents in a two-phase stationary coordinate system to a synchronous rotating coordinate system. Therefore, based on the Clarke and Park transformations, it is possible to convert the three-phase currents of a motor into direct-axis and quadrature-axis currents.

[0241] For example, the α-axis current and β current in the two-phase stationary coordinate system obtained by Clarke transformation of the three-phase current in the three-phase coordinate system satisfy the following formula (27).

[0242]

[0243] Among them, i α i represents the α-axis current of the motor in a two-phase stationary coordinate system. β i represents the β-axis current of the motor in a two-phase stationary coordinate system. a i represents the a-axis current of the motor in a three-phase stationary coordinate system. b i represents the b-axis current of the motor in a three-phase stationary coordinate system. c This represents the c-axis current of the motor in a three-phase stationary coordinate system.

[0244] The direct-axis current and quadrature-axis current in the synchronous rotating coordinate system obtained by Park transformation of the α-axis current and β current in the two-phase stationary coordinate system satisfy the following formula (28).

[0245]

[0246] Among them, i d i represents the direct-axis current of the motor in a synchronous rotating coordinate system. q i represents the quadrature-axis current of the motor in a synchronous rotating coordinate system. α i represents the α-axis current of the motor in a two-phase stationary coordinate system. β This represents the β-axis current of the motor in a two-phase stationary coordinate system.

[0247] In some embodiments, motor parameter identification can be used to optimize motor control strategies. Therefore, after step S202 above, the motor parameter identification method provided in this application further includes the following step S203.

[0248] S203. Send the motor parameters to the vehicle controller so that the vehicle controller, upon determining that preset conditions are met, sends the motor parameters to the cloud platform; wherein, the cloud platform is used to perform parameter analysis of the motor based on the motor parameters.

[0249] For example, the vehicle controller can determine whether the motor is in an abnormal working state based on the motor parameters, and send the motor parameters to the cloud platform when the motor is in an abnormal working state.

[0250] It should be noted that the vehicle controller, as a key control unit in the vehicle, typically does not communicate directly with the cloud platform outside the vehicle. Therefore, a communication device within the vehicle can isolate the vehicle controller from the external network, allowing the vehicle controller to communicate with the cloud platform located on the external network. For example, the communication device could be a PAD (Pad for Access Devices).

[0251] Among them, the PAD, as a visual terminal in the vehicle, can send information sent by the vehicle controller to the PAD to the cloud platform through vehicle-cloud communication, and can also send information sent by the cloud platform to the PAD to the vehicle controller, thereby realizing the communication connection between the cloud platform and the vehicle controller.

[0252] In some embodiments, the preset conditions include at least one of the following: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0253] In some embodiments, the cloud platform can send control adjustment commands to the motor control device based on the received motor parameters, if it is determined that the motor parameters are inconsistent with the nominal parameters.

[0254] It should be noted that since the cloud platform resides in the vehicle's external network, it typically cannot directly communicate with control units inside the vehicle, such as the vehicle controller and motor control unit. Therefore, the cloud platform can communicate with the vehicle's internal control units through communication devices within the vehicle. For example, the cloud platform can send control adjustment commands to the motor control unit via a PAD and the vehicle controller.

[0255] Based on this, after sending the motor parameters to the vehicle controller, the motor parameter identification method provided in this application also includes the following steps S204-S205.

[0256] S204, Receive control adjustment instructions.

[0257] Among them, the control adjustment command is issued by the cloud platform when it determines that the motor parameters are inconsistent with the nominal parameters.

[0258] In some embodiments, the cloud platform can send control adjustment commands to the motor control device.

[0259] For example, control adjustment commands can be sent from the cloud platform to the motor control unit via the PAD and the vehicle controller.

[0260] S205. In response to the control adjustment command, adjust the control parameters of the motor.

[0261] See Figure 4 This is a flowchart illustrating a motor parameter analysis method provided in an embodiment of this application. Figure 4 As shown, the motor parameter analysis method provided in this application can be implemented through the above-mentioned vehicle controller, specifically including the following steps S301-S302.

[0262] S301, Receive motor parameters sent by the motor control device.

[0263] Among them, the motor parameters are obtained by identifying the motor parameters based on the observation matrix; the observation matrix is ​​constructed based on the motor output signal within a preset time period, and the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state.

[0264] In some embodiments, the motor control device can identify motor parameters based on the observation matrix. The specific implementation process is as described in steps S201-S202 above, and will not be repeated here.

[0265] S302. If the preset conditions are met, send the motor parameters to the cloud platform so that the cloud platform can perform parameter analysis of the motor based on the motor parameters.

[0266] In some embodiments, the vehicle controller can also send motor parameters to the cloud platform via the vehicle's communication device, such as a PAD, when preset conditions are met, so that the cloud platform can monitor the vehicle status in real time. Based on this, the preset conditions include at least one of the following: determining that the motor is in an abnormal working state; and meeting a preset transmission time.

[0267] In some embodiments, after receiving motor parameters sent by the motor control device via the PAD, the cloud platform can analyze the motor parameters based on these parameters. When the motor parameters do not match the electronic control strategy, the electronic control strategy can be adjusted to improve motor performance.

[0268] Understandably, sending motor parameters to the cloud platform within the preset transmission time allows for timely synchronization of these parameters, improving the real-time monitoring of vehicle status. Sending motor parameters to the cloud platform when an abnormal motor condition is confirmed enables a timely response to motor malfunctions caused by parameter changes, enhancing motor reliability and safety.

[0269] See Figure 5This is a flowchart illustrating another motor parameter analysis method provided in an embodiment of this application. Figure 5 As shown, the motor parameter analysis method provided in this application can be implemented through the aforementioned cloud platform, specifically including the following steps S401 to S402.

[0270] S401: Receive motor parameters sent by the vehicle controller.

[0271] Among them, the motor parameters are obtained by identifying the motor parameters based on the observation matrix; the observation matrix is ​​constructed based on the motor output signal within a preset time period, and the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state.

[0272] In some embodiments, the motor control device can identify motor parameters based on the observation matrix. The specific implementation process is as described in steps S201-S202 above, and will not be repeated here.

[0273] In some embodiments, the vehicle controller can send motor parameters to the cloud platform via a PAD.

[0274] S402. Perform parameter analysis of the motor based on motor parameters.

[0275] In some embodiments, step S402 can be specifically implemented as follows: when it is determined that the motor parameters are inconsistent with the nominal parameters, a control adjustment command is sent to the motor control device; the control adjustment command is used to instruct the motor to adjust the motor control parameters.

[0276] For example, control adjustment commands can be sent to the motor control unit via the PAD and the vehicle controller, so that the motor control unit can instruct the motor to adjust the motor's control parameters.

[0277] As can be seen from steps S401-S402 above, when the motor parameters are inconsistent with the nominal parameters, the cloud platform sends a control adjustment command to the motor control device, enabling the motor control device to adjust the motor's control parameters. This allows the cloud platform to adjust the motor's control parameters when they change, ensuring the motor is in a better working state. This not only improves the motor's flexibility and adaptability but also enhances its performance.

[0278] The motor parameter identification method of this application is described below with reference to a specific embodiment. Figure 6 As shown, the specific implementation process of this method can be achieved as follows: steps S501-S513.

[0279] S501, the vehicle controller sends vehicle control commands to the motor control unit, and the corresponding motor control unit receives the vehicle control commands sent by the vehicle controller.

[0280] S502. In response to the received vehicle control command, the motor control device acquires the motor output signal within a preset time period.

[0281] S503, The motor control device constructs an observation matrix based on the motor output signal within a preset time period.

[0282] The observation matrix is ​​used to reflect the relationship between the output signal and the motor state.

[0283] S504 The motor control device identifies motor parameters based on the observation matrix.

[0284] S505: The motor control unit sends motor parameters to the vehicle controller, and the vehicle controller receives the motor parameters sent by the motor control unit.

[0285] S506, the vehicle controller determines the operating status of the motor.

[0286] S507. Under the condition that the preset conditions are met, the vehicle controller sends motor parameters to the PAD, and the PAD receives the motor parameters sent by the vehicle controller.

[0287] For example, the preset conditions include at least one of the following: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0288] The S508 and PAD send motor parameters to the cloud platform, and the cloud platform receives the motor parameters sent by the PAD.

[0289] For example, the PAD can send motor parameters to the cloud platform via vehicle-to-cloud communication.

[0290] S509: In response to the motor parameters sent by the PAD, the cloud platform performs parameter analysis on the motor based on the motor parameters.

[0291] When the S510 cloud platform determines that the motor parameters are inconsistent with the nominal parameters, it sends a control adjustment command to the PAD. In turn, the PAD receives the control adjustment command sent by the cloud platform.

[0292] S511, PAD sends control adjustment commands to the vehicle controller, and the vehicle controller receives the control adjustment commands sent by PAD accordingly.

[0293] S512, The vehicle controller sends a control adjustment command to the motor control unit, and the corresponding motor control unit receives the control adjustment command sent by the vehicle controller.

[0294] S513. In response to the control adjustment command, the motor control device adjusts the control parameters of the motor.

[0295] In some embodiments, this application provides a motor control device that can execute any of the motor parameter identification methods included in the above embodiments.

[0296] In some embodiments, this application also provides a vehicle controller capable of executing any of the motor parameter analysis methods included in steps S301-S302 above.

[0297] In some embodiments, this application also provides a cloud platform capable of executing any of the motor parameter analysis methods included in steps S401-S402 above.

[0298] In some embodiments, this application also provides an in-vehicle system, which includes the aforementioned motor control device, the aforementioned vehicle controller, and the communication device. The in-vehicle system is communicatively connected to the aforementioned cloud platform.

[0299] In some embodiments, the communication device is used to send the motor parameters output by the vehicle controller to the cloud platform, so that the cloud platform can perform parameter analysis of the motor based on the motor parameters.

[0300] In some embodiments, the communication device is further configured to send control adjustment commands sent by the cloud platform to the motor control device through the vehicle controller, so that the motor control device can adjust the control parameters of the motor.

[0301] In some embodiments, the communication device may be a PAD.

[0302] Figure 7 A schematic diagram of a motor control system provided in this application embodiment includes: a speed regulator, a quadrature-axis current regulator, a direct-axis current regulator, an inverse Parker converter module, a space vector pulse width modulation (SVPWM) module, a three-phase inverter, a Parker converter module, a Clarke converter module, a speed and position sensor, an interior permanent magnet synchronous motor (IPMSM), and a motor parameter identification module.

[0303] Among them, the speed regulator, quadrature axis current regulator, and direct axis current regulator are all PI controllers.

[0304] The input to the speed regulator is the ideal motor speed ω. e * and actual motor speed ω e The error between them, the output is the ideal quadrature-axis current i of the motor in the synchronous rotating coordinate system. q *The speed regulator is used to generate the required electromagnetic torque command based on the error between the set ideal motor speed and the actual measured motor speed.

[0305] The input to the quadrature-axis current regulator is the ideal direct-axis current i of the motor in the synchronous rotating coordinate system. d * and actual direct-axis current i d The error between them, the output is the quadrature-axis voltage u of the motor in the synchronous rotating coordinate system. q .

[0306] The input to the direct-axis current regulator is the ideal quadrature-axis current i of the motor in the synchronous rotating coordinate system. q * and the actual quadrature-axis current i q The error between them is output as the direct-axis voltage u of the motor in the synchronous rotating coordinate system. d .

[0307] The input to the inverse Parker transformation module is the direct-axis voltage u of the motor in the synchronous rotating coordinate system. d and quadrature axis voltage u q The output is the α-axis voltage u of the motor in a two-phase stationary coordinate system (α-β coordinate system). α and β voltage u β .

[0308] The input to the SVPWM module is the α-axis voltage u of the motor in a two-phase stationary coordinate system. α and β voltage u β The output consists of six pulse width modulation (PWM) signals. These six PWM signals are divided into three groups, with two PWM signals from each group used to control the switching of the three upper and lower arms of the three-phase inverter, respectively. The SVPWM module generates the PWM signals, which are then used to control the switching states of the three-phase inverter.

[0309] The input to the three-phase inverter is the PWM signal generated by the SVPWM module and the DC voltage u of the motor. dc The output is the three-phase current i of the motor in the three-phase stationary coordinate system. α i b and i c A three-phase inverter is used to convert DC power into three-phase AC power with variable frequency and amplitude to power motors.

[0310] The input to the Parker transformation module is the α-axis current i of the motor in a two-phase stationary coordinate system. α and β current i β The output is the direct-axis current i of the motor in the synchronous rotating coordinate system. d and cross-axis current iq .

[0311] The input to the Clarke transform module is the three-phase current i of the motor in the three-phase stationary coordinate system. α i b and i c The output is the α-axis current i of the motor in a two-phase stationary coordinate system. α and β current i β .

[0312] The speed and position sensor is used to monitor the motor speed and rotor position in real time. The output of the speed and position sensor is the motor speed ω. e .

[0313] The input to the IPMSM is the three-phase current i of the motor in the three-phase stationary coordinate system. α i b and i c The IPMSM is used to generate corresponding mechanical movements based on instructions from the vehicle controller and is connected to the speed and position sensors.

[0314] The motor parameter identification module is used to identify motor parameters. The input to the motor parameter identification module is the direct-axis current i of the motor in the synchronous rotating coordinate system. d Cross-axis current i q Direct-axis voltage u d and quadrature axis voltage u q The output is the direct-axis inductance parameter L. d Quadrature axis inductance parameter L q Magnetic flux linkage parameter R s and resistance parameter Ψ f .

[0315] As can be seen, the above mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, the embodiments of this application provide corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the modules and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0316] This application embodiment can divide the motor parameter identification device or motor parameter analysis device into functional modules according to the above method examples. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0317] In some embodiments, this application also provides a motor parameter identification device. This motor parameter identification device may include one or more functional modules for implementing the motor parameter identification method of the above method embodiments.

[0318] For example, Figure 8 This is a schematic diagram illustrating the composition of a motor parameter identification device provided in an embodiment of this application. Figure 8 As shown, the motor parameter identification device 600 includes: identification module 601.

[0319] The identification module 601 is used to construct an observation matrix based on the motor output signal within a preset time period; the observation matrix is ​​used to reflect the relationship between the output signal and the motor state; and the motor parameters are identified based on the observation matrix.

[0320] In some embodiments, the observation matrix includes at least one of the following: a first observation matrix, which reflects the relationship between the motor output signal and the motor state in the direct axis direction; and a second observation matrix, which reflects the relationship between the motor output signal and the motor state in the quadrature axis direction.

[0321] In some other embodiments, the first observation matrix includes a first output matrix and a first state matrix; the motor output signal includes direct-axis current, quadrature-axis current, direct-axis voltage, and motor speed; constructing the observation matrix based on the motor output signal within a preset time period includes: determining the first output matrix based on the direct-axis current and a first modulation parameter; the first modulation parameter is determined based on the identification time and a first integration interval; the first integration interval is determined based on the preset time period; and determining the first state matrix based on the direct-axis current, quadrature-axis current, direct-axis voltage, motor speed, and the first modulation parameter.

[0322] In other embodiments, the elements in the first output matrix are determined based on the integration result of the first integration object within the first integration interval; wherein the first integration object is the product of the direct-axis current and the first derivative; the first derivative is the derivative of the first modulation parameter with respect to the time variable.

[0323] In other embodiments, the first state matrix includes a first element, a second element, and a third element; the first element is determined based on the integration result of a second integral object within a first integration interval; wherein the second integral object is the product of the direct-axis current and the first modulation parameter; the second element is determined based on the integration result of a third integral object within the first integration interval; wherein the third integral object is the product of the quadrature-axis current, the motor speed, and the first modulation parameter; the third element is determined based on the integration result of a fourth integral object within the first integration interval; wherein the fourth integral object is the product of the direct-axis voltage and the first modulation parameter.

[0324] In other embodiments, the second observation matrix includes a second output matrix and a second state matrix; the output signals include: direct-axis current, quadrature-axis current, quadrature-axis voltage, and motor speed; the identification module 601 is specifically used to determine the second output matrix based on the quadrature-axis current and the second modulation parameter; the second modulation parameter is determined based on the identification time and the second integration interval; the second integration interval is determined based on a preset time period; and the second state matrix is ​​determined based on the direct-axis current, quadrature-axis current, quadrature-axis voltage, motor speed, and the second modulation parameter.

[0325] In other embodiments, the elements in the second output matrix are determined based on the integration result of the fifth integral object within the second integration interval; wherein the fifth integral object is the product of the cross-axis current and the second derivative; the second derivative is the derivative of the second modulation parameter with respect to the time variable.

[0326] In other embodiments, the second state matrix includes a fourth element, a fifth element, a sixth element, and a seventh element; the fourth element is determined based on the integration result of the sixth integral object within the second integration interval; wherein the sixth integral object is the product of the direct-axis current, the motor speed, and the second modulation parameter; the fifth element is determined based on the integration result of the seventh integral object within the second integration interval; wherein the seventh integral object is the product of the quadrature-axis current and the second modulation parameter; the sixth element is determined based on the integration result of the eighth integral object within the second integration interval; wherein the eighth integral object is the product of the quadrature-axis voltage and the second modulation parameter; the seventh element is determined based on the integration result of the ninth integral object within the second integration interval; wherein the ninth integral object is the product of the motor speed and the second modulation parameter.

[0327] In other embodiments, the identification module 601 is specifically used to determine a parameter matrix based on a first observation matrix and / or a second observation matrix, the parameter matrix including at least one parameter vector, the parameter vector being used to determine the predicted values ​​of the motor parameters; and to determine the motor parameters based on at least one parameter vector in the parameter matrix.

[0328] In other embodiments, the identification module 601 is specifically used to determine the parameter matrix based on the first observation matrix and / or the second observation matrix using the least squares method.

[0329] In other embodiments, the parameter matrix includes at least one of the following: a first parameter matrix, which is obtained by solving a first parameter estimation equation based on a first observation matrix; and a second parameter matrix, which is obtained by solving a second parameter estimation equation based on a second observation matrix.

[0330] In other embodiments, the motor parameters include at least one of the following: a first motor parameter, which is determined based on at least one parameter vector in a first parameter matrix; and a second motor parameter, which is determined based on at least one parameter vector in a second parameter matrix.

[0331] In other embodiments, the first motor parameters include at least one of the following: a first direct-axis inductance parameter, a first quadrature-axis inductance parameter, and a first resistance parameter; and / or, the second motor parameters include at least one of the following: a second direct-axis inductance parameter, a second quadrature-axis inductance parameter, a second resistance parameter, and a flux linkage parameter.

[0332] In other embodiments, the motor parameters are determined based on a first motor parameter, the weight corresponding to the first motor parameter, and the weight corresponding to the second motor parameter and the second motor parameter.

[0333] In other embodiments, when the motor output signal includes direct-axis current and quadrature-axis current, the direct-axis current and the quadrature-axis current are obtained based on the motor's three-phase current through Clarke transformation and Park transformation.

[0334] In some embodiments, the motor parameter identification device 600 further includes a communication module 602. The communication module 602 is used to acquire the motor output signal within a preset time period in response to a received vehicle control command.

[0335] In other embodiments, the communication module 602 is further configured to send motor parameters to the vehicle controller, so that the vehicle controller, upon determining that preset conditions are met, sends the motor parameters to the cloud platform; wherein the cloud platform is used to perform parameter analysis of the motor based on the motor parameters.

[0336] In other embodiments, the preset conditions include at least one of the following: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0337] In other embodiments, the communication module 602 is also used to receive control adjustment instructions; the control adjustment instructions are issued by the cloud platform when it is determined that the motor parameters are inconsistent with the nominal parameters; the identification module 601 is also used to adjust the control parameters of the motor in response to the control adjustment instructions.

[0338] In some embodiments, this application also provides a motor parameter analysis device. This motor parameter analysis device may include one or more functional modules for implementing the motor parameter analysis method of the above method embodiments.

[0339] For example, Figure 9 This is a schematic diagram illustrating the composition of a motor parameter analysis device provided in an embodiment of this application. Figure 9 As shown, the motor parameter analysis device 700 includes a communication module 701.

[0340] The communication module 701 is used to receive motor parameters sent by the motor control device. The motor parameters are obtained by identifying motor parameters based on the observation matrix. The observation matrix is ​​constructed based on the motor output signal within a preset time period and is used to reflect the relationship between the motor output signal and the motor state. When the preset conditions are met, the motor parameters are sent to the cloud platform so that the cloud platform can perform parameter analysis of the motor based on the motor parameters.

[0341] In some embodiments, the preset conditions include at least one of the following: determining that the motor is in an abnormal working state; and meeting the preset transmission time.

[0342] For example, Figure 10 This is a schematic diagram illustrating the composition of another motor parameter analysis device provided in an embodiment of this application. Figure 10 As shown, the motor parameter analysis device 800 includes a communication module 801 and an analysis module 802.

[0343] The communication module 801 is used to receive motor parameters sent by the vehicle controller. The motor parameters are obtained by identifying motor parameters based on the observation matrix. The observation matrix is ​​constructed based on the motor output signal within a preset time period and is used to reflect the relationship between the motor output signal and the motor state.

[0344] Analysis module 802 is used to perform parameter analysis of the motor based on the motor parameters.

[0345] In some embodiments, the analysis module 802 is specifically used to send a control adjustment command to the motor control device when it is determined that the motor parameters are inconsistent with the nominal parameters; the control adjustment command is used to instruct the motor to adjust the motor control parameters.

[0346] In the case of implementing the functions of the integrated modules described above in hardware, this embodiment of the invention provides a possible structural schematic diagram of the electronic device involved in the above embodiments. For example... Figure 11 As shown, the electronic device 900 includes: a processor 902, a communication interface 903, and a bus 904. Optionally, the electronic device 900 may also include a memory 901.

[0347] Processor 902 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 902 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 902 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0348] The communication interface 903 is used to connect to other devices via a communication network. This communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0349] The memory 901 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0350] As one possible implementation, the memory 901 can exist independently of the processor 902. The memory 901 can be connected to the processor 902 via a bus 904 and is used to store instructions or program code. When the processor 902 calls and executes the instructions or program code stored in the memory 901, it can implement the motor parameter identification method or the motor parameter analysis method provided in this embodiment of the invention.

[0351] In another possible implementation, the memory 901 can also be integrated with the processor 902.

[0352] The 904 bus can be an extended industry standard architecture (EISA) bus, etc. The 904 bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 11The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0353] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the service calling device can be divided into different functional modules to complete all or part of the functions described above.

[0354] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be executed by computer instructions instructing related hardware. The program can be stored in the aforementioned computer-readable storage medium, and when executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be any of the foregoing embodiments or memory. The aforementioned computer-readable storage medium can also be an external storage device of the aforementioned service invocation device, such as a pluggable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the aforementioned service invocation device. Further, the aforementioned computer-readable storage medium can include both internal storage units of the aforementioned service invocation device and external storage devices. The aforementioned computer-readable storage medium is used to store the aforementioned computer program and other programs and data required by the aforementioned service invocation device. The aforementioned computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0355] This application also provides a computer program product, which includes a computer program that, when run on a computer, causes the computer to execute any of the motor parameter identification methods or motor parameter analysis methods provided in the above embodiments.

[0356] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for identifying motor parameters, used in a motor control device, characterized in that, The method includes: An observation matrix is ​​constructed based on the motor output signal within a preset time period; the observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state. Based on the observation matrix, the motor parameters are identified.

2. The method according to claim 1, characterized in that, The observation matrix includes at least one of the following: A first observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state in the direct axis direction; The second observation matrix is ​​used to reflect the relationship between the motor output signal and the motor state in the quadrature axis direction.

3. The method according to claim 2, characterized in that, The first observation matrix includes a first output matrix and a first state matrix; the motor output signal includes direct-axis current, quadrature-axis current, direct-axis voltage, and motor speed; The construction of the observation matrix based on the motor output signal within a preset time period includes: The first output matrix is ​​determined based on the direct-axis current and the first modulation parameters; the first modulation parameters are determined based on the identification time and the first integration interval; the first integration interval is determined based on the preset time period. The first state matrix is ​​determined based on the direct-axis current, the quadrature-axis current, the direct-axis voltage, the motor speed, and the first modulation parameter.

4. The method according to claim 3, characterized in that, The elements in the first output matrix are determined based on the integration result of the first integral object within the first integration interval; wherein, the first integral object is the product of the direct-axis current and the first derivative; the first derivative is the derivative of the first modulation parameter with respect to the time variable.

5. The method according to claim 3, characterized in that, The first state matrix includes a first element, a second element, and a third element; The first element is determined based on the integration result of the second integral object within the first integration interval; wherein the second integral object is the product of the direct-axis current and the first modulation parameter; The second element is determined based on the integration result of the third integral object within the first integration interval; wherein the third integral object is the product of the quadrature-axis current, the motor speed, and the first modulation parameter; The third element is determined based on the integration result of the fourth integral object within the first integration interval; wherein the fourth integral object is the product of the direct-axis voltage and the first modulation parameter.

6. The method according to claim 2, characterized in that, The second observation matrix includes a second output matrix and a second state matrix; the output signals include: direct-axis current, quadrature-axis current, quadrature-axis voltage, and motor speed; The construction of the observation matrix based on the motor output signal within a preset time period includes: The second output matrix is ​​determined based on the quadrature-axis current and the second modulation parameter; the second modulation parameter is determined based on the identification time and the second integration interval; the second integration interval is determined based on the preset time period. The second state matrix is ​​determined based on the direct-axis current, the quadrature-axis current, the quadrature-axis voltage, the motor speed, and the second modulation parameter.

7. The method according to claim 6, characterized in that, The elements in the second output matrix are determined based on the integration result of the fifth integral object within the second integration interval; wherein the fifth integral object is the product of the cross-axis current and the second derivative; the second derivative is the derivative of the second modulation parameter with respect to the time variable.

8. The method according to claim 6, characterized in that, The second state matrix includes a fourth element, a fifth element, a sixth element, and a seventh element; The fourth element is determined based on the integration result of the sixth integral object within the second integration interval; wherein, the sixth integral object is the product of the direct-axis current, the motor speed, and the second modulation parameter; The fifth element is determined based on the integration result of the seventh integral object within the second integration interval; wherein the seventh integral object is the product of the cross-axis current and the second modulation parameter; The sixth element is determined based on the integration result of the eighth integral object within the second integration interval; wherein the eighth integral object is the product of the cross-axis voltage and the second modulation parameter; The seventh element is determined based on the integration result of the ninth integral object within the second integration interval; wherein the ninth integral object is the product of the motor speed and the second modulation parameter.

9. The method according to any one of claims 2 to 8, characterized in that, The process of identifying the motor parameters based on the observation matrix includes: A parameter matrix is ​​determined based on the first observation matrix and / or the second observation matrix, the parameter matrix including at least one parameter vector, the parameter vector being used to determine the predicted values ​​of the motor parameters; The motor parameters are determined based on at least one of the parameter vectors in the parameter matrix.

10. The method according to claim 9, characterized in that, The step of determining the parameter matrix based on the first observation matrix and / or the second observation matrix includes: The parameter matrix is ​​determined by the least squares method based on the first observation matrix and / or the second observation matrix.

11. The method according to claim 9, characterized in that, The parameter matrix includes at least one of the following: The first parameter matrix is ​​obtained by solving the first parameter estimation equation constructed based on the first observation matrix; The second parameter matrix is ​​obtained by solving the second parameter estimation equation constructed based on the second observation matrix.

12. The method according to claim 11, characterized in that, The motor parameters include at least one of the following: First motor parameters, the first motor parameters being determined based on at least one parameter vector in the first parameter matrix; The second motor parameters are determined based on at least one parameter vector in the second parameter matrix.

13. The method according to claim 12, characterized in that, The first motor parameters include at least one of the following: a first direct-axis inductance parameter, a first quadrature-axis inductance parameter, and a first resistance parameter; And / or, the second motor parameters include at least one of the following: a second direct-axis inductance parameter, a second quadrature-axis inductance parameter, a second resistance parameter, and a flux linkage parameter.

14. The method according to claim 12, characterized in that, The motor parameters are determined based on the first motor parameters, the weights corresponding to the first motor parameters, the second motor parameters, and the weights corresponding to the second motor parameters.

15. The method according to claim 1, characterized in that, When the motor output signal includes direct-axis current and quadrature-axis current, the direct-axis current and the quadrature-axis current are obtained based on the three-phase current of the motor through Clarke transformation and Park transformation.

16. The method according to claim 1, characterized in that, Before constructing the observation matrix based on the motor output signal within a preset time period, the method further includes: In response to a received vehicle control command, the motor output signal within the preset time period is acquired.

17. The method according to claim 1, characterized in that, After identifying the motor parameters based on the observation matrix, the method further includes: The motor parameters are sent to the vehicle controller, so that the vehicle controller, upon determining that preset conditions are met, sends the motor parameters to the cloud platform; wherein, the cloud platform is used to perform parameter analysis of the motor based on the motor parameters.

18. The method according to claim 17, characterized in that, The preset conditions include at least one of the following: It has been determined that the motor is in an abnormal operating state; Meets the preset transmission time.

19. The method according to claim 17, characterized in that, The method further includes: Receive control adjustment instructions; the control adjustment instructions are issued by the cloud platform when it determines that the motor parameters are inconsistent with the nominal parameters; In response to the control adjustment command, the control parameters of the motor are adjusted.

20. A method for analyzing motor parameters, used in a vehicle controller, characterized in that, The method includes: The system receives motor parameters sent by a motor control device. These motor parameters are obtained by identifying motor parameters based on an observation matrix. The observation matrix is ​​constructed based on the motor output signal within a preset time period and is used to reflect the relationship between the motor output signal and the motor state. If the preset conditions are met, the motor parameters are sent to the cloud platform so that the cloud platform can perform parameter analysis on the motor based on the motor parameters.

21. The method according to claim 20, characterized in that, The preset conditions include at least one of the following: It has been determined that the motor is in an abnormal operating state; Meets the preset transmission time.

22. A method for analyzing motor parameters, used in a cloud platform, characterized in that, The method includes: The system receives motor parameters sent by the vehicle controller; these motor parameters are obtained by identifying motor parameters based on an observation matrix; the observation matrix is ​​constructed based on the motor output signal within a preset time period, and is used to reflect the relationship between the motor output signal and the motor state. Based on the motor parameters, perform parameter analysis on the motor.

23. The method according to claim 22, characterized in that, The parameter analysis of the motor based on the motor parameters includes: If it is determined that the motor parameters are inconsistent with the nominal parameters, a control adjustment command is sent to the motor control device; the control adjustment command is used to instruct the motor to adjust the motor control parameters.

24. A motor control device, characterized in that, Used to perform the motor parameter identification method as described in any one of claims 1 to 19.

25. A vehicle controller, characterized in that, Used to perform the motor parameter analysis method as described in any one of claims 20 to 21.

26. A cloud platform, characterized in that, Used to perform the motor parameter analysis method as described in any one of claims 22 to 23.

27. An electronic device, characterized in that, The device includes a processor and a memory, the processor being coupled to the memory; the memory is used to store computer instructions, the computer instructions being loaded and executed by the processor to enable the computer device to implement the motor parameter identification method as described in any one of claims 1 to 19; Alternatively, the motor parameter analysis method as described in any one of claims 20 to 21; Alternatively, the motor parameter analysis method as described in any one of claims 22 to 23.

28. A vehicle-mounted system, characterized in that, The vehicle system includes the motor control device as described in claim 24, the vehicle controller as described in claim 25, and the communication device; The communication device is used to send the motor parameters output by the vehicle controller to the cloud platform, so that the cloud platform can execute the parameter analysis method as described in any one of claims 22 to 23.

29. A vehicle, characterized in that, This includes the motor control device as described in claim 24; or the vehicle controller as described in claim 25; or the electronic device as described in claim 27; or the in-vehicle system as described in claim 28.

30. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes computer-executable instructions that, when executed on a computer, cause the computer to perform the motor parameter identification method according to any one of claims 1 to 19; Alternatively, the motor parameter analysis method as described in any one of claims 20 to 21; Alternatively, the motor parameter analysis method as described in any one of claims 22 to 23.

31. A computer program product, characterized in that, The computer program product includes a computer program that, when run on an electronic device, causes the electronic device to perform the motor parameter identification method as described in any one of claims 1 to 19. Alternatively, the motor parameter analysis method as described in any one of claims 20 to 21; Alternatively, the motor parameter analysis method as described in any one of claims 22 to 23.

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