Motor pump all-in-one machine combined control method and system

Abstract

The invention relates to the field of pump control, in particular to a joint control method and system for a motor-pump all-in-one machine, and the method comprises the steps: collecting multi-source sensor data and equipment configuration parameters of the motor-pump all-in-one machine, carrying out the preprocessing of the collected data, and constructing a state feature vector; state analysis and dynamic weighted compensation are carried out based on the state feature vector, and a compensation torque considering the response speed and the suppression capability is generated by constructing an effective adjustment intensity coefficient and a disturbance separation factor; the compensation torque is superimposed to the speed loop output to generate a final motor torque command. The control logic conflict caused by the fact that a traditional observer cannot distinguish an expected load from unknown disturbance is solved, and high dynamic response and high stability are both considered.

Description

Technical Field

[0001] This invention relates to the field of pump control. More specifically, this invention relates to a combined control method and system for an integrated motor-pump unit. Background Technology

[0002] The integrated motor-pump unit combines a servo motor, driver, and hydraulic pump into a single power unit. It employs a dual closed-loop control architecture: the inner loop controls the motor speed, and the outer loop controls the hydraulic output. In actual operation, changes in motor output torque originate from two different sources: one is the desired load change due to process requirements, which the motor must actively follow; the other is unknown disturbances such as system friction, leakage, or external impacts, which need to be suppressed.

[0003] Existing technologies typically employ extended state observers to estimate and compensate for system disturbances. However, this method treats all load changes uniformly as disturbances that need to be suppressed. In the control scenario of an integrated motor-pump system, the observer cannot distinguish between desired loads and unknown disturbances, misinterpreting normal pressure increases as disturbances for suppression, making it difficult to achieve effective suppression while maintaining dynamic response. Summary of the Invention

[0004] To address the technical problem that the aforementioned observers cannot distinguish between desired loads and unknown disturbances, misinterpreting normal pressure rises as disturbances and thus failing to suppress them effectively while maintaining dynamic response, this invention provides solutions in the following aspects.

[0005] In the first aspect, a combined control method for an integrated motor-pump unit includes: Collect multi-source sensor data and equipment configuration parameters of the integrated motor-pump machine, preprocess the collected data, and construct a state feature vector; Based on the real-time flow rate, target flow rate, current pressure, and inherent parameters of the motor in the state feature vector, the flow deviation factor, motor efficiency calibration factor, and pressure safety constraint factor are determined. The effective regulation intensity coefficient is obtained by multiplying the flow deviation factor, motor efficiency calibration factor, and pressure safety constraint factor. Based on the actual torque change rate, pressure change rate, displacement conversion coefficient, and effective adjustment intensity coefficient in the state feature vector, the predicted value of the expected torque change rate is calculated. Based on the residual between the actual torque change rate and the predicted value of the expected torque change rate, and the total energy of the actual torque change rate and the predicted value of the expected torque change rate, a disturbance separation factor is constructed to characterize the proportion of unknown disturbance in torque change. Based on the current pressure and displacement conversion coefficient in the state feature vector, the feedforward torque is calculated, and the total disturbance torque estimated by the extended state observer and the feedforward torque are weighted and fused together using the disturbance separation factor as the weight to construct the compensation torque. The compensated torque is superimposed on the base torque command output by the speed loop to generate the final motor torque command, which is then output to the servo drive unit for execution.

[0006] Optionally, the collected data includes: The system collects operating pressure, motor rotor position and speed, motor three-phase current, real-time system flow rate, and target flow rate analyzed from the upper-level controller. Read the inherent parameters of the motor from the non-volatile storage area. The inherent parameters of the motor include the rated torque of the motor, the rated current of the motor, the torque constant of the motor, the reference pressure, the maximum working pressure, the pressure-displacement mapping parameter set containing multiple calibrated pressure levels corresponding to the oil pump displacement values, and the displacement corresponding to the reference pressure.

[0007] Optionally, preprocessing the collected data includes: The collected system operating pressure, motor three-phase current and system real-time flow are filtered. Based on the motor rotor position and the motor three-phase current, a vector transformation algorithm is applied to calculate the motor's current actual output torque; interpolation processing is performed on the pressure-displacement mapping parameter set to establish a continuous pressure-displacement function, and the displacement conversion coefficient is calculated based on the pressure-displacement function; The target rotational speed is calculated based on the target flow rate and the actual displacement under the current pressure. Based on the actual output torque and pressure sequence of the current control cycle and several previous control cycles, the actual torque change rate and pressure change rate are calculated.

[0008] Optionally, the flow deviation factor is the result of dividing the absolute value of the difference between the real-time flow and the target flow by the target flow. The motor efficiency calibration factor is the result of dividing the motor's rated torque in the motor's inherent parameters by the product of the motor's torque constant and the motor's rated current. The pressure safety constraint factor is the result of dividing the difference between the maximum working pressure and the current pressure by the difference between the maximum working pressure and the reference pressure.

[0009] Optionally, the construction of the perturbation separation factor includes: The absolute value of the difference between the actual torque change rate and the predicted value of the expected torque change rate is taken as the torque change residual term; the predicted value of the expected torque change rate is the product of the effective adjustment intensity coefficient, the absolute value of the pressure change rate, and the displacement conversion coefficient. The sum of the absolute value of the actual torque change rate and the predicted value of the expected torque change rate is used as the energy normalization term; The disturbance separation factor is obtained by dividing the torque change residual by the energy normalization term.

[0010] Optionally, generating the final motor torque command also includes: The final generated motor torque command is then limited. The motor torque command after amplitude limiting is smoothed and filtered.

[0011] Optionally, the estimation of the total disturbance torque includes: Using the actual output torque and motor speed in the state feature vector as input, the total disturbance torque of the system is estimated in real time through a pre-designed extended state observer algorithm.

[0012] In a second aspect, a combined control system for an integrated motor and pump includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the combined control method for the integrated motor and pump described in any one of the claims is implemented.

[0013] The present invention has the following beneficial effects: 1. This invention constructs a unified state feature vector, and based on this vector, sequentially determines the effective adjustment intensity coefficient, constructs a disturbance separation factor, and dynamically weights and fuses the feedforward torque and observer torque, ultimately generating a compensation torque that is superimposed on the speed loop output, forming a complete multi-source data fusion and dynamic weighted compensation mechanism. This mechanism can analyze online the respective proportions of desired load and unknown disturbance in the current torque change. When the desired load dominates, the compensation torque is mainly contributed by the feedforward torque calculated based on pressure, ensuring that the motor torque quickly and actively follows the load change, solving the response lag problem caused by the misjudgment of load in traditional observers. When the unknown disturbance dominates, the compensation torque is mainly contributed by the total disturbance torque estimated by the extended state observer, and the observer fully suppresses the disturbance, ensuring the stability of the system. This mechanism fundamentally solves the control logic conflict caused by the inability of traditional extended state observers to distinguish between desired load and unknown disturbance, while simultaneously meeting the dual requirements of high dynamic response performance and high stability.

[0014] 2. By introducing a motor efficiency calibration factor into the effective adjustment strength coefficient, this invention eliminates the efficiency inconsistency caused by differences in electromagnetic design and mechanical processes among different motor models. This makes the calculation benchmark of the effective adjustment strength coefficient universal across motors of different power and series, achieving parameter self-adaptation of the algorithm. It eliminates the need for cumbersome on-site parameter tuning for different models of equipment, significantly reducing the workload of debugging. Attached Figure Description

[0015] Figure 1 This is a flowchart of steps S1-S3 in a combined control method for an integrated motor and pump according to an embodiment of the present invention.

[0016] Figure 2 This is a flowchart illustrating the acquisition of compensation torque in a combined control method for an integrated motor and pump according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0018] This invention relates to a power unit comprising a permanent magnet synchronous servo motor, a servo driver, and a hydraulic pump. Typical applications include hydraulic machinery such as injection molding machines, die-casting machines, and bending machines, which require both rapid response and steady-state pressure holding capabilities. The control cycle involved in this invention is set as the execution cycle of the current loop and speed loop of the servo drive unit, typically ranging from 0.125ms to 1ms, with the specific value depending on the processing power of the hardware platform.

[0019] Reference Figure 1 A combined control method for an integrated motor-pump machine includes steps S1-S3, as detailed below: S1: Collect multi-source sensor data and equipment configuration parameters, preprocess and extract features from all collected data, and construct a unified state feature vector for state observation.

[0020] In the dual-closed-loop control architecture of the integrated motor-pump system, accurate sensing of motor and hydraulic states is a physical prerequisite for precise control. However, the raw sensor signals inevitably contain high-frequency noise and electromagnetic interference—diaphragm vibration of pressure sensors, switching noise of current sampling circuits. Directly using instantaneous values ​​for calculation amplifies single-point noise, leading to misjudgments in subsequent identification algorithms. Furthermore, pressure and torque belong to different physical dimensions and cannot be directly algebraically calculated; flow deviations also need to eliminate differences in magnitude under different operating conditions. Therefore, it is necessary to systematically clean, transform, and extract features from multi-source heterogeneous data to provide a clean, synchronous input dataset with clear physical meaning.

[0021] Furthermore, within each control cycle, the following operations are performed: Step 1, Real-time Acquisition of Multi-Source Data: Using a sampling clock synchronized with the aforementioned control cycle as a reference, the following data are acquired in parallel: Hydraulic load data: The system operating pressure is collected by a pressure sensor installed on the outlet flange of the hydraulic pump.

[0022] Motor motion data: The rotor position and speed of the motor are collected through the encoder built into the servo motor.

[0023] Electromagnetic load data: The three-phase current of the motor is collected through the current sampling circuit of the servo drive unit.

[0024] Flow supply and demand data: The real-time flow of the hydraulic system is collected through the flow detection unit of the hydraulic system, which represents the actual supply capacity of the hydraulic circuit; and the target flow is parsed from the command bus of the upper-level controller, which represents the process expectation target of the hydraulic circuit.

[0025] Equipment inherent attributes: Read equipment nameplate parameters and calibration data from the non-volatile storage area of ​​the drive unit, including: motor rated torque, motor rated current, motor torque constant, reference pressure, maximum working pressure, pressure-displacement mapping parameter set (containing oil pump displacement values ​​corresponding to multiple calibration pressure levels) and displacement corresponding to the reference pressure.

[0026] The second step is data preprocessing and feature extraction: Low-pass filtering noise reduction: A low-pass filter with an appropriate cutoff frequency is used to filter pressure, current, and real-time flow. This aims to effectively suppress high-frequency noise from the sensor and electromagnetic interference caused by the switching of power devices, while accurately preserving the effective low-frequency signal that reflects the essential changes in the load. The selection of the cutoff frequency should balance noise suppression effectiveness with signal fidelity, with typical values ​​ranging from 30Hz to 100Hz.

[0027] Dimensional conversion of physical quantities: Based on the motor rotor position and the motor three-phase current, a vector transformation algorithm is applied to calculate the current actual output torque of the motor, which is the product of the motor torque constant and the transformed quadrature axis current component.

[0028] Interpolation is performed on the pressure-displacement mapping parameter set to establish a continuous pressure-displacement function. This function reflects a core physical characteristic of the hydraulic pump—the actual displacement changes with working pressure: as pressure increases, internal leakage increases and the compressibility of the oil increases, leading to a decrease in actual displacement. Through interpolation (such as linear interpolation or spline interpolation), the actual displacement corresponding to any pressure can be obtained, and the displacement conversion coefficient can be derived, which is the actual displacement corresponding to the pressure divided by 2. .

[0029] Based on the target flow rate and the actual displacement under the current pressure, the target speed is calculated according to the physical relationship between flow rate, rotational speed and displacement (which can accurately reflect the process requirements and automatically compensate for the impact of pressure changes on displacement).

[0030] Dynamic feature extraction and processing: In order to obtain stable system dynamic features, the instantaneous difference method, which is susceptible to noise interference, is abandoned. Instead, the sliding window linear regression method is adopted to extract the actual output torque and pressure sequences of the current control cycle and several previous control cycles (e.g., 5 to 20). The least squares method is applied to fit a straight line, and the slope of the fitted line is the actual output torque change rate and pressure change rate of the current control cycle.

[0031] Timing alignment: Based on the control cycle clock, all processed data are timestamped to ensure that all parameters within the same control cycle have a unified time base, thus avoiding calculation errors caused by timing misalignment.

[0032] In summary, all the data processed through the above acquisition, filtering, transformation, extraction, and alignment steps are encapsulated into a unified state feature vector, which serves as the standard input for subsequent steps. This state feature vector contains the following three types of information: Real-time status variables include filtered system operating pressure, motor speed, target speed, actual output torque, real-time flow rate, and target flow rate. These parameters constitute a static snapshot of the system at the current moment.

[0033] Conversion parameters include the continuous pressure-displacement function, displacement conversion coefficients, and a set of inherent device parameters read from storage. These parameters form the bridge and benchmark for physical model calculations, enabling physical quantities with different dimensions to be integrated and calculated within the same mathematical framework.

[0034] Dynamic characteristics: These include the actual rate of change of output torque and the rate of change of pressure during the current control cycle. These parameters characterize the dynamic evolution trend of the system and are key features for subsequent identification of load sources.

[0035] Furthermore, using parameters such as the actual output torque and motor speed from the aforementioned state feature vector as input, a pre-designed extended state observer algorithm is used to estimate the total disturbance torque of the system in real time. This total disturbance torque integrates the lumped effect of all factors not described by the model—including the hydraulic pump load torque, internal system friction, oil leakage, and external impacts. The observer can be designed using a conventional linear extended state observer or a nonlinear extended state observer; the selection of parameters such as bandwidth requires a trade-off between estimation speed and noise sensitivity.

[0036] S2: Based on the state feature vector, state analysis and dynamic weighted compensation are performed. By constructing an effective adjustment intensity coefficient and disturbance separation factor, a compensation torque that balances response speed and suppression capability is generated.

[0037] The above S1 obtains a unified state feature vector including real-time state variables, transformation parameters, and dynamic feature variables. However, to achieve precise control using this information, it is necessary not only to address the fundamental shortcomings of traditional extended state observers: treating all factors causing torque changes, whether the desired load caused by process instructions or external disturbances caused by friction leakage, as a "total disturbance" and suppressing them in the opposite direction, but also to accurately analyze the current state of the system: whether it is in a dynamic adjustment period that requires rapid response or a disturbance period that requires stable suppression; and whether the current torque change is the desired load required by the process or an unknown disturbance that needs to be suppressed.

[0038] Specifically, refer to Figure 2 The process of analyzing the system state and generating compensation torque includes S20-S22: S20: Determine the regulation intention and safety constraints based on the state feature vector, and construct an effective regulation intensity coefficient.

[0039] Before deciding on a control strategy, it is essential to understand the current operating context. The actual output torque adjustment requirement of the motor depends not only on the flow deviation but also on the system pressure level. Traditional methods evaluate these two factors independently, severing their physical coupling and increasing the complexity of parameter tuning.

[0040] The aforementioned state feature vector already includes real-time flow rate, target flow rate, current pressure, and inherent motor parameters. Based on these parameters, the effective regulation strength coefficient is calculated. This effective regulation strength coefficient is obtained by multiplying three factors with clearly defined physical meanings, satisfying the following relationship: In the formula, To effectively adjust the strength coefficient, For flow deviation factor, This is the motor efficiency calibration factor. This is the pressure safety constraint factor.

[0041] Among them, the flow deviation factor is the result of dividing the absolute value of the difference between the real-time flow and the target flow by the target flow. This flow deviation factor increases with the increase of the flow difference, purely reflecting the intensity of the system's dynamic adjustment intention. The motor efficiency calibration factor is the result of dividing the motor's rated torque by the product of the motor torque constant and the motor's rated current. The product of the motor torque constant and the motor rated current represents the theoretical electromagnetic torque under rated operating conditions. The ratio calculation reflects the energy conversion efficiency of the motor. The pressure safety constraint factor is the difference between the maximum working pressure and the current pressure, divided by the difference between the maximum working pressure and the reference pressure. When the current pressure is much lower than the maximum working pressure, this pressure safety constraint factor is close to 1 or greater than 1, indicating that the adjustment space is sufficient. When the current pressure approaches the upper limit, this pressure safety constraint factor approaches 0, forcibly suppressing the adjustment intensity to prioritize safety.

[0042] The aforementioned effective regulation intensity coefficient is a dimensionless comprehensive index that reflects the urgency of the system response flow deviation within the current pressure safety boundary. The larger the value, the more likely the system is in a safe phase that urgently needs dynamic adjustment. The smaller the value, the more likely the system is in a steady state or under high pressure and risk, and stability should be given priority.

[0043] S21: Based on the state feature vector and the constructed effective adjustment intensity coefficient, analyze the deviation between the actual and expected torque change rate, and construct the disturbance separation factor.

[0044] The expected load change caused by process regulation will inevitably be accompanied by predictable pressure change, and its intensity should be constrained by the current effective regulation intensity coefficient, while the torque change caused by unknown disturbance has a weak correlation with pressure change.

[0045] The aforementioned state feature vector already includes the actual torque change rate, pressure change rate, and displacement conversion coefficient. Based on these parameters and the effective adjustment intensity coefficient in S20 above, the disturbance separation factor is calculated, satisfying the following relationship: In the formula, The perturbation separation factor, For the torque variation residual term, For energy normalization term, It is a small constant to prevent the denominator from being 0.

[0046] The torque variation residual term is the absolute value of the difference between the absolute value of the actual output torque variation rate and the product of the effective regulation strength coefficient, the absolute value of the pressure variation rate, and the displacement conversion coefficient (this product can be labeled as the predicted value of the expected torque variation rate). By multiplying the pressure variation rate by the displacement conversion coefficient, the pressure variation rate is converted into the theoretical torque variation rate. After correction by the effective regulation strength coefficient, the torque variation component that should be regarded as the expected load under the current operating conditions is quantified. The larger the torque variation residual term, the more of the actual variation cannot be explained by process regulation, that is, the higher the possibility that unknown disturbances dominate.

[0047] The energy normalization term is the sum of the products of the absolute value of the actual output torque change rate, the effective regulation strength coefficient, the absolute value of the pressure change rate, and the displacement conversion coefficient, representing the total dynamic energy of the system at present.

[0048] By dividing the torque change residual term by the energy normalization term, the effective regulation strength coefficient is smoothly compressed into the range of 0 to 1, making the disturbance proportions under different amplitude conditions comparable. When the effective regulation strength coefficient approaches 0, it indicates that the actual torque change is highly consistent with the expected prediction, and the system dynamics are mainly dominated by the expected load; when the effective regulation strength coefficient approaches 1, it indicates that the actual torque change far exceeds the expected prediction, and the system dynamics are mainly dominated by unknown disturbances.

[0049] S22: Based on the state feature vector and the disturbance separation factor, the feedforward torque and the observer torque are dynamically weighted and fused to construct the compensation torque.

[0050] Although the proportion of unknown disturbances has been analyzed using the disturbance separation factor, a specific execution mechanism is still needed to translate it into control commands. Traditional strategies either use feedforward (fast response but poor robustness) or observer feedback (strong robustness but slow response).

[0051] Therefore, a "fusionist" is needed that can seamlessly switch between the two strategies based on real-time indications of the perturbation analysis factors.

[0052] The aforementioned state feature vector already includes the current pressure and displacement conversion coefficients. Therefore, the product of the current pressure and displacement conversion coefficients is used as the feedforward torque. Furthermore, based on the total disturbance torque obtained in S1, and using the disturbance separation factor as the weight, the final compensation torque is calculated, satisfying the following relationship: In the formula, To compensate for torque, The perturbation separation factor, The total disturbance torque is... This is the feedforward torque.

[0053] Through the above operations, the final compensation torque is obtained. Under the condition where the desired load dominates, the compensation torque mainly follows the feedforward to ensure a fast dynamic response. Under the condition where the unknown disturbance dominates, the compensation torque mainly follows the observer to ensure the system's disturbance rejection capability.

[0054] S3: Add the compensation torque to the speed loop output to generate the final motor torque command.

[0055] The compensation torque generated by S2 above is an adaptive correction to the total output torque of the motor. The specific correction process is as follows: The speed loop regulator of the servo drive unit typically uses a PID (Proportional-Integral-Derivative) control algorithm to calculate the basic torque command used to maintain speed tracking based on the actual motor speed and target speed generated by S1.

[0056] Furthermore, the compensation torque generated by S2 is added to the basic torque command to obtain the final motor torque command, realizing the coordinated operation of conventional control and intelligent compensation.

[0057] In addition, the final motor torque command is numerically limited to ensure that it does not exceed the maximum allowable torque of the motor (including rated torque and short-term overload capacity), protecting the motor and drive from electrical or mechanical overload. Furthermore, the limited motor torque command is subjected to low-pass filtering or rate limiting to suppress abrupt changes in the command, making the change in motor torque output smoother and reducing the impact and vibration on the hydraulic system.

[0058] The motor torque command, after being limited and smoothed, is converted into a corresponding switching signal by the PWM (Pulse Width Modulation) module of the servo drive unit, driving the inverter power devices and precisely controlling the motor output torque.

[0059] At the end of this control cycle, the key state data of this operation is stored in the driver's circular history buffer. This data will become the input for the sliding window differential calculation of S1 in the next control cycle, thus forming a complete closed-loop feedback system. At the beginning of the next control cycle, the system restarts from S1.

[0060] The present invention also provides a combined control system for an integrated motor and pump. The system includes a processor and a memory, the memory storing computer program instructions. When the processor executes the computer program instructions, it implements the combined control method for the integrated motor and pump according to the first aspect of the present invention.

[0061] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0062] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A combined control method for an integrated motor-pump unit, characterized in that, include: Collect multi-source sensor data and equipment configuration parameters of the integrated motor-pump machine, preprocess the collected data, and construct a state feature vector; Based on the real-time flow rate, target flow rate, current pressure, and inherent parameters of the motor in the state feature vector, the flow deviation factor, motor efficiency calibration factor, and pressure safety constraint factor are determined. The effective regulation intensity coefficient is obtained by multiplying the flow deviation factor, motor efficiency calibration factor, and pressure safety constraint factor. Based on the actual torque change rate, pressure change rate, displacement conversion coefficient, and effective adjustment intensity coefficient in the state feature vector, the predicted value of the expected torque change rate is calculated. Based on the residual between the actual torque change rate and the predicted value of the expected torque change rate, and the total energy of the actual torque change rate and the predicted value of the expected torque change rate, a disturbance separation factor is constructed to characterize the proportion of unknown disturbance in torque change. Based on the current pressure and displacement conversion coefficient in the state feature vector, the feedforward torque is calculated, and the total disturbance torque estimated by the extended state observer and the feedforward torque are weighted and fused together using the disturbance separation factor as the weight to construct the compensation torque. The compensated torque is superimposed on the base torque command output by the speed loop to generate the final motor torque command, which is then output to the servo drive unit for execution.

2. The method for combined control of an integrated motor and pump according to claim 1, characterized in that, The collected data includes: The system collects operating pressure, motor rotor position and speed, motor three-phase current, real-time system flow rate, and target flow rate analyzed from the upper-level controller. Read the inherent parameters of the motor from the non-volatile storage area. The inherent parameters of the motor include the rated torque of the motor, the rated current of the motor, the torque constant of the motor, the reference pressure, the maximum working pressure, the pressure-displacement mapping parameter set containing multiple calibrated pressure levels corresponding to the oil pump displacement values, and the displacement corresponding to the reference pressure.

3. The method for combined control of an integrated motor and pump according to claim 2, characterized in that, Preprocessing of the collected data includes: The collected system operating pressure, motor three-phase current and system real-time flow are filtered. Based on the motor rotor position and the motor three-phase current, a vector transformation algorithm is applied to calculate the motor's current actual output torque; interpolation processing is performed on the pressure-displacement mapping parameter set to establish a continuous pressure-displacement function, and the displacement conversion coefficient is calculated based on the pressure-displacement function; The target rotational speed is calculated based on the target flow rate and the actual displacement under the current pressure. Based on the actual output torque and pressure sequence of the current control cycle and several previous control cycles, the actual torque change rate and pressure change rate are calculated.

4. The method for combined control of an integrated motor and pump according to claim 3, characterized in that, The flow deviation factor is the result of dividing the absolute value of the difference between the real-time flow and the target flow by the target flow. The motor efficiency calibration factor is the result of dividing the motor's rated torque in the motor's inherent parameters by the product of the motor's torque constant and the motor's rated current. The pressure safety constraint factor is the result of dividing the difference between the maximum working pressure and the current pressure by the difference between the maximum working pressure and the reference pressure.

5. The method for combined control of an integrated motor and pump according to claim 3, characterized in that, The construction of the perturbation separation factor includes: The absolute value of the difference between the actual torque change rate and the predicted value of the expected torque change rate is taken as the torque change residual term; the predicted value of the expected torque change rate is the product of the effective adjustment intensity coefficient, the absolute value of the pressure change rate, and the displacement conversion coefficient. The sum of the absolute value of the actual torque change rate and the predicted value of the expected torque change rate is used as the energy normalization term; The disturbance separation factor is obtained by dividing the torque change residual by the energy normalization term.

6. The method for combined control of an integrated motor and pump according to claim 1, characterized in that, The process of generating the final motor torque command also includes: The final generated motor torque command is then limited. The motor torque command after amplitude limiting is smoothed and filtered.

7. The method for combined control of an integrated motor and pump according to claim 3, characterized in that, The estimation of the total disturbance torque includes: Using the actual output torque and motor speed in the state feature vector as input, the total disturbance torque of the system is estimated in real time through a pre-designed extended state observer algorithm.

8. A combined control system for an integrated motor and pump, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement the combined control method for the integrated motor and pump according to any one of claims 1-7.

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