A current dynamic coupling correction method for a permanent magnet synchronous motor of an electric drive axle system

Abstract

The application relates to the technical field of motor control, and discloses a current dynamic coupling correction method for a permanent magnet synchronous motor of an electric drive axle system, which comprises the following steps: performing decoupling processing on three-phase current signals of the permanent magnet synchronous motor to obtain current components; performing real-time updating on a dynamic coupling coefficient on the basis of the current components and real-time monitored motor parameters and operating states of the permanent magnet synchronous motor to obtain a current dynamic coupling component; performing dynamic error monitoring analysis on the current dynamic coupling component to obtain a coupling disturbance estimation value; performing compensation response on the current components on the basis of the coupling disturbance estimation value and a preset feedforward compensation mechanism to obtain a current dynamic correction signal; performing correction superposition on the current dynamic correction signal on the basis of a voltage control loop of the permanent magnet synchronous motor to obtain a control voltage signal; and performing pulse width modulation on the control voltage signal to obtain an inverter control signal of the permanent magnet synchronous motor; and the application can improve the operating efficiency of the permanent magnet synchronous motor of the electric drive axle system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor control, and in particular to a current dynamic coupling correction method for a permanent magnet synchronous motor of an electric drive axle system. BACKGROUND

[0002] In the electric drive axle system, the permanent magnet synchronous motor becomes the core power component due to its high power density and high operating efficiency, and the current control accuracy of the permanent magnet synchronous motor directly determines the power output stability and energy efficiency of the electric drive axle system. However, the existing current coupling correction methods for the permanent magnet synchronous motor generally have the problem of insufficient adaptability to dynamic working conditions. When decoupling the three-phase current signals, a fixed algorithm or a static model is usually used, and the real-time operating state and dynamic parameters of the motor are not fully combined for collaborative adjustment, resulting in incomplete separation of current components during decoupling, mutual interference between direct-axis and quadrature-axis currents, and further causing current control deviation, which affects the motor control accuracy.

[0003] The existing current dynamic coupling correction technology also has the defect of lag in disturbance estimation and compensation mechanism. Most methods rely on preset static coupling coefficients or simple error feedback adjustment, and cannot update the dynamic coupling coefficients in real time to match the changes in motor operating conditions. When the motor is in a high dynamic operating scenario, it is easy to produce coupling disturbance errors and difficult to estimate accurately and quickly. At the same time, the traditional compensation mechanism lacks deep coordination with the voltage control loop, and the compensation signal and the control voltage are easy to have phase deviation or amplitude mismatch when superimposed, resulting in a decrease in the accuracy of the inverter control signal, which not only reduces the dynamic response speed of the electric drive axle system, but also may cause an increase in motor operating noise and energy consumption, making it difficult to meet the actual application requirements of the electric drive axle system for high dynamic response and high precision control. Therefore, how to improve the operating efficiency of the electric drive axle system has become a problem to be solved. SUMMARY

[0004] The present application provides a current dynamic coupling correction method for a permanent magnet synchronous motor of an electric drive axle system to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides a current dynamic coupling correction method for a permanent magnet synchronous motor of an electric drive axle system, comprising:

[0006] S1, decoupling the three-phase current signals of the permanent magnet synchronous motor to obtain the current components of the permanent magnet synchronous motor;

[0007] S2, based on the current components and the real-time monitored motor parameters and operating state of the permanent magnet synchronous motor, updating the dynamic coupling coefficients of the permanent magnet synchronous motor in real time to obtain the current dynamic coupling components of the permanent magnet synchronous motor;

[0008] S3, performing dynamic error monitoring analysis on the current dynamic coupling component to obtain a coupling disturbance estimation value of the permanent magnet synchronous motor;

[0009] S4, based on the coupling disturbance estimation value and a preset feedforward compensation mechanism, performing compensation response on the current component to obtain a current dynamic correction signal of the permanent magnet synchronous motor;

[0010] S5, based on a voltage control loop of the permanent magnet synchronous motor, performing correction superposition on the current dynamic correction signal to obtain a control voltage signal of the permanent magnet synchronous motor;

[0011] S6, performing pulse width modulation on the control voltage signal to obtain an inverter control signal of the permanent magnet synchronous motor.

[0012] In a preferred embodiment, the decoupling processing of the three-phase current signal of the permanent magnet synchronous motor to obtain the current component of the permanent magnet synchronous motor comprises:

[0013] Real-time acquisition of the three-phase current signal in the permanent magnet synchronous motor to obtain three-phase current data of the permanent magnet synchronous motor;

[0014] Rotating coordinate system transformation processing of the three-phase current data to obtain coordinate axis current components of the three-phase current data;

[0015] Dynamic coupling separation of the coordinate axis current components to obtain the current component of the permanent magnet synchronous motor.

[0016] In a preferred embodiment, the real-time updating of the dynamic coupling coefficient of the permanent magnet synchronous motor based on the current component and the real-time monitored motor parameters and operating state of the permanent magnet synchronous motor to obtain the current dynamic coupling component of the permanent magnet synchronous motor comprises:

[0017] Digital encapsulation of the real-time monitored motor parameters and operating state of the permanent magnet synchronous motor to obtain real-time operating data of the permanent magnet synchronous motor;

[0018] Interaction evaluation of the real-time operating data and the current component to obtain a real-time coupling influence factor of the permanent magnet synchronous motor;

[0019] Normalization processing of the real-time coupling influence factor to obtain a coupling coefficient adjustment amount of the permanent magnet synchronous motor;

[0020] Based on the coupling coefficient adjustment amount, gradually updating the dynamic coupling coefficient of the permanent magnet synchronous motor to obtain a dynamic coupling optimization coefficient of the permanent magnet synchronous motor;

[0021] Nonlinearly superimposing the dynamic coupling optimization coefficient and the current component to obtain a current dynamic coupling component of the permanent magnet synchronous motor.

[0022] In a preferred embodiment, the interaction evaluation of the real-time operation data and the current component to obtain a real-time coupling influence factor of the permanent magnet synchronous motor comprises:

[0023] Dynamic response characteristic monitoring of the current component to obtain a current interaction characteristic of the current component;

[0024] Evolution analysis of the current interaction characteristic based on the real-time operation data to obtain an interaction influence degree of the current interaction characteristic;

[0025] Threshold value quantization comparison of the interaction influence degree to obtain the real-time coupling influence factor of the permanent magnet synchronous motor.

[0026] In a preferred embodiment, the dynamic error monitoring analysis of the current dynamic coupling component to obtain a coupling disturbance estimation value of the permanent magnet synchronous motor comprises:

[0027] Waveform characteristic extraction of the current dynamic coupling component to obtain a fluctuation characteristic component of the current dynamic coupling component;

[0028] Matching analysis of the fluctuation characteristic component based on a preset reference disturbance characteristic to obtain dynamic error data of the current dynamic coupling component;

[0029] Completeness inspection of the dynamic error data to obtain the coupling disturbance estimation value of the permanent magnet synchronous motor, wherein a calculation formula of the coupling disturbance estimation value is as follows:

[0030] ;

[0031] In the formula, the coupling disturbance estimation value is a scaling coefficient is an inverse tangent function is a sensitivity coefficient of the dynamic error data is the dynamic error data of the matching result of the fluctuation characteristic component and the reference disturbance characteristic.

[0032] In a preferred embodiment, the matching analysis of the fluctuation characteristic component based on a preset reference disturbance characteristic to obtain dynamic error data of the current dynamic coupling component comprises:

[0033] Real-time monitoring of a change trend of an amplitude and a frequency of the fluctuation characteristic component to obtain an instantaneous characteristic of the fluctuation characteristic component.

[0034] The instantaneous characteristics are compared with the preset reference disturbance characteristics to obtain the deviation patterns of the fluctuation characteristic components;

[0035] Based on the deviation pattern, the degree of matching between the fluctuation characteristic component and the reference disturbance characteristic is analyzed and evaluated to obtain the error index of the deviation pattern;

[0036] The timing consistency of the error index is verified to obtain the dynamic error data of the current dynamic coupling component.

[0037] In a preferred embodiment, the step of compensating the current component based on the coupling disturbance estimate and a preset feedforward compensation mechanism to obtain the current dynamic correction signal of the permanent magnet synchronous motor includes:

[0038] Based on a preset feedforward compensation mechanism, the estimated value of the coupling disturbance is mapped by a strategy to obtain the compensation strategy for the current component.

[0039] The compensation strategy is analyzed to obtain the compensation parameters for the current component;

[0040] Based on the compensation parameters, the current component is compensated and injected to obtain the current dynamic correction signal of the permanent magnet synchronous motor.

[0041] In a preferred embodiment, the voltage control loop based on the permanent magnet synchronous motor corrects and superimposes the current dynamic correction signal to obtain the control voltage signal for the permanent magnet synchronous motor, including:

[0042] Based on the voltage control loop of the permanent magnet synchronous motor, the current dynamic correction signal is adjusted to obtain the voltage adjustment amount of the permanent magnet synchronous motor.

[0043] The voltage regulation amount is adapted and superimposed with the current voltage of the voltage control loop to obtain the superimposed voltage signal of the permanent magnet synchronous motor;

[0044] The superimposed voltage signal is subjected to amplitude limiting processing to obtain the control voltage signal of the permanent magnet synchronous motor.

[0045] In a preferred embodiment, the voltage control loop based on the permanent magnet synchronous motor performs reference adjustment on the current dynamic correction signal to obtain the voltage adjustment amount of the permanent magnet synchronous motor, including:

[0046] Based on the voltage control loop, the current dynamic correction signal is adaptively adjusted to obtain the reference adjustment signal of the voltage control loop;

[0047] The reference adjustment signal is subjected to phase synchronization processing to obtain the phase synchronization signal of the reference adjustment signal;

[0048] Impedance matching is performed on the phase synchronization signal to obtain the voltage regulation amount of the permanent magnet synchronous motor.

[0049] In a preferred embodiment, the step of pulse width modulation of the control voltage signal to obtain the inverter control signal for the permanent magnet synchronous motor includes:

[0050] The control voltage signal is pulse-width modulated to obtain the pulse duty cycle signal of the controlled voltage signal;

[0051] The pulse duty cycle signal is level-converted to obtain the electrical drive signal of the control voltage signal;

[0052] Based on the preset electrical isolation characteristics, the electrical drive signal is configured with a dead time to obtain the inverter control signal of the magnetic synchronous motor.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The current dynamic coupling correction method for permanent magnet synchronous motors in electric drive bridge systems provided by this invention can significantly improve the accuracy and dynamic adaptability of current dynamic coupling correction. This method decouples the three-phase current signals of the permanent magnet synchronous motor and, combined with real-time monitoring parameters and operating status of the motor, achieves real-time updates of the dynamic coupling coefficient. This allows the dynamic coupling components of the current to accurately match changes in motor operating conditions, effectively improving the thoroughness and accuracy of current component separation, reducing interference between direct-axis and quadrature-axis currents, thereby improving current control accuracy and ensuring stable motor output under different operating scenarios.

[0055] 2. This invention can also significantly optimize the current correction response efficiency and control signal quality. By performing dynamic error monitoring and analysis on the dynamic coupling components of the current, and calculating the estimated value of the coupling disturbance using a specific formula, the coupling disturbance information can be accurately captured. Then, relying on a preset feedforward compensation mechanism, the current component is compensated in a timely manner, and the current dynamic correction signal is corrected and superimposed through a voltage control loop. Finally, a precise inverter control signal is obtained through pulse width modulation. This series of processes can accelerate the dynamic response speed of the current correction, ensure the accuracy of the control voltage signal and the inverter control signal, effectively improve the operating efficiency of the electric drive bridge system, reduce the risk of signal deviation during motor operation, and further ensure the reliable operation of the electric drive bridge system. Attached Figure Description

[0056] Figure 1 This is a flowchart illustrating a method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system according to an embodiment of the present invention.

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0059] This application provides a method for dynamic coupling correction of the current of a permanent magnet synchronous motor in an electric drive bridge system. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0060] Reference Figure 1 The diagram shown is a flowchart illustrating a method for dynamic coupling correction of the current in a permanent magnet synchronous motor of an electric drive bridge system according to an embodiment of the present invention. In this embodiment, the method for dynamic coupling correction of the current in a permanent magnet synchronous motor of an electric drive bridge system includes:

[0061] S1. Decouple the three-phase current signal of the permanent magnet synchronous motor to obtain the current component of the permanent magnet synchronous motor.

[0062] In this embodiment of the invention, the decoupling process of the three-phase current signal of the permanent magnet synchronous motor to obtain the current components of the permanent magnet synchronous motor includes:

[0063] The three-phase current signal in the permanent magnet synchronous motor is acquired in real time to obtain the three-phase current data of the permanent magnet synchronous motor.

[0064] The three-phase current data is subjected to a rotating coordinate system transformation to obtain the coordinate axis current components of the three-phase current data.

[0065] The current components of the permanent magnet synchronous motor are obtained by dynamically coupling and separating the current components of the coordinate axes.

[0066] Specifically, when acquiring the three-phase current signal in a permanent magnet synchronous motor in real time, current sensors, such as Hall effect current sensors or electromagnetic current transformers, need to be installed on the three-phase power supply lines of the motor. These sensors are directly connected in series with the power supply lines of the A-phase, B-phase, and C-phase windings of the motor, and can sense the current changes in each phase line in real time. The sensors convert the sensed current signal into a voltage signal proportional to it. These voltage signals are transmitted to the data acquisition module through shielded cables. The data acquisition module performs analog-to-digital conversion on the voltage signal according to a preset sampling period, converting the analog voltage signal into a digital signal. These digital signals are the three-phase current data that can reflect the magnitude of the current in phases A, B, and C at each moment.

[0067] Furthermore, when performing a rotating coordinate system transformation on the three-phase current data, a Clarke transformation is first performed. That is, based on the current values ​​of phases A, B, and C in the three-phase current data, the current in the three-phase stationary coordinate system is converted into current components in a two-phase stationary coordinate system. Specifically, the process utilizes the balance relationship of the three-phase currents, taking the phase A current and phase B current as the basis, and calculates the α-axis current component and β-axis current component through a specific coordinate transformation logic. The α-axis coincides with the axis of the phase A winding, and the β-axis is perpendicular to the α-axis. This transformation eliminates the phase coupling between the three-phase currents, resulting in two orthogonal AC current components. Then, a Park transformation is performed to convert the α-axis and β-axis current components in the two-phase stationary coordinate system into current components in the two-phase rotating coordinate system. Here, the rotating coordinate system is consistent with the rotational speed of the motor rotor, the d-axis coincides with the excitation direction of the rotor permanent magnet, and the q-axis is perpendicular to the d-axis. By rotating and projecting the α-axis and β-axis current components according to the real-time position angle of the rotor, the original AC current components are converted into DC current components. These d-axis and q-axis current components are the coordinate axis current components of the three-phase current data.

[0068] Furthermore, when dynamically separating the coordinate axis current components, the rotor rotation during motor operation leads to cross-coupling between the d-axis and q-axis. This means changes in the d-axis current affect the q-axis current, and vice versa, stemming from electromagnetic induction within the motor. Dynamic coupling separation requires first determining the specific manifestation of the coupling components based on the motor's real-time operating state, including rotor speed and current d-axis and q-axis current values. Specifically, it involves identifying the coupling components in the d-axis current caused by changes in the q-axis current and vice versa. Then, based on the magnitude and direction of these coupling components, targeted compensation is performed on the existing coordinate axis current components. This specifically involves subtracting the coupling components generated by the q-axis current from the d-axis current components and vice versa. After this separation process, the resulting d-axis and q-axis current components no longer influence each other and independently reflect the motor's excitation and torque characteristics. These separated current components are the current components of the permanent magnet synchronous motor.

[0069] In general, real-time acquisition of three-phase current signals in a permanent magnet synchronous motor is achieved by installing current sensors on the three-phase power supply lines of the motor to sense current changes, converting them into voltage signals, and then performing analog-to-digital conversion by a data acquisition module to finally obtain three-phase current data reflecting the magnitude of the currents in phases A, B, and C at each moment.

[0070] In general, the rotating coordinate system transformation of three-phase current data involves first converting the current in the three-phase stationary coordinate system into the α-axis and β-axis current components in the two-phase stationary coordinate system using the Clarke transformation, and then converting it into the d-axis and q-axis current components in the two-phase rotating coordinate system that rotates synchronously with the rotor using the Park transformation, thereby obtaining the coordinate axis current components of the three-phase current data.

[0071] In summary, dynamic coupling separation of coordinate axis current components involves determining the coupling portion between the d-axis and q-axis currents based on the real-time operating state of the motor, and then specifically subtracting the coupling components caused by the other from each component to obtain the current components of the permanent magnet synchronous motor that do not affect each other and separately reflect the excitation and torque characteristics.

[0072] S2. Based on the current component and the motor parameters and operating status monitored in real time in the permanent magnet synchronous motor, the dynamic coupling coefficient of the permanent magnet synchronous motor is updated in real time to obtain the current dynamic coupling component of the permanent magnet synchronous motor.

[0073] In this embodiment of the invention, the step of updating the dynamic coupling coefficient of the permanent magnet synchronous motor in real time based on the current component and the motor parameters and operating status monitored in real time in the permanent magnet synchronous motor to obtain the current dynamic coupling component of the permanent magnet synchronous motor includes:

[0074] The motor parameters and operating status monitored in real time in the permanent magnet synchronous motor are digitally encapsulated to obtain the real-time operating data of the permanent magnet synchronous motor;

[0075] The interaction between the real-time operating data and the current component is evaluated to obtain the real-time coupling influence factor of the permanent magnet synchronous motor.

[0076] The real-time coupling influence factor is normalized to obtain the coupling coefficient adjustment amount of the permanent magnet synchronous motor;

[0077] Based on the aforementioned coupling coefficient adjustment, the dynamic coupling coefficient of the permanent magnet synchronous motor is progressively updated to obtain the dynamic coupling optimization coefficient of the permanent magnet synchronous motor.

[0078] The dynamic coupling optimization coefficient and the current component are nonlinearly superimposed to obtain the current dynamic coupling component of the permanent magnet synchronous motor.

[0079] The evaluation of the interaction between the real-time operating data and the current component to obtain the real-time coupling influence factor of the permanent magnet synchronous motor includes:

[0080] The dynamic response characteristics of the current component are monitored to obtain the current interaction characteristics of the current component;

[0081] Based on the real-time operating data, the evolution analysis of the current interaction characteristics is performed to obtain the degree of interaction influence of the current interaction characteristics.

[0082] The degree of interaction influence is compared by threshold quantization to obtain the real-time coupling influence factor of the permanent magnet synchronous motor.

[0083] Specifically, when digitizing the motor parameters and operating status monitored in real time in a permanent magnet synchronous motor, the motor parameters to be monitored are first defined as inherent effect parameters such as stator resistance, stator inductance, and permanent magnet flux linkage, as well as dynamic changes in operating status such as rotor speed, motor temperature, terminal voltage, and output torque. Physical signals of these parameters and statuses are collected by sensors installed at corresponding locations on the motor, such as using a temperature sensor to collect stator winding temperature, an encoder to collect rotor speed, and a voltage sensor to collect terminal voltage. These different types of physical signals are transmitted to signal conditioning circuits for filtering, amplification, and other processing to remove noise. The processed analog signals are then converted into digital signals by an analog-to-digital converter. Subsequently, these digital signals are uniformly encoded according to a preset data format to form a structured dataset, which constitutes the real-time operating data of the permanent magnet synchronous motor.

[0084] Furthermore, when evaluating the interaction between real-time operating data and the current component, the parameters and states in the real-time operating data are first correlated with the current component one by one. Specifically, it is observed which parameters or states in the real-time operating data change when the current component changes, as well as the trend and magnitude of the change, such as the change in stator inductance when the d-axis current increases; simultaneously, it is observed how the current component changes when the parameters or states in the real-time operating data change, such as the response of the q-axis current when the rotor speed increases. Through this bidirectional correlation analysis, the specific manifestation of the interaction between each piece of real-time operating data and the current component is determined. Then, based on the significance of these effects, they are quantified and classified to form a set of indicators that reflect the strength of their interaction. This set of indicators constitutes the real-time coupling influence factor of the permanent magnet synchronous motor.

[0085] Furthermore, when normalizing the real-time coupling influence factors, the value range of all real-time coupling influence factors is first determined, and the maximum and minimum values ​​are found. Then, for each real-time coupling influence factor, its value is transformed into the set range by subtracting the minimum value and then dividing by the difference between the maximum and minimum values. This process eliminates the interference caused by differences in dimensions and magnitudes of different influence factors, allowing them to be compared and integrated on the same scale. The value obtained after this transformation is the adjustment amount of the coupling coefficient of the permanent magnet synchronous motor.

[0086] Furthermore, when progressively updating the dynamic coupling coefficient of a permanent magnet synchronous motor based on the coupling coefficient adjustment, the adjustment amount is gradually incorporated into the current dynamic coupling coefficient at a fixed ratio. Specifically, a small portion of the coupling coefficient adjustment is first taken as a single adjustment value and added to the current dynamic coupling coefficient to obtain the initially adjusted coupling coefficient. This initially adjusted coupling coefficient is then applied to the real-time operation analysis of the motor to observe whether it can more accurately reflect the coupling relationship between the current component and the motor parameters and operating state. If it does not meet expectations, the above process is repeated, continuing to add the remaining coupling coefficient adjustment until the adjustment is fully incorporated. The final coefficient that more accurately reflects the actual coupling situation is the dynamic coupling optimization coefficient of the permanent magnet synchronous motor.

[0087] Furthermore, when nonlinearly superimposing the dynamic coupling optimization coefficients and the current components, the influence weight of the dynamic coupling optimization coefficients corresponding to different current component values ​​is determined based on the actual correlation characteristics between the two. For example, when the current component is in a lower range, the influence weight of the dynamic coupling optimization coefficients is smaller, and when the current component is in a higher range, the weight increases accordingly. According to this weighting relationship, the dynamic coupling optimization coefficients and the corresponding current components are combined for calculation, so that the superposition result can accurately reflect the coupling effect under nonlinear correlation. The final result is the current dynamic coupling component of the permanent magnet synchronous motor.

[0088] Specifically, when monitoring the dynamic response characteristics of the current components, it is necessary to continuously collect the values ​​of the d-axis and q-axis current components at different times and record their curves over time. Simultaneously, it is necessary to monitor the changes in the d-axis and q-axis current components when the external input to the motor undergoes a step change or a ramp change, including the transition time from the initial value to the new stable value, the fluctuation amplitude during the change process, and the deviation between the final stable value and the theoretical value.

[0089] Furthermore, through detailed recording and observation of these changes, key characteristics that reflect the interaction between the current component and other factors are extracted, such as response speed, fluctuation frequency, and stability deviation. These characteristics together constitute the current interaction characteristics of the current component.

[0090] Furthermore, when analyzing the evolution of current interaction characteristics based on real-time operational data, the parameters and operating states in the real-time operational data are correlated with the changes in current interaction characteristics in chronological order. Specifically, when a parameter or state in the real-time operational data changes, it is observed which characteristics of the current interaction characteristics change accordingly, and the direction and extent of the change. For example, when the motor temperature rises, does the response speed of the current interaction characteristics slow down, or does the fluctuation amplitude increase? Through this time-by-time correspondence analysis, the specific ways and patterns of influence of various factors in the real-time operational data on the current interaction characteristics are clarified, thereby determining the strength of each influence, i.e., obtaining the degree of interaction influence of the current interaction characteristics.

[0091] Furthermore, when performing threshold quantification comparison of the interaction impact level, multiple impact thresholds of different levels are first preset based on the motor's design parameters and operating experience. These thresholds correspond to different impact intensity ranges, such as slight impact, moderate impact, and significant impact. The obtained interaction impact level is compared with these preset thresholds one by one to determine which intensity range it falls into. Based on the range it belongs to, a corresponding quantified value is assigned to the interaction impact level; for example, 1 is assigned to the slight impact range, 2 to the moderate impact range, and 3 to the significant impact range. These quantified values ​​can directly reflect the strength of the coupling effect between real-time operating data and current components, which is the real-time coupling impact factor of the permanent magnet synchronous motor.

[0092] In summary, the digital encapsulation of real-time monitored motor parameters and operating status in permanent magnet synchronous motors involves collecting physical signals of various parameters and statuses through sensors, processing them into digital signals, and then encoding them according to a preset format to form structured real-time operating data of the permanent magnet synchronous motor.

[0093] In summary, the interaction assessment of real-time operating data and current components involves bidirectional correlation analysis to determine the specific manifestations and significance of the influence, quantify and classify them, and obtain the real-time coupling influence factor of the permanent magnet synchronous motor that reflects the intensity of the interaction.

[0094] In general, normalizing the real-time coupling influence factors involves determining their value range, then using numerical conversion to unify each influence factor within a set range, eliminating differences in dimensions and magnitudes, and obtaining the adjustment amount of the coupling coefficient of the permanent magnet synchronous motor.

[0095] In summary, the incremental update of the dynamic coupling coefficient based on the adjustment amount of the coupling coefficient is to gradually incorporate the adjustment amount and verify the effect based on the current dynamic coupling coefficient, until it is fully integrated, so as to obtain a more accurate dynamic coupling optimization coefficient of the permanent magnet synchronous motor that reflects the actual situation.

[0096] In summary, the nonlinear superposition of the dynamic coupling optimization coefficient and the current component determines the influence weight of different current components based on their correlation characteristics. The current dynamic coupling component of the permanent magnet synchronous motor that can accurately reflect the nonlinear coupling effect is then calculated according to this weight combination.

[0097] In general, monitoring the dynamic response characteristics of current components involves continuously acquiring the change curves of current components, recording their transition process when external input changes, extracting key features such as response speed and fluctuation amplitude, and obtaining the current interaction characteristics of current components.

[0098] In summary, the evolution analysis of current interaction characteristics based on real-time operating data involves correlating the changes in real-time operating data with the changes in current interaction characteristics at each moment, analyzing the influence of various parameters and states on the characteristics, determining the strength of the influence, and obtaining the degree of interaction influence of current interaction characteristics.

[0099] In general, threshold quantification comparison of the degree of interaction influence involves comparing the degree of interaction influence with preset thresholds of different levels, determining the intensity range to which it belongs, and assigning corresponding quantified values ​​to obtain the real-time coupling influence factor of the permanent magnet synchronous motor.

[0100] S3. Perform dynamic error monitoring and analysis on the dynamic coupling components of the current to obtain the estimated value of the coupling disturbance of the permanent magnet synchronous motor;

[0101] In this embodiment of the invention, the step of performing dynamic error monitoring and analysis on the dynamic coupling component of the current to obtain the estimated value of the coupling disturbance of the permanent magnet synchronous motor includes:

[0102] Waveform feature extraction is performed on the current dynamic coupling component to obtain the fluctuation feature component of the current dynamic coupling component;

[0103] Based on the preset reference disturbance characteristics, the fluctuation characteristic components are matched and analyzed to obtain the dynamic error data of the current dynamic coupling component.

[0104] The dynamic error data is subjected to integrity verification to obtain the coupling disturbance estimate of the permanent magnet synchronous motor. The calculation formula for the coupling disturbance estimate is as follows:

[0105] ;

[0106] In the formula, The estimated value of the coupling disturbance is... This is the scaling factor. It is the arctangent function. The sensitivity coefficient for dynamic error data. This refers to the dynamic error data of the matching result between the fluctuation characteristic component and the reference disturbance characteristic.

[0107] The process of performing matching analysis on the fluctuation characteristic components based on preset reference disturbance characteristics to obtain dynamic error data of the current dynamic coupling component includes:

[0108] The amplitude and frequency variation trends of the wave characteristic components are monitored in real time to obtain the instantaneous characteristics of the wave characteristic components;

[0109] The instantaneous characteristics are compared with the preset reference disturbance characteristics to obtain the deviation patterns of the fluctuation characteristic components;

[0110] Based on the deviation pattern, the degree of matching between the fluctuation characteristic component and the reference disturbance characteristic is analyzed and evaluated to obtain the error index of the deviation pattern;

[0111] The timing consistency of the error index is verified to obtain the dynamic error data of the current dynamic coupling component.

[0112] Specifically, when extracting waveform features from the dynamic coupling component of the current, it is necessary to continuously record the complete waveform of the dynamic coupling component over time. By observing the changes in the waveform segment by segment, key information reflecting its fluctuation characteristics can be extracted. Specifically, the duration of each fluctuation cycle in the waveform is recorded to determine the fluctuation frequency; the difference between the highest and lowest points of the waveform within each cycle is measured to obtain the fluctuation amplitude; the slope changes during the rising and falling phases of the waveform are observed to determine the steepness of the fluctuation; and the location and shape of any abnormal bulges or depressions in the waveform are marked. These extracted information, such as frequency, amplitude, steepness, and abnormal shapes, are integrated into a set of feature parameters, which constitute the fluctuation characteristic components of the dynamic coupling component of the current.

[0113] Furthermore, based on preset reference disturbance characteristics, when performing matching analysis on the fluctuation characteristic components, the preset reference disturbance characteristics refer to the set of waveform characteristics corresponding to typical disturbances measured and summarized through numerous experiments when the motor is running under standard operating conditions. These characteristics include standard fluctuation frequency ranges, amplitude intervals, waveform slope ranges, and standard patterns of common abnormal forms. Each characteristic parameter in the extracted fluctuation characteristic component is compared one by one with the corresponding parameter in the reference disturbance characteristics. For example, the actual fluctuation frequency is compared with the standard frequency range to determine its deviation range; the actual fluctuation amplitude is compared with the standard amplitude interval to calculate its excess or deficiency; and the abnormal form of the actual waveform is compared with the standard abnormal pattern to determine its degree of fit. Based on these comparison results, the specific differences between each characteristic parameter and the reference are recorded. The set of these differences constitutes the dynamic error data of the current dynamic coupling component.

[0114] Furthermore, when verifying the completeness of the dynamic error data, the first step is to check whether the dynamic error data includes the difference values ​​corresponding to all dimensions of the baseline disturbance characteristics, ensuring that no comparison results of any characteristic parameter are omitted. Next, the records of each difference value are checked for clarity and accuracy, without any ambiguity or contradictions. For missing difference values, dynamic error data from adjacent moments within the same time period are searched, and reasonable supplementation is made based on their changing trends. For abnormal difference values ​​that significantly deviate from the normal range, the original waveform of the current dynamic coupling component is reviewed to confirm whether they are caused by a real disturbance. If it is a real disturbance, it is retained; if it is a measurement error, it is corrected. After the above verification and processing, all valid dynamic error data are summarized, and the overall disturbance situation reflected by these data is comprehensively evaluated. The final evaluation result, which comprehensively represents the current magnitude and characteristics of the coupling disturbance, is the estimated value of the coupling disturbance of the permanent magnet synchronous motor.

[0115] Furthermore, It is dynamic error data, which comes from the matching analysis of the fluctuation feature components based on the preset benchmark disturbance features. Specifically, it is the set of specific difference values ​​between each feature parameter and the benchmark after comparing each feature parameter in the fluctuation feature component with the corresponding parameter in the benchmark disturbance feature one by one. It is the sensitivity coefficient of dynamic error data, which comes from the testing and analysis of the motor under different operating conditions. By observing the correlation between the changes in dynamic error data and the actual changes in coupling disturbance under various operating conditions, the coefficient value that can reflect the sensitivity of dynamic error data to coupling disturbance is determined.

[0116] Furthermore, among them This is a scaling factor, derived from calibration using extensive experimental or operational data based on the actual application scenario and required range of the coupled perturbation estimate. It is used to adjust the calculated intermediate results to a numerical range that meets practical needs. The formula's significance lies in using dynamic error data... Combined with its sensitivity coefficient After processing with the arctangent function, the changes in dynamic error data are mapped to a finite and reasonable range, and then a scaling factor is applied. The results are adjusted to the range required for practical applications, ultimately yielding an estimate of the coupling disturbance that can quantify the magnitude of the coupling disturbance in a permanent magnet synchronous motor. This value accurately reflects the degree of disturbance in the dynamic coupling component of the current.

[0117] Specifically, when monitoring the amplitude and frequency trends of a wave characteristic component in real time, it is necessary to continuously collect the amplitude and frequency values ​​of the wave characteristic component at each sampling moment. By comparing the amplitude values ​​at adjacent moments, it is determined whether the amplitude shows an increasing, decreasing, or stable trend. Simultaneously, the frequency values ​​at adjacent moments are compared to determine the frequency trend. During the recording of these values ​​and trends, the time point of each moment is simultaneously marked. The amplitude magnitude, frequency value, and the direction of change of both corresponding to each time point are integrated to form an information set that reflects the state of the wave characteristic component at any instant. This information set is the instantaneous characteristic of the wave characteristic component.

[0118] Furthermore, when performing pattern comparison between instantaneous characteristics and preset reference disturbance features, the preset reference disturbance features include typical instantaneous characteristic patterns of wave characteristic components under standard conditions, specifically including standard amplitude range, standard frequency range, and standard amplitude and frequency variation trend combinations. The amplitude, frequency, and variation trend of the instantaneous characteristics obtained in real time are compared one by one with the corresponding standard range and pattern in the reference disturbance features. For example, it is determined whether the amplitude of the instantaneous characteristics is within the standard amplitude range, whether the frequency conforms to the standard frequency range, and whether the variation trend is consistent with the standard trend. All discrepancies found after comparison are classified and recorded according to categories such as amplitude deviation, frequency deviation, and trend deviation. The deviation manifestations of these classified records are the deviation patterns of the wave characteristic components.

[0119] Furthermore, based on the deviation pattern, when analyzing and evaluating the degree of matching between the fluctuation characteristic components and the benchmark disturbance characteristics, the specific degree of deviation from the benchmark is determined for each type of deviation recorded in the deviation pattern. For example, in amplitude deviation, the specific value by which the actual amplitude exceeds or falls below the standard range; in frequency deviation, the difference between the actual frequency and the standard frequency; and in trend deviation, the duration for which the actual trend is opposite to the standard trend. Based on these specific degrees, the severity of each type of deviation is graded, such as slight deviation, moderate deviation, and severe deviation. The number and total proportion of each type of deviation are then statistically analyzed. These grading results and statistical data are integrated into specific indicators that can quantify the degree of matching between the two; these indicators are the error indicators of the deviation pattern.

[0120] Furthermore, when verifying the temporal consistency of the error indices, the error indices obtained at different times are arranged in chronological order to observe whether their changes show a continuous and reasonable trend. For example, if there is a slight amplitude deviation at one time, does it transition to a moderate amplitude deviation or return to normal at another time, rather than suddenly jumping to a severe frequency deviation? For abrupt error indices, the original data and instantaneous characteristics of the fluctuation characteristic components at the corresponding time are traced back to check whether they are caused by data acquisition errors or instantaneous interference. If they are errors, they are corrected; if they are real disturbances, they are retained. After checking the consistency of the error indices at all times and correcting for anomalies, a complete and consistent sequence of error indices is formed, which is the dynamic error data of the current dynamic coupling component.

[0121] In summary, waveform feature extraction of the dynamic coupling component of the current is achieved by continuously recording its complete waveform over time, extracting key information such as fluctuation frequency, amplitude, steepness, and abnormal morphology, and integrating them into feature parameters to obtain the fluctuation feature component of the dynamic coupling component of the current.

[0122] In summary, matching analysis of the fluctuation characteristic components based on the preset reference disturbance characteristics involves comparing the fluctuation characteristic components with the corresponding parameters in the reference disturbance characteristics one by one, recording the specific differences between the two, and obtaining the dynamic error data of the current dynamic coupling components.

[0123] In summary, the integrity check of dynamic error data involves verifying whether the data is complete and accurate, supplementing missing values ​​and correcting outliers, summarizing valid data to comprehensively assess the disturbance situation, and obtaining the estimated value of the coupling disturbance of the permanent magnet synchronous motor.

[0124] In general, real-time monitoring of the amplitude and frequency trends of wave characteristic components involves continuously collecting amplitude and frequency values ​​at each sampling moment, comparing values ​​at adjacent moments to determine the trend, synchronously marking time points, and integrating the amplitude, frequency, and direction of change at each moment to obtain the instantaneous characteristics of the wave characteristic components that reflect the state of the wave characteristic components at any instant.

[0125] In general, the pattern comparison between instantaneous characteristics and preset reference disturbance characteristics involves comparing the amplitude, frequency and trend of instantaneous characteristics with the corresponding standard range and typical patterns in the reference disturbance characteristics one by one, recording all discrepancies and classifying them according to the deviation category to obtain the deviation patterns of the fluctuation characteristic components.

[0126] In summary, the analysis and evaluation of the matching degree between the fluctuation characteristic components and the benchmark disturbance characteristics based on the deviation model involves determining the specific degree of deviation from the benchmark for each type of deviation in the deviation model, classifying the severity level, and statistically analyzing the number and proportion of deviations. These are then integrated into a quantitative indicator reflecting the matching degree, resulting in the error index of the deviation model.

[0127] In summary, verifying the temporal consistency of error indicators involves arranging the error indicators in chronological order to observe their changing trends, retrospectively correcting abrupt changes in abnormal indicators, forming a complete and coherent sequence of error indicators, and obtaining dynamic error data of the current dynamic coupling component.

[0128] S4. Based on the estimated value of the coupling disturbance and the preset feedforward compensation mechanism, the current component is compensated to obtain the current dynamic correction signal of the permanent magnet synchronous motor.

[0129] In this embodiment of the invention, the step of compensating the current component based on the estimated coupling disturbance value and a preset feedforward compensation mechanism to obtain the current dynamic correction signal of the permanent magnet synchronous motor includes:

[0130] Based on a preset feedforward compensation mechanism, the estimated value of the coupling disturbance is mapped by a strategy to obtain the compensation strategy for the current component.

[0131] The compensation strategy is analyzed to obtain the compensation parameters for the current component;

[0132] Based on the compensation parameters, the current component is compensated and injected to obtain the current dynamic correction signal of the permanent magnet synchronous motor.

[0133] Specifically, based on a preset feedforward compensation mechanism, when mapping the estimated coupling disturbance value using a strategy, the preset feedforward compensation mechanism is a strategy library pre-constructed according to different coupling disturbance degrees of the permanent magnet synchronous motor. This strategy library clearly divides multiple continuous intervals of estimated coupling disturbance values, and each interval uniquely corresponds to a current component compensation method. For example, one interval corresponds to a compensation method that adjusts only the d-axis current component, while another interval corresponds to a compensation method that adjusts both the d-axis and q-axis current components simultaneously. The actual obtained estimated coupling disturbance value is compared one by one with the intervals in the strategy library to determine the specific interval to which the estimated value belongs. Then, the compensation method corresponding to that interval is extracted; this compensation method is the compensation strategy for the current component.

[0134] Furthermore, when analyzing the compensation strategy, it is necessary to break down the compensation method explicitly defined in the strategy. If the compensation strategy only adjusts the d-axis current component, it is necessary to further determine whether the adjustment direction is to increase or decrease, the specific magnitude of a single adjustment, the execution interval of the adjustment operation, and the duration of the entire compensation process. If the compensation strategy adjusts both the d-axis and q-axis current components simultaneously, in addition to determining the adjustment direction, magnitude, frequency, and duration of the d-axis current component as described above, it is also necessary to determine the adjustment direction, magnitude, frequency, and duration of the q-axis current component using the same logic. Integrating these specific information such as adjustment direction, magnitude, frequency, and duration obtained from the breakdown, these information constitute the compensation parameters for the current components.

[0135] Furthermore, when injecting compensation into the current component based on the compensation parameters, the type of current component to be adjusted is first determined according to the compensation parameters. Then, the corresponding current component is numerically adjusted according to the adjustment direction and magnitude in the compensation parameters. For example, if the compensation parameters require a reduction in the q-axis current component with a fixed magnitude, then this fixed value is subtracted from the current q-axis current component. Simultaneously, the adjustment frequency in the compensation parameters is strictly followed, and the above adjustment operation is repeated periodically until the duration specified by the compensation parameters ends. After this compensation injection process, the final adjusted current component is the dynamic current correction signal of the permanent magnet synchronous motor.

[0136] In summary, the strategy mapping of the coupled disturbance estimate based on the preset feedforward compensation mechanism is achieved by comparing the coupled disturbance estimate with the intervals divided in the preset strategy library, determining the interval to which it belongs, extracting the corresponding compensation method, and obtaining the compensation strategy for the current component.

[0137] In summary, strategy analysis of the compensation strategy involves breaking down the compensation methods within the strategy, determining and integrating specific information such as adjustment direction, amplitude, frequency, and duration to obtain the compensation parameters for the current component.

[0138] In summary, the current component compensation injection based on compensation parameters involves determining the type of current component to be adjusted according to the compensation parameters, performing the operation according to the adjustment direction and amplitude, and following the frequency and duration requirements to obtain the current dynamic correction signal of the permanent magnet synchronous motor.

[0139] S5. Based on the voltage control loop of the permanent magnet synchronous motor, the current dynamic correction signal is corrected and superimposed to obtain the control voltage signal of the permanent magnet synchronous motor.

[0140] In this embodiment of the invention, the voltage control loop based on the permanent magnet synchronous motor corrects and superimposes the current dynamic correction signal to obtain the control voltage signal of the permanent magnet synchronous motor, including:

[0141] Based on the voltage control loop of the permanent magnet synchronous motor, the current dynamic correction signal is adjusted to obtain the voltage adjustment amount of the permanent magnet synchronous motor.

[0142] The voltage regulation amount is adapted and superimposed with the current voltage of the voltage control loop to obtain the superimposed voltage signal of the permanent magnet synchronous motor;

[0143] The superimposed voltage signal is subjected to amplitude limiting processing to obtain the control voltage signal of the permanent magnet synchronous motor.

[0144] The voltage control loop based on the permanent magnet synchronous motor performs reference adjustment on the current dynamic correction signal to obtain the voltage adjustment amount of the permanent magnet synchronous motor, including:

[0145] Based on the voltage control loop, the current dynamic correction signal is adaptively adjusted to obtain the reference adjustment signal of the voltage control loop;

[0146] The reference adjustment signal is subjected to phase synchronization processing to obtain the phase synchronization signal of the reference adjustment signal;

[0147] Impedance matching is performed on the phase synchronization signal to obtain the voltage regulation amount of the permanent magnet synchronous motor.

[0148] Specifically, based on the voltage control loop of the permanent magnet synchronous motor, when adjusting the current dynamic correction signal, a standard voltage reference corresponding to different operating conditions of the motor is pre-set within the voltage control loop. This reference clarifies the voltage range required to maintain stable motor operation under each condition. The current adjustment requirement reflected by the current dynamic correction signal is correlated with the standard voltage reference for the corresponding operating condition within the voltage control loop. This determines which direction of voltage adjustment from the voltage control loop is needed to match the standard voltage reference. For example, if the current dynamic correction signal requires an increase in the q-axis current to improve torque, the required increase in the q-axis voltage within the voltage control loop must be determined. Through this correlation and determination, the voltage adjustment value that meets the standard voltage reference requirement is calculated, and this value is the voltage adjustment amount of the permanent magnet synchronous motor.

[0149] Furthermore, when adapting and superimposing the voltage regulation amount with the current voltage of the voltage control loop, the real-time voltage value at the output of the voltage control loop is first acquired through a voltage sensor; this value is the current voltage of the voltage control loop. The superposition method is determined based on the positive or negative attribute of the voltage regulation amount. If the voltage regulation amount is positive, indicating that the current voltage needs to be increased, the current voltage of the voltage control loop is directly added to the voltage regulation amount. If the voltage regulation amount is negative, indicating that the current voltage needs to be decreased, the absolute value of the voltage regulation amount is subtracted from the current voltage of the voltage control loop. During the superposition process, it is necessary to ensure that the dimensions of the voltage regulation amount and the current voltage are consistent to avoid errors in the superposition result due to unit differences. The voltage value obtained after the above superposition operation is the superimposed voltage signal of the permanent magnet synchronous motor.

[0150] Furthermore, when limiting the superimposed voltage signal, the voltage control loop pre-sets an upper and lower voltage limit for safe motor operation. This range is determined based on parameters such as the motor's rated voltage, insulation class, and power module withstand capability, ensuring that the voltage does not exceed the safe bearing range of the motor and related components. The superimposed voltage signal is compared with the preset upper and lower voltage limits. If the superimposed voltage signal is greater than the upper voltage limit, it is forcibly adjusted to the preset upper voltage limit; if the superimposed voltage signal is less than the lower voltage limit, it is forcibly adjusted to the preset lower voltage limit; if the superimposed voltage signal is between the upper and lower voltage limits, it remains unchanged. The voltage signal obtained after this limiting process is the control voltage signal of the permanent magnet synchronous motor.

[0151] Specifically, based on the voltage control loop, when adaptively adjusting the current dynamic correction signal, the voltage control loop pre-sets corresponding adjustment rules according to different operating states of the permanent magnet synchronous motor. These rules clarify the appropriate voltage response logic under different current adjustment requirements. For example, when the current dynamic correction signal requires increasing the q-axis current to increase torque, the rules will instruct the voltage control loop to provide voltage support in the q-axis direction. The specific current adjustment requirements reflected by the current dynamic correction signal are matched one by one with the adjustment rules in the voltage control loop to determine the voltage adjustment logic that meets the current adjustment requirements. Then, based on this logic, a preliminary voltage adjustment signal that can adapt to the current dynamic correction signal is calculated. This preliminary voltage adjustment signal is the reference adjustment signal of the voltage control loop.

[0152] Furthermore, when performing phase synchronization processing on the reference adjustment signal, the rotor's position information is first acquired in real time by an encoder installed on the motor rotor. The real-time phase of the rotor is determined based on this position information; this phase is the target phase that the reference adjustment signal needs to synchronize with. The current phase of the reference adjustment signal is compared with the real-time rotor phase, and the phase difference between the two is calculated. If the reference adjustment signal phase leads the real-time rotor phase, the reference adjustment signal is appropriately delayed using a delay circuit. If the reference adjustment signal phase lags behind the real-time rotor phase, the reference adjustment signal is advanced using an advance trigger circuit. This adjustment is repeated until the phase of the reference adjustment signal is completely consistent with the real-time rotor phase. The signal obtained at this point is the phase synchronization signal of the reference adjustment signal.

[0153] Furthermore, when performing impedance matching on the phase synchronization signal, the equivalent impedance of the voltage control loop output is first measured using an impedance measuring instrument. This equivalent impedance includes line impedance, motor stator winding impedance, etc. The measured value is the target impedance to be matched. The output impedance of the phase synchronization signal is compared with the target impedance. If the output impedance of the phase synchronization signal is greater than the target impedance, a suitable impedance attenuation element is connected in series in the transmission path of the phase synchronization signal to reduce the output impedance. If the output impedance of the phase synchronization signal is less than the target impedance, a suitable impedance compensation element is connected in parallel in the transmission path to increase the output impedance. This adjustment continues until the output impedance of the phase synchronization signal is completely equal to the equivalent impedance of the voltage control loop output. At this point, the voltage value corresponding to the phase synchronization signal after impedance matching is the voltage regulation amount of the permanent magnet synchronous motor.

[0154] In summary, the voltage control loop of the permanent magnet synchronous motor performs reference adjustment on the current dynamic correction signal by processing the current dynamic correction signal through the adjustment mechanism of the voltage control loop to make it meet the reference requirements of the voltage control loop, thereby obtaining the voltage adjustment amount of the permanent magnet synchronous motor.

[0155] In summary, adapting and superimposing the voltage regulation amount with the current voltage of the voltage control loop involves superimposing the voltage regulation amount with the real-time acquired current voltage in an adaptive manner to obtain the superimposed voltage signal of the permanent magnet synchronous motor.

[0156] In general, the amplitude limiting process for the superimposed voltage signal involves comparing the superimposed voltage signal with a preset safe voltage range. If the signal exceeds the range, it is adjusted to the boundary value to obtain the control voltage signal for the permanent magnet synchronous motor.

[0157] In summary, adaptive adjustment of the current dynamic correction signal based on the voltage control loop is achieved by matching the current adjustment requirements reflected by the current dynamic correction signal with the adjustment rules corresponding to different operating states preset within the voltage control loop, determining the appropriate voltage adjustment logic, calculating the preliminary voltage adjustment signal, and obtaining the reference adjustment signal of the voltage control loop.

[0158] In general, phase synchronization processing of the reference adjustment signal involves acquiring the real-time phase of the rotor through an encoder, comparing the current phase of the reference adjustment signal with the real-time phase of the rotor, and adjusting the phase through a delay or advance triggering circuit until the two are consistent, thus obtaining the phase synchronization signal of the reference adjustment signal.

[0159] In general, impedance matching of the phase synchronization signal involves measuring the equivalent impedance of the voltage control loop output terminal with an impedance measuring instrument as the target impedance, comparing the output impedance of the phase synchronization signal with the target impedance, and adjusting the impedance components in series or parallel until they are equal to obtain the voltage regulation amount of the permanent magnet synchronous motor.

[0160] S6. Pulse width modulation is performed on the control voltage signal to obtain the inverter control signal of the permanent magnet synchronous motor.

[0161] In this embodiment of the invention, the step of pulse width modulation of the control voltage signal to obtain the inverter control signal for the permanent magnet synchronous motor includes:

[0162] The control voltage signal is pulse-width modulated to obtain the pulse duty cycle signal of the controlled voltage signal;

[0163] The pulse duty cycle signal is level-converted to obtain the electrical drive signal of the control voltage signal;

[0164] Based on the preset electrical isolation characteristics, the electrical drive signal is configured with a dead time to obtain the inverter control signal of the magnetic synchronous motor.

[0165] Specifically, when pulse width modulation is performed on the control voltage signal to obtain the pulse duty cycle signal of the controlled voltage signal, a triangular wave signal with a fixed frequency is first generated. The frequency of this triangular wave signal is consistent with the switching frequency of the inverter's switching transistors. The control voltage signal and the triangular wave signal are compared in real time. When the instantaneous value of the control voltage signal is higher than the instantaneous value of the triangular wave signal, a high-level signal is output; when the instantaneous value of the control voltage signal is lower than the instantaneous value of the triangular wave signal, a low-level signal is output. The duration of the high-level signal within one triangular wave cycle and the total time of the entire cycle are continuously recorded. By calculating the ratio of the high-level duration to the total cycle time, a periodic pulse signal reflecting the magnitude of the control voltage signal is formed. This periodic pulse signal is the pulse duty cycle signal of the controlled voltage signal.

[0166] Furthermore, when performing level conversion on the pulse duty cycle signal to obtain the electrical drive signal for the control voltage signal, the drive level requirements of the inverter switching transistor are first determined. Typically, the inverter switching transistor requires a relatively high drive level to achieve reliable conduction. The current pulse duty cycle signal level range is observed. If its level is lower than the drive requirement of the inverter switching transistor, the pulse duty cycle signal is connected to a level conversion circuit. This circuit, through transistor amplification or a dedicated level conversion chip, boosts the low-level pulse duty cycle signal to a high level that meets the drive requirements of the inverter switching transistor, while maintaining the pulse signal's duty cycle unchanged. The pulse signal obtained after level conversion, which can directly drive the inverter switching transistor, is the electrical drive signal for the control voltage signal.

[0167] Furthermore, based on preset electrical isolation characteristics, a dead-time configuration is applied to the electrical drive signal to obtain the inverter control signal for the magnetic synchronous motor. The preset electrical isolation characteristics include a safety rule that the upper and lower bridge arm switches of the inverter cannot be turned on simultaneously, and a time interval requirement to ensure isolation performance. A dead-time generation module is integrated into the transmission path of the electrical drive signal. This module monitors the switching moments between high and low levels in the electrical drive signal. When it detects that the upper bridge arm electrical drive signal is about to switch from high to low and the lower bridge arm is about to switch from low to high, a brief low-level time is inserted between the two switching events. Similarly, when the lower bridge arm switches to low and the upper bridge arm switches to high, a low-level time of the same duration is also inserted. This inserted low-level time is the dead time, used to prevent a short circuit caused by the simultaneous turn-on of the upper and lower bridge arm switches due to switching delays. The electrical drive signal after dead-time configuration becomes the inverter control signal for the magnetic synchronous motor.

[0168] In general, pulse width modulation of the control voltage signal involves comparing the control voltage signal with a fixed-frequency triangular wave in real time, outputting high and low level signals, and calculating the ratio of the high level duration to the period to obtain the pulse duty cycle signal of the control voltage signal.

[0169] In general, level conversion of the pulse duty cycle signal involves using a level conversion circuit to boost the pulse duty cycle signal to a level that meets the driving requirements of the inverter's switching transistors, while maintaining the duty cycle, to obtain the electrical drive signal for the control voltage signal.

[0170] In summary, configuring the dead time of the electrical drive signal based on the preset electrical isolation characteristics is to insert a brief low-level time when the electrical drive signal is switched to prevent the upper and lower bridge arm switches from conducting simultaneously, thereby obtaining the inverter control signal for the permanent magnet synchronous motor.

[0171] In the several embodiments provided by this invention, it should be understood that the disclosed method can be implemented in other ways.

[0172] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0173] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0174] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for dynamic coupling correction of current in a permanent magnet synchronous motor of an electric drive bridge system, characterized in that, The method includes: S1. Decouple the three-phase current signal of the permanent magnet synchronous motor to obtain the current component of the permanent magnet synchronous motor. S2. Based on the current component and the motor parameters and operating status monitored in real time in the permanent magnet synchronous motor, the dynamic coupling coefficient of the permanent magnet synchronous motor is updated in real time to obtain the current dynamic coupling component of the permanent magnet synchronous motor. S3. Perform dynamic error monitoring and analysis on the dynamic coupling components of the current to obtain the estimated value of the coupling disturbance of the permanent magnet synchronous motor; S4. Based on the estimated value of the coupling disturbance and the preset feedforward compensation mechanism, the current component is compensated to obtain the current dynamic correction signal of the permanent magnet synchronous motor. S5. Based on the voltage control loop of the permanent magnet synchronous motor, the current dynamic correction signal is corrected and superimposed to obtain the control voltage signal of the permanent magnet synchronous motor. S6. Pulse width modulation is performed on the control voltage signal to obtain the inverter control signal of the permanent magnet synchronous motor.

2. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The process of decoupling the three-phase current signal of the permanent magnet synchronous motor to obtain the current components of the permanent magnet synchronous motor includes: The three-phase current signal in the permanent magnet synchronous motor is acquired in real time to obtain the three-phase current data of the permanent magnet synchronous motor. The three-phase current data is subjected to a rotating coordinate system transformation to obtain the coordinate axis current components of the three-phase current data. The current components of the permanent magnet synchronous motor are obtained by dynamically coupling and separating the current components of the coordinate axes.

3. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The process of updating the dynamic coupling coefficient of the permanent magnet synchronous motor in real time based on the current component and the motor parameters and operating status monitored in real time, to obtain the current dynamic coupling component of the permanent magnet synchronous motor, includes: The motor parameters and operating status monitored in real time in the permanent magnet synchronous motor are digitally encapsulated to obtain the real-time operating data of the permanent magnet synchronous motor; The interaction between the real-time operating data and the current component is evaluated to obtain the real-time coupling influence factor of the permanent magnet synchronous motor. The real-time coupling influence factor is normalized to obtain the coupling coefficient adjustment amount of the permanent magnet synchronous motor; Based on the aforementioned coupling coefficient adjustment, the dynamic coupling coefficient of the permanent magnet synchronous motor is progressively updated to obtain the dynamic coupling optimization coefficient of the permanent magnet synchronous motor. The dynamic coupling optimization coefficient and the current component are nonlinearly superimposed to obtain the current dynamic coupling component of the permanent magnet synchronous motor.

4. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 3, characterized in that, The evaluation of the interaction between the real-time operating data and the current component to obtain the real-time coupling influence factor of the permanent magnet synchronous motor includes: The dynamic response characteristics of the current component are monitored to obtain the current interaction characteristics of the current component; Based on the real-time operating data, the evolution analysis of the current interaction characteristics is performed to obtain the degree of interaction influence of the current interaction characteristics. The degree of interaction influence is compared by threshold quantization to obtain the real-time coupling influence factor of the permanent magnet synchronous motor.

5. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The step of performing dynamic error monitoring and analysis on the dynamic coupling components of the current to obtain the estimated value of the coupling disturbance of the permanent magnet synchronous motor includes: Waveform feature extraction is performed on the current dynamic coupling component to obtain the fluctuation feature component of the current dynamic coupling component; Based on the preset reference disturbance characteristics, the fluctuation characteristic components are matched and analyzed to obtain the dynamic error data of the current dynamic coupling component. The dynamic error data is subjected to integrity verification to obtain the coupling disturbance estimate of the permanent magnet synchronous motor. The calculation formula for the coupling disturbance estimate is as follows: ； In the formula, The estimated value of the coupling disturbance is... This is the scaling factor. It is the arctangent function. The sensitivity coefficient for dynamic error data. This refers to the dynamic error data of the matching result between the fluctuation characteristic component and the reference disturbance characteristic.

6. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 5, characterized in that, The process of performing matching analysis on the fluctuation characteristic components based on preset reference disturbance characteristics to obtain dynamic error data of the current dynamic coupling component includes: The amplitude and frequency variation trends of the wave characteristic components are monitored in real time to obtain the instantaneous characteristics of the wave characteristic components; The instantaneous characteristics are compared with the preset reference disturbance characteristics to obtain the deviation patterns of the fluctuation characteristic components; Based on the deviation pattern, the degree of matching between the fluctuation characteristic component and the reference disturbance characteristic is analyzed and evaluated to obtain the error index of the deviation pattern; The timing consistency of the error index is verified to obtain the dynamic error data of the current dynamic coupling component.

7. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The step of compensating the current component based on the estimated coupling disturbance and a preset feedforward compensation mechanism to obtain the dynamic current correction signal of the permanent magnet synchronous motor includes: Based on a preset feedforward compensation mechanism, the estimated value of the coupling disturbance is mapped by a strategy to obtain the compensation strategy for the current component. The compensation strategy is analyzed to obtain the compensation parameters for the current component; Based on the compensation parameters, the current component is compensated and injected to obtain the current dynamic correction signal of the permanent magnet synchronous motor.

8. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The voltage control loop based on the permanent magnet synchronous motor corrects and superimposes the current dynamic correction signal to obtain the control voltage signal for the permanent magnet synchronous motor, including: Based on the voltage control loop of the permanent magnet synchronous motor, the current dynamic correction signal is adjusted to obtain the voltage adjustment amount of the permanent magnet synchronous motor. The voltage regulation amount is adapted and superimposed with the current voltage of the voltage control loop to obtain the superimposed voltage signal of the permanent magnet synchronous motor; The superimposed voltage signal is subjected to amplitude limiting processing to obtain the control voltage signal of the permanent magnet synchronous motor.

9. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 8, characterized in that, The voltage control loop based on the permanent magnet synchronous motor performs reference adjustment on the current dynamic correction signal to obtain the voltage adjustment amount of the permanent magnet synchronous motor, including: Based on the voltage control loop, the current dynamic correction signal is adaptively adjusted to obtain the reference adjustment signal of the voltage control loop; The reference adjustment signal is subjected to phase synchronization processing to obtain the phase synchronization signal of the reference adjustment signal; Impedance matching is performed on the phase synchronization signal to obtain the voltage regulation amount of the permanent magnet synchronous motor.

10. The method for dynamic coupling correction of permanent magnet synchronous motor current in an electric drive bridge system as described in claim 1, characterized in that, The step of pulse width modulation of the control voltage signal to obtain the inverter control signal for the permanent magnet synchronous motor includes: The control voltage signal is pulse-width modulated to obtain the pulse duty cycle signal of the control voltage signal; The pulse duty cycle signal is level-converted to obtain the electrical drive signal of the control voltage signal; Based on the preset electrical isolation characteristics, the electrical drive signal is configured with a dead time to obtain the inverter control signal of the permanent magnet synchronous motor.

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