Motor parameter control method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a motor parameter control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first-phase sampling current and a second-phase sampling current of a motor at a current sampling moment based on a preset sampling period when a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal are continuously input into the motor, the preset sampling period is obtained based on a signal period of the motor, and the first phase sinusoidal voltage signal and the second phase sinusoidal voltage signal are orthogonal signals; performing differential calculation on the first phase sampling current to obtain a first differential current, and performing differential calculation on the second phase sampling current to obtain a second differential current; calculating a rotor position error signal based on the current sampling moment, the first differential current and the second differential current; and the rotor position estimation value of the motor observer is adjusted based on the rotor position error signal, and operation control is performed on the motor based on the adjusted rotor position estimation value, so that the motor control performance is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of control, and particularly relates to a motor parameter control method and device, electronic equipment and a storage medium. BACKGROUND

[0002] Permanent magnet synchronous motor (PMSM) has been widely used in electric vehicles, industrial robots and high-end CNC machine tools due to its high efficiency and high power density. The premise of accurate control of the permanent magnet synchronous motor is to obtain the position information of the rotor in real time. The traditional control scheme realizes real-time acquisition of the position information of the rotor by installing a physical position sensor (such as an encoder or a rotary transformer), but this increases the cost, volume and fault points of the system. Therefore, sensorless control technology has become a research hotspot. In related technologies, a high-frequency injection method is usually used, that is, a high-frequency sinusoidal voltage signal is injected into the stationary coordinate system of the motor, and the rotor position is estimated by analyzing the corresponding high-frequency current containing the rotor position information, so as to realize accurate position estimation of the rotor at low speed and zero speed.

[0003] When the high-frequency injection method is used, in order to separate the weak high-frequency response current from the large-amplitude fundamental operation current, a high-pass or band-pass filter needs to be used to process the sampled current to filter out the fundamental component and extract the effective signal used for position calculation. However, the filter itself will introduce phase delay and amplitude attenuation, which directly reduces the dynamic response speed and accuracy of the rotor position estimation, especially when the load or speed of the motor changes suddenly, the delay effect will cause the control performance to deteriorate, thereby causing the motor control performance to be low. SUMMARY

[0004] The motor parameter control method and device, electronic equipment and storage medium provided by the embodiments of the present application can improve the motor control performance.

[0005] To achieve the above object, a first aspect of the embodiments of the present application provides a motor parameter control method, which comprises the following steps:

[0006] When the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, the first-phase sampling current and the second-phase sampling current of the motor at a current sampling moment are obtained based on a preset sampling period, the preset sampling period is obtained based on a signal period of the motor, and the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal are mutually orthogonal signals;

[0007] The first-phase sampling current is subjected to differential calculation to obtain a first differential current, and the second-phase sampling current is subjected to differential calculation to obtain a second differential current;

[0008] a rotor position error signal is calculated based on the current sampling time, the first differential current and the second differential current;

[0009] a rotor position estimation value of a motor observer is adjusted based on the rotor position error signal, and the motor is controlled based on the adjusted rotor position estimation value.

[0010] In some embodiments, the step of generating the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal comprises:

[0011] a time angle is obtained based on a product of twice the value of pi and a time parameter, and then divided by the signal period;

[0012] a first-phase difference angle is obtained based on a ratio of the value of pi and a first value, and a second-phase difference angle is obtained based on a ratio of the value of pi and a second value;

[0013] a first-phase angle is obtained based on a difference between the time angle and the first-phase difference angle, and the first-phase sinusoidal voltage signal is obtained based on a product of a sine value of the first-phase angle and a signal amplitude;

[0014] a second-phase angle is obtained based on a difference between the time angle and the second-phase difference angle, and the second-phase sinusoidal voltage signal is obtained based on a product of a sine value of the second-phase angle and a signal amplitude.

[0015] In some embodiments, the step of calculating the first differential current based on the first-phase sampling current comprises:

[0016] a first previous sampling current and a second previous sampling current corresponding to two sampling times adjacent to the current sampling time are obtained;

[0017] a first previous differential current is obtained based on a difference between the first-phase sampling current and twice the first previous sampling current;

[0018] the first differential current is obtained based on an accumulated value of the first previous differential current and the second previous sampling current.

[0019] In some embodiments, the step of calculating the rotor position error signal based on the current sampling time, the first differential current and the second differential current comprises:

[0020] the current sampling time is substituted into a sign selection function to obtain a corresponding first sign and a second sign;

[0021] obtaining an error denominator based on the preset sampling period, obtaining a first position signal and a second position signal based on the first differential current, the second differential current, the first sign, the second sign, and the error denominator;

[0022] obtaining the rotor position error signal based on the first position signal and the second position signal.

[0023] In some embodiments, the obtaining the error denominator based on the preset sampling period comprises:

[0024] obtaining a first error denominator based on a difference between a square of an average inductance and a square of a half differential inductance;

[0025] obtaining a second error denominator based on a product of the preset sampling period, a signal amplitude, and the half differential inductance;

[0026] obtaining the error denominator based on a ratio of the second error denominator and the first error denominator.

[0027] In some embodiments, the obtaining the first position signal and the second position signal based on the first differential current, the second differential current, the first sign, the second sign, and the error denominator comprises:

[0028] obtaining a previous first differential current and a previous second differential current at a previous sampling time;

[0029] obtaining a first error current based on the first sign raised to a third power multiplied by the previous second differential current;

[0030] obtaining the first position signal based on a difference between the first differential current and the first error current divided by the error denominator;

[0031] obtaining a second error current based on the second sign raised to the third power multiplied by the previous first differential current;

[0032] obtaining the second position signal based on a difference between the second differential current and the second error current divided by the error denominator.

[0033] In some embodiments, the adjusting the rotor position estimation value of the motor observer based on the rotor position error signal comprises:

[0034] obtaining a current rotor position estimation value of the motor observer, and determining a corresponding reference signal based on the rotor position estimation value;

[0035] performing a heterodyne operation based on the rotor position error signal and the reference signal to obtain an error signal.

[0036] adjust the rotor position estimation value of the motor observer based on the error signal.

[0037] To achieve the above object, a second aspect of the embodiment of the present application provides a motor parameter control device, which comprises:

[0038] a current sampling module, configured to, when a motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, acquire a first-phase sampling current and a second-phase sampling current of the motor at a current sampling moment based on a preset sampling period, the preset sampling period being obtained based on a signal period of the motor, the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal being mutually orthogonal signals;

[0039] a difference calculation module, configured to perform difference calculation on the first-phase sampling current to obtain a first difference current, and perform difference calculation on the second-phase sampling current to obtain a second difference current;

[0040] an error signal calculation module, configured to calculate a rotor position error signal based on the current sampling moment, the first difference current and the second difference current;

[0041] an adjustment control module, configured to adjust a rotor position estimation value of a motor observer based on the rotor position error signal, and perform operation control on the motor based on the adjusted rotor position estimation value.

[0042] To achieve the above object, a third aspect of the embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the motor parameter control method of the first aspect when executing the computer program.

[0043] To achieve the above object, a fourth aspect of the embodiment of the present application provides a storage medium, which is a computer readable storage medium, the storage medium stores a computer program, and the computer program is executed by a processor to implement the motor parameter control method of the first aspect.

[0044] The motor parameter control method, device, electronic device, and storage medium proposed in this application include the following steps: First, when the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, the first-phase sampling current and the second-phase sampling current of the motor at the current sampling time are acquired based on a preset sampling period. The preset sampling period is based on the signal period of the motor, and the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal are orthogonal signals. Then, the first-phase sampling current is differentially calculated to obtain a first differential current, and the second-phase sampling current is differentially calculated to obtain a second differential current. Next, a rotor position error signal is calculated based on the current sampling time, the first differential current, and the second differential current. Finally, the rotor position estimate of the motor observer is adjusted based on the rotor position error signal, and the motor is operated and controlled based on the adjusted rotor position estimate. This application embodiment directly extracts rotor position information by injecting orthogonal sinusoidal signals with a specific period and combining it with differential operations on the current response. This eliminates the reliance on high-pass or band-pass filters found in traditional high-frequency injection methods. Through differential calculation, the influence of the large-amplitude motor fundamental current component can be directly eliminated, thereby avoiding the inherent phase delay and amplitude attenuation problems of filters. This makes rotor position estimation more timely and accurate, significantly improving the dynamic response performance and robustness of the motor control system under conditions such as load changes and dynamic start-stop, thus improving motor control performance. Secondly, since there is no need to compensate for filter insertion loss, the use of a lower-amplitude high-frequency injection signal effectively reduces the resulting additional power loss, electromagnetic noise, and torque ripple, improving the overall operating efficiency and quietness of the motor. Finally, the use of simple algebraic differential operations to replace complex filter design and implementation greatly simplifies the structure of the control algorithm, reduces the requirements for processor computing resources and the complexity of software development, thereby improving system reliability and reducing hardware costs.

[0045] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the structure of an electric motor provided in one embodiment of this application.

[0047] Figure 2 This is a flowchart of a motor parameter control method provided in another embodiment of this application.

[0048] Figure 3 This is a flowchart illustrating the generation of a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, provided in another embodiment of this application.

[0049] Figure 4 This is a schematic diagram of a sampling current provided in another embodiment of this application.

[0050] Figure 5 yes Figure 2 The flowchart for step 202.

[0051] Figure 6 This is a schematic diagram of the sampling values ​​and differential values ​​of a high-frequency voltage signal at various sampling times, provided in another embodiment of this application.

[0052] Figure 7 yes Figure 2 The flowchart for step 203.

[0053] Figure 8 This is a schematic diagram illustrating the calculation of an orthogonal signal according to another embodiment of this application.

[0054] Figure 9 yes Figure 7 The flowchart for step 702.

[0055] Figure 10 yes Figure 7 Another flowchart for step 702.

[0056] Figure 11 yes Figure 2 The flowchart for step 204.

[0057] Figure 12 This is a simulation diagram of the first motor parameter control method provided in another embodiment of this application.

[0058] Figure 13 This is a simulation diagram of a second motor parameter control method provided in another embodiment of this application.

[0059] Figure 14 This is a simulation diagram of a third motor parameter control method provided in another embodiment of this application.

[0060] Figure 15 This is a simulation diagram of the fourth motor parameter control method provided in another embodiment of this application.

[0061] Figure 16 This is a simulation diagram of the fifth motor parameter control method provided in another embodiment of this application.

[0062] Figure 17 This is a simulation diagram of the sixth motor parameter control method provided in another embodiment of this application.

[0063] Figure 18This is a schematic diagram of the structure of a motor parameter control device provided in another embodiment of this application.

[0064] Figure 19 This is a schematic diagram of the hardware structure of an electronic device provided in another embodiment of this application. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0066] It should be noted that although functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0068] Permanent magnet synchronous motors (PMSMs) are widely used in electric vehicles, industrial robots, and high-end CNC machine tools due to their high efficiency and high power density. Precise control of PMSMs requires real-time acquisition of the rotor's position information. Traditional control schemes achieve this by installing physical position sensors (such as encoders or resolvers), but this increases system cost, size, and potential failure points. Therefore, sensorless control technology has become a research hotspot. Commonly used techniques include high-frequency injection, injecting a high-frequency sinusoidal voltage signal into the motor's stationary coordinate system. By analyzing the corresponding high-frequency current containing rotor position information, the rotor position is estimated, enabling precise rotor position estimation at low and zero speeds.

[0069] When using the high-frequency injection method, to separate the weak high-frequency response current from the large-amplitude fundamental operating current, a high-pass or band-pass filter is needed to process the sampled current, filtering out the fundamental component and extracting the effective signal for position calculation. However, the filter itself introduces phase delay and amplitude attenuation, which directly reduces the dynamic response speed and accuracy of rotor position estimation. Especially when the motor load or speed changes abruptly, the delay effect can lead to deterioration of control performance. Secondly, the insertion loss of the filter needs to be compensated by increasing the amplitude of the injected high-frequency voltage, which not only increases the motor's power loss and electromagnetic noise but may also cause unnecessary torque ripples, affecting the smoothness of motor operation. In addition, designing and debugging complex digital filters increases the computational burden of the control algorithm and the complexity of system development. Therefore, existing technologies urgently need to address the problems of poor system dynamic performance, low energy efficiency, and high control system complexity caused by reliance on filters in sensorless control.

[0070] To improve motor control performance, this application employs a specific period of orthogonal sinusoidal signal injection combined with differential operations on the current response to directly extract rotor position information. This eliminates the reliance on high-pass or band-pass filters found in traditional high-frequency injection methods. Through differential calculation, the influence of the large-amplitude motor fundamental current component can be directly eliminated, thus avoiding the inherent phase delay and amplitude attenuation problems of filters. This makes rotor position estimation more timely and accurate, significantly improving the dynamic response performance and robustness of the motor control system under conditions such as load changes and dynamic start-stop, thereby enhancing motor control performance. Secondly, since there is no need to compensate for filter insertion loss, the use of a smaller amplitude high-frequency injection signal effectively reduces the resulting additional power loss, electromagnetic noise, and torque ripple, improving the overall operating efficiency and quietness of the motor. Finally, the use of simple algebraic differential operations replaces the complex filter design and implementation, greatly simplifying the structure of the control algorithm, reducing the requirements for processor computing resources and the complexity of software development, thereby improving system reliability and reducing hardware costs.

[0071] To better illustrate the motor control method provided in this application, this embodiment first describes the motor structure in which the motor control method is applied. (Refer to...) Figure 1 The diagram shown is a structural schematic of a motor provided in an embodiment of this application. Figure 1 The diagram shown is a block diagram of a sensorless control system for a permanent magnet synchronous motor (PMSM) based on high-frequency signal injection, provided in an embodiment of this application. This system replaces traditional filters through signal processing methods. Figure 1 As shown, the entire system is built on a dual-closed-loop vector control framework, and its workflow begins with receiving the external velocity reference command ω. refThe command is linked to the velocity estimated from the position observer. The comparison is performed, and the q-axis current command is generated after passing through the speed loop PI regulator. and d-axis current command These commands, operating in the dq rotating coordinate system, are used together as inputs to the current loop. After PI regulation and decoupling operations, these commands generate the fundamental voltage command. and Then, through the inverse Park transformation, it is converted into voltage in the α-β stationary coordinate system. and The core innovation of the system lies in the fact that a specific high-frequency voltage signal generated by a "high-frequency signal injection" module will interact with the aforementioned fundamental voltage. and The voltage signals are superimposed and synthesized, then used by the SVPWM module to drive the inverter and control the motor. Simultaneously, the system acquires the three-phase motor currents and performs Clarke transformation to obtain the α-β axis currents i. α and i β The key is that these two current signals are directly fed into a "differential operation" module. This module cleverly eliminates the fundamental component and extracts the high-frequency response carrying rotor position information by performing differential calculations on the current, thereby outputting a signal equal to sin2θ. e and cos2θ e These signals are proportional. After normalization, they are sent to the "position observation" module, which ultimately calculates a high-precision estimate of the rotor position. and speed estimates These estimates are then fed back to the velocity loop and coordinate transformation module, forming a highly efficient closed-loop control system with excellent dynamic performance that requires no physical sensors or digital filters.

[0072] Based on the aforementioned permanent magnet synchronous motor, the motor parameter control method in the embodiments of this application will be described in detail below. (Refer to...) Figure 2 This is an optional flowchart of the motor parameter control method provided in the embodiments of this application. Figure 2 The method may include, but is not limited to, steps 201 to 204. It is also understood that this embodiment... Figure 2 The order of steps 201 to 204 is not specifically limited; the order of steps can be adjusted or certain steps can be added or removed according to actual needs. The motor parameter control method provided in this embodiment can be applied to the motor, or to smart terminals, servers, computers, etc., connected to the motor.

[0073] Step 201: When the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, the first-phase sampling current and the second-phase sampling current of the motor at the current sampling time are obtained based on a preset sampling period. The preset sampling period is obtained based on the signal period of the motor.

[0074] Step 201 will be described in detail below.

[0075] The core concept of this application is a sensorless control strategy based on sinusoidal signal injection into a stationary shaft. High-frequency signals are directly extracted through differential operations, replacing traditional filters to simplify the control structure and reduce losses. The sinusoidal signal injection optimizes harmonic components and improves the motor's operating environment.

[0076] Therefore, specific electromagnetic response conditions need to be created first for subsequent position information extraction. Specifically, the controller continuously injects a first-phase sinusoidal voltage signal uα, which is an orthogonal signal, into the stator windings of the motor in a two-phase stationary coordinate system. in With the second phase sinusoidal voltage signal uβ in The two injected first-phase sinusoidal voltage signals and the second-phase sinusoidal voltage signal have a constant, predetermined phase difference in time (typically 90 degrees or π / 2 radians). This orthogonality aims to enable the motor to produce distinguishable and easily decoupled responses in different electric shaft directions. The generation of the first-phase sinusoidal voltage signal uα is further described below. in Second phase sinusoidal voltage signal uβ in .

[0077] Reference Figure 3 The steps for generating the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal include steps 301 to 304.

[0078] Step 301: Based on the product of twice pi and the time parameter, and then divided by the signal period, the time angle is obtained.

[0079] Step 302: Based on the ratio of pi to the first value, obtain the first phase difference angle, and based on the ratio of pi to the second value, obtain the second phase difference angle.

[0080] Step 303: Based on the difference between the time angle and the first phase angle, obtain the first phase angle, and based on the product of the sine value of the first phase angle and the signal amplitude, obtain the first phase sinusoidal voltage signal.

[0081] Step 304: Based on the difference between the time angle and the second phase angle, obtain the second phase angle, and based on the product of the sine value of the second phase angle and the signal amplitude, obtain the second phase sinusoidal voltage signal.

[0082] Steps 301 to 304 are described in detail below.

[0083] In some embodiments, in order to generate a suitable first-phase sinusoidal voltage signal uα in Second phase sinusoidal voltage signal uβ in First, a time reference needs to be established for generating the periodic sinusoidal signal. This is done by multiplying a fixed constant, twice the mathematical constant pi (2π), by a continuously varying time parameter t. The product is then divided by a preset signal period, T, to generate an angle variable that grows linearly with time, namely the time angle 2πt / T. The signal period T is the time required for the sinusoidal waveform to repeat once. Therefore, this time angle physically corresponds to the product ωt of the angular frequency and time in the standard sine function sin(ωt), providing the fundamental phase information for subsequently generating a sinusoidal voltage signal with a specific frequency.

[0084] Next, the required fixed phase difference between the two sinusoidal voltage signals needs to be determined. This is done by proportionaling pi (π) to a first value (e.g., 4) and a second value (e.g., 4 / 3), to calculate the first phase difference angle π / 4 and the second phase difference angle 3π / 4. These first and second values ​​(e.g., 4 and 4 / 3) are pre-defined constants that precisely define the offset of each sinusoidal signal relative to the fundamental time phase. The "first phase difference angle" and "second phase difference angle" set in this way together ensure that the two ultimately generated voltage signals can form a specific phase difference (e.g., π / 2) necessary to achieve orthogonality.

[0085] Next, the time angle and the first phase difference angle are subtracted to obtain a phase-modulated first phase angle. Then, based on the sine value of this first phase angle, a preset signal amplitude U is calculated. in Multiplying them together yields the desired first-phase sinusoidal voltage signal uα to be injected. in As shown in formula (1) below.

[0086]

[0087] Among them, the signal amplitude U in =10V is the injected amplitude, and T=0.8ms is the signal period. The entire process actually implements the mathematical expression. The calculations generate a periodic voltage waveform with a specific frequency, amplitude, and initial phase.

[0088] Similarly, the time angle and the second phase difference angle are subtracted to obtain a phase-modulated second phase angle. Then, based on the sine value of this second phase angle, a preset signal amplitude U is calculated. in Multiplying them together yields the desired second-phase sinusoidal voltage signal uβ. inAs shown in formula (2) below.

[0089]

[0090] By independently setting the "second phase difference angle," a preset, fixed phase difference is ensured between the "second-phase sinusoidal voltage signal" and the "first-phase sinusoidal voltage signal," thus achieving the technical requirement that the two signals are orthogonal and completing the mathematical expression. The calculation.

[0091] Through steps 301 to 304 above, by decoupling and independently setting the frequency (determined by the "signal period"), phase (determined by the "first value" and "second value"), and amplitude (determined by the "signal amplitude") of the signal, it is possible to accurately construct the "first phase sinusoidal voltage signal" and "second phase sinusoidal voltage signal" that meet specific technical requirements (i.e., orthogonality). This is a necessary prerequisite for subsequent high-precision rotor position estimation using differential operations. It ensures that the excitation signal injected into the motor has stable and known characteristics, providing a solid foundation for the effectiveness and reliability of the entire sensorless control scheme.

[0092] At the same time, the control system will synchronously acquire the "first phase sampling current" and "second phase sampling current" fed back by the motor according to a preset sampling period. This "preset sampling period" is not arbitrarily set, but is strictly related to the "signal period" of the injected voltage signal (that is, one-quarter of the signal period, i.e., Ts = T / 4 = 0.2ms). This synchronous sampling mechanism is the basis for ensuring that the subsequent differential operation can effectively extract the target signal.

[0093] Reference Figure 4 This is a schematic diagram of a sampling current provided in an embodiment of this application. Figure 4 As shown in the figure, this application collects the current value i at times t = (n-1)T+3Ts, nT, nT+Ts, and nT+2Ts. αk i βk Four samples are taken within each signal period T (k = 0 to 3), covering the complete phase period (0 to 2π) of the high-frequency signal. Continuous sampling across periods is achieved by using k = 4n + i (i = 0, 1, 2, 3).

[0094] The following is a description of its working principle.

[0095] Since the mathematical model of the built-in three-phase PMSM in the two-phase rotating coordinate system can be expressed as shown in the following formula (3).

[0096]

[0097] Then, transforming formula (3) to a two-phase stationary coordinate system, we can obtain the forms shown in formulas (4) to (6).

[0098]

[0099] Among them, L d L q L represents the d-axis and q-axis inductances in the motor system. σ =(L d +L q ) / 2 is the average inductance, L Δ =(L d -L q ) / 2 is the half-differential inductance, u α u β Let i be the α-axis and β-axis voltage components in a two-phase stationary system. α i β Let θ be the α-axis and β-axis current components in a two-phase stationary system. e ψ is the rotor position electrical angle, R is the stator three-phase winding phase resistance, and ψ is the rotor position electrical angle. f It is a permanent magnet flux linkage.

[0100] Because the high-frequency injected signal is much higher than the motor's fundamental frequency, and the selected sampling time should be shorter than the period of the high-frequency injected signal, the sampling time will be much shorter than the motor's mechanical and electrical time constants when the motor is operating at medium to low speeds. Therefore, within the sampling time range, the motor's fundamental frequency current, voltage, and rotor position electrical angle θ will be within the range. e It can be regarded as a constant. And formula (4) can be rewritten in difference form. By rearranging the terms of formula (4) and rewriting the differential form of the current in difference form using the forward Euler method, we can obtain the following formulas (7) to (8).

[0101]

[0102] Among them, i α k、i βk i αk-1 i βk-1 —kT respectively s Time, (k-1)T s Current sampling values ​​along the α and β axes at time points; u α k、u βk u αk-1 u βk-1 —kT respectively s Time, (k-1)T s Current sampling values ​​along the α and β axes at time points.

[0103] To simplify the writing, the definitions shown in formulas (10) to (12) are as follows.

[0104]

[0105] Substituting equations (10), (11), and (12) into equation (8), and since when θ e When ψ is considered as a constant, f d / dt[cosθ e sinθ e The derivative of ] is 0. Substituting it into equation (8), we can obtain the following formula (13).

[0106]

[0107] Because the sampling time is short, the base frequency voltage and current can be regarded as constants within the sampling time range. When performing differential operation, the difference of the base frequency signal is 0. Therefore, equation (13) can be modified into the form shown in equation (14) below.

[0108]

[0109] u αin i αin These are the high-frequency injection voltage and the high-frequency injection response current (i.e., the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal), respectively. Since the resistance is much smaller than the inductance at high frequencies, it can be ignored. In this case, equation (14) can be simplified to the following formula (15).

[0110]

[0111] As can be seen from equation (15), in the inverse matrix A -1 Since it contains rotor electrical angle information, by selecting a suitable high-frequency voltage signal for injection, the orthogonal information of the motor rotor position can be obtained by performing simple calculations on the signal.

[0112] In the inverse matrix A -1 Although it contains rotor electrical angle information, the choice and sampling of the injected signal affect the ease of calculating the electrical angle information. Therefore, a signal that can obtain the orthogonal information of the rotor position through simple calculations is the most ideal choice.

[0113] It can be seen from equation (15) that Δ 2 i αk Δ 2 i βk and Δu αink-1 , Δu βink-1 Since they are coupled together, to simplify the calculation, we consider choosing a sinusoidal signal with a phase difference, such that during sampling, Δu αink-1 , Δu βink-1 In each difference operation result, there is exactly one item that is zero.

[0114] Based on this, this application proposes a first-phase sinusoidal voltage signal uα as shown in formulas (1) and (2). in With the second phase sinusoidal voltage signal uβ in Signal injection. In this type of signal injection, the sampling time interval is chosen to be T. s =T / 4. This allows the sampled current signal to be decoupled from the orthogonal signal through simple calculations.

[0115] Step 202: Perform differential calculation on the first phase sampling current to obtain the first differential current, and perform differential calculation on the second phase sampling current to obtain the second differential current.

[0116] Step 202 will be described in detail below.

[0117] In some embodiments, the first phase sampling current i is obtained at multiple consecutive sampling times. αk Second phase sampling current i βk Then, the sampling current i of the first phase was respectively... αk Second phase sampling current i βk Perform differential calculations to obtain the corresponding first differential current Δ. 2 i αk Second differential current Δ 2 i βk This differential calculation is a digital signal processing technique that uses current and historical sampled values ​​to perform algebraic operations (e.g., calculating i(k) - 2*i(k-1) + i(k-2)), thus cleverly replacing traditional bandpass or high-pass filters. The main technical objective of this calculation is to effectively suppress or eliminate the low-frequency fundamental component in the current signal, which is generated by the normal operation of the motor and has an amplitude much larger than the high-frequency response. This highlights the weak high-frequency response current carrying rotor position information, which is submerged in strong background noise, providing a high signal-to-noise ratio input signal for subsequent accurate calculations. The following section will further describe how to perform differential calculations on the sampled current.

[0118] Reference Figure 5 The first phase sampling current is differentially calculated to obtain the first differential current, including the following steps 501 to 503.

[0119] Step 501: Obtain the first preceding sampling current and the second preceding sampling current corresponding to the two sampling times adjacent to the current sampling time.

[0120] Step 502: Based on the difference between the first phase sampling current and the first preceding sampling current, which is twice the value, the first preceding differential current is obtained.

[0121] Step 503: Based on the sum of the first preceding differential current and the second preceding sampling current, obtain the first differential current.

[0122] Steps 501 to 503 are described in detail below.

[0123] In some embodiments, the first phase sampling current i αk For example, we first retrospectively obtain the current measurement values ​​corresponding to two temporally adjacent sampling times (i.e., k-1 and k-2) before the current sampling time k, i.e., the first preceding sampling current i. αk-1 Second preceding sampling current i αk-2 The first preceding sampling current refers to the current value at the sampling time immediately preceding the current sampling time, while the second preceding sampling current refers to the current value at the sampling time before that.

[0124] Next, based on the first phase sampling current i αk With twice the value of the first preceding sampling current 2i αk-1 Perform a subtraction operation to obtain the first preceding differential current i. αk -2i αk-1 By subtracting the current value from the most recent historical value using weighted averages, the trend of signal change is initially captured, which is a key step in forming the final difference result.

[0125] Then, the first preceding differential current i αk -2i αk-1 With the acquired second preceding sampled current i αk-2 Perform the cumulative value operation, that is, perform an addition operation to obtain the first differential current as shown in the following formula (16).

[0126] Δ 2 i αk =i αk -2i αk-1 +i αk-2 (16)

[0127] By combining the preceding differential results with earlier historical data, this step fully realizes the calculation logic of the second-order central differential. Its output, the "first differential current," is a signal that has been effectively processed, with the low-frequency fundamental component basically eliminated while retaining the high-frequency response component. It can be directly used for subsequent location information calculation.

[0128] Similarly, the second differential current Δ 2 i βk As shown in formula (17) below.

[0129] Δ 2 i βk =i βk-2i βk-1 +i βk-2 (17)

[0130] Through steps 501 to 503 above, an operation mathematically equivalent to a second-order high-pass filter is decomposed into three clear and independent arithmetic steps: data acquisition, weighted subtraction, and accumulation. This not only effectively suppresses the interference of the motor's fundamental current and accurately extracts the high-frequency signal used for position estimation, but also requires only simple addition, subtraction, and multiplication operations, resulting in minimal computational load and greatly reducing the requirements on the controller's processing power. Thus, it provides a computationally lightweight and highly efficient and reliable signal preprocessing method for sensorless control systems.

[0131] Reference Figure 6 This is a schematic diagram illustrating the sampled values ​​and differential values ​​of a high-frequency voltage signal at various sampling times, provided in an embodiment of this application. Figure 6 The figure shows the high-frequency injected voltage signal values ​​along the α and β axes at each sampling time, as well as the difference values. From the differential operation of the high-frequency injected voltage signal, it can be seen that when the sampling time k is even, Δu αin When = 0, When the sampling time k is odd, Δu βin When = 0, It can satisfy the condition that orthogonal signals are relatively easy to solve. In one example, when k = 4n + i (i = 0, 1, 2, 3), it should actually be: t = nT + iTs, such as n = 0, i = 0 → t = 0ms, n = 0, i = 1 → t = 0.2ms, n = 1, i = 0 → t = 0.8ms.

[0132] Step 203: Calculate the rotor position error signal based on the current sampling time, the first differential current, and the second differential current.

[0133] Step 203 will be described in detail below.

[0134] In some embodiments, after obtaining the first differential current Δ 2 i αk Second differential current Δ 2 i βk Then, the data processed in the previous steps is used to calculate the key signal characterizing the rotor position, namely, based on the current sampling time k and the calculated first differential current Δ. 2 i αk and "second differential current Δ 2 i βk The rotor position error signal (including the first position signal COS2θ) is calculated through specific algebraic operations. e Second position signal sin2θ eThe current sampling time information (e.g., the parity of the sampling point) serves as a crucial input parameter, used to select the correct decoupling logic, thereby separating the orthogonal position information coupled in the differential current. The rotor position error signal here is typically not a direct rotor angle value, but rather a set of orthogonal signals proportional to the sine and cosine functions of the rotor position electrical angle (e.g., sin(2θe) and cos(2θe)). It accurately reflects the deviation between the current rotor position estimate and the true value. The method for obtaining the rotor position error signal will be further described below.

[0135] Reference Figure 7 Based on the current sampling time, the first differential current and the second differential current, the rotor position error signal is calculated, including the following steps 701 to 703.

[0136] Step 701: Substitute the current sampling time into the symbol selection function to obtain the corresponding first symbol and second symbol.

[0137] Step 702: Obtain the error denominator term based on the preset sampling period, and obtain the first position signal and the second position signal based on the first differential current, the second differential current, the first symbol, the second symbol, and the error denominator term.

[0138] Steps 701 to 703 are described in detail below.

[0139] In some embodiments, the specific symbol required for subsequent decoupling operations is first determined based on the time point corresponding to the current sampling time k. Specifically, the current sampling time k is taken as input and substituted into a predefined symbol selection function (r,s), as shown in the following formula (18).

[0140]

[0141] The "symbol selection function" is a logical or mathematical rule that outputs a pair of preset symbol values, namely the first symbol r and the second symbol s, based on the input time information. This step is a crucial preparatory step for achieving orthogonal signal decoupling. By dynamically selecting symbols, the system can use different combinations of operations at different times to separate coupled position information.

[0142] The following is a description of the principle.

[0143] Δu αin When = 0, Substituting into equation (15), we get the following formula (19).

[0144]

[0145] Similarly, Δuβin When = 0, Substituting into equation (15), we get the following formula (20).

[0146]

[0147] When using forward Euler operations, Δi α(β)k The result of the calculation is related to the high-frequency injection voltage value at time k-1. Therefore, by substituting the high-frequency injection voltage values ​​at sampling times k-2 and k-1 into equations (19) and (20) respectively, we can obtain Δ 2 i α(β)k-1 and Δ 2 i α(β)k In other words, during continuous sampling, two sets of equations (19) and (20) can be obtained in sequence. By simply calculating the two sets of equations, the orthogonal signals can be obtained.

[0148] Reference Figure 8 This is a schematic diagram illustrating the solution of orthogonal signals provided in an embodiment of this application. For example... Figure 8 The diagram illustrates how orthogonal signals are solved during continuous sampling.

[0149] Therefore, for ease of generalization, the sign selection function (r, s) is defined as shown in the above formula (18).

[0150] Based on this, the calculation rules for orthogonal signals are described below.

[0151] When the sampling time k is even, the following formula (21) applies.

[0152]

[0153] When the sampling time k is odd, the following formula (22) applies.

[0154]

[0155] Among them, China

[0156] Therefore, it can be seen from equations (21) and (22) that by properly configuring the symbol selection function, the orthogonal signal of the rotor position electrical angle can be obtained through simple calculation.

[0157] After normalizing the orthogonal signals, the observation position and rotational speed can be obtained using the heterodyne method and a rotor position tracking observer.

[0158] Based on the above principle description, after obtaining the first symbol r and the second symbol s corresponding to the current sampling time using the symbol selection function (r, s) as shown in formula (18), based on the preset sampling period Ts In addition to the inherent inductance parameters of the motor, an error denominator term M is calculated. This term serves as a normalization factor to eliminate the scaling effect related to the system parameters in the calculation results, as described below.

[0159] Reference Figure 9 The error denominator is obtained based on a preset sampling period, including the following steps 901 to 903.

[0160] Step 901: Based on the difference between the square of the average inductance and the square of the half-differential inductance, obtain the first error denominator term.

[0161] Step 902: Based on the product of the preset sampling period, signal amplitude, and half-differential inductance, obtain the second error denominator term.

[0162] Step 903: Obtain the error denominator term based on the ratio of the second error denominator term to the first error denominator term.

[0163] Steps 901 to 903 are described in detail below.

[0164] In some embodiments, in order to calculate the appropriate error denominator M, the calculation is first based on the two core inductance parameters of the motor—average inductance L. σ (Usually refers to the average value of the d-axis and q-axis inductances, characterizing the overall inductance level of the motor) and half-differential inductance L Δ (Usually referring to half the difference between the d-axis and q-axis inductances, characterizing the salient polarity or non-uniform reluctance of the motor) – this is used for calculation. The square of the average inductance L... 2 σ With the square of the half-differential inductance L 2 Δ Subtract the two terms to obtain the first error denominator term L. 2 σ -L 2 Δ In a physical sense, it reflects the combined effect of the nonlinearity and anisotropy of the motor's magnetic circuit, and is the basis for eliminating the influence of the motor's own parameters when performing subsequent signal normalization processing.

[0165] Next, the preset sampling period T will be... s The signal amplitude U of the injected voltage in And the motor's half-differential inductance L Δ These three quantities are multiplied together to obtain the second error denominator. The preset sampling period and signal amplitude here are parameters set by the control system, while the half-differential inductance is an inherent property of the motor. Therefore, the second error denominator term integrates the influence of external excitation intensity, system sampling speed, and motor salient polarity on the high-frequency response current amplitude, constituting another core factor in the normalization process.

[0166] Finally, the second error denominator term With the first error denominator term L 2 σ -L 2 Δ Perform a division operation, that is, calculate the "ratio" of the two quantities, to obtain the error denominator M as shown in the following formula (23).

[0167]

[0168] Through steps 901 to 903 above, by explicitly combining the inherent parameters of the motor, such as the average inductance and half-differential inductance, with external setting parameters such as the preset sampling period and signal amplitude, all key factors affecting the amplitude of the high-frequency response current are precisely quantified. This enables the subsequent position signal calculation process to effectively eliminate the interference of these factors, ensuring the consistency and accuracy of the calculation results. This greatly improves the robustness of the entire sensorless control algorithm and its universality to different motors and operating conditions.

[0169] Subsequently, the system comprehensively utilizes the first differential current Δ 2 i αk Second differential current Δ 2 i βk The first symbol r, the second symbol s, and the calculated error denominator M are used to perform a series of pre-defined algebraic operations to finally obtain the first position signal COS2θ. e Second position signal sin2θ e The operational logic here typically involves the cross-combination of the current differential current and the differential current at the previous moment, and weights them by sign, thereby cleverly separating the orthogonal components coupled in the two differential current quantities. The resulting "first position signal" and "second position signal" correspond to the sine and cosine components of a certain multiple of the rotor position electrical angle, respectively, as described below.

[0170] Reference Figure 10 Based on the first differential current, the second differential current, the first symbol, the second symbol, and the error denominator, the first position signal and the second position signal are obtained, including the following steps 1001 to 1005.

[0171] Step 1001: Obtain the first differential current and the second differential current before the preceding sampling time.

[0172] Step 1002: Based on the first sign power of the third value, multiply it by the previous second differential current to obtain the first error current.

[0173] Step 1003: Based on the difference between the first differential current and the first error current, divide by the error denominator to obtain the first position signal.

[0174] Step 1004: Based on the second sign power of the third value, multiply it by the first differential current in the previous order to obtain the second error current.

[0175] Step 1005: Based on the difference between the second differential current and the second error current, divide by the error denominator to obtain the second position signal.

[0176] Steps 1001 to 1005 are described in detail below.

[0177] In some embodiments, in order to calculate a suitable first position signal sin2θ e Second position signal COS2θ e First, it is necessary to retrieve from storage the differential current value calculated at the previous sampling time k-1 before the current sampling time k, i.e., the first differential current Δ of the previous sampling time. 2 i αk-1 and the preceding second differential current Δ 2 i βk-1 These data are not the original sampled currents, but rather the results after differential processing.

[0178] Next, a preset third value (i.e., -1) is raised to the power of the first symbol r, i.e., (-1). r The first sign here is either +1 or -1, previously determined by the sign selection function. Therefore, the result of this power operation dynamically determines whether the sign is positive or negative based on the parity of the current sampling time. Subsequently, this signed result (-1) is... r Multiply by the second differential current Δ in the previous sequence 2 i βk-1 To obtain the first error current (-1) r Δ 2 i β-1 The first error current combines the second-phase differential information from the previous moment with the symbol logic of the current moment to form the current first-phase differential current Δ. 2 i αk The key components to be corrected.

[0179] Then, the first differential current Δ at the current moment is... 2 i αk The first error current (-1) obtained is compared with this. r Δ 2 i βk-1The subtraction operation, a crucial step in the decoupling process, effectively eliminates the non-target position component coupled to the first differential current by subtracting a cleverly constructed correction term related to another phase. Finally, this difference is normalized by dividing the result by a pre-calculated error denominator M, yielding the pure first position signal COS2θ. e As shown in formula (24) below.

[0180]

[0181] Similarly, the preset third value (i.e., -1) is raised to the power of the second symbol s, i.e., (-1). s The resulting signed result is then multiplied by the first differential current Δ in the preceding sequence. 2 i αk-1 Thus, the second error current (-1) is obtained. s Δ 2 i αk-1 Corresponding to the construction logic of the first error current, the second error current (-1) s Δ 2 iα k-1 It combines the first-phase differential information from the previous moment with the symbol logic of the current moment to correct the current second-phase differential current Δ. 2 i βk .

[0182] Similarly, the second differential current Δ at the current moment 2 i βk With the second error current (-1) s Δ 2 i αk-1 The subtraction operation eliminates the coupling between the second differential current Δ and the current. 2 i βk The non-target position component is then calculated. Finally, this difference result is normalized by dividing by the error denominator M, and the final result is the second position signal sin2θ, which is orthogonal to the first position signal. e As shown in formula (25) below.

[0183]

[0184] Through steps 1001 to 1005 above, by utilizing the differential current between the current time and the previous time, and combining it with a dynamically changing sign selection logic, the two coupled signal channels are effectively separated without any complex matrix inversion or iterative calculations. By constructing "first error current" and "second error current" as correction terms and performing simple subtraction and division operations, the normalized "first position signal" and "second position signal" can be obtained directly and accurately. This not only greatly reduces the computational burden of the real-time control system, but also ensures the speed and accuracy of position information calculation. It is a key technological innovation for realizing high-performance sensorless control.

[0185] Step 703: Based on the first position signal and the second position signal, obtain the rotor position error signal.

[0186] Step 703 will be described in detail below.

[0187] In step 703 of some embodiments, this step converts the basic position signal calculated in the previous step into a final error signal that can be directly used for observer correction. The system is based on the first position signal COS2θ obtained in the previous step. e and "second position signal sin2θ" e As a rotor position error signal.

[0188] Through steps 701 to 703 above, by introducing a sign selection function and clever cross-combination operations, the orthogonal position information coupled in the differential current is successfully separated and transformed into a clear rotor position error signal. This solution method has clear logic, and the calculation process only involves simple algebraic operations, avoiding the high computational load operations such as complex phase-locked loops or matrix inversion in traditional methods. It not only ensures the accuracy and real-time performance of position estimation, but also greatly simplifies the implementation of the control algorithm, providing key technical support for building a high-performance, low-cost sensorless motor control system.

[0189] Step 204: Adjust the rotor position estimate of the motor observer based on the rotor position error signal, and perform motor operation control based on the adjusted rotor position estimate.

[0190] Step 204 will be described in detail below.

[0191] In some embodiments, after obtaining the rotor position error signal (including the first position signal COS2θ) e Second position signal sin2θ e After that, the rotor position estimate inside the motor observer... Adjustments are needed. The motor observer here is a software algorithm model used to estimate the internal states of the motor (such as position and speed), while the rotor position estimate... It is an estimate of the current actual position of the motor rotor. By continuously correcting this estimate using error signals, it can track the rotor's true position in real time and accurately. Finally, the system uses this dynamically adjusted "rotor position estimate" as position feedback to perform precise vector "run control" of the motor, thereby achieving high-performance motor drive without relying on physical sensors.

[0192] The following section will further describe how to adjust the rotor position estimate of the motor observer based on the rotor position error signal.

[0193] Reference Figure 11 Adjusting the estimated rotor position of the motor based on the rotor position error signal includes the following steps 1101 to 1103.

[0194] Step 1101: Obtain the current rotor position estimate of the motor observer, and determine the corresponding reference signal based on the rotor position estimate.

[0195] Step 1102: Perform heterodyne calculation based on the rotor position error signal and the reference signal to obtain the error signal.

[0196] Step 1103: Adjust the rotor position estimate of the motor observer based on the error signal.

[0197] Steps 1101 to 1103 are described in detail below.

[0198] In some embodiments, the current rotor position estimate is first obtained from the motor observer. Subsequently, the system based on the rotor position estimate To calculate or generate a corresponding set of reference signals, which are the sine and cosine functions of the estimated angle value, i.e. and They are formally matched with the previously calculated rotor position error signal, providing the necessary local reference for subsequent accurate phase comparison.

[0199] Next, based on the rotor position error signal (including the first position signal COS2θ) e Second position signal sin2θ e ) and the reference signal generated in the previous step (i.e. and This process involves performing heterodyne calculations to obtain the error signal (a scalar value). Heterodyne calculation is a signal processing technique, typically implemented using trigonometric functions and difference angle formulas, such as calculating... The result of its calculation When the angular deviation is very small, it is approximately equal to Therefore, this error signal can linearly and with high sensitivity reflect the difference between the actual rotor position and the estimated rotor position.

[0200] Finally, based on the obtained error signal, the internal state of the motor observer (i.e., the Luenberger observer) is corrected, thereby adjusting the rotor position estimate of the motor observer. Specifically, the error signal is used as the input of the observer (such as a phase-locked loop (PLL) or a Luenberger observer), and after processing through a proportional-integral (PI) regulator and other stages, it is used to drive the update of the observer's internal state variables. Through this feedback correction mechanism, the observer can continuously reduce the estimation error, making its output rotor position estimate... It continuously and dynamically converges and accurately tracks the actual rotor position of the motor.

[0201] In one example, assume the complete sampled data includes Δ 2 i αk-1 and Δ 2 i βk-1 For example: Δ 2 i αk-1 =1, Δ 2 i βk-1 =2, then the correct calculation should be sin2θ e = (4-1) / 5 = 0.6, cos2θ e = (3 + 2 / 5) = 1.0, at this time, 2θ e =arctan(1.0 / 0.6) = 30.96, then

[0202] Through steps 1101 to 1103 above, the actual measurement information is efficiently compared with the internal state of the observer through heterodyne operation, generating a linear error signal. Compared with other nonlinear error processing methods, this has better convergence and stability. Subsequently, this high-quality error signal is used to drive the motor observer to make adjustments, forming a robust closed-loop feedback system. This not only ensures the high accuracy and high dynamic response characteristics of the rotor position estimate, but also enables the entire sensorless control system to effectively suppress noise and external disturbances, ultimately achieving smooth and precise operation control of the motor.

[0203] To further verify the reliability of the motor parameter control method provided in this application, the following experimental performance simulation verification was conducted.

[0204] The hardware configuration used in the simulation of this application is as follows: STM32F407 controller, Infineon FS75R12KE3 inverter module, and LEM LA25-NP current sensor.

[0205] The software flow is as follows: initialize DSP registers and configure the PWM waveform generator; acquire current signals in real time, perform differential operations and quadrature demodulation; and iteratively update the rotor position using a Luenberger observer.

[0206] Reference Figure 12 This is a simulation diagram of the first motor parameter control method provided in the embodiments of this application. Figure 12 The figure shows the speed estimation performance of the sensorless control method proposed in this application under stable no-load operation of the motor. In the figure, the horizontal axis t represents time in seconds (s), and the vertical axis represents the deviation between the actual and estimated speed values ​​in revolutions per minute (r / min). As can be seen from the figure, the speed estimation error curve fluctuates between -1.5 r / min and +1.5 r / min throughout the entire observation time range, remaining stable within ±1 r / min for most of the time. This experiment verifies that under no-load operation, the maximum deviation between the estimated and actual speed values ​​is only 1.4 r / min. Figure 12 This intuitively demonstrates that the motor parameter control method provided in this application can achieve high-precision speed tracking with small error fluctuations, indicating the effectiveness and stability of the sensorless control strategy under no-load conditions.

[0207] Reference Figure 13 This is a simulation diagram of the second motor parameter control method provided in the embodiments of this application. Figure 13 The figure shows the position estimation performance of the sensorless control method proposed in this application under stable no-load operation of the motor. The figure consists of three sub-figures, with the horizontal axis representing time t in seconds (s). The top sub-figure (black curve) shows the actual value of the rotor angle, exhibiting a periodic sawtooth wave, indicating continuous motor rotation. The middle sub-figure (red curve) shows the rotor angle estimate obtained by the method of this application; its waveform highly overlaps with the actual value, indicating good tracking capability. The bottom sub-figure (blue curve) is the core verification part of this invention, showing the error between the actual and estimated rotor angle values, with the vertical axis in radians (rad). This error curve is stable within 0.02 rad. Figure 13 The results clearly show that the error fluctuation is extremely small and always close to zero, which strongly proves that the motor parameter control method provided in this application can achieve high-precision rotor position estimation and provide reliable position feedback for precise motor control.

[0208] Reference Figure 14 This is a simulation diagram of the third motor parameter control method provided in the embodiments of this application. Figure 14 The figure shows the speed estimation performance of the sensorless control method proposed in this application when the motor is running stably under a constant load of 1 N·m. Figure 14 In the graph, the horizontal axis 't' represents time in seconds (s), and the vertical axis represents the deviation between the actual and estimated speed in revolutions per minute (r / min). Compared to the no-load condition, the fluctuation range of the error curve slightly increases after applying a load, but it remains within a small range, fluctuating mostly between ±1.5 r / min. Under load, the maximum speed error is 1.9 r / min. Figure 14 The experimental results are consistent with this description, verifying that even under load disturbances, the motor parameter control method provided in this application can still maintain high speed estimation accuracy and demonstrate good resistance to load disturbances.

[0209] Reference Figure 15 This is a simulation diagram of the fourth motor parameter control method provided in the embodiments of this application. Figure 15 The figure shows the position estimation performance of the sensorless control method proposed in this application when the motor is running stably under a constant load of 1 N·m. This figure also consists of three sub-figures, with the horizontal axis representing time t in seconds (s). The top and middle sub-figures show the actual and estimated values ​​of the rotor angle, respectively; the waveforms of both remain highly consistent, indicating excellent tracking performance under load. The bottom sub-figure shows the error between the actual and estimated rotor angle values, with the vertical axis in radians (rad). After applying a load, the maximum position error increases to 0.09 rad, but still meets the control requirements. Figure 15 The results show that the error curve rises and fluctuates slightly compared to the no-load condition, but it remains at a low level overall. This proves that the motor parameter control method provided in this application can still provide sufficiently accurate position information under load conditions, ensuring the stable operation of the control system.

[0210] Reference Figure 16 This is a simulation diagram of the fifth motor parameter control method provided in the embodiments of this application. Figure 16 The figure shows the dynamic speed response performance of the motor when a sudden load of 2 N·m is applied during operation. In the figure, the horizontal axis t represents time in seconds (s), and the vertical axis represents speed in revolutions per minute (r / min). The black curve represents the actual motor speed, and the red curve represents the speed estimate obtained by the method of this application. Figure 16As can be seen, the two curves highly overlap, indicating that the speed estimation can accurately track changes in the actual speed. Around 0.3 seconds, when the load suddenly increases, the motor speed experiences a brief drop, but thanks to the rapid adjustment of the control system, the speed quickly recovers to near the set value. A magnified view more clearly shows this dynamic process, with the estimated speed closely following the actual value. This figure strongly demonstrates that the motor parameter control method provided in this application has excellent dynamic response characteristics and strong resistance to sudden load increases, maintaining stable control performance under drastic changes in operating conditions.

[0211] Reference Figure 17 This is a simulation diagram of the sixth motor parameter control method provided in the embodiments of this application. Figure 17 The figure shows the dynamic response performance of the motor's position estimation when a sudden load of 2 N·m is applied during operation. The graph consists of three subplots, with the horizontal axis representing time t in seconds (s). The top and middle subplots show the actual and estimated values ​​of the rotor angle, respectively; both waveforms maintain good correlation even during sudden load changes. The bottom subplot shows the error between the actual and estimated rotor angle values, with the vertical axis in radians (rad). The slope of the position error curve increases with the sudden load application, but the maximum error remains controllable within 0.05 rad. Figure 17 The data shows that near the 0.3-second load change point, the position error exhibits a brief peak, but is quickly suppressed and recovers to a small level. This indicates that the position estimation algorithm corresponding to the motor parameter control method provided in this application has good robustness under dynamic disturbances, can quickly suppress errors, and ensures the stability and reliability of the control system under load change conditions.

[0212] The motor parameter control method, device, electronic device, and storage medium proposed in this application include: First, when the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, the first-phase sampling current and the second-phase sampling current of the motor at the current sampling moment are obtained based on a preset sampling period. The preset sampling period is obtained based on the signal period of the motor. The first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal are orthogonal signals. The generation steps of the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal include: obtaining a time angle by multiplying twice the value of pi by a time parameter and then dividing by the signal period; obtaining a first phase difference angle based on the ratio of pi to a first value; and obtaining a time angle based on the value of pi. The ratio of the first phase angle to the second phase angle is used to obtain the second phase difference angle. The first phase angle is obtained based on the difference between the time angle and the first phase difference angle. The first phase sinusoidal voltage signal is obtained based on the product of the sine value of the first phase angle and the signal amplitude. The second phase angle is obtained based on the difference between the time angle and the second phase difference angle. The second phase sinusoidal voltage signal is obtained based on the product of the sine value of the second phase angle and the signal amplitude. Then, the first preceding sampling current and the second preceding sampling current corresponding to the two sampling times adjacent to the current sampling time are obtained. The first preceding differential current is obtained based on the difference between the first phase sampling current and twice the value of the first preceding sampling current. The sum of the first preceding differential current and the second preceding sampling current is used to obtain the first preceding differential current. The first differential current is obtained by calculating the value of the sampled current of the second phase, and the second differential current is obtained by differential calculation of the sampled current of the second phase. Next, the current sampling time is substituted into the sign selection function to obtain the corresponding first sign and second sign. The first error denominator is obtained based on the difference between the square of the average inductance and the square of the half-differential inductance. The second error denominator is obtained based on the product of the preset sampling period, signal amplitude, and half-differential inductance. The error denominator is obtained based on the ratio of the second error denominator to the first error denominator. The previous first differential current and the previous second differential current at the previous sampling time are obtained. The first error current is obtained by multiplying the first sign power of the third value by the previous second differential current. The first error current is obtained based on the first differential current and the first error. The difference in currents is divided by the error denominator to obtain the first position signal. The second sign power of the third value is multiplied by the preceding first differential current to obtain the second error current. The difference between the second differential current and the second error current is divided by the error denominator to obtain the second position signal. The rotor position error signal is obtained based on the first and second position signals. Finally, the current rotor position estimate of the motor observer is obtained, and the corresponding reference signal is determined based on the rotor position estimate. Heterodyne operation is performed on the rotor position error signal and the reference signal to obtain the error signal. The rotor position estimate of the motor observer is adjusted based on the error signal, and the motor is controlled based on the adjusted rotor position estimate.

[0213] This application embodiment directly extracts rotor position information by injecting orthogonal sinusoidal signals with a specific period and combining this with differential operations on the current response. This eliminates the reliance on high-pass or band-pass filters found in traditional high-frequency injection methods. Through differential calculation, the influence of the large-amplitude motor fundamental current component can be directly eliminated, thus avoiding the inherent phase delay and amplitude attenuation problems of filters. This makes rotor position estimation more timely and accurate, significantly improving the dynamic response performance and robustness of the motor control system under conditions such as sudden load changes and dynamic start-stop, thereby enhancing motor control performance. Furthermore, since there is no need to compensate for filter insertion loss, a smaller amplitude... High-frequency signal injection effectively reduces the resulting additional power loss, electromagnetic noise, and torque ripple, improving the overall operating efficiency and quietness of the motor. Finally, by replacing complex filter design and implementation with simple algebraic difference operations, the structure of the control algorithm is greatly simplified, reducing the requirements for processor computing resources and the complexity of software development, thereby improving system reliability and reducing hardware costs. Furthermore, by decoupling and independently setting the signal frequency (determined by the "signal period"), phase (determined by the "first value" and "second value"), and amplitude (determined by the "signal amplitude"), it is possible to precisely construct a signal that meets specific technical requirements. The required "first-phase sinusoidal voltage signal" and "second-phase sinusoidal voltage signal" (i.e., orthogonal relationship) are necessary prerequisites for subsequent high-precision rotor position estimation using differential operations. This ensures that the excitation signal injected into the motor has stable and known characteristics, providing a solid foundation for the effectiveness and reliability of the entire sensorless control scheme. Furthermore, decomposing an operation mathematically equivalent to a second-order high-pass filter into three clear and independent arithmetic steps—data acquisition, weighted subtraction, and accumulation—not only effectively suppresses interference from the motor's fundamental current and accurately extracts the high-frequency signal used for position estimation, but also requires only simple addition, subtraction, and multiplication in implementation. The computation is minimal, greatly reducing the requirements on the controller's processing power. This provides a computationally lightweight and highly efficient signal preprocessing method for sensorless control systems. Furthermore, by explicitly combining inherent parameters such as the motor's average inductance and half-differential inductance with external parameters such as the preset sampling period and signal amplitude, all key factors affecting the high-frequency response current amplitude are precisely quantified. This allows the subsequent position signal calculation process to effectively eliminate the interference of these factors, ensuring the consistency and accuracy of the calculation results. This greatly improves the robustness of the entire sensorless control algorithm and its universality to different motors and operating conditions.Furthermore, by utilizing the differential current between the current and previous moments, combined with a dynamically changing sign selection logic, effective separation of the two coupled signal channels is achieved without any complex matrix inversion or iterative operations. By constructing "first error current" and "second error current" as correction terms and performing simple subtraction and division operations, the normalized "first position signal" and "second position signal" can be obtained directly and accurately. This not only greatly reduces the computational burden of the real-time control system but also ensures the speed and accuracy of position information calculation, representing a key technological innovation for achieving high-performance sensorless control. In addition, by introducing a sign selection function and ingenious cross-combination operations, the orthogonal position information coupled in the differential current is successfully separated and transformed into a clear rotor position error signal. This calculation method has clear logic and is computationally efficient. The process involves only simple algebraic operations, avoiding the computationally intensive operations such as complex phase-locked loops or matrix inversions found in traditional methods. This not only ensures the accuracy and real-time performance of position estimation but also greatly simplifies the implementation of the control algorithm, providing crucial technical support for building a high-performance, low-cost sensorless motor control system. Finally, heterodyne calculations efficiently compare the actual measurement information with the internal state of the observer, generating a linear error signal. Compared to other nonlinear error processing methods, this signal exhibits better convergence and stability. Subsequently, this high-quality error signal is used to drive the motor observer for adjustment, forming a robust closed-loop feedback system. This not only ensures the high accuracy and high dynamic response characteristics of the rotor position estimate but also enables the entire sensorless control system to effectively suppress noise and external disturbances, ultimately achieving smooth and precise motor operation control.

[0214] This application also provides a motor parameter control device that can implement the above-described motor parameter control method, see reference. Figure 18 The device 1800 includes:

[0215] The current sampling module 1810 is used to obtain the first phase sampling current and the second phase sampling current of the motor at the current sampling time based on a preset sampling period when the motor is continuously input with a first phase sinusoidal voltage signal and a second phase sinusoidal voltage signal. The preset sampling period is obtained based on the signal period of the motor. The first phase sinusoidal voltage signal and the second phase sinusoidal voltage signal are orthogonal signals to each other.

[0216] The differential calculation module 1820 is used to perform differential calculation on the first phase sampled current to obtain the first differential current, and to perform differential calculation on the second phase sampled current to obtain the second differential current.

[0217] The error signal calculation module 1830 is used to calculate the rotor position error signal based on the current sampling time, the first differential current, and the second differential current.

[0218] The adjustment control module 1840 is used to adjust the rotor position estimate of the motor observer based on the rotor position error signal, and to control the operation of the motor based on the adjusted rotor position estimate.

[0219] In some embodiments, the current sampling module 1810 is further configured to:

[0220] The time angle is obtained by multiplying twice the value of pi by the time parameter and then dividing by the signal period.

[0221] The first phase difference angle is obtained based on the ratio of pi to the first value, and the second phase difference angle is obtained based on the ratio of pi to the second value.

[0222] The first phase angle is obtained based on the difference between the time angle and the first phase difference angle, and the first phase sinusoidal voltage signal is obtained based on the product of the sine value of the first phase angle and the signal amplitude.

[0223] The second phase angle is obtained based on the difference between the time angle and the second phase difference angle. The second phase sinusoidal voltage signal is obtained based on the product of the sine value of the second phase angle and the signal amplitude.

[0224] In some embodiments, the difference calculation module 1820 is further configured to:

[0225] Obtain the first and second preceding sampled currents corresponding to the two sampling times adjacent to the current sampling time, respectively;

[0226] The first preceding differential current is obtained based on the difference between the first phase sampling current and the first preceding sampling current, which is twice the value.

[0227] The first differential current is obtained by summing the first preceding differential current and the second preceding sampled current.

[0228] In some embodiments, the error signal calculation module 1830 is further configured to:

[0229] Substituting the current sampling time into the symbol selection function yields the corresponding first and second symbols;

[0230] The error denominator term is obtained based on the preset sampling period, and the first position signal and the second position signal are obtained based on the first differential current, the second differential current, the first symbol, the second symbol, and the error denominator term.

[0231] The rotor position error signal is obtained based on the first position signal and the second position signal.

[0232] In some embodiments, the error signal calculation module 1830 is further configured to:

[0233] The first error denominator term is obtained based on the difference between the square of the average inductance and the square of the half-differential inductance.

[0234] The second error denominator term is obtained based on the product of the preset sampling period, signal amplitude, and half-differential inductance.

[0235] The error denominator is obtained based on the ratio of the second error denominator to the first error denominator.

[0236] In some embodiments, the error signal calculation module 1830 is further configured to:

[0237] Obtain the preceding first differential current and the preceding second differential current at the preceding sampling time;

[0238] The first error current is obtained by multiplying the third value by the first sign power and then by the second differential current in the preceding order.

[0239] The first position signal is obtained by dividing the difference between the first differential current and the first error current by the error denominator.

[0240] The second error current is obtained by multiplying the second sign power of the third value by the first differential current in the preceding sequence.

[0241] The second position signal is obtained by dividing the difference between the second differential current and the second error current by the error denominator.

[0242] In some embodiments, the adjustment control module 1840 is further configured to:

[0243] Obtain the current rotor position estimate from the motor observer, and determine the corresponding reference signal based on the rotor position estimate;

[0244] The error signal is obtained by performing heterodyne calculation based on the rotor position error signal and the reference signal;

[0245] Adjust the rotor position estimate of the motor observer based on the error signal.

[0246] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, the specific implementation of the motor parameter control device is basically the same as the specific implementation of the motor parameter control method described above, and will not be repeated here.

[0247] In this embodiment, the motor parameter control device directly extracts rotor position information by injecting orthogonal sinusoidal signals with a specific period and combining this with differential calculation of the current response. This eliminates the reliance on high-pass or band-pass filters found in traditional high-frequency injection methods. Through differential calculation, the influence of the large-amplitude fundamental current component of the motor can be directly eliminated, thus avoiding the inherent phase delay and amplitude attenuation problems of filters. This makes rotor position estimation more timely and accurate, significantly improving the dynamic response performance and robustness of the motor control system under conditions such as load changes and dynamic start-stop, thereby improving motor control performance. Furthermore, since there is no need to compensate for filter insertion loss, through... By employing a higher frequency injection signal with a smaller amplitude, the resulting additional power loss, electromagnetic noise, and torque ripple are effectively reduced, improving the overall operating efficiency and quietness of the motor. Finally, simple algebraic difference operations replace complex filter design and implementation, greatly simplifying the control algorithm structure, reducing the requirements for processor computing resources and the complexity of software development, thereby improving system reliability and reducing hardware costs. Furthermore, by decoupling and independently setting the signal frequency (determined by the "signal period"), phase (determined by the "first value" and "second value"), and amplitude (determined by the "signal amplitude"), a precise full-range signal can be constructed. The "first-phase sinusoidal voltage signal" and "second-phase sinusoidal voltage signal" that meet specific technical requirements (i.e., orthogonality) are necessary prerequisites for subsequent high-precision rotor position estimation using differential operations. This ensures that the excitation signal injected into the motor has stable and known characteristics, providing a solid foundation for the effectiveness and reliability of the entire sensorless control scheme. Furthermore, decomposing an operation mathematically equivalent to a second-order high-pass filter into three clear and independent arithmetic steps—data acquisition, weighted subtraction, and accumulation—not only effectively suppresses interference from the motor's fundamental current and accurately extracts the high-frequency signal for position estimation, but also requires only simple implementation. Addition, subtraction, multiplication, and arithmetic operations require minimal computation, significantly reducing the demands on the controller's processing power. This provides a computationally lightweight and highly efficient signal preprocessing method for sensorless control systems. Furthermore, by explicitly combining inherent parameters such as the motor's average inductance and half-differential inductance with external parameters such as the preset sampling period and signal amplitude, all key factors affecting the high-frequency response current amplitude are precisely quantified. This allows the subsequent position signal calculation process to effectively eliminate the interference of these factors, ensuring the consistency and accuracy of the calculation results. This greatly enhances the robustness of the entire sensorless control algorithm and its universality to different motors and operating conditions.Furthermore, by utilizing the differential current between the current and previous moments, combined with a dynamically changing sign selection logic, effective separation of the two coupled signal channels is achieved without any complex matrix inversion or iterative operations. By constructing "first error current" and "second error current" as correction terms and performing simple subtraction and division operations, the normalized "first position signal" and "second position signal" can be obtained directly and accurately. This not only greatly reduces the computational burden of the real-time control system but also ensures the speed and accuracy of position information calculation, representing a key technological innovation for achieving high-performance sensorless control. In addition, by introducing a sign selection function and ingenious cross-combination operations, the orthogonal position information coupled in the differential current is successfully separated and transformed into a clear rotor position error signal. This calculation method has clear logic and is computationally efficient. The process involves only simple algebraic operations, avoiding the computationally intensive operations such as complex phase-locked loops or matrix inversions found in traditional methods. This not only ensures the accuracy and real-time performance of position estimation but also greatly simplifies the implementation of the control algorithm, providing crucial technical support for building a high-performance, low-cost sensorless motor control system. Finally, heterodyne calculations are used to efficiently compare the actual measurement information with the internal state of the observer, generating a linear error signal. Compared to other nonlinear error processing methods, this has better convergence and stability. Subsequently, this high-quality error signal is used to drive the motor observer to make adjustments, forming a robust closed-loop feedback system. This not only ensures the high accuracy and high dynamic response characteristics of the rotor position estimate but also enables the entire sensorless control system to effectively suppress noise and external disturbances, ultimately achieving smooth and precise operation control of the motor. This application also provides an electronic device, including:

[0248] At least one memory;

[0249] At least one processor;

[0250] At least one program;

[0251] The program is stored in a memory, and the processor executes the at least one program to implement the motor parameter control method described above. The electronic device can be any smart terminal, including mobile phones, tablets, personal digital assistants (PDAs), and in-vehicle computers.

[0252] Please see Figure 19 , Figure 19 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0253] The processor 1901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0254] The memory 1902 can be implemented in the form of ROM (Read-Only Memory), static storage device, dynamic storage device, or RAM (Random Access Memory). The memory 1902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1902 and is called and executed by the processor 1901 to execute the motor parameter control method of the embodiments of this application.

[0255] The input / output interface 1903 is used to implement information input and output;

[0256] The communication interface 1904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0257] Bus 1905 transmits information between various components of the device (e.g., processor 1901, memory 1902, input / output interface 1903, and communication interface 1904);

[0258] The processor 1901, memory 1902, input / output interface 1903, and communication interface 1904 are connected to each other within the device via bus 1905.

[0259] This application embodiment also provides a storage medium, which is a computer-readable storage medium, storing a computer program that, when executed by a processor, implements the above-described motor parameter control method.

[0260] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0261] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0262] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0263] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0264] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0265] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0266] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0267] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. The coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, or indirect coupling or communication connection between the apparatus or units, and may be electrical, mechanical, or other forms.

[0268] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0269] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0270] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0271] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for controlling motor parameters, characterized in that, include: When the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal, the first-phase sampling current and the second-phase sampling current of the motor at the current sampling time are obtained based on a preset sampling period. The preset sampling period is obtained based on the signal period of the motor. The first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal are orthogonal signals to each other. Differential calculation is performed on the first phase sampling current to obtain the first differential current, and differential calculation is performed on the second phase sampling current to obtain the second differential current; Based on the current sampling time, the first differential current, and the second differential current, the rotor position error signal is calculated. The rotor position estimate of the motor observer is adjusted based on the rotor position error signal, and the motor is operated and controlled based on the adjusted rotor position estimate.

2. The motor parameter control method according to claim 1, characterized in that, The steps for generating the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal include: The time angle is obtained by multiplying twice the value of pi by the time parameter and then dividing by the signal period. The first phase difference angle is obtained based on the ratio of pi to the first value, and the second phase difference angle is obtained based on the ratio of pi to the second value. Based on the difference between the time angle and the first phase angle, the first phase angle is obtained, and based on the product of the sine value of the first phase angle and the signal amplitude, the first phase sinusoidal voltage signal is obtained. The second phase angle is obtained based on the difference between the time angle and the second phase angle, and the second phase sinusoidal voltage signal is obtained based on the product of the sine value of the second phase angle and the signal amplitude.

3. The motor parameter control method according to claim 1, characterized in that, The step of performing differential calculation on the sampled current of the first phase to obtain the first differential current includes: Obtain the first preceding sampling current and the second preceding sampling current corresponding to the two sampling times adjacent to the current sampling time, respectively; The first preceding differential current is obtained based on the difference between the first phase sampling current and the first preceding sampling current which is twice the value. The first differential current is obtained based on the sum of the first preceding differential current and the second preceding sampled current.

4. The motor parameter control method according to claim 1, characterized in that, The calculation of the rotor position error signal based on the current sampling time, the first differential current, and the second differential current includes: Substituting the current sampling time into the symbol selection function yields the corresponding first and second symbols; Based on the preset sampling period, an error denominator term is obtained. Based on the first differential current, the second differential current, the first symbol, the second symbol, and the error denominator term, a first position signal and a second position signal are obtained. The rotor position error signal is obtained based on the first position signal and the second position signal.

5. The motor parameter control method according to claim 4, characterized in that, The step of obtaining the error denominator based on the preset sampling period includes: The first error denominator term is obtained based on the difference between the square of the average inductance and the square of the half-differential inductance. The second error denominator term is obtained based on the product of the preset sampling period, the signal amplitude, and the half-differential inductance. The error denominator term is obtained based on the ratio of the second error denominator term to the first error denominator term.

6. The motor parameter control method according to claim 4, characterized in that, The process of obtaining the first position signal and the second position signal based on the first differential current, the second differential current, the first symbol, the second symbol, and the error denominator term includes: Obtain the preceding first differential current and the preceding second differential current at the preceding sampling time; The first error current is obtained by multiplying the first sign power of the third value by the preceding second differential current. The first position signal is obtained by dividing the difference between the first differential current and the first error current by the error denominator. The second error current is obtained by multiplying the second sign power of the third value by the preceding first differential current. The second position signal is obtained by dividing the difference between the second differential current and the second error current by the error denominator.

7. The motor parameter control method according to claim 1, characterized in that, The adjustment of the rotor position estimate of the motor observer based on the rotor position error signal includes: Obtain the current rotor position estimate of the motor observer, and determine the corresponding reference signal based on the rotor position estimate; Heterodyne calculation is performed based on the rotor position error signal and the reference signal to obtain the error signal; The rotor position estimate of the motor observer is adjusted based on the error signal.

8. A motor parameter control device, characterized in that, include: The current sampling module is used to obtain the first-phase sampling current and the second-phase sampling current of the motor at the current sampling time based on a preset sampling period when the motor is continuously input with a first-phase sinusoidal voltage signal and a second-phase sinusoidal voltage signal. The preset sampling period is obtained based on the signal period of the motor, and the first-phase sinusoidal voltage signal and the second-phase sinusoidal voltage signal are orthogonal signals to each other. The differential calculation module is used to perform differential calculation on the first phase sampled current to obtain the first differential current, and to perform differential calculation on the second phase sampled current to obtain the second differential current; The error signal calculation module is used to calculate the rotor position error signal based on the current sampling time, the first differential current, and the second differential current; The adjustment control module is used to adjust the rotor position estimate of the motor observer based on the rotor position error signal, and to perform operation control of the motor based on the adjusted rotor position estimate.

9. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the motor parameter control method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the motor parameter control method according to any one of claims 1 to 7.

Images