A hydraulic pump motor torque control method and system

Abstract

The application discloses a hydraulic pump motor torque control method and system, and belongs to the technical field of hydraulic transmission control. The method comprises the following steps: acquiring the torque of a current hydraulic pump motor, the angular acceleration of a motion mechanism installed on the hydraulic pump motor, the shaking amplitude of the motion mechanism, the weight of a load on the motion mechanism, and the shaking data of the load; generating a motion mechanism state influence coefficient according to the angular acceleration of the motion mechanism and the shaking amplitude of the motion mechanism; generating a load state influence coefficient according to the weight of the load and the shaking data of the load; acquiring the rotating speed of the hydraulic pump motor, and generating a hydraulic pump motor rotating speed correction factor according to the rotating speed of the hydraulic pump motor; generating a hydraulic pump motor torque correction value according to the torque of the current hydraulic pump motor, the motion mechanism state influence coefficient, the load state influence coefficient and the hydraulic pump motor rotating speed correction factor, and adjusting the torque of the hydraulic pump motor. The application can improve the control precision, enhance the system operation stability and optimize the energy consumption level.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of hydraulic transmission control, and particularly relates to a hydraulic pump motor torque control method and system. BACKGROUND

[0002] As the core power element of industrial equipment, the torque control precision of the hydraulic pump motor directly affects the motion stability and positioning accuracy of the actuator. In application scenarios such as engineering machinery and hoisting equipment, the hydraulic pump motor often faces complex working condition changes, including dynamic interference factors such as rapid start-stop of the actuator, irregular shaking of the load, and abnormal fluctuations in the rotation speed.

[0003] The traditional hydraulic pump motor torque control method mainly adopts a PID regulation strategy with fixed parameters. This control method has obvious technical limitations. First, the fixed parameter control is difficult to adapt to the dynamic changes of the load. When the actuator performs rapid start-stop actions or the load shakes violently, the system response lags, resulting in large fluctuations in the torque output, which seriously affects the smoothness of the equipment operation. Second, the existing technology lacks comprehensive analysis capability for the coupling effect of actuator shaking and load shaking, cannot accurately evaluate the combined influence of multi-source state parameters on the torque output, and causes insufficient compensation accuracy. In addition, the traditional method has poor predictability for abnormal changes in the rotation speed of the hydraulic pump motor. In the rotation speed fluctuation working condition, there is no effective dynamic correction mechanism, which not only affects the control accuracy, but also increases the energy consumption of the system.

[0004] With the development of industrial equipment towards high speed and high precision, the existing hydraulic pump motor torque control technology has been difficult to meet the strict requirements of modern industrial equipment on motion control quality and energy efficiency level. In view of the above problems, the existing technology needs to be improved. SUMMARY

[0005] In view of the deficiencies of the prior art, the application provides a hydraulic pump motor torque control method and system, which solves the above problems.

[0006] To achieve the above purpose, the application is implemented by the following technical scheme: a hydraulic pump motor torque control method, specifically comprising the following steps:

[0007] Obtaining the torque of the current hydraulic pump motor, the motion angular acceleration of the actuator installed on the hydraulic pump motor, the actuator shaking amplitude, the weight of the load on the actuator, and the load shaking data;

[0008] Generating an actuator state influence coefficient according to the motion angular acceleration of the actuator and the actuator shaking amplitude;

[0009] According to the load weight and the load swing data, a swing analysis model is established, and a load state influence coefficient is generated; wherein the load swing data includes a swing angle, a swing speed and an equivalent pendulum length from the load gravity center to the suspension point.

[0010] The hydraulic pump motor speed is acquired, and according to the hydraulic pump motor speed, a hydraulic pump motor speed correction model is established, and a hydraulic pump motor speed correction factor is generated.

[0011] According to the current hydraulic pump motor torque, the actuator state influence coefficient, the load state influence coefficient and the hydraulic pump motor speed correction factor, a hydraulic pump motor torque correction value is generated.

[0012] According to the hydraulic pump motor torque correction value, the torque of the hydraulic pump motor is adjusted.

[0013] On the basis of the above technical scheme, the application further provides the following optional technical schemes.

[0014] Further technical scheme: the generation mode of the actuator state influence coefficient specifically includes:

[0015] Through the formula:

[0016] ;

[0017] The actuator state influence coefficient is generated ;

[0018] In the formula, represents a normalized value of the actuator motion angular acceleration, represents a normalized value of the actuator jitter amplitude, , are weight coefficients.

[0019] Further technical scheme: the generation mode of the load state influence coefficient specifically includes:

[0020] According to the swing angle and the swing speed, an angle influence coefficient is generated;

[0021] According to the angle influence coefficient, the load weight and the equivalent pendulum length from the load gravity center to the suspension point, a swing analysis model is established, and a load state influence coefficient is generated.

[0022] Further technical scheme: the generation mode of the angle influence coefficient specifically includes:

[0023] Through the formula:

[0024] ;

[0025] The angle influence coefficient is generated ;

[0026] In the formula, is a normalized value of the swing angle, is a swing speed, , are weight coefficients.

[0027] Further technical solutions: the expression of the swing analysis model is specifically:

[0028] ;

[0029] In the expression, is a load state influence coefficient, is an angle influence coefficient, is an equivalent pendulum length from the load center of gravity to the suspension point, is a reference equivalent pendulum length;

[0030] The generation mode of the reference equivalent pendulum length is specifically:

[0031] Through the formula:

[0032] ;

[0033] In the formula, is a load weight, is a load density, is a load form coefficient.

[0034] Further technical solutions: the generation mode of the hydraulic pump motor speed correction factor specifically includes:

[0035] Setting a monitoring period, acquiring the hydraulic pump motor speed in the monitoring period;

[0036] Generating a hydraulic pump motor speed prediction value according to the hydraulic pump motor speed in the monitoring period;

[0037] Establishing a hydraulic pump motor speed correction model according to the hydraulic pump motor speed prediction value, and generating a hydraulic pump motor speed correction factor.

[0038] Further technical solutions: the generation mode of the hydraulic pump motor speed prediction value specifically includes:

[0039] Through the formula:

[0040] ;

[0041] Generating a hydraulic pump motor speed prediction value ;

[0042] In the formula, represents the hydraulic pump motor speed of the current monitoring period k, M represents the prediction step, represents the hydraulic pump motor speed of the last monitoring period k-1.

[0043] Further technical solutions: the expression of the hydraulic pump motor speed correction model is specifically:

[0044]

[0045] In the formula, represents the hydraulic pump motor speed correction factor, represents the hydraulic pump motor speed set value, represents the prediction compensation coefficient.

[0046] Further technical solutions: the generation mode of the hydraulic pump motor torque correction value specifically includes:

[0047] Through the formula:

[0048]

[0049] The hydraulic pump motor torque correction value is generated

[0050] In the formula, represents the current hydraulic pump motor torque, represents the actuator state influence coefficient, represents the load state influence coefficient, represents the hydraulic pump motor speed correction factor.

[0051] A hydraulic pump motor torque control system adopts the above hydraulic pump motor torque control method, and specifically includes:

[0052] A data acquisition unit is configured to acquire the current hydraulic pump motor torque, the actuator angular acceleration, the actuator jitter amplitude, the load weight on the actuator, and the load swing data.

[0053] An actuator jitter analysis unit is configured to generate the actuator state influence coefficient according to the actuator angular acceleration and the actuator jitter amplitude.

[0054] A load swing analysis unit is configured to establish a swing analysis model according to the load weight and the load swing data to generate the load state influence coefficient. The load swing data includes the swing angle, the swing speed, and the equivalent pendulum length from the load center of gravity to the suspension point.

[0055] ​​​The rotational speed abnormality analysis unit is configured to acquire the rotational speed of the hydraulic pump motor, establish a hydraulic pump motor rotational speed correction model according to the rotational speed of the hydraulic pump motor, and generate a hydraulic pump motor rotational speed correction factor.

[0056] The torque correction analysis unit is configured to generate a hydraulic pump motor torque correction value according to the torque of the current hydraulic pump motor, the actuator state influence coefficient, the load state influence coefficient, and the hydraulic pump motor rotational speed correction factor.

[0057] The adjustment unit is configured to adjust the torque of the hydraulic pump motor according to the hydraulic pump motor torque correction value.

[0058] The present application provides a hydraulic pump motor torque control method and system, which has the following advantages compared with the prior art.

[0059] The present application generates a torque correction value in real time and adjusts the output by comprehensively considering the multi-source dynamic parameters such as the actuator state, the load swing, and the rotational speed fluctuation, thereby solving the problems of response lag and insufficient compensation precision of the traditional method, improving the control precision, enhancing the system operation stability, and optimizing the energy consumption level. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 A flowchart of a hydraulic pump motor torque control method is provided.

[0061] Figure 2 A structural diagram of a hydraulic pump motor torque control system is provided. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0063] The specific implementation of the present application is described in detail below in combination with specific examples.

[0064] Please refer to Figure 1 A hydraulic pump motor torque control method provided by an embodiment of the present application includes the following steps.

[0065] Step S10: acquiring the torque of the current hydraulic pump motor, the actuator angular acceleration, the actuator jitter amplitude, the load weight on the actuator, and the load swing data.

[0066] Step S20: generating an actuator state influence coefficient according to the actuator angular acceleration and the actuator jitter amplitude.

[0067] Step S30: According to the load weight and the load swing data, a swing analysis model is established, and a load state influence coefficient is generated; wherein the load swing data includes a swing angle, a swing speed and an equivalent pendulum length of the load center of gravity to the suspension point;

[0068] Step S40: The hydraulic pump motor speed is obtained, and a hydraulic pump motor speed correction model is established according to the hydraulic pump motor speed, to generate a hydraulic pump motor speed correction factor;

[0069] Step S50: According to the current hydraulic pump motor torque, the actuator state influence coefficient, the load state influence coefficient and the hydraulic pump motor speed correction factor, a hydraulic pump motor torque correction value is generated;

[0070] Step S60: According to the hydraulic pump motor torque correction value, the torque of the hydraulic pump motor is adjusted;

[0071] The actuator angular acceleration is the rate of change of the angular velocity of the actuator during the movement process, which can be measured by a gyroscope or an angular acceleration sensor, and is used to quantify the inertial impact of the actuator during the start and stop phases;

[0072] The actuator shaking amplitude is the vibration displacement amount generated by the actuator during the movement process, which can be collected by a vibration sensor or a displacement sensor, and is used to reflect the dynamic stability of the mechanical system. The load swing data includes a swing angle, a swing speed and an equivalent pendulum length, which can be obtained by an inertial measurement unit or a visual sensor, and is used to represent the swing amplitude and energy change of the load in the suspended state;

[0073] The hydraulic pump motor speed correction factor is a dynamic compensation coefficient generated based on the deviation between the speed prediction value and the set value, which can be calculated by a time series prediction algorithm, and is used to correct the influence of speed fluctuation on torque in advance.

[0074] Specifically, the method generates an actuator state influence coefficient by real-time collecting the actuator angular acceleration and shaking amplitude, normalizing and weighting calculation, so as to comprehensively reflect the demand change of the dynamic stability of the mechanical system on the torque. The load weight and the equivalent pendulum length are combined with the swing angle and speed data to calculate the load swing energy through a physical model, to generate a load state influence coefficient and quantify the disturbance of the load dynamic behavior to the system. The hydraulic pump motor speed data generates a speed correction factor through a prediction model, to compensate the influence of speed deviation on torque output in advance. Finally, the basic torque is multiplied by the three dynamic correction coefficients to generate a torque correction value and closed-loop adjustment, so that the torque output always matches the real-time working condition demand.

[0075] Compared with the prior art, the traditional method only relies on fixed parameter PID adjustment and cannot fuse the dynamic parameters of the actuator, the load state parameters and the speed prediction parameters for collaborative analysis. The method can realize real-time dynamic compensation of torque by collecting multi-dimensional state parameters and dynamic correction model, and can realize real-time dynamic compensation of torque by collecting multi-dimensional state parameters and dynamic correction model. The inertia impact of the mechanical system, the load swing energy and the speed fluctuation trend are included in the unified calculation framework. The prior art lacks modeling capability for the coupling effect of load form and motion, and the method improves the accuracy of load state analysis by establishing a physical model of equivalent swing length and weight parameters.

[0076] Through the above technical solutions, the application can effectively solve the problems of response lag, control precision decline and energy consumption increase caused by the coupling influence of load dynamic change, actuator jitter and load swing and the insufficient predictability of speed fluctuation in hydraulic pump motor torque control. Through the multi-source parameter fusion and dynamic correction mechanism, the matching degree of torque output and real-time working condition is improved, the vibration amplitude of the actuator and the swing amplitude of the load are reduced, and the energy loss caused by speed fluctuation is reduced.

[0077] Preferably, the application further proposes a generation method of the actuator state influence coefficient, which specifically includes:

[0078] Through the formula:

[0079] ;

[0080] Generate the actuator state influence coefficient ;

[0081] In the formula, represents the normalized value of the angular acceleration of the actuator motion, represents the normalized value of the actuator jitter amplitude, , are weight coefficients;

[0082] Among them, the normalized value refers to converting physical quantities of different dimensions into a unified dimensionless value range, which can be realized by linear transformation or standardization method, so as to eliminate the dimensional difference between parameters for weighting calculation;

[0083] The weight coefficient , is a regulation factor assigned to different parameters, which can be determined by experiment calibration or optimization algorithm, and is used to dynamically adjust the contribution proportion of different parameters to the final coefficient;

[0084] The actuator state influence coefficient is a quantitative index that comprehensively reflects the motion state and vibration intensity of the actuator, which can be generated by linear weighting and calculation, and is used to represent the dynamic influence degree of the actuator on torque control.

[0085] Specifically, the normalization processing of the actuator angular acceleration makes acceleration data of different orders of magnitude comparable, and the normalization of the jitter amplitude ensures that the vibration intensity parameter and the acceleration are in the same calculation dimension. By setting the weight coefficient, the priority of the angular acceleration and the jitter amplitude can be adjusted according to the actual working condition, for example, the weight of the angular acceleration is increased in the high dynamic response scene to enhance the system sensitivity, and the weight of the jitter amplitude is increased in the stability priority scene to suppress vibration interference. The finally generated actuator state influence coefficient fuses the two key parameters in a linear superposition manner, providing a dynamic adjustment basis for torque correction.

[0086] Compared with the prior art, the traditional method usually only uses a single parameter or a fixed threshold for state evaluation, and cannot cooperatively analyze the coupling effect of motion state and vibration characteristics. The present scheme eliminates the dimensional difference through normalization processing, and realizes multi-parameter dynamic fusion combined with adjustable weight coefficients, so that the state evaluation is more comprehensive and adapts to different working condition requirements.

[0087] Through the above technical scheme, the present application can effectively quantify the dynamic characteristics and vibration intensity of the actuator, improve the state evaluation accuracy through parameter fusion and weight distribution, thereby solving the torque compensation lag problem caused by isolated parameter analysis in the traditional method, and enhancing the response ability of the system to the change of the motion state of the actuator.

[0088] Preferably, the present application further proposes that the generation method of the load state influence coefficient f specifically comprises:

[0089] Step S31: generating an angle influence coefficient according to the swing angle and the swing speed;

[0090] Step S32: establishing a swing analysis model according to the angle influence coefficient, the load weight and the equivalent pendulum length of the load center of gravity to the suspension point, and generating a load state influence coefficient;

[0091] The swing angle refers to the instantaneous inclination angle of the load relative to the suspension point, which can be measured by a gyroscope or an inclination sensor, and is used to represent the attitude deviation of the load in space;

[0092] The swing speed refers to the angular change rate of the load per unit time, which can be obtained by an angular velocity sensor or by angle difference calculation, and is used to reflect the motion trend of the load;

[0093] The equivalent pendulum length refers to the geometric distance from the center of gravity of the load to the suspension point, which can be obtained by a laser range finder or calculated based on the geometric size of the load, and is used to quantify the influence of the suspension structure on the swing inertia;

[0094] The angle influence coefficient refers to a dynamic parameter fusing the shaking angle and the shaking speed, which can be specifically generated by a weighted summation algorithm and used to comprehensively represent the instantaneous dynamic characteristics of the load shaking;

[0095] The shaking analysis model refers to a mathematical model associating the angle influence coefficient with the equivalent swing length and the load weight, which can be specifically constructed by superimposing the geometric amplification effect and the mass inertia effect and used to quantize the comprehensive influence of the load shaking on the system stability.

[0096] Specifically, when generating the angle influence coefficient, the real-time data of the shaking angle and the shaking speed are input into a weighted calculation module, and by dynamically adjusting the weight proportion of the two, the dynamic characteristics of the load in different motion stages are captured. For example, in the rapid shaking stage, the weight of the shaking speed can be set to be higher than that of the shaking angle, so as to strengthen the response ability to sudden motion. Subsequently, the angle influence coefficient and the equivalent swing length are input into a geometric amplification calculation module, and by analyzing the deviation of the swing length from the reference value, the change amplitude of the load swing inertia is calculated. At the same time, the load weight is introduced into a mass inertia calculation module, and combined with the calculation results of the angle influence coefficient and the equivalent swing length, a state influence coefficient reflecting the comprehensive dynamic characteristics of the load is finally generated.

[0097] Compared with the prior art, the traditional method usually only evaluates the load state based on the static angle or a single speed parameter, ignoring the dynamic coupling relationship between the angle and the speed and the amplification effect of the equivalent swing length on the swing inertia. For example, in the prior art, a fixed threshold is used to judge whether the angle is out of limit, which cannot distinguish the inertia difference caused by different speeds under the same angle. However, the present scheme can simultaneously reflect the instantaneous posture, motion trend and suspension structure characteristics of the load by establishing the correlation model of the angle influence coefficient and the equivalent swing length, thereby solving the evaluation error problem caused by isolated parameter analysis in the traditional method.

[0098] Through the above technical scheme, the present application can accurately quantize the synergistic effect of the angle change rate and the equivalent swing length in the load shaking process, and eliminate the torque compensation lag caused by ignoring the dynamic coupling relationship. For example, when the load shakes with high frequency and small amplitude, the system can identify the potential unstable trend through the geometric amplification effect of the equivalent swing length, so as to introduce the suppression measures in advance in the torque correction, thereby avoiding the shaking of the actuator caused by the sudden change of load inertia.

[0099] Preferably, the present application further proposes that the generation method of the angle influence coefficient specifically comprises:

[0100] The angle influence coefficient is generated by the formula:

[0101] ;

[0102] The angle influence coefficient is generated by the formula: ;

[0103] In the formula, represents a normalized value of the swing angle, represents a normalized value of the swing speed, , are weight coefficients;

[0104] wherein the normalized value of the swing angle refers to converting the actual measured angle value into a dimensionless value, which can be realized by using the maximum-minimum normalization method to eliminate the influence of different dimensions on the calculation;

[0105] The swing speed refers to the angle change of the load in unit time, which can be realized by using a gyroscope sensor to collect data in real time, reflecting the instantaneous dynamic characteristics of the load swing;

[0106] The weight coefficient , refers to a proportional factor for adjusting the contribution degree of the angle parameter and the speed parameter to the final coefficient, which can be determined by offline calibration test combined with gradient descent method optimization, realizing the differentiated weighting of the angle static deviation and the speed dynamic disturbance.

[0107] Specifically, during the swing of the load, the angle normalized value establishes a unified evaluation benchmark by eliminating the dimensional difference, and the speed parameter directly reflects the dynamic change trend in the swing process. By multiplying and , the influence of the cumulative effect of angle deviation on system stability is strengthened; at the same time, by multiplying and , the instantaneous interference caused by speed mutation is captured. The linear superposition relationship of the two not only retains the independent action characteristics of the angle and speed parameters, but also dynamically adjusts the coupling proportion of the two through the weight coefficient. For example, when the load is in high-frequency small-amplitude swing, can be set to a larger value to enhance the compensation effect of the speed term; when the load has a sustained large-angle deviation, can be set to a larger value to strengthen the correction effect of the angle term. The composite influence coefficient constructed in this way can accurately represent the synergistic action mechanism of the angle and speed parameters.

[0108] Compared with the prior art, the traditional method usually processes the angle or speed parameter separately, and uses a fixed threshold to judge the swing state, which cannot effectively quantify the dynamic coupling relationship between the two. This scheme realizes the comprehensive evaluation of dynamic and static interference factors in the swing process by establishing a linear combination model of angle and speed, combined with an adjustable weight coefficient.

[0109] By the technical solution, the application can dynamically quantify the combined interference effect of angle deviation and speed change in the load swing process, and accurately identify the system disturbance characteristics under different swing modes. The scheme effectively solves the compensation lag problem caused by independent processing of angle and speed parameters in traditional control methods, optimizes the torque compensation response speed by adjusting the weight coefficient in real time, and significantly reduces the torque fluctuation of the hydraulic pump motor caused by load swing.

[0110] Preferably, the application further proposes that the expression of the swing analysis model is specifically:

[0111] ;

[0112] In the expression, represents the load state influence coefficient, represents the angle influence coefficient, represents the equivalent swing length from the load center of gravity to the suspension point, represents the reference equivalent swing length;

[0113] The generation method of the reference equivalent swing length is specifically:

[0114] Through the formula:

[0115] ;

[0116] In the formula, represents the load weight, represents the load density, represents the load form coefficient;

[0117] The equivalent swing length L refers to the distance from the load center of gravity to the suspension point, which can be realized by laser ranging or mechanical structure parameter measurement, and is used to represent the amplification effect of the load suspension state on the swing.

[0118] The reference equivalent swing length is a theoretical swing length reference value calculated according to the physical properties of the load, which can be realized by cubic root operation of weight, density and form coefficient, and is used to dynamically correct the deviation between the actual swing length and the theoretical value.

[0119] The load form coefficient is a parameter describing the influence of the geometric shape of the load on the swing, which can be realized by preset empirical value or feature extraction based on three-dimensional model, for example, the form coefficient of spherical load can be 1, and the form coefficient of long strip-shaped load can be 1.2.

[0120] Specifically, the swing analysis model adjusts the angle influence coefficient through the proportional relationship between the equivalent swing length and the reference value. When the actual equivalent swing length exceeds the reference value, the load state influence coefficient increases linearly with the swing length deviation, thereby quantifying the interference of the suspension state change on the torque. The reference equivalent swing length fuses the physical properties and geometric characteristics of the load by introducing weight, density, and shape coefficients, for example, a metal load with high density and a plastic load with low density will generate different reference values, so that the model can adapt to the inherent characteristics of different loads.

[0121] Compared with the prior art, the traditional method does not consider the influence of dynamic changes of the equivalent swing length on the load swing, and only calculates the compensation value based on fixed parameters, resulting in inaccurate torque compensation when the suspension state changes. However, the present scheme dynamically calculates the reference equivalent swing length and compares it with the actual swing length in real time, and incorporates the weight, density, and shape of the load into the model parameters, so that the compensation coefficient can be adaptively adjusted according to the physical properties of the load, solving the compensation deviation problem caused by ignoring the suspension state change in the traditional technology.

[0122] Through the above technical scheme, the present application realizes accurate quantification of the influence of load swing, and through dynamic correction of the equivalent swing length and fusion calculation of the physical properties, effectively suppresses the torque fluctuation caused by changes in the suspension state of the load, and improves the control accuracy and stability of the hydraulic pump motor under dynamic load conditions.

[0123] Preferably, the present application further proposes a generation method of the hydraulic pump motor speed correction factor, which specifically includes:

[0124] Step S41: set a monitoring period and acquire the hydraulic pump motor speed in the monitoring period;

[0125] Step S42: generate a hydraulic pump motor speed prediction value according to the hydraulic pump motor speed in the monitoring period;

[0126] Step S43: establish a hydraulic pump motor speed correction model according to the hydraulic pump motor speed prediction value, and generate a hydraulic pump motor speed correction factor;

[0127] The monitoring period refers to the time interval for periodic sampling of the hydraulic pump motor speed, which can be realized by using a fixed time window or an adaptively adjusted time interval, for example, collecting speed data every 100 milliseconds. Its function is to capture the dynamic change characteristics of the speed in real time and provide a time series data basis for the prediction model;

[0128] The hydraulic pump motor speed prediction value refers to an estimated value of the future speed trend based on historical speed data, which can be specifically realized by linear extrapolation or moving average algorithm, for example, the trend is predicted by the difference between the current period and the previous period speed, which serves to identify the potential risk of speed deviation from the set value in advance, and provides a forward-looking basis for correction factor calculation;

[0129] The hydraulic pump motor speed correction model refers to a mathematical model that converts the deviation between the prediction value and the set value into a correction factor, which can be specifically realized by proportional compensation or dynamic gain adjustment method, for example, the correction factor is generated by the product of the normalized deviation and the compensation coefficient, which serves to quantify the influence of speed fluctuation on torque as an adjustable parameter that can be superimposed, realizing dynamic compensation of torque control.

[0130] Specifically, the actual speed data of the hydraulic pump motor is continuously collected in the monitoring period, and the speed change trend is extracted by time series analysis method. The prediction value is calculated based on the difference between the current period and the previous period speed, for example, when the speed shows an increasing trend, the prediction value will be higher than the current actual value. The correction model converts the deviation between the prediction value and the set value into a correction factor, and when the prediction value is lower than the set value, the correction factor increases to increase the torque output in advance, offsetting the power shortage caused by speed drop. Therefore, before the abnormal fluctuation of speed occurs, the torque control instruction has been dynamically adjusted according to the prediction result, avoiding the decline of control accuracy caused by lag compensation in traditional method.

[0131] Compared with the prior art, the traditional method only adjusts passively according to the current speed deviation, and cannot foresee the speed change trend, resulting in lag of compensation action relative to actual working condition change. While the present scheme identifies the speed fluctuation direction in advance through the prediction model, and starts the correction mechanism when the abnormal speed has not yet significantly affected the system performance, so that the torque adjustment and speed change realize synchronous response, effectively reducing the problem of increased energy consumption caused by compensation delay.

[0132] Through the above technical scheme, the present application can generate a correction factor matched with the prediction deviation in advance when the speed of the hydraulic pump motor abnormally fluctuates, so that the torque control instruction dynamically adapts to the speed change trend. Therefore, the torque output oscillation caused by lag compensation of speed fluctuation is reduced, the positioning error of the actuator caused by power mismatch is avoided, and the additional energy consumption of the system to maintain the speed stability is reduced.

[0133] Preferably, the present application further proposes that the generation mode of the hydraulic pump motor speed prediction value specifically comprises:

[0134] Through the formula:

[0135] ;

[0136] generate the hydraulic pump motor speed prediction value ;

[0137] In the formula, represents the hydraulic pump motor speed of the current monitoring period k, M represents the prediction step, represents the hydraulic pump motor speed of the previous monitoring period k-1;

[0138] Wherein, the current monitoring period refers to the time window for real-time collection of hydraulic pump motor speed, which can be realized by fixed time interval sampling method, for example, collecting data once every 100 milliseconds. The prediction step refers to the coefficient for adjusting the prediction trend amplitude, which can be set according to the dynamic response characteristics of the hydraulic system, for example, taking an integer between 1 and 3;

[0139] The previous monitoring period refers to the previous time window adjacent to the current monitoring period, and the speed data thereof is used to calculate the speed change of the adjacent period.

[0140] Specifically, the difference between the actual speed of the current monitoring period and the actual speed of the previous monitoring period reflects the instantaneous gradient of the speed change. By multiplying this difference by the prediction step, the speed trend can be linearly extrapolated. For example, when the prediction step is set to 2, the predicted value will be superimposed on the current speed by twice the speed change of the adjacent period, so as to amplify the prediction trend. This prediction method can predict the speed state at the next moment in advance, providing forward-looking input for the calculation of the subsequent correction factor. When the hydraulic pump motor speed changes suddenly, for example, the actuator suddenly accelerates or the load shakes violently, causing speed fluctuation, the prediction model can capture the change direction through historical data and dynamically adjust the prediction step to balance the response speed and stability.

[0141] Compared with the prior art, the traditional method usually only relies on the current speed data for feedback control, lacking predictability of speed change. For example, the PID regulator with fixed parameters can only compensate after the speed fluctuation occurs, which has a response lag. However, the present scheme introduces historical speed data to construct a linear extrapolation model, which can predict the speed change trend in advance and integrate the prediction result into the speed correction factor, so that the torque adjustment action can be started in advance before the actual speed anomaly occurs. This active control mechanism based on prediction effectively reduces the torque output fluctuation caused by delay in traditional methods.

[0142] By the technical solution, the application solves the problem of poor predictability of abnormal changes in the rotation speed of the hydraulic pump motor. During the operation of the hydraulic system, when the actuator is quickly started and stopped or the load is shaken to cause rotation speed fluctuations, the prediction model can identify the rotation speed change trend in advance and dynamically compensate the torque through a correction factor. For example, in the hoisting operation of a crane, the periodic fluctuation of the rotation speed of the hydraulic pump motor caused by the swing of the load can be adjusted in advance to offset its impact, thereby reducing the amplitude of the actuator jitter. The technical solution improves the adaptability of the hydraulic system to abnormal changes in the rotation speed and reduces the control error caused by response lag.

[0143] Preferably, the application further provides an expression of the rotation speed correction model of the hydraulic pump motor, which is specifically:

[0144] ;

[0145] In the formula, represents the rotation speed correction factor of the hydraulic pump motor, represents the rotation speed set value of the hydraulic pump motor, represents the prediction compensation coefficient.

[0146] The rotation speed correction factor of the hydraulic pump motor refers to a proportional coefficient for dynamically adjusting the torque output, which can be calculated by combining the deviation proportion of the set value and the prediction value with the prediction compensation coefficient. Its function is to quantify the influence of rotation speed fluctuation on torque as a correction term that can be superimposed.

[0147] The rotation speed set value of the hydraulic pump motor refers to a target rotation speed parameter set in advance, which can be determined by the input of the control system or a preset program, and is used to represent the expected operating state of the hydraulic pump motor.

[0148] The rotation speed prediction value of the hydraulic pump motor refers to a future rotation speed parameter calculated based on historical rotation speed data, which can be generated by using a linear extrapolation method or a time series analysis method, and is used to predict the rotation speed change trend in advance.

[0149] The prediction compensation coefficient refers to a weighting parameter for adjusting the dynamic response amplitude of the correction factor, which can be determined by system identification or experimental calibration, and its function is to balance the correction speed and stability to avoid over-adjustment or under-adjustment.

[0150] Specifically, during the operation of the hydraulic pump motor, the future speed prediction value is generated by monitoring the current and historical speed data in real time and using a prediction algorithm. The relative deviation between the set value and the prediction value is taken as the input, and the speed correction factor is calculated through a correction model. The correction factor is designed in the form of a combination of a reference value 1 and a deviation compensation term, where the deviation compensation term is weighted and adjusted by a prediction compensation coefficient. When the prediction value deviates from the set value, the correction factor is automatically adjusted, thereby dynamically compensating the torque output. For example, when the prediction value is lower than the set value, the correction factor increases to increase the torque output to suppress the speed drop trend; when the prediction value is higher than the set value, the correction factor decreases to reduce the torque output to avoid speed overshoot.

[0151] Compared with the prior art, the traditional method relies on fixed parameter adjustment and cannot foresee the speed fluctuation trend, resulting in lagging compensation. However, the present scheme can identify the abnormal change direction of the speed in advance by introducing the deviation ratio of the speed prediction value and the set value, and dynamically adjust the correction amplitude in combination with the prediction compensation coefficient. This correction mechanism based on prediction deviation can effectively reduce the influence of speed fluctuation on system stability, and significantly improve the response speed and accuracy of torque control compared with the traditional method.

[0152] Through the above technical scheme, the present application can predict the change trend in advance and dynamically adjust the torque output when the speed of the hydraulic pump motor abnormally fluctuates, thereby reducing the problem of increased system energy consumption caused by speed deviation accumulation, and avoiding the decrease in control accuracy through real-time correction. The scheme is especially suitable for fast start-stop or load mutation scenarios of actuators, and ensures stable operation of the hydraulic pump motor under complex working conditions.

[0153] Preferably, the present application further proposes that the generation method of the torque correction value of the hydraulic pump motor specifically comprises:

[0154] The torque correction value of the hydraulic pump motor is generated by the formula:

[0155] ;

[0156] The torque correction value of the hydraulic pump motor is generated by the formula: ;

[0157] In the formula, represents the torque of the current hydraulic pump motor, represents the actuator state influence coefficient, represents the load state influence coefficient, represents the speed correction factor of the hydraulic pump motor;

[0158] The torque of the current hydraulic pump motor refers to the real-time collected hydraulic pump motor output torque value, which can be directly measured by a torque sensor and used as a basis value for dynamic correction.

[0159] Actuator state influence coefficient , which refers to a parameter reflecting the comprehensive influence of actuator angular acceleration and shaking amplitude, can be generated by weighted summation of normalized angular acceleration and shaking amplitude, and is used to quantify the adjustment effect of actuator dynamic characteristics on torque demand;

[0160] Load state influence coefficient , which refers to a parameter representing the influence of load sway on system stability, can be calculated by a sway analysis model established by sway angle, speed and equivalent swing length, and is used to compensate for torque deviation caused by load inertia;

[0161] Hydraulic pump motor speed correction factor , which refers to a correction parameter generated based on the deviation between the predicted value and the set value of the speed, can be generated by a speed historical data prediction model combined with a compensation coefficient, and is used to suppress the torque response lag caused by speed fluctuation.

[0162] Specifically, the technical scheme realizes the coordinated compensation of multiple source parameters through a dynamic product model. First, the real-time acquisition of as the basic torque value ensures that the correction process is synchronized with the current working condition. Then, The influence of mechanical vibration on torque is converted into quantifiable parameters, such as angular acceleration normalized value and shaking amplitude normalized value , which are multiplied by weight coefficients and respectively and then added. At the same time, The angle influence coefficient is generated according to the load sway angle, speed and equivalent swing length, and the equivalent swing length deviation is calculated by combining the load weight. The shaking amplitude influence is adjusted by the ratio of equivalent swing length to reference value. In addition, Based on the predicted value of the hydraulic pump motor speed , dynamic adjustment is performed, such as generating a predicted value according to the speed difference between the current period and the previous period multiplied by the prediction step M, and then generating a correction factor by combining the deviation ratio of the predicted value and the set value with a compensation coefficient . Finally, the above three types of coefficients are multiplied with the basic torque, so that the corrected can synchronously offset the interference caused by actuator vibration, load sway and speed fluctuation.

[0163] Compared with the prior art, the traditional method usually only relies on fixed parameter adjustment or single factor compensation, such as adjusting torque only through PID control, and cannot respond in real time to the complex disturbance caused by the dynamic change of the actuator and the load swing. However, the scheme establishes a product correction model of multiple dimensions for the first time, and integrates the actuator motion state, load swing characteristics and speed prediction deviation into a unified calculation framework, for example, when the load swings violently, The compensation amount can be dynamically adjusted based on the real-time change of the equivalent swing length, and The torque output is corrected in advance by predicting the speed deviation, thereby solving the response lag problem caused by isolated parameter processing in the traditional method.

[0164] Through the above technical scheme, the hydraulic pump motor torque can be dynamically and accurately controlled. When the load swings, the inertia torque deviation caused by the change of the equivalent swing length is compensated in real time; when the actuator is rapidly started and stopped, the influence of the sudden change of the angular acceleration on the torque is inhibited; and when the hydraulic pump motor speed abnormally fluctuates, the torque output is corrected in advance. Therefore, the system can still maintain stable torque output under complex working conditions, reduce the positioning error and mechanical vibration of the actuator, and reduce the energy loss caused by speed fluctuation.

[0165] Please refer to Figure 2 The application further provides a hydraulic pump motor torque control system, which is used to execute the hydraulic pump motor torque control method and specifically comprises:

[0166] A data acquisition unit 10 is configured to acquire the torque of the current hydraulic pump motor, the angular acceleration of the actuator installed on the hydraulic pump motor, the actuator jitter amplitude, the weight of the load on the actuator, and the load swing data.

[0167] An actuator jitter analysis unit 20 is configured to generate an actuator state influence coefficient according to the angular acceleration of the actuator and the actuator jitter amplitude.

[0168] A load swing analysis unit 30 is configured to establish a swing analysis model according to the weight of the load and the load swing data, and generate a load state influence coefficient. The load swing data includes the swing angle, the swing speed and the equivalent swing length from the load center of gravity to the suspension point.

[0169] A speed anomaly analysis unit 40 is configured to acquire the speed of the hydraulic pump motor, establish a hydraulic pump motor speed correction model according to the speed of the hydraulic pump motor, and generate a hydraulic pump motor speed correction factor.

[0170] ​​​The torque correction analysis unit 50 is configured to generate a hydraulic pump motor torque correction value according to the current hydraulic pump motor torque, the actuator state influence coefficient, the load state influence coefficient and the hydraulic pump motor speed correction factor;

[0171] The adjustment unit 60 is configured to adjust the torque of the hydraulic pump motor according to the hydraulic pump motor torque correction value.

[0172] Preferably, the load swing analysis unit 30 further comprises:

[0173] The angle analysis module is configured to generate an angle influence coefficient according to the swing angle and the swing speed;

[0174] The load state influence coefficient generation module is configured to establish a swing analysis model according to the angle influence coefficient, the load weight and the equivalent pendulum length from the load center of gravity to the suspension point, and generate a load state influence coefficient.

[0175] Preferably, the speed anomaly analysis unit 40 further comprises:

[0176] The speed acquisition module is configured to set a monitoring period and acquire the hydraulic pump motor speed in the monitoring period;

[0177] The prediction module is configured to generate a hydraulic pump motor speed prediction value according to the hydraulic pump motor speed in the monitoring period;

[0178] The correction factor generation module is configured to establish a hydraulic pump motor speed correction model according to the hydraulic pump motor speed prediction value, and generate a hydraulic pump motor speed correction factor.

[0179] Although the embodiments of the present application have been shown and described, it is to be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A hydraulic pump motor torque control method characterized by, Specifically comprising the following steps: Obtaining the torque of the current hydraulic pump motor, the motion angular acceleration of the actuator installed on the hydraulic pump motor, the actuator jitter amplitude, the weight of the load on the actuator, and the load swing data; According to the motion angular acceleration of the actuator and the actuator jitter amplitude, the actuator state influence coefficient is generated; According to the weight of the load and the load swing data, a swing analysis model is established, and the load state influence coefficient is generated; wherein the load swing data includes the swing angle, the swing speed and the equivalent pendulum length from the load center of gravity to the suspension point; Obtaining the hydraulic pump motor speed, and establishing a hydraulic pump motor speed correction model according to the hydraulic pump motor speed to generate a hydraulic pump motor speed correction factor; According to the torque of the current hydraulic pump motor, the actuator state influence coefficient, the load state influence coefficient and the hydraulic pump motor speed correction factor, the hydraulic pump motor torque correction value is generated; According to the hydraulic pump motor torque correction value, the torque of the hydraulic pump motor is adjusted.

2. The hydraulic pump-motor torque control method according to claim 1, characterized by, The generation method of the actuator state influence coefficient specifically includes: Through the formula: ； Generating actuator state influence coefficients ; In the formula, represents the normalized value of the actuator angular acceleration, represents the normalized value of the actuator jitter amplitude, , are weight coefficients.

3. The hydraulic pump-motor torque control method according to claim 1, characterized by, The generation method of the load state influence coefficient specifically includes: According to the swing angle and the swing speed, the angle influence coefficient is generated; According to the angle influence coefficient, the weight of the load and the equivalent pendulum length from the load center of gravity to the suspension point, a swing analysis model is established, and the load state influence coefficient is generated.

4. The hydraulic pump-motor torque control method according to claim 3, characterized by, The generation method of the angle influence coefficient specifically includes: Through the formula: ； Generation angle influence coefficient ; In the formula, is a normalized value of the sway angle, is a sway speed, , are weight coefficients.

5. The hydraulic pump-motor torque control method according to claim 4, characterized by, The expression of the swing analysis model is specifically: ； In the expression, represents a load state influence coefficient, represents an angle influence coefficient, represents an equivalent swing length from the load center of gravity to the suspension point, represents a reference equivalent swing length; The generation method of the reference equivalent pendulum length is specifically: Through the formula: ； In the formula, represents the weight of the load, represents the density of the load, represents the form factor of the load.

6. The hydraulic pump-motor torque control method according to claim 1, characterized by, The generation method of the hydraulic pump motor speed correction factor specifically includes: Setting a monitoring period, and obtaining the hydraulic pump motor speed in the monitoring period; According to the hydraulic pump motor speed in the monitoring period, the hydraulic pump motor speed prediction value is generated; According to the hydraulic pump motor speed prediction value, a hydraulic pump motor speed correction model is established, and a hydraulic pump motor speed correction factor is generated.

7. The hydraulic pump-motor torque control method according to claim 6, characterized by, The generation method of the hydraulic pump motor speed prediction value specifically includes: Through the formula: ； Generating a hydraulic pump motor rotational speed prediction value ; In the formula, represents the hydraulic pump motor speed of the current monitoring period k, M represents the prediction step, represents the hydraulic pump motor speed of the previous monitoring period k-1.

8. The hydraulic pump-motor torque control method according to claim 7, characterized by, The expression of the hydraulic pump motor speed correction model is specifically: ； In the formula, represents a hydraulic pump motor speed correction factor, represents a hydraulic pump motor speed set value, represents a prediction compensation coefficient.

9. The hydraulic pump-motor torque control method according to claim 1, characterized by, The generation method of the hydraulic pump motor torque correction value specifically includes: Through the formula: ； Generating a hydraulic pump motor torque correction value ; In the formula, represents the current torque of the hydraulic pump motor, represents the actuator state influence coefficient, represents the load state influence coefficient, represents the hydraulic pump motor speed correction factor.

10. A hydraulic pump motor torque control system characterized by, The system is used for executing the hydraulic pump motor torque control method of any one of claims 1-9, and specifically includes: A data acquisition unit is configured to obtain the torque of the current hydraulic pump motor, the motion angular acceleration of the actuator installed on the hydraulic pump motor, the actuator jitter amplitude, the weight of the load on the actuator, and the load swing data; An actuator jitter analysis unit is configured to generate the actuator state influence coefficient according to the motion angular acceleration of the actuator and the actuator jitter amplitude; A load swing analysis unit is configured to establish a swing analysis model according to the weight of the load and the load swing data, and generate the load state influence coefficient; wherein the load swing data includes the swing angle, the swing speed and the equivalent pendulum length from the load center of gravity to the suspension point; A speed anomaly analysis unit is configured to obtain the hydraulic pump motor speed, and establish a hydraulic pump motor speed correction model according to the hydraulic pump motor speed to generate a hydraulic pump motor speed correction factor; A torque correction analysis unit is configured to generate a hydraulic pump motor torque correction value based on a current hydraulic pump motor torque, an actuator state influence coefficient, a load state influence coefficient, and a hydraulic pump motor speed correction factor. An adjustment unit is configured to adjust the torque of the hydraulic pump motor based on the hydraulic pump motor torque correction value.

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