Method and system for driving and controlling a plunger pump with a servo motor

Abstract

The application relates to the technical field of hydraulic transmission control, and discloses a method and system for driving and controlling a plunger pump by a servo motor, wherein the method for driving and controlling the plunger pump by the servo motor comprises the following steps: obtaining initialization data and equipment configuration parameters of a servo motor control system; performing hardware state detection and pressure working condition parameter configuration through a controller; establishing a quantitative relationship between the rotating speed of the servo motor and the output flow of the plunger pump; performing pressure working condition identification and mode switching, and verifying the working characteristics of the plunger pump; performing solenoid pulse width modulation control; determining a current working mode, performing mode-specific rotating speed strategy formulation and proportional-integral-derivative parameter adaptive control; and performing multi-mode performance comparison and cooperation effect analysis; the application can intelligently identify pressure working condition changes and automatically perform smooth mode switching, thereby ensuring optimal control performance under different working conditions.

Description

Technical Field

[0001] This invention relates to the field of hydraulic transmission control technology, and more specifically, to a method and system for controlling a piston pump by driving a servo motor. Background Technology

[0002] Hydraulic transmission systems, as the core power source of modern industrial equipment, are widely used in injection molding machines, hydraulic presses, and construction machinery. Traditional hydraulic systems often employ a control method using a fixed-displacement pump in conjunction with a proportional valve or a variable-displacement pump operating independently. However, this approach has certain technical limitations when facing complex and variable operating conditions. While fixed-displacement pump systems can achieve precise flow control, under low-pressure and light-load conditions, the system still needs to maintain high-pressure operation to overcome the pressure loss of the proportional valve, resulting in significant energy loss as heat and low system efficiency. Although variable-displacement pump systems possess constant-power variable characteristics, enabling some energy savings under low-pressure conditions, their constant-power characteristic leads to unstable flow output under high-pressure conditions, making it difficult to meet the flow control requirements of precision machining and high-precision control.

[0003] Existing hydraulic control systems generally suffer from the technical contradiction of "difficulty in achieving both energy saving and precise control." Traditional variable displacement pumps, limited by their constant power variable characteristics under high-pressure conditions, automatically reduce their displacement to maintain constant power as system pressure increases. This results in flow output fluctuating with pressure, making precise flow control impossible and severely impacting the system's control accuracy and response characteristics. While fixed displacement pumps offer stable flow output, they cannot automatically adjust their output power according to load demands under low-pressure conditions, always operating at rated power, leading to significant energy waste. Furthermore, existing control systems lack intelligent operating condition recognition and mode switching mechanisms, failing to automatically optimize control strategies based on actual working pressure and load characteristics. This results in poor system adaptability and difficulty achieving optimal overall performance under complex operating conditions.

[0004] With the continuous improvement of industrial automation and increasingly stringent requirements for energy conservation and environmental protection, there is an urgent need for an intelligent hydraulic control technology that can automatically switch control modes under different pressure conditions. This technology can fully leverage the energy-saving advantages of variable pumps under low-pressure conditions and achieve precise flow control of fixed-displacement pumps under high-pressure conditions, thereby solving the technical problem that traditional hydraulic systems cannot simultaneously achieve energy conservation and precise control. Summary of the Invention

[0005] This invention provides a method and system for controlling a plunger pump with a servo motor, solving the technical problem in related technologies that cannot simultaneously achieve energy-saving operation and precise flow control under different pressure conditions.

[0006] This invention provides a method for controlling a plunger pump using a servo motor, comprising the following steps: The initialization data and equipment configuration parameters of the servo motor control system are obtained. The hardware status is detected and the pressure condition parameters are configured through the controller. A quantitative relationship between the servo motor speed and the output flow of the plunger pump is established, and the coordinated control parameters of the servo motor and the plunger pump are obtained. Based on the coordinated control parameters of the servo motor plunger pump, pressure condition identification and mode switching are performed to verify the working characteristics of the plunger pump and obtain a plunger pump working characteristic verification report. Based on the verification report of the working characteristics of the plunger pump, solenoid valve pulse width modulation control was performed to obtain a verification report of variable quantitative conversion. Based on the variable quantitative conversion verification report, the current working mode is determined, and the sub-mode speed strategy is formulated and proportional-integral-derivative parameter adaptive control is performed to obtain the motor operating status report. Based on the motor operating status report, a multi-mode performance comparison and coordination effect analysis were conducted to obtain a servo motor plunger pump coordination effect evaluation report.

[0007] In a preferred embodiment, the hardware status detection includes: The controller uses the device communication protocol to perform initialization tests on each hardware module in sequence. For servo motors, the controller establishes a communication connection with the servo motor driver through the controller area network bus, and parses and extracts the servo motor speed range parameters and rated torque parameters; For hydraulic high-pressure high-speed piston variable pumps, the controller obtains the maximum displacement parameters and the maximum working pressure parameters, and detects the pump's working status through pressure sensors and flow sensors; For two-position four-way solenoid directional valves, pressure reducing valves, and check valves, the controller detects the coil resistance of the solenoid directional valve, the pressure difference across the pressure reducing valve, and the sealing performance of the check valve. For pressure sensors, flow sensors, and position sensors, the controller collects output signals to determine the signal amplitude and stability; The controller summarizes and generates a hardware status report for the control system.

[0008] In a preferred embodiment, the pressure condition parameter configuration includes: The controller uses a multi-level threshold configuration method to set the judgment criteria for pressure condition identification, divides the working pressure into low-pressure condition range and high-pressure condition range, and sets the upper limit threshold for low-pressure condition and the lower limit threshold for high-pressure condition. For variable mode, the controller sets the maximum swashplate angle parameter of the piston pump and the constant power variable coefficient; For the quantitative mode, the controller sets the fixed swashplate angle parameter to the minimum swashplate angle of the plunger pump and sets the output pressure setting value of the pressure reducing valve; The controller summarizes the configuration parameters to form a pressure condition identification parameter table.

[0009] In a preferred embodiment, establishing a quantitative relationship between the servo motor speed and the plunger pump output flow rate includes: The controller uses a flow calculation model to establish a quantitative relationship between the servo motor speed and the output flow of the plunger pump; For the variable mode, the flow calculation formula is established as follows: the output flow is equal to the servo motor speed multiplied by the single-revolution displacement of the plunger pump, multiplied by the sine function value of the current swashplate angle, and multiplied by the constant power variable coefficient. For the quantitative mode, a simplified flow calculation formula is established as follows: the output flow rate is equal to the servo motor speed multiplied by the single-revolution displacement of the plunger pump and then multiplied by the sine function value of the fixed swashplate angle. The controller calibrates the optimal motor speed range under different pressure conditions and sets the motor speed transition strategy when switching modes.

[0010] In a preferred embodiment, the pressure condition identification includes: The controller uses a convolutional neural network multi-frequency filtering and trend analysis method to process the current hydraulic system working pressure, and uses a convolutional neural network for intelligent filtering. The controller uses a trend analysis method to calculate the pressure change rate and determines the operating condition based on the filtered current pressure value and pressure threshold. When the current pressure value is less than or equal to the upper limit threshold of the low-pressure condition, it is determined to be a low-pressure condition; when the current pressure value is greater than the lower limit threshold of the high-pressure condition, it is determined to be a high-pressure condition.

[0011] In a preferred embodiment, the mode switching includes: The controller uses a multi-factor evaluation and delay decision-making method to make a comprehensive decision on mode switching. During the multi-factor evaluation process, the controller evaluates the stability of hydraulic system pressure, the changing characteristics of flow demand, and the speed status of servo motor. The controller uses a logic synthesis method to generate a switching permission signal. The switching permission signal is set to allow switching only when three conditions are met simultaneously: the hydraulic system pressure is stable, the flow demand is stable, and the motor is in normal condition. The controller uses a delay decision method to calculate the switching delay time, sets a switching delay timer, and continuously monitors the pressure conditions and switching conditions during the delay period.

[0012] In a preferred embodiment, the solenoid valve pulse width modulation control includes: The controller reads the current actual angle value of the plunger pump swashplate through the position sensor and calculates the angle control deviation as the target angle value minus the current actual angle value. The controller uses pulse width modulation technology to control the energization state of the solenoid valve and generate a pulse width modulation signal; The controller uses a proportional control algorithm to calculate the duty cycle, which is equal to the angle deviation multiplied by the proportional gain coefficient. The controller sends the pulse width modulation signal to the solenoid coil of the two-position four-way solenoid valve through the digital output interface.

[0013] In a preferred embodiment, the mode-specific speed strategy formulation and proportional-integral-derivative parameter adaptive control include: The controller employs a deep reinforcement learning-based parameter adaptive proportional-integral-derivative (PID) control method, using a deep reinforcement learning network for online optimization of the PID parameters. The controller implements closed-loop speed control, calculates the speed control error, and inputs the speed error into the proportional-integral-derivative controller for calculation. The controller implements torque limiting protection and monitors the actual output torque of the servo motor.

[0014] In a preferred embodiment, the multi-mode performance comparison and coordination effect analysis includes: For variable mode, the controller focuses on monitoring energy-saving effect and load adaptability, and calculates the energy saving rate as the theoretical maximum power consumption minus the actual power consumption and then divided by the theoretical maximum power consumption. For the quantitative mode, the controller focuses on monitoring the flow control accuracy and the linearity of speed and flow, and uses the linear regression method to analyze the relationship between the actual flow and the motor speed; The controller measures mode switching performance, including switching response time and switching process stability, and monitors pressure and flow fluctuations during mode switching.

[0015] In a preferred embodiment, a system for driving and controlling a plunger pump with a servo motor is used to perform the above-described method for driving and controlling a plunger pump with a servo motor, comprising: The initialization parameter acquisition module is used to acquire initialization data and servo motor plunger pump coordination control parameters, perform hardware detection and parameter calibration, and obtain servo motor plunger pump coordination control parameters. The pressure condition identification module is used to identify and switch modes based on the coordinated control parameters of the servo motor plunger pump, verify the working characteristics of the plunger pump, and obtain a plunger pump working characteristic verification report. The solenoid valve control module, based on the plunger pump working characteristic verification report, performs solenoid valve pulse width modulation control to obtain a variable quantitative conversion verification report; The speed control module is used to determine the current working mode based on the variable quantitative conversion verification report, perform sub-mode speed strategy formulation and proportional-integral-derivative parameter adaptive control, and obtain a motor operating status report. The evaluation module, based on the motor operating status report, performs multi-mode performance comparison and coordination effect analysis to obtain a servo motor plunger pump coordination effect evaluation report.

[0016] The beneficial effects of this invention are as follows: This invention effectively solves the technical problem of balancing energy saving and precise control in traditional hydraulic systems by combining servo motor precision control technology with the variable and quantitative dual-mode switching technology of a piston pump. Under low-pressure conditions, the system automatically switches to variable mode, fully utilizing the constant-power variable characteristics of the piston pump to achieve energy-saving operation and reduce power consumption. Under high-pressure conditions, the system automatically switches to quantitative mode, locking the swashplate angle at its minimum value through solenoid valve control, eliminating the constant-power variable characteristics, and making the flow output entirely determined by the servo motor speed, achieving precise flow control. Employing advanced algorithms such as Transformer multimodal fusion sensing, convolutional neural network intelligent filtering, and deep reinforcement learning parameter adaptation, the system can intelligently identify changes in pressure conditions and automatically execute smooth mode switching, ensuring optimal control performance under different operating conditions.

[0017] This invention establishes a complete system performance monitoring and evaluation system. By real-time monitoring and comparative analysis of key indicators such as energy-saving effect, flow control accuracy, and mode switching response time under variable and quantitative modes, it achieves comprehensive evaluation and continuous optimization of the system's operating status. Compared with traditional hydraulic control schemes, this invention achieves significant energy-saving effects under low-pressure conditions while ensuring improved flow control accuracy under high-pressure conditions. The system response speed and dynamic performance are also improved to some extent. Furthermore, this invention possesses fault diagnosis and parameter self-optimization capabilities, automatically adjusting control parameters based on operating data, thus improving system reliability and adaptability, and providing important technical support for the intelligent development of hydraulic transmission systems. Attached Figure Description

[0018] Figure 1 This is a flowchart of the main process of a servo motor driven control method for a plunger pump in this invention; Figure 2 This is a detailed flowchart of a method for controlling a plunger pump with a servo motor driven according to the present invention; Figure 3 This is a block diagram of a servo motor driven control system for a piston pump according to the present invention. Detailed Implementation

[0019] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, some features described in the examples may be combined in other examples.

[0020] At least one embodiment of the present invention discloses a method for controlling a plunger pump by driving a servo motor, such as... Figures 1 to 2 As shown, it includes the following steps: Step 1: Obtain the initialization data and equipment configuration parameters of the servo motor control system, perform hardware status detection and pressure condition parameter configuration through the controller, establish a quantitative relationship between the servo motor speed and the output flow of the plunger pump, and obtain the coordinated control parameters of the servo motor and the plunger pump. Step 1.1, Hardware status detection; Based on the received control system start signal and equipment configuration parameters, the controller sequentially initializes and tests each hardware module using the device communication protocol. The control system mainly includes a servo motor, a hydraulic high-pressure high-speed piston variable pump, a two-position four-way solenoid directional valve, a pressure reducing valve, a check valve, a pressure sensor, a flow sensor, a position sensor, and a controller.

[0021] For servo motors, the controller establishes a communication connection with the servo motor driver via the Controller Area Network (CLAN) bus, sends a status query command, and the servo motor driver returns a data packet showing the motor's operating status. The controller then parses this data packet to extract the servo motor's speed range and rated torque parameters to determine if the motor is operating normally. For hydraulic high-pressure, high-speed variable displacement piston pumps, the controller reads the pump's nameplate parameters or configuration file to obtain the maximum displacement and maximum operating pressure parameters. It uses a pressure sensor to detect the pump's outlet pressure to determine the pump's sealing status and a flow sensor to detect the pump's output flow rate to determine the pump's volumetric efficiency. For pressure reducing valves, check valves, and 2-position 4-way solenoid directional valves, the controller sends an on / off test command to the solenoid directional valve, detects the coil resistance to determine if the valve core is functioning correctly, monitors the pressure difference across the pressure reducing valve using a pressure sensor to determine if the pressure reducing valve is working correctly, and performs a reverse pressure test to determine the sealing performance of the check valve. For pressure sensors, flow sensors, and position sensors, the controller collects the output signals of each sensor, determines if the signal amplitude is within the normal range, and uses signal stability analysis methods to determine if the sensors are drifting or experiencing abnormal noise. The controller summarizes the test results of all hardware modules and generates a control system hardware status report that includes parameters such as servo motor speed range, rated torque, maximum displacement of piston pump, maximum working pressure, valve group working status, and sensor calibration status. When all hardware modules are in normal condition, the controller enters the next initialization phase. When a hardware fault exists, the controller generates a fault code and stops the initialization process.

[0022] Step 1.2, Configure pressure condition parameters; Based on the maximum operating pressure parameter of the plunger pump and the pressure characteristics of the application scenario in the control system hardware status report output in step 1.1, the controller adopts a multi-level threshold configuration method to set the judgment criteria for pressure condition identification. According to the typical operating pressure range of the application scenario, the controller divides the system operating pressure into low-pressure and high-pressure ranges, setting an upper threshold for low-pressure and a lower threshold for high-pressure. A pressure hysteresis range is formed between these two thresholds. The hysteresis width setting needs to consider the measurement accuracy of the pressure sensor and the system pressure fluctuation characteristics to avoid frequent switching of operating modes near the critical pressure. For the parameter configuration of the variable mode, the controller sets the maximum swashplate angle parameter of the plunger pump, which corresponds to the maximum flow output capacity of the plunger pump. A constant power variable coefficient is set, which reflects the characteristic of the variable pump automatically adjusting the displacement to maintain constant power output under different pressures. For the parameter configuration of the fixed displacement mode, the controller sets a fixed swashplate angle parameter. This angle should be set to the minimum swashplate angle of the plunger pump, so that the plunger pump operates in the minimum displacement state. At this time, the output flow of the plunger pump is completely determined by the servo motor speed, exhibiting the operating characteristics of a fixed displacement pump. The controller sets the output pressure setpoint of the pressure reducing valve. This pressure value must meet the mechanical requirements of pushing the swashplate angle to its minimum position and maintaining stability, while also considering the pressure regulating accuracy and response speed characteristics of the pressure reducing valve. The controller summarizes the above-configured upper limit threshold for low-pressure conditions, lower limit threshold for high-pressure conditions, pressure hysteresis width, maximum swashplate angle parameter, constant power variable coefficient, fixed swashplate angle parameter, and pressure reducing valve output pressure setpoint to form a pressure condition identification parameter table. This parameter table serves as the benchmark data for subsequent pressure condition identification and mode switching decisions.

[0023] In some embodiments, due to the differences in pressure conditions in different application scenarios, such as the high frequency of pressure changes in the hydraulic system of an injection molding machine and the long pressure holding time in the hydraulic system of a hydraulic press, an adaptive threshold configuration method can be adopted. The purpose is to optimize the pressure threshold setting based on actual operating data and improve the adaptability of mode switching. Specifically, the controller continuously records historical data of pressure changes during device operation, calculates the probability density function of the pressure distribution using statistical analysis methods, identifies bimodal or multimodal characteristics in the pressure distribution, uses the pressure value corresponding to the probability density valley as the initial threshold, uses a clustering algorithm to divide the historical pressure data into low-pressure clusters and high-pressure clusters, calculates the separation index between the two clusters, increases the pressure hysteresis width when the separation index is lower than the set value, and decreases the pressure hysteresis width when the separation index is higher than the set value, and periodically updates the pressure threshold parameters using a sliding window method, enabling the controller to adapt to different operating conditions. This adaptive threshold configuration method achieves dynamic optimization of the pressure threshold through statistical learning of historical data, avoiding the subjectivity and limitations of manually setting the threshold.

[0024] Step 1.3, Establish coordinated control parameters; Based on the maximum swashplate angle parameter, constant power variable coefficient, and fixed swashplate angle parameter from the pressure condition identification parameter table output in step 1.2, as well as the structural parameters of the plunger pump, the controller uses a flow calculation model to construct a quantitative relationship between the servo motor speed and the plunger pump output flow rate, thus obtaining the coordinated control parameters of the servo motor and plunger pump. For flow calculation in variable mode, the controller establishes a flow calculation formula: the output flow rate equals the servo motor speed multiplied by the plunger pump's single-revolution displacement, multiplied by the sine function value of the current swashplate angle, and multiplied by the constant power variable coefficient. The single-revolution displacement is determined by the plunger pump's plunger diameter, number of plungers, and plunger distribution circle radius, etc. The current swashplate angle is obtained in real-time through a position sensor. The constant power variable coefficient reflects the plunger pump's automatic displacement adjustment characteristics under different pressures; this coefficient decreases as the pressure increases to maintain constant output power. For flow calculation in quantitative mode, the controller establishes a simplified flow calculation formula: the output flow rate equals the servo motor speed multiplied by the piston pump's single-revolution displacement, multiplied by the sine function value of the fixed swashplate angle. Since the swashplate angle is locked at its minimum value and does not change with pressure, the constant power variable characteristic is eliminated, and the output flow rate exhibits a linear relationship with the servo motor speed. Based on the established flow calculation model, the controller calibrates the optimal motor speed range under different pressure conditions. Under low-pressure conditions, to fully utilize the energy-saving characteristics of the variable pump, the motor speed range is set to a low-to-medium speed range to avoid mechanical losses and noise caused by high-speed motor operation. Under high-pressure conditions, to achieve precise flow control and meet the rapid response requirements of the hydraulic system, the motor speed range is set to a medium-to-high speed range, ensuring that the target flow rate can be quickly and accurately achieved through speed adjustment in quantitative mode. The controller employs a motor speed transition strategy during mode switching. When the control system switches from variable mode to fixed mode, the controller calculates the speed change required to maintain the same flow output before and after the switch. A ramp function is used to generate a speed transition trajectory, ensuring a smooth change in motor speed to the target value and avoiding flow shocks and pressure fluctuations caused by sudden speed changes. When the control system switches from fixed mode to variable mode, the controller synchronously adjusts the swashplate angle and motor speed to ensure continuous and stable output flow during the switching process. The controller summarizes the established variable mode flow calculation parameters, fixed mode flow calculation parameters, optimal motor speed range, and speed transition strategy parameters to form the servo motor plunger pump coordinated control parameters. These parameters serve as the baseline data for subsequent servo motor control.

[0025] In some embodiments, since the piston pump experiences wear and tear during long-term operation, leading to a decrease in volumetric efficiency, and oil temperature changes affect oil viscosity, thus impacting leakage, an online correction method for the flow model based on a long short-term memory network can be employed. The aim is to improve flow prediction accuracy by correcting the flow calculation model based on actual measured flow. Specifically, the controller establishes a long short-term memory network flow prediction model. This network includes an input layer that receives multi-dimensional time-series data such as pressure, temperature, rotational speed, and swashplate angle. The long short-term memory layer contains three gated units—a forget gate, an input gate, and an output gate—to handle long-term dependencies in the time-series information. The hidden layer uses a fully connected structure for feature fusion, and the output layer generates the flow correction system. The method uses historical operating data to construct a training set for the network training process, which includes input feature sequences under different operating conditions and corresponding actual flow correction coefficients. The mean square error is used as the loss function, and the adaptive moment estimation optimization algorithm is used to update the parameters. The network weights are trained through the backpropagation algorithm. After training, the network can predict the flow correction coefficient based on the current control system state. The controller incorporates the predicted correction coefficient into the flow calculation formula. The corrected output flow is equal to the theoretical flow multiplied by the flow correction coefficient predicted by the long short-term memory network. This method uses deep learning technology to adapt to the wear state and operating temperature changes of the piston pump, thereby improving the flow tracking accuracy of the servo motor speed control.

[0026] Step 2: Based on the coordinated control parameters of the servo motor plunger pump, identify the pressure condition and switch modes to verify the working characteristics of the plunger pump and obtain a plunger pump working characteristic verification report. Step 2.1, Multimodal state assessment; Based on the servo motor plunger pump coordinated control parameters output in step 1.3 and the real-time data collected by the multi-source sensors of the control system, the controller uses the Transformer multimodal fusion sensing method to comprehensively evaluate the operating status of the control system and obtain the comprehensive evaluation result of the control system status. To address the complex coupling relationships between multi-source heterogeneous sensor data such as pressure, flow, temperature, and vibration in hydraulic systems, a multimodal fusion network based on the Transformer architecture is established for the controller. This network includes a multimodal input encoding layer that encodes features for pressure time-series data, flow time-series data, temperature data, and vibration spectrum data respectively; a position encoding layer that adds temporal and spatial location information to different modal data; a multi-head self-attention mechanism layer that calculates the correlation weights and dependencies between different modal data; a feedforward neural network layer that performs feature transformation and nonlinear mapping; and an output layer that generates the fused system state feature vector. During network training, a training set is constructed using historical multimodal sensor data and corresponding system state labels. A masked language model pre-training method is used to learn the intrinsic representation of multimodal data. Supervised learning methods are used to fine-tune the network parameters, and the loss function is designed as a combination of state classification loss and multimodal alignment loss. The trained network can automatically discover the implicit correlations between different sensor data, achieving intelligent fusion of multimodal information. The controller processes current multi-source sensor data through a trained Transformer network. The network outputs a comprehensive state feature vector that includes hydraulic system pressure condition assessment, flow stability assessment, temperature anomaly detection, and vibration fault early warning. Compared to single sensor data, this feature vector contains richer information about the control system's state and can more accurately reflect the control system's true operating state. The controller then summarizes the hydraulic system pressure condition assessment results, flow stability assessment results, temperature anomaly detection results, vibration fault early warning results, and multi-modal fusion feature vector output by the Transformer network to form a comprehensive control system state assessment result. This result serves as the input basis for subsequent intelligent mode switching decisions.

[0027] Step 2.2, Intelligent identification of pressure conditions; Based on the hydraulic system pressure condition assessment results in the comprehensive evaluation results of the control system status output in step 2.1 and the low-pressure condition upper limit threshold, high-pressure condition lower limit threshold, and pressure hysteresis width in the servo motor piston pump coordinated control parameters output in step 1.3, the controller uses a convolutional neural network multi-frequency filtering and trend analysis method to process and judge the current hydraulic system working pressure, and obtain the pressure condition identification results.

[0028] The controller sets the sampling frequency of the pressure sensor, which must be higher than the highest frequency component of the hydraulic system pressure change to satisfy the Nyquist sampling theorem. An analog-to-digital converter converts the analog signal from the pressure sensor into a digital signal, and pressure values ​​from multiple sampling periods are continuously acquired to form a pressure time series. To address the complex noise and multi-frequency interference present in the hydraulic system pressure signal, the controller employs a convolutional neural network for intelligent filtering. This network includes an input layer that receives the raw pressure time series data, a one-dimensional convolutional layer that uses multiple convolutional kernels of different sizes to extract features of different frequencies, a pooling layer for feature dimensionality reduction and noise suppression, a fully connected layer for feature fusion, and an output layer that generates the denoised pressure signal. During network training, noisy pressure signals are used as input, and clean pressure signals are used as labels. Mean squared error loss function and gradient descent optimization algorithm are used to train the network parameters. The trained network can adapt to different types of pressure noise to achieve intelligent denoising. After processing by the convolutional neural network, a smooth pressure signal is obtained, which can accurately reflect the pressure change trend of the hydraulic system without being affected by instantaneous disturbances. The controller uses a trend analysis method to calculate the pressure change rate. It subtracts the pressure value from the previous sampling time from the current sampling pressure value and divides by the sampling time interval to obtain the first derivative of pressure with respect to time. The sign of this derivative indicates the upward or downward trend of pressure, and its magnitude indicates the rate of pressure change. When the absolute value of the pressure change rate is greater than a set rapid change threshold, the controller determines it to be in a rapid pressure change phase and increases the pressure sampling frequency and filter response speed. When the absolute value of the pressure change rate is less than a set stable pressure threshold, the controller determines it to be in a stable pressure phase and appropriately reduces the sampling frequency to save computational resources. Based on the filtered current pressure value and the pressure threshold in the servo motor plunger pump coordinated control parameters output in step 1.3, the controller determines the operating condition. When the current pressure value is less than or equal to the upper limit threshold for low-pressure operation, the controller determines it to be in low-pressure operation. When the current pressure value is greater than the lower limit threshold for high-pressure operation, the controller determines it to be in high-pressure operation. When the current pressure value is within the pressure hysteresis interval between the low-pressure and high-pressure thresholds, the controller maintains the current operating mode without switching, avoiding frequent switching near critical pressures that could cause control system oscillations.

[0029] To ensure the stability and reliability of operating condition judgment, the controller employs a continuous judgment mechanism. It requires that the pressure values ​​across multiple consecutive sampling periods meet the same operating condition judgment criteria before confirming a change in operating condition type, thus avoiding misjudgments caused by instantaneous pressure fluctuations or sensor noise. Based on the operating condition judgment result and the current control system operating mode, the controller generates a switching demand flag. When the current mode is variable and the condition is determined to be high pressure, the switching demand flag is set to switch to quantitative mode. When the current mode is quantitative and the condition is determined to be low pressure, the flag is set to switch to variable mode. When the operating condition type matches the current mode, the flag is set to maintain the current mode. The controller summarizes the processed current pressure value, the calculated pressure change trend, the determined operating condition type, and the generated switching demand flag to form a pressure operating condition identification result, which serves as the input data for mode switching decisions.

[0030] Step 2.3, Mode switching decision generation; Based on the switching demand flag and the current control system operating mode in the pressure condition identification result output in step 2.2, the controller uses a multi-factor evaluation and delay decision-making method to make a comprehensive decision on mode switching, obtaining the mode switching decision result. The controller determines whether the switching demand flag indicates a need for mode switching. When the switching demand flag indicates maintaining the current mode, the controller maintains the current variable or quantitative mode operating state and does not execute the switching decision process. When the switching demand flag indicates a need for switching, the controller initiates the multi-factor evaluation process for mode switching. During the multi-factor evaluation process, the controller assesses the stability of the hydraulic system pressure. By analyzing the variance of the pressure change rate over several recent sampling periods, it determines whether the pressure is in a stable state. When the pressure variance is less than the stability threshold, the hydraulic system pressure is determined to be stable and suitable for mode switching. When the pressure variance is greater than the stability threshold, the hydraulic system pressure is determined to be in a fluctuating state, and the mode switching is delayed until the pressure stabilizes. The controller assesses the changing characteristics of flow demand. By analyzing the time series of the target flow command, it determines whether the current flow is in a rapid adjustment phase. When the rate of change in flow demand exceeds a set threshold, the controller identifies it as a rapid adjustment phase. Switching modes at this point may affect flow tracking performance, so the switch is delayed. When the flow demand is relatively stable, the controller determines it's a suitable time to switch. The controller also assesses the servo motor's speed, reading the current speed and rate of change to determine if the motor is in a stable operating range. When the motor speed is within the rated speed range and the rate of change is small, the controller determines the motor state is suitable for mode switching. When the motor is in a transition phase between acceleration and deceleration, the switch is delayed. Based on the above multi-factor assessment results, the controller uses a logic synthesis method to generate a switching permission signal. Switching is only permitted when all three conditions are met simultaneously: stable hydraulic system pressure, stable flow demand, and normal motor status. Otherwise, switching is prohibited. For situations where switching is permitted, the controller employs a delay-based decision-making method to calculate the switching delay time. The delay time setting must comprehensively consider the pressure change rate and the control system's response characteristics. When the pressure change rate is fast, a shorter delay time is set to quickly respond to changes in operating conditions; when the pressure change rate is slow, a longer delay time is set to fully confirm operating condition stability and avoid unnecessary switching due to temporary pressure fluctuations. The controller sets a switching delay timer, starting from the moment the switching permission signal is generated. During the delay period, it continuously monitors the pressure conditions and switching conditions. If the switching conditions change during the delay period, causing the switching requirements to no longer be met, the switching decision is canceled and the timer is reset. If the switching conditions remain met during the delay period, a formal switching decision command is generated when the delay time expires.The controller predicts the performance indicators of the control system after the switch based on the switching direction. When switching from variable mode to quantitative mode, it predicts that the flow control accuracy will improve, the control system energy consumption may increase, and the response speed will be faster. When switching from quantitative mode to variable mode, it predicts that the control system energy consumption will decrease, the flow control accuracy may decrease, and the load adaptability will be enhanced. The controller confirms the safety of the switching process, assesses the magnitude of possible pressure surges during the switching process, determines whether the pressure surges are within the safe tolerance range of the control system, assesses the magnitude of flow changes during the switching process, and determines whether flow fluctuations will affect the normal operation of the load equipment. When the safety assessment is passed, the controller generates the final switching decision command. When the safety assessment fails, the controller cancels the switching decision or adjusts the switching strategy to reduce the switching risk. The controller summarizes the generated switching decision command, the calculated switching delay setpoint, the predicted post-switching performance indicators, and the safety confirmation results to form the mode switching decision result. This result serves as the basis for subsequent swashplate angle control and servo motor coordinated control commands.

[0031] In some embodiments, due to the potential for pressure and flow coupling oscillations in the control system under certain special operating conditions, frequent mode switching can exacerbate the instability of the control system. A fuzzy neural network switching decision method can be employed. The aim is to improve the robustness of switching decisions by integrating multiple uncertainties through fuzzy inference. Specifically, the controller establishes a fuzzy neural network inference system. This network includes a fuzzification layer that converts input variables, including pressure deviation, pressure change rate, flow tracking error, and control system oscillation indicators, into fuzzy sets; a rule layer that stores fuzzy rules in the form of expert experience; a normalization layer that normalizes the rule activation intensity; and a defuzzification layer that uses the centroid method to convert the fuzzy output into a precise switching urgency value. The network training process uses historical switching decision data to construct a training set, and uses the backpropagation algorithm to adjust the membership function parameters and rule weights. The training objective is to minimize the error between the predicted switching urgency and the expert-labeled value. After training, the network can output the switching urgency based on the current control system state. The controller determines whether to execute a switch and the duration of the switch delay based on the switching urgency value. This fuzzy neural network switching decision method can handle the uncertainty and fuzziness of input information, and achieves a comprehensive balance of multiple factors by learning from expert experience, thereby improving the adaptability and stability of switching decisions under complex operating conditions.

[0032] Step 2.4, Verification and confirmation of working characteristics; Based on the switching decision command and real-time status data of the plunger pump in the mode switching decision result output in step 2.3, the controller uses a characteristic parameter detection and comparison verification method to verify the variable quantitative characteristics of the plunger pump, and obtains a plunger pump working characteristic verification report. When the mode switching decision command is to switch to quantitative mode, the controller waits for the swashplate angle control to complete; then it begins to verify whether the plunger pump has successfully switched to quantitative working characteristics. The controller reads the actual angle value of the swashplate through the position sensor and determines whether the actual angle value is within the allowable deviation range of the fixed swashplate angle. The allowable deviation range is determined according to the measurement accuracy of the position sensor and the accuracy requirements of the swashplate angle control. When the deviation between the actual angle value and the target fixed angle is less than the allowable deviation threshold, the controller determines that the swashplate angle has been successfully locked at the minimum value. When the deviation is greater than the allowable deviation threshold, the controller determines that the swashplate angle locking has failed and generates an angle control abnormality alarm. After confirming the swashplate angle lock, the controller verifies the flow characteristics. The actual motor speed is read by the servo motor driver, and the actual output flow of the plunger pump is measured by the flow sensor. A linear regression method is used to analyze the relationship between the actual flow and the motor speed, calculating the regression coefficient and correlation coefficient. When the correlation coefficient is close to 1, it indicates a good linear relationship between flow and speed, verifying the plunger pump's operating characteristic in fixed-displacement mode where the flow is entirely determined by the motor speed. When the correlation coefficient deviates from 1, it indicates an unsatisfactory linear relationship between flow and speed, potentially indicating that constant power variable characteristics have not been completely eliminated. The controller uses a fixed-displacement pump characteristic verification method, controlling the servo motor to run at different speeds, recording the output flow corresponding to each speed, and calculating the ratio of flow to speed (i.e., flow per unit speed). It is then determined whether this ratio remains constant across different speeds. When the coefficient of variation of the flow per unit speed is less than a set threshold, the plunger pump exhibits fixed-displacement pump characteristics. When the coefficient of variation is greater than the set threshold, it indicates that the flow is still affected by other factors.

[0033] When the mode switching decision command is to switch to variable mode, the controller waits for the swashplate angle control to complete; then it begins to verify whether the plunger pump has successfully switched to variable operation characteristics. The controller continuously monitors the changes in the swashplate angle through the position sensor, applies different load pressures, and observes whether the swashplate angle automatically adjusts with changes in load pressure. When the load pressure increases, the swashplate angle should decrease; when the load pressure decreases, the swashplate angle should increase. By analyzing the correspondence between the changes in swashplate angle and load pressure, it determines whether the swashplate can freely adjust according to the load. When the swashplate angle can freely change within the allowable range and shows a negative correlation with the load pressure, the controller determines that the swashplate angle adjustment function is normal, verifying the variable pump characteristics. When the swashplate angle remains unchanged or its change pattern is abnormal, the controller determines that the swashplate angle adjustment function is abnormal. The controller verifies the constant power variable characteristic by keeping the servo motor speed constant and gradually increasing the hydraulic system load pressure while monitoring the output flow and output power of the piston pump. The output power is calculated based on the relationship that power equals pressure multiplied by flow. It is then determined whether the output power remains relatively constant under different pressures. When the fluctuation range of the output power is within the allowable range of the constant power variable coefficient, the piston pump is verified to exhibit constant power variable characteristics. When the output power changes with pressure, it indicates that the constant power variable characteristic is not obvious.

[0034] Regardless of whether switching to quantitative or variable mode, the controller must monitor the pressure response characteristics during the switching process. The controller records the hydraulic system pressure at the moment the mode switching command is issued, continuously acquires the pressure time series during the switching process, and analyzes the transient response characteristics of the pressure, including pressure peak value, pressure overshoot, and pressure settling time. It determines whether the hydraulic system pressure is stable and free from abnormal fluctuations after the mode switch. When the pressure overshoot is less than the allowable overshoot threshold and the pressure settling time is less than the allowable time threshold, the controller determines that the mode switching process is smooth. When the pressure overshoot is too large or continuous oscillation occurs, the controller determines that there is a pressure shock problem during the mode switching process, requiring optimization of the switching strategy. The controller records key parameter data during the switching process, including the switching time (from the issuance of the switching command to the swashplate angle reaching the target value and stabilizing), the pressure change curve (the trajectory of pressure change over time before and after the switch), the flow rate change curve (the trajectory of flow rate change over time before and after the switch), and the swashplate angle change curve (the adjustment process of the swashplate angle). This data is used for post-process analysis and parameter optimization of the switching process. The controller summarizes the swashplate angle locking confirmation or adjustment function confirmation, quantitative characteristic verification results or variable characteristic verification results, pressure response characteristic analysis results, switching process recorded data, and control system stability assessment conclusions into a plunger pump working characteristic verification report. This report serves as the basis for confirming the successful completion of the mode switching and subsequent servo motor speed control.

[0035] Step 3: Based on the plunger pump working characteristic verification report, perform solenoid valve pulse width modulation control to obtain variable quantitative conversion verification report; Step 3.1, Calculate the target swashplate angle; Based on the current mode switching status and target operating mode in the plunger pump operating characteristic verification report output in step 2.4, the controller uses the angle target value calculation and reachability analysis method to determine the swashplate angle control target. When the target operating mode is the quantitative mode, the controller reads the fixed swashplate angle parameter from the pressure condition identification parameter table output in step 1.2 and sets this fixed angle as the swashplate angle target value. This target value should be the minimum allowable angle of the plunger pump swashplate, so that the plunger pump operates in the minimum displacement state. At this time, the output flow of the plunger pump is completely determined by the servo motor speed and is not affected by the change of the swashplate angle, thus realizing the quantitative pump operating characteristics. When the target operating mode is variable mode, the controller needs to dynamically calculate the target swashplate angle value based on the current load pressure and flow demand. The controller reads the parameters of the constant power variable control algorithm from the servo motor plunger pump coordinated control parameters output in step 1.3. This algorithm is based on the constant power principle. Under the given motor speed and target output power, it calculates the optimal swashplate angle based on the current load pressure. The calculation formula is that the sine value of the target swashplate angle is equal to the target output power divided by the motor speed multiplied by the single-revolution displacement multiplied by the current pressure and then multiplied by the constant power variable coefficient. The target swashplate angle value is obtained by calculating the arcsine function. This angle enables the plunger pump to output an appropriate flow rate under the current pressure to achieve the target power, avoid motor overload and ensure energy-saving operation.

[0036] The controller performs an reachability check on the calculated target angle to determine whether the target angle is within the physical limits of the plunger pump swashplate. The minimum angle of the swashplate is limited by the structural design of the plunger pump and cannot be zero, otherwise the plunger pump will have no flow output. The maximum angle of the swashplate is limited by the mechanical strength and volumetric efficiency of the plunger pump and cannot be too large, otherwise it will cause increased internal leakage and excessive mechanical stress. The controller compares the target angle with the minimum angle limit and the maximum angle limit. When the target angle is less than the minimum angle limit, the target angle is corrected to the minimum angle limit. When the target angle is greater than the maximum angle limit, the target angle is corrected to the maximum angle limit. When the target angle is within the allowable range, the calculated target angle value is maintained. The controller sets a rate limit for the change of swashplate angle. To avoid flow shocks and pressure fluctuations in the hydraulic system caused by rapid changes in the swashplate angle, the controller limits the rate of change of the swashplate angle to no more than the maximum allowable rate of change. This maximum allowable rate of change is determined based on the inertia and damping characteristics of the hydraulic system. The controller calculates the shortest adjustment time required from the current swashplate angle to the target swashplate angle. This time is equal to the angle change divided by the maximum allowable rate of change. When the calculated adjustment time is less than one control cycle, it indicates that the angle change is small and can be completed within one cycle. When the adjustment time is greater than one control cycle, the controller generates a trajectory plan for the angle change, decomposing the angle adjustment process into multiple control cycles. The angle change in each cycle does not exceed the rate limit.

[0037] The controller establishes angle control accuracy requirements and sets allowable angle control errors based on the different accuracy requirements of the swashplate angle control under different operating modes. In quantitative mode, the swashplate angle needs to be precisely locked at a fixed value to eliminate the constant power variable characteristic. High angle control accuracy is required, so the controller sets a relatively small angle control accuracy threshold in quantitative mode. When the deviation between the actual angle and the target angle is less than this accuracy threshold, the angle control is considered adequate. In variable mode, the swashplate angle needs to be freely adjustable according to the load. The absolute accuracy requirement for angle control is relatively low, but the flexibility of adjustment is high. The controller sets a relatively large angle control accuracy threshold in variable mode, allowing for a larger angle control error to ensure the flexibility of swashplate adjustment. The controller summarizes the calculated and set target angle value, angle change rate limit, angle control accuracy requirements, and the correspondence between modes and angles to form the swashplate angle control target. This control target serves as the basis for the instructions executed by the solenoid valve control.

[0038] Step 3.2, solenoid valve pulse width control; Based on the target angle value output in step 3.1 and the current actual position of the swashplate measured by the position sensor, the controller uses deviation calculation and solenoid valve pulse width modulation to achieve precise adjustment of the swashplate angle, obtaining the solenoid valve control execution result. The controller reads the current actual angle value of the plunger pump swashplate through the position sensor, which can be an angle encoder or a linear displacement sensor, installed on the swashplate shaft or swashplate drive mechanism, capable of measuring the swashplate's deflection angle relative to the neutral position in real time. The controller calculates the angle control deviation by subtracting the current actual angle value from the target angle value. The sign of the angle deviation indicates whether the swashplate angle needs to be increased or decreased, and the magnitude of the angle deviation indicates the required adjustment range.

[0039] Based on the calculated angle deviation, the controller determines the control strategy for the two-position four-way solenoid directional valve. This solenoid directional valve has two operating positions: energized and de-energized, and two working ports. One working port connects to the pressure reducing valve outlet and the check valve, while the other working port connects to the swashplate control port of the piston pump. When the solenoid valve is de-energized, the valve core is in its initial position, the swashplate control port is connected to the return port, and the hydraulic oil from the control port flows back to the oil tank. Under the force of the return spring, the swashplate angle increases to its maximum value, and the piston pump operates at maximum displacement. When the solenoid valve is energized, the valve core is pushed to the operating position. The high-pressure oil, after being depressurized by the pressure reducing valve, enters the swashplate control port through the check valve and the solenoid valve. The control oil pressure generates thrust on the swashplate's working surface, overcoming the return spring force and load force, causing the swashplate angle to decrease to its minimum value, and the piston pump operates at minimum displacement. The controller determines the control strategy of the solenoid valve based on the sign and magnitude of the angle deviation. When the angle deviation is greater than the positive control dead zone threshold, it indicates that the current angle is greater than the target angle and the swashplate angle needs to be reduced. The controller issues an energizing command to the solenoid valve, causing control oil pressure to enter the swashplate control port and push the swashplate angle to decrease. When the angle deviation is less than the negative control dead zone threshold, it indicates that the current angle is less than the target angle and the swashplate angle needs to be increased. The controller issues a de-energizing command to the solenoid valve, connecting the swashplate control port to the return oil, and the swashplate angle increases under the action of spring force. When the absolute value of the angle deviation is less than or equal to the control dead zone threshold, it indicates that the current angle is close to the target angle. The controller maintains the current state of the solenoid valve without switching it to avoid oscillation and solenoid valve overheating caused by frequent power-on and power-off.

[0040] To achieve precise control and rapid response of the swashplate angle, the controller employs pulse width modulation (PWM) technology to control the energization of the solenoid valve. The controller generates a PWM signal, a periodic square wave with the frequency of the PWM signal. The duty cycle of the square wave, i.e., the proportion of the high-level time to the entire cycle, is determined based on the angle deviation. When the angle deviation is large, it indicates a greater control force is needed for rapid swashplate adjustment. The controller sets a larger duty cycle, allowing the solenoid valve a longer energization time within a PWM cycle, thus providing more time for the control oil pressure to act on the swashplate and drive the angle change. When the angle deviation is small, it indicates the swashplate angle is close to the target value, requiring a reduction in control force to avoid overshoot. The controller sets a smaller duty cycle, shortening the solenoid valve's energization time within a cycle, thus reducing the control oil pressure's action time and achieving smoother control. The controller uses a proportional control algorithm to calculate the duty cycle. The duty cycle equals the angle deviation multiplied by the proportional gain coefficient. The proportional gain coefficient is tuned according to the system's response characteristics and stability requirements. When the proportional gain is too large, the system response is fast but prone to oscillation; when the proportional gain is too small, the system is stable but the response is slow. The controller can determine the optimal proportional gain using experimental or theoretical analysis methods. To prevent the duty cycle from exceeding the allowable range, the controller limits the calculated duty cycle. When the duty cycle is greater than 100%, it is limited to 100%, indicating that the solenoid valve is continuously energized; when the duty cycle is less than 0%, it is limited to 0%, indicating that the solenoid valve is continuously de-energized.

[0041] The controller sends a pulse width modulation (PWM) signal to the solenoid coil of the solenoid directional valve via a digital output interface. The solenoid coil obtains an average current based on the duty cycle of the PWM signal, and the electromagnetic force generated by this average current drives the valve core. Since the frequency of the PWM signal is much higher than the response frequency of the hydraulic and mechanical systems, the solenoid valve and hydraulic system exhibit an averaging effect on the PWM signal, equivalent to receiving a continuous control signal proportional to the duty cycle, thus achieving continuous adjustment of the swashplate angle. During the process of the solenoid valve being energized and allowing control oil to enter the swashplate control port, the controller monitors the establishment of control oil pressure. By measuring the control oil pressure value using a pressure sensor installed in the swashplate control oil circuit, the controller determines whether the control oil pressure has reached the set value. When the high-pressure oil from the piston pump outlet is reduced to the set pressure value by the pressure reducing valve, it enters the swashplate control port through the check valve and the energized solenoid valve, establishing a stable control pressure within the swashplate control oil chamber. This control pressure needs to be sufficiently large to overcome the swashplate return spring force and load reaction force, pushing the swashplate angle down to the target value and maintaining stability. The controller determines whether the control oil pressure is within the allowable deviation range of the set pressure. When the control oil pressure is too low, the swashplate angle may not be able to decrease to the target value. The controller generates an alarm message for insufficient control oil pressure. When the control oil pressure is normal, it confirms that the control oil pressure has been successfully established.

[0042] The controller monitors the swashplate angle in real time using position sensors to determine if the angle is adjusting in the expected direction. When the solenoid valve is energized and control oil pressure is established, the swashplate angle should continuously decrease. The controller checks if the swashplate angle shows a decreasing trend over several consecutive control cycles. If the angle does decrease, the swashplate response is confirmed to be normal; if the angle remains unchanged or changes in the opposite direction, the swashplate response is considered abnormal, potentially indicating mechanical jamming or sensor malfunction. When the solenoid valve is de-energized and the control port is connected to the return oil, the swashplate angle should continuously increase under spring force. The controller checks if the swashplate angle shows an increasing trend, confirming the swashplate reset function is normal. The controller continuously executes the above deviation calculation and pulse width modulation control process, forming a closed-loop feedback control of the swashplate angle until the deviation between the actual swashplate angle and the target angle is less than the control accuracy requirement. The controller then determines that the angle control is in place and stops the angle adjustment. The controller summarizes the parameters of the solenoid valve control signal, the monitoring results of the control oil pressure status, the confirmation information of the swashplate angle response, and the evaluation data of the angle adjustment accuracy to form the solenoid valve control execution result. This result serves as the basis for verifying the quantitative conversion effect of variables.

[0043] Step 3.3, Quantitative transformation and verification of variables; Based on the angle adjustment completion confirmation and actual operating data of the plunger pump in the solenoid valve control execution results output in step 3.2, the controller uses a flow linearity detection and conversion parameter optimization method to comprehensively verify the quantitative conversion effect of variables. When the control system switches to quantitative mode, the controller verifies the quantitative mode conversion effect. The controller confirms that the swashplate angle has been stably locked at the fixed swashplate angle, i.e., the minimum angle position, and continuously monitors the swashplate angle through the position sensor to determine whether the angle value remains stable without drift. The controller performs flow rate and speed linearity detection, controls the servo motor to run at multiple different speeds, maintains stable operation at each speed for a period of time, measures the corresponding plunger pump output flow rate through the flow sensor, records the flow rate data pairs for each speed, and uses the least squares method to perform linear fitting on the speed and flow rate data to obtain the slope and intercept of the fitted line. The goodness of fit, i.e., the coefficient of determination, is calculated. When the coefficient of determination is close to 1, it indicates that the flow rate and speed have a highly linear relationship, verifying that in quantitative mode, the flow rate change completely follows the speed change, and the constant power variable characteristic is successfully eliminated. The controller calculates the flow linearity deviation. For each measurement point, it calculates the deviation between the actual flow and the flow predicted by the fitted straight line, and counts the maximum value and root mean square value of the deviation for all measurement points to determine whether the linearity deviation is within the allowable range. When the linearity deviation is small, it confirms that the quantitative mode conversion effect is good.

[0044] When the control system switches to variable mode, the controller verifies the effect of the variable mode transition. The controller confirms that the swashplate angle can be freely adjusted without being locked. By changing the load pressure of the control system, it observes whether the swashplate angle changes accordingly. When the load pressure increases, it monitors whether the swashplate angle automatically decreases to maintain constant power output; when the load pressure decreases, it monitors whether the swashplate angle automatically increases to increase flow output. The controller performs constant power variable characteristic testing, keeping the servo motor speed constant, and gradually increasing the control system load pressure. At each pressure level, it measures the output flow rate of the plunger pump and the swashplate angle, calculating the output power at each operating point. Output power equals pressure multiplied by flow rate. The controller analyzes the variation of output power with pressure. When the output power remains relatively constant under different pressures, it verifies that the plunger pump exhibits constant power variable characteristics. When the load increases, the flow rate automatically decreases to achieve energy-saving operation. The controller calculates the constant power deviation, statistically analyzes the mean and standard deviation of the output power under different pressures, and determines whether the power fluctuation is within the allowable range of the constant power variable coefficient, confirming the effect of the variable mode transition.

[0045] The controller measures the response time of mode switching, recording the time from the moment the mode switching command is issued to the moment the swashplate angle reaches the target value and stabilizes. The difference between these two moments is the switching response time, which includes the solenoid valve action time, the hydraulic system charging and discharging time, and the swashplate mechanical movement time. The controller determines whether the switching response time meets the system's dynamic performance requirements. An excessively long response time indicates a slow switching speed, affecting the system's adaptability to changes in operating conditions. The controller assesses system stability during the switching process by continuously acquiring pressure, flow, and speed signals. It analyzes the fluctuation amplitude and frequency characteristics of each signal to determine if unstable phenomena such as pressure surges, sudden flow changes, or speed oscillations occur. When the fluctuation amplitude of each signal is within the allowable range and the fluctuations decay rapidly, the switching process is considered stable. Continuous oscillations or shocks exceeding safe limits indicate a stability problem in the switching process. The controller monitors oil temperature changes during the switching process, measuring the hydraulic oil temperature using a temperature sensor to determine if the temperature rise is normal, thus preventing system overheating problems caused by frequent switching.

[0046] The controller records key data on the conversion effect, including swashplate angle control accuracy data (statistics of the maximum and average deviations between the actual and target angles), conversion response time data (recording the time from command issuance to control arrival), system stability data (recording pressure fluctuation amplitude, flow fluctuation amplitude, and temperature change amplitude), and flow characteristic change data (recording flow linearity in quantitative mode and constant power characteristics in variable mode). Based on the recorded conversion effect data, the controller optimizes the conversion parameters and analyzes the relationship between the conversion effect and control parameters. When the conversion response time is long, the solenoid valve pulse width modulation parameter is adjusted to increase the proportional gain or increase the pulse width modulation frequency to speed up the response. When oscillations occur during the conversion process, the control dead zone threshold is adjusted or the proportional gain is decreased to improve stability. When the angle control accuracy is insufficient, the position feedback control algorithm is optimized or the position sensor is calibrated to improve accuracy. When the control oil pressure is unstable, the pressure reducing valve setpoint is adjusted or the one-way valve performance is checked to stabilize the oil pressure. The controller updates the optimized parameters to the control system and uses the optimized parameters to improve conversion performance during subsequent mode switching processes. The controller will compile the verified quantitative or variable mode conversion effect, the measured conversion response time, the assessed system stability conclusions, the recorded key conversion effect data, and the generated parameter optimization suggestions into a variable quantitative conversion verification report. This report serves as the basis for confirming the successful mode conversion and for subsequent coordinated control of servo motor speed.

[0047] Step 4: Based on the variable quantitative conversion verification report, determine the current working mode, formulate the sub-mode speed strategy and perform proportional-integral-derivative parameter adaptive control, and obtain the motor operating status report; Step 4.1, Motor speed scheme formulation; Based on the current piston pump operating mode confirmation and target flow command in the variable quantitative conversion verification report output in step 3.3, the controller receives the target flow command from the upper control system or operation panel through the communication interface. This command is determined comprehensively based on the current process requirements, load characteristics, and system operating status, reflecting the expected flow value that the hydraulic system needs to output under the current operating conditions. The controller checks the validity of the received target flow command, determining whether the command value is within the piston pump's flow output range. When the target flow exceeds the maximum output capacity, it performs amplitude limiting; when the target flow is lower than the minimum stable output, it performs lower limit protection, ensuring the executability of the target flow command.

[0048] Based on the confirmed target flow command, the controller uses a speed calculation and parameter grading setting method to generate a speed control scheme for the servo motor.

[0049] When the plunger pump operates in fixed-rate mode, the controller employs a precise speed control strategy to achieve precise flow control. The controller reads the fixed-rate mode flow calculation parameters from the servo motor-plunger pump coordinated control parameters output in step 1.3, including the plunger pump's single-revolution displacement and fixed swashplate angle. Based on the target flow command, it calculates the required target servo motor speed. The calculation formula is: target speed equals target flow divided by single-revolution displacement, then divided by the sine of the fixed swashplate angle. Since the swashplate angle lock in fixed-rate mode results in a strictly linear relationship between flow and speed, precise control of the motor speed allows for precise control of the output flow. The controller performs a feasibility check on the calculated target speed to determine if it falls within the servo motor's speed range. If the target speed is lower than the motor's minimum stable speed, the target speed is corrected to the minimum stable speed, and the target flow is adjusted accordingly. If the target speed is higher than the motor's maximum allowable speed, the target speed is corrected to the maximum allowable speed, and the target flow is adjusted accordingly. If the target speed is within the allowable range, the calculated target speed value is maintained.

[0050] When the plunger pump operates in variable mode, the controller employs a coordinated speed control strategy for coarse adjustment. In variable mode, the output flow rate of the plunger pump is determined by both the servo motor speed and the swashplate angle, which automatically adjusts according to the load pressure. Therefore, simply controlling the speed cannot precisely control the flow rate; the servo motor speed primarily serves as a coarse adjustment mechanism. Based on the target flow command and the current load pressure, and considering the constant power variable characteristics, the controller calculates a suitable motor speed. This calculation must take into account the constant power variable coefficient and the influence of the current pressure on the swashplate angle. An iterative calculation method is used to determine the motor speed, ensuring that the output flow rate is close to the target flow rate at the current pressure and corresponding swashplate angle. The controller monitors the deviation between the actual flow rate and the target flow rate. When the deviation is significant, the controller fine-tunes the motor speed to achieve coarse flow adjustment. Because the flow rate in variable mode is also affected by changes in the swashplate angle, the flow tracking accuracy of speed adjustment is not as high as in quantitative mode, but it can achieve a certain degree of flow control and fully utilize the constant power variable characteristics for energy saving.

[0051] The controller sets the speed control accuracy requirements based on the current operating mode. In quantitative mode, to achieve precise flow control, high accuracy is required for servo motor speed control. The controller sets a relatively small speed control accuracy threshold in quantitative mode, requiring the deviation between the actual speed and the target speed to be less than this accuracy threshold. Higher speed control accuracy results in correspondingly higher flow control accuracy. In variable mode, since flow is primarily regulated by constant power variable characteristics, the absolute accuracy requirement for speed control is relatively lower. The controller sets a relatively large speed control accuracy threshold in variable mode, allowing for larger speed control errors and reducing the control requirements on the servo motor. The controller establishes a speed change rate limit. To avoid flow shocks and mechanical shocks caused by rapid changes in motor speed, the controller limits the speed change rate to no more than the maximum allowable value. In quantitative mode, to achieve rapid flow response, a larger speed change rate limit is set, allowing for rapid acceleration and deceleration of the motor. In variable mode, since flow changes are also buffered by the automatic adjustment of the swashplate angle, a smaller speed change rate limit is set to ensure smooth motor operation. When the target speed changes, the controller generates a speed change trajectory based on the speed change rate limit, and uses a trapezoidal speed curve or an S-shaped speed curve to plan the acceleration and deceleration process of the speed to ensure smooth speed change.

[0052] The controller calculates and predicts the torque demand of the servo motor. To avoid motor overload and ensure efficient motor operation, it needs to predict the motor's torque demand at the target speed. Based on the working principle of a plunger pump, the controller calculates the pump's driving torque as output pressure multiplied by displacement divided by twice pi. Displacement is equal to displacement per revolution multiplied by the sine of the swashplate angle. Pressure is measured in real-time by a pressure sensor, and the swashplate angle is measured in real-time by a position sensor. The controller calculates the driving torque required by the plunger pump under the current operating conditions, considering the pump's mechanical efficiency and the coupling's transmission efficiency. It then calculates the actual torque required by the servo motor and determines whether the predicted torque exceeds the servo motor's rated torque. If the predicted torque is within the rated torque range, the motor can be driven normally. If the predicted torque exceeds the rated torque, an overload warning is generated, requiring a reduction in the target flow rate or optimization of operating parameters to avoid motor overload. The controller summarizes the calculated target speed value, the set speed control accuracy requirements, the established speed change rate limit, and the predicted motor torque demand to form a motor speed control scheme. This scheme serves as the command basis for the servo motor drive control.

[0053] In some embodiments, due to the possibility that the system may simultaneously face high flow rate demand and high pressure conditions under certain operating conditions, the power output of the servo motor may approach or exceed its rated power. A power-limited speed-flow coordination control method can be adopted. The aim is to optimize the allocation strategy of speed and flow rate while ensuring system safety. Specifically, the controller monitors the real-time output power of the servo motor, which is equal to the motor output torque multiplied by the motor speed. A safe upper limit for motor power is set as a certain proportion of the rated power. When the output power is detected to be close to the safe upper limit, the controller initiates a power-limiting control strategy, prioritizing ensuring that the system pressure demand meets the load requirements. Under this premise, the target flow rate is appropriately reduced to decrease the power demand, or the target speed is appropriately reduced in quantitative mode, or the swashplate angle is reduced to decrease the displacement under high pressure by switching to quantitative mode. The controller uses a power feedback control algorithm to solve for the optimal combination of speed and flow rate with the power safe upper limit as a constraint. The Lagrange multiplier method or linear programming method is used for optimization to obtain a speed command that satisfies the power constraint and is as close as possible to the target flow rate. This power-limited speed-flow coordination control method balances performance requirements and safety constraints through multi-objective optimization, avoiding motor overload operation and extending equipment lifespan.

[0054] Step 4.2, adaptive speed control is executed; Based on the target speed value in the motor speed control scheme output in step 4.1 and the current operating state of the servo motor, the controller employs a deep reinforcement learning-based parameter adaptive proportional-integral-derivative (PID) control and torque limiting method to achieve precise drive control of the servo motor. The controller adjusts the parameters of the PID controller according to the current piston pump operating mode, achieving intelligent adaptive optimization of the control parameters. Addressing the nonlinear characteristics and time-varying parameters of the servo motor under different operating conditions, the controller uses a deep reinforcement learning network for online optimization of the PID parameters. This network adopts a deep Q-network architecture, including an input layer that receives state information such as current speed error, speed change rate, load torque, and system pressure; a hidden layer using a multi-layer fully connected neural network for feature extraction and state value evaluation; and an output layer that generates adjustment actions for the proportional, integral, and derivative coefficients. During network training, an experience replay mechanism stores historical state action reward sequences, and a temporal difference learning algorithm updates the network weights. The reward function is designed as the negative value of the speed tracking error plus a system stability reward. By interacting with the environment to learn the optimal parameter adjustment strategy, the trained network can adjust the PID parameters in real time according to the current system state, achieving intelligent parameter adaptation. A proportional-integral-derivative (PID) controller comprises a proportional, integral, and derivative element. The weighted sum of the outputs of these three elements yields the total controller output. The weighting coefficients of each element—the proportional, integral, and derivative coefficients—are optimized in real-time by a deep reinforcement learning network. In quantitative mode, since the flow rate is entirely determined by the rotational speed and the flow-speed relationship is linear, the system has a fast dynamic response, requiring high speed and accuracy in speed control. The deep reinforcement learning network learns to set a larger proportional coefficient to enhance system response speed, a moderate integral coefficient to eliminate steady-state error, and a smaller derivative coefficient to suppress overshoot and oscillation. In variable mode, since the swashplate angle automatically adjusts according to the load, the system involves multivariable coupling. Excessive control gain may cause system oscillation. The deep reinforcement learning network learns to set a smaller proportional coefficient to avoid over-adjustment, a larger integral coefficient to ensure speed tracking, and an appropriate derivative coefficient to improve dynamic performance.

[0055] The controller implements closed-loop speed control. It reads the actual speed feedback value of the motor from the servo motor driver and calculates the speed control error. The speed error equals the target speed minus the actual speed. The sign of the speed error indicates whether acceleration or deceleration is needed, and the magnitude of the speed error indicates the degree of deviation. The controller inputs the speed error into a proportional-integral-derivative (PID) controller for calculation. The output of the proportional term equals the speed error multiplied by the proportional coefficient. The proportional term can respond quickly to errors but cannot eliminate steady-state errors. The output of the integral term equals the cumulative sum of historical speed errors multiplied by the integral coefficient. The integral term can eliminate steady-state errors but may cause overshoot. The output of the derivative term equals the rate of change of the speed error multiplied by the derivative coefficient. The derivative term can predict error trends and improve dynamic response but is sensitive to noise. The controller filters the input of the derivative term to reduce noise impact. The controller calculates the total output of the PID controller, which equals the proportional term plus the integral term plus the derivative term. This total output serves as the control signal for the servo motor, reflecting the required driving torque.

[0056] The controller implements torque limiting protection, monitoring the actual output torque of the servo motor. It reads the torque feedback value from the motor driver or estimates the output torque based on the current signal to determine if the actual torque is close to or exceeds the rated torque. When the actual torque is less than the safety threshold of the rated torque, the motor operates within the normal range, and the controller directly controls the motor according to the proportional-integral-derivative (PID) control output. When the actual torque approaches the rated torque, the motor is at risk of overload, and the controller activates the torque limiting protection strategy, limiting the speed increase rate or limiting the maximum value of the control output to prevent further torque increase. When the actual torque exceeds the rated torque, the motor is at risk of burnout due to overload operation, and the controller forcibly reduces the motor speed or limits the output torque to a safe range, while simultaneously generating an overload alarm to indicate system abnormality. The torque limiting strategy is implemented by limiting the PID control output, setting an upper and lower limit for the control output. When the calculated control output exceeds the upper limit, the control output is limited to the upper limit; when the control output is below the lower limit, the control output is limited to the lower limit. By limiting the control output, the motor torque output is indirectly limited, protecting the motor from overload.

[0057] The controller communicates with the servo motor driver via the Controller Area Network (CLAN) bus, sending speed commands and torque limit parameters. The controller packages the calculated target speed and control output into a control data frame, which includes the target speed value, control mode, torque limit value, enable signal, and other information. This frame is then sent to the servo motor driver via the CLAN bus. Upon receiving the control data frame, the servo motor driver parses the command information and performs internal current and speed loop control based on the target speed and current speed feedback, driving the motor to the target speed. The controller interacts with the driver at a specific communication cycle, which must be shorter than the control cycle to ensure real-time control. Within each communication cycle, the controller receives motor status information from the driver, including actual speed, actual torque, motor temperature, and fault codes.

[0058] The controller monitors the servo motor's response performance and records key parameters during speed tracking. It calculates the speed tracking error, the deviation between the actual and target speeds, and statistically analyzes the maximum, average, and standard deviation of the tracking error to assess whether the speed control accuracy meets requirements. A small and stable tracking error confirms good speed control performance, while a large or volatile tracking error indicates the need for control parameter optimization or system interference. The controller measures the speed response time, recording the time from a change in target speed to the actual speed reaching and stabilizing at the new target value. This response time reflects the system's dynamic performance; a short response time indicates good system speed, while a long response time indicates high system inertia or conservative control parameters. The controller monitors torque changes, recording the motor's torque output during acceleration, deceleration, and steady-state operation. It analyzes the torque-load matching relationship to determine if the motor is operating within its high-efficiency range. Finally, the controller calculates the system's power consumption, which equals the actual torque multiplied by the actual speed. It statistically analyzes power consumption data under different operating conditions to evaluate the system's energy efficiency level. The controller summarizes the actual speed value monitored and recorded, the calculated speed tracking error, the measured response time, the monitored torque output value, and the calculated power consumption to form a motor operating status report, which serves as the data basis for system performance evaluation and optimization.

[0059] Step 5: Based on the motor operating status report, perform multi-mode performance comparison and coordination effect analysis to obtain the servo motor plunger pump coordination effect evaluation report; Step 5.1, performance monitoring and comparison; Based on the motor operating parameters in the motor operating status report output in step 4.2 and the real-time data collected by various system sensors, the controller employs a performance index classification monitoring and comparative analysis method to comprehensively evaluate the system performance under both variable and quantitative modes. The controller establishes performance monitoring index systems for both variable and quantitative modes, and verifies the effectiveness of the technical solution of this invention through comparative analysis of the system operating status under the two modes.

[0060] For performance monitoring in variable mode, the controller focuses on energy-saving effects and load adaptability. In energy-saving evaluation, the controller monitors the actual power consumption of the servo motor, calculates the average power in variable mode, and calculates the theoretical maximum power consumption based on system pressure and flow requirements. The theoretical maximum power consumption corresponds to the power consumption of the plunger pump running at maximum displacement. The energy-saving rate is calculated as the theoretical maximum power consumption minus the actual power consumption, divided by the theoretical maximum power consumption. A higher energy-saving rate indicates better energy saving. The controller analyzes the energy-saving rate variation under different load pressures, verifying the energy-saving advantage of the constant power variable characteristics of the variable pump under low-pressure conditions. When the load pressure is low, the swashplate angle automatically increases to provide a larger flow rate, but the power consumption remains within a reasonable range due to the low pressure, achieving energy-saving operation. In load adaptability evaluation, the controller monitors the response characteristics of flow rate with load changes. When the load pressure changes, it records the adjustment process of the plunger pump's output flow rate, analyzes the response speed and stability of the flow rate adjustment, and evaluates whether the variable pump can automatically adjust the output flow rate according to load requirements, verifying the ability of the constant power variable characteristics to enable the system to adapt to different load conditions. The controller's statistical variable mode measures the fluctuations in flow rate, pressure, and motor speed to assess the stability of system operation.

[0061] For performance monitoring in the quantitative mode, the controller focuses on monitoring flow control accuracy and speed-flow linearity. Regarding flow control accuracy evaluation, the controller measures the actual output flow of the plunger pump using a flow sensor, compares it with the target flow command, and calculates the flow control error. The flow control error equals the actual flow minus the target flow. The maximum, average, and standard deviation of the flow control error are statistically analyzed to calculate the flow control accuracy index. A smaller standard deviation indicates higher flow control accuracy, verifying the technical effect of precise control achieved by the flow rate being entirely determined by the servo motor speed in the quantitative mode. The controller analyzes the flow control accuracy under different pressure conditions, verifying that the flow rate is unaffected by pressure after eliminating the constant power variable characteristic in the quantitative mode under high pressure. When the system pressure changes, the flow rate remains stable, following the target flow rate, proving that the quantitative mode overcomes the problem of flow instability in variable pumps under high pressure. Regarding speed-flow linearity evaluation, the controller collects output flow data corresponding to different motor speeds, plots a speed-flow scatter plot, and uses a linear regression method to fit the speed-flow relationship curve. The correlation coefficient and linearity deviation of the fitted line are calculated. When the correlation coefficient is close to 1 and the linearity deviation is small, it verifies that the speed and flow rate exhibit a good linear relationship in the quantitative mode, fully leveraging the advantages of servo motor speed control.

[0062] The controller measures mode switching performance, including switching response time and switching process stability. Regarding switching response time measurement, the controller records the time from the issuance of the switching command to the completion and stabilization of each mode switch, and statistically analyzes the average, shortest, and longest response times across multiple switches to assess the system's mode switching speed. A short switching response time indicates that the system can quickly adapt to changes in operating conditions. Regarding switching process stability assessment, the controller monitors pressure and flow fluctuations during mode switching, records the pressure and flow time series before and after the switching moment, analyzes the fluctuation amplitude and recovery time, calculates pressure and flow overshoot, and assesses the smoothness of the switching process. When the pressure and flow fluctuation amplitudes are small and can quickly recover to stability, the stability and reliability of the mode switching strategy of this invention are verified.

[0063] The controller establishes a performance comparison database, classifying and storing performance monitoring data under different operating conditions and modes, and creating a data index for easy querying and analysis. The database records information such as pressure range, flow demand, operating mode, motor speed, plunger pump flow, and system power consumption performance indicators for each operating condition, providing data support for subsequent performance optimization and fault diagnosis. The controller uses statistical analysis methods to mine historical data in the database, identifying performance characteristics and advantageous ranges under different modes, providing a basis for optimizing mode switching strategies. The controller summarizes the monitored variable mode performance indicators (including energy saving rate and load adaptability indicators), quantitative mode performance indicators (including flow control accuracy, speed, and flow linearity), switching performance evaluation results (including switching response time and switching process stability), and the established performance comparison database information to form a system performance monitoring report. This report serves as the data foundation for evaluating the cooperation effect between the servo motor and the plunger pump.

[0064] Step 5.2: Comprehensive evaluation of the combined effects; Based on the performance data in the system performance monitoring report output in step 5.1 and the design objectives of this invention, the controller employs a multi-dimensional effect evaluation and problem diagnosis method to comprehensively evaluate the overall effect of the servo motor and plunger pump working together. The controller assesses whether the technical solution of this invention has achieved the expected technical objectives, namely, fully leveraging the energy-saving advantages of the variable pump under low-pressure conditions and achieving precise flow control under high-pressure conditions.

[0065] In evaluating the performance under low-pressure conditions, the controller extracts operating data from the system performance monitoring report to determine whether the system is operating in variable mode and to verify the significant energy-saving effect under variable mode. The controller compares the power consumption of variable mode and fixed-displacement mode under the same low-pressure conditions, calculates the energy-saving percentage, and evaluates the energy-saving advantages brought by the constant power variable characteristics of the variable pump. When the power consumption in variable mode is significantly lower than that in fixed-displacement mode, it confirms that the energy-saving characteristics of the variable pump are fully utilized under low-pressure conditions. The controller analyzes the system's adaptability to load changes in variable mode. When load demand changes, it observes the adjustment process of the plunger pump flow rate and swashplate angle to evaluate whether the system can automatically optimize flow output and achieve load adaptability optimization.

[0066] In terms of high-voltage operating condition performance evaluation, the controller extracts operating data under high-voltage conditions from the system performance monitoring report to determine whether the system is operating in quantitative mode and to verify whether the flow control accuracy in quantitative mode meets the requirements. The controller compares the flow control accuracy of quantitative and variable modes under the same high-voltage conditions, evaluating the improvement in flow control accuracy after eliminating the constant power variable characteristic in quantitative mode. When the flow control error in quantitative mode is significantly smaller than that in variable mode, it confirms that precise flow control has been achieved under high-voltage conditions. The controller analyzes the correspondence between servo motor speed control and flow output in quantitative mode, verifying whether the flow is entirely determined by the motor speed and evaluating whether the advantages of precise servo motor control are fully utilized.

[0067] The controller analyzes the coordination between the servo motor and the plunger pump, monitoring the synchronization of motor speed changes and pump flow rate changes. The controller employs correlation analysis to calculate the cross-correlation function between the motor speed time series and the pump flow rate time series, analyzing their time delay and coupling strength. A large peak at zero time delay indicates high synchronization and good coordination between speed and flow rate changes. A delay or small peak indicates a lack of coordination. The controller also evaluates the smoothness of motor speed transitions during mode switching. When the system switches from variable mode to quantitative mode or vice versa, the controller records the motor speed change trajectory before and after the switch, analyzing whether the speed change is smooth and without abrupt changes, and calculating whether the speed change rate is within the set limits. A smooth transition of speed along the planned trajectory verifies good coordinated control of the servo motor and plunger pump mode switching. Abrupt changes or oscillations in speed indicate that the coordinated control strategy needs optimization.

[0068] The controller calculates the overall performance indicators of the system, quantitatively evaluating the performance improvement of this invention compared to traditional solutions. The controller calculates the overall energy efficiency improvement index by comparing the total energy consumption of the proposed solution and a pure fixed-displacement pump solution under the same working cycle, calculating the percentage improvement in energy efficiency, and verifying the energy-saving effect achieved by the proposed invention through low-pressure variable pump mode. The controller calculates the flow control accuracy improvement index by comparing the flow control error of the proposed solution and a pure variable pump solution under high-pressure conditions, calculating the percentage improvement in accuracy, and verifying the control accuracy improvement achieved by the proposed invention through high-pressure fixed-displacement mode. The controller calculates the system response speed improvement index by comparing the flow response time of the proposed solution and a traditional hydraulic control solution, evaluating the dynamic performance improvement brought about by the fast response characteristics of the servo motor.

[0069] The controller identifies problems and deficiencies in the coordination process and discovers potential performance bottlenecks by analyzing system operating data. When the controller detects a long mode switching delay, it records it as a slow mode switching response problem. Possible causes include excessive pressure signal filtering time, excessive switching decision delay, and slow swashplate angle adjustment speed. When the controller detects a large speed tracking error in quantitative mode, it records it as an insufficient speed control accuracy problem. Possible causes include improper proportional-integral-derivative parameter settings, large motor load disturbances, and sensor measurement errors. When the controller detects pressure fluctuations during mode switching, it records it as an insufficient switching process stability problem. Possible causes include excessively rapid swashplate angle change, large solenoid valve impact, and asynchronous speed regulation.

[0070] Based on the identified problems, the controller establishes an improvement suggestion list, proposing specific improvement measures and parameter adjustment suggestions for each problem. For the slow mode switching response, it is recommended to optimize the pressure signal filtering algorithm to shorten the filtering delay, optimize the switching decision logic to reduce unnecessary delays, and increase the solenoid valve pulse width modulation frequency to accelerate the swashplate angle adjustment speed. For the insufficient speed control accuracy, it is recommended to optimize the proportional-integral-derivative controller parameters using an adaptive parameter tuning method, add feedforward control to compensate for the impact of load disturbances, improve the speed sensor accuracy, or use a Kalman filter method to improve speed estimation accuracy. For the insufficient stability during the switching process, it is recommended to optimize the swashplate angle change trajectory using a flexible control strategy, improve the solenoid valve control method to use buffer control to reduce impact, and optimize the motor speed coordination control to achieve synchronous adjustment of speed and swashplate angle.

[0071] The controller will evaluate the following conclusions regarding the coordination effect: low-pressure energy saving effect assessment and high-pressure precise control effect assessment; the coordination results obtained from the analysis include speed and flow synchronization and mode switching smoothness; the comprehensive performance indicators obtained from the calculation include percentage improvement in energy efficiency, percentage improvement in accuracy, and multiple improvement in response speed; a list of identified problems; and the proposed improvement suggestions. These will be summarized into a servo motor plunger pump coordination effect evaluation report, which serves as an important basis for system performance verification and continuous improvement.

[0072] A system for controlling a plunger pump with a servo motor drive, such as Figure 3 As shown, a method for performing the above-described servo motor-driven control of a piston pump includes: The initialization parameter acquisition module is used to acquire the initialization data and equipment configuration parameters of the servo motor control system. Through the controller, it performs hardware status detection and pressure condition parameter configuration, establishes a quantitative relationship between the servo motor speed and the output flow of the plunger pump, and obtains the coordinated control parameters of the servo motor and the plunger pump. The pressure condition identification module is used to identify and switch modes based on the coordinated control parameters of the servo motor plunger pump, verify the working characteristics of the plunger pump, and obtain a plunger pump working characteristic verification report. The solenoid valve control module, based on the plunger pump working characteristic verification report, performs solenoid valve pulse width modulation control to obtain a variable quantitative conversion verification report; The speed control module is used to determine the current working mode based on the variable quantitative conversion verification report, perform sub-mode speed strategy formulation and proportional-integral-derivative parameter adaptive control, and obtain a motor operating status report. The evaluation module, based on the motor operating status report, performs multi-mode performance comparison and coordination effect analysis to obtain a servo motor plunger pump coordination effect evaluation report.

[0073] In one embodiment of the present invention, a specific example is provided: A certain model of injection molding machine is equipped with the servo motor driven plunger pump control system of the present invention. The servo motor has a rated power of 55 kW, a speed range of 800 to 1800 rpm, and a rated torque of 105 N·m. The hydraulic high-pressure high-speed plunger variable pump has a maximum displacement of 45 cubic centimeters and a maximum working pressure of 30 MPa per revolution. The system is equipped with a two-position four-way solenoid directional valve, a pressure reducing valve, a check valve, and corresponding sensors. The controller performs system control according to the method of the present invention.

[0074] During the initialization phase, the controller completes hardware detection to obtain equipment parameters, sets the upper limit threshold for low-pressure operation to 8 MPa, the lower limit threshold for high-pressure operation to 10 MPa, forms a 2 MPa pressure hysteresis loop, configures the maximum swashplate angle for variable mode to 18 degrees and the constant power variable coefficient to 0.85, configures the fixed swashplate angle for quantitative mode to 3 degrees, and sets the output pressure of the pressure reducing valve to 6 MPa.

[0075] During the mold closing stage of the injection molding machine, the system pressure is 5 MPa, which is considered a low-pressure condition. The controller is in variable mode, the solenoid directional valve is de-energized, the swashplate control port is connected to the return oil, the swashplate angle is 18 degrees, and the piston pump operates at maximum displacement. The system operating data during the mold closing stage is shown in Table 1. Table 1: System operation data during the mold closing stage;

[0076] As can be seen from Table 1, during the low-pressure mold closing stage, the system operates in variable mode, the swashplate angle is automatically adjusted according to the load, and the motor power is kept at a low level to achieve energy-saving operation.

[0077] When the injection molding machine enters the injection holding stage, the system pressure rises to 12 MPa, exceeding the high-pressure threshold. The controller determines that it needs to switch to the quantitative injection mode. After a 0.1-second delay for confirmation, the controller issues a mode switching command. The solenoid directional valve is energized, and the high-pressure oil is reduced to 6 MPa by the pressure reducing valve before entering the swashplate control port. This pushes the swashplate angle from 18 degrees to 3 degrees and locks it, completing the switch to the quantitative injection mode. The system operating data during the injection holding stage is shown in Table 2. Table 2: System operation data during the injection pressure holding phase;

[0078] As can be seen from Table 2, during the high-pressure injection and holding stage, the system operates in quantitative mode, with the swashplate angle locked at 3 degrees. The output flow rate is entirely determined by the motor speed. Even if the pressure fluctuates between 12 and 13 MPa, the flow error remains within 0.3 liters per minute, achieving precise flow control.

[0079] Through comparative analysis, after adopting the technical solution of this invention, the injection molding machine has lower average power consumption in the complete working cycle compared with the traditional pure quantitative pump solution. Compared with the traditional pure variable pump solution, the flow control accuracy is improved in the high pressure stage, the mode switching process is smooth, the switching response time is 0.4 seconds, and the pressure fluctuation amplitude is less than 0.5 MPa, which verifies the effectiveness and practicality of the technical solution of this invention.

[0080] Through the above specific implementation methods, the present invention successfully realizes the intelligent switching control of variable displacement and quantitative flow control of servo motor driven piston pump. It fully leverages the energy-saving advantages of variable displacement pump under low-pressure conditions and achieves precise flow control under high-pressure conditions. It solves the fundamental contradiction between the use of servo motor and variable displacement piston pump and provides an energy-saving and precise control solution for high-pressure hydraulic systems.

[0081] The embodiments of the present invention have been described above. However, the embodiments are not limited to the specific implementation methods described above. The specific implementation methods described above are merely illustrative and not restrictive. Those skilled in the art can make more equivalent embodiments under the guidance of the present embodiments, and all of them are within the protection scope of the present embodiments.

Claims

1. A method for controlling a plunger pump by driving a servo motor, characterized in that, Includes the following steps: The initialization data and equipment configuration parameters of the servo motor control system are obtained. The hardware status is detected and the pressure condition parameters are configured through the controller. A quantitative relationship between the servo motor speed and the output flow of the plunger pump is established, and the coordinated control parameters of the servo motor and the plunger pump are obtained. Based on the coordinated control parameters of the servo motor plunger pump, pressure condition identification and mode switching are performed to verify the working characteristics of the plunger pump and obtain a plunger pump working characteristic verification report. Based on the verification report of the working characteristics of the plunger pump, solenoid valve pulse width modulation control was performed to obtain a verification report of variable quantitative conversion. Based on the variable quantitative conversion verification report, the current working mode is determined, and the sub-mode speed strategy is formulated and proportional-integral-derivative parameter adaptive control is performed to obtain the motor operating status report. Based on the motor operating status report, a multi-mode performance comparison and coordination effect analysis were conducted to obtain a servo motor plunger pump coordination effect evaluation report.

2. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The hardware status detection includes: The controller uses the device communication protocol to perform initialization tests on each hardware module in sequence. For servo motors, the controller establishes a communication connection with the servo motor driver through the controller area network bus, and parses and extracts the servo motor speed range parameters and rated torque parameters; For hydraulic high-pressure high-speed piston variable pumps, the controller obtains the maximum displacement parameters and the maximum working pressure parameters, and detects the pump's working status through pressure sensors and flow sensors; For two-position four-way solenoid directional valves, pressure reducing valves, and check valves, the controller detects the coil resistance of the solenoid directional valve, the pressure difference across the pressure reducing valve, and the sealing performance of the check valve. For pressure sensors, flow sensors, and position sensors, the controller collects output signals to determine the signal amplitude and stability; The controller summarizes and generates a hardware status report for the control system.

3. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The pressure condition parameter configuration includes: The controller uses a multi-level threshold configuration method to set the judgment criteria for pressure condition identification, divides the working pressure into low-pressure condition range and high-pressure condition range, and sets the upper limit threshold for low-pressure condition and the lower limit threshold for high-pressure condition. For variable mode, the controller sets the maximum swashplate angle parameter of the piston pump and the constant power variable coefficient; For the quantitative mode, the controller sets the fixed swashplate angle parameter to the minimum swashplate angle of the plunger pump and sets the output pressure setting value of the pressure reducing valve; The controller summarizes the configuration parameters to form a pressure condition identification parameter table.

4. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The establishment of a quantitative relationship between the servo motor speed and the plunger pump output flow rate includes: The controller uses a flow calculation model to establish a quantitative relationship between the servo motor speed and the output flow of the plunger pump; For the variable mode, the flow calculation formula is established as follows: the output flow is equal to the servo motor speed multiplied by the single-revolution displacement of the plunger pump, multiplied by the sine function value of the current swashplate angle, and multiplied by the constant power variable coefficient. For the quantitative mode, a simplified flow calculation formula is established as follows: the output flow rate is equal to the servo motor speed multiplied by the single-revolution displacement of the plunger pump and then multiplied by the sine function value of the fixed swashplate angle. The controller calibrates the optimal motor speed range under different pressure conditions and sets the motor speed transition strategy when switching modes.

5. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The pressure condition identification includes: The controller uses a convolutional neural network multi-frequency filtering and trend analysis method to process the current hydraulic system working pressure, and uses a convolutional neural network for intelligent filtering. The controller uses a trend analysis method to calculate the pressure change rate and determines the operating condition based on the filtered current pressure value and pressure threshold. When the current pressure value is less than or equal to the upper limit threshold of the low-pressure condition, it is determined to be a low-pressure condition; when the current pressure value is greater than the lower limit threshold of the high-pressure condition, it is determined to be a high-pressure condition.

6. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The mode switching includes: The controller uses a multi-factor evaluation and delay decision-making method to make a comprehensive decision on mode switching. During the multi-factor evaluation process, the controller evaluates the stability of hydraulic system pressure, the changing characteristics of flow demand, and the speed status of servo motor. The controller uses a logic synthesis method to generate a switching permission signal. The switching permission signal is set to allow switching only when three conditions are met simultaneously: the hydraulic system pressure is stable, the flow demand is stable, and the motor is in normal condition. The controller uses a delay decision method to calculate the switching delay time, sets a switching delay timer, and continuously monitors the pressure conditions and switching conditions during the delay period.

7. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The solenoid valve pulse width modulation control includes: The controller reads the current actual angle value of the plunger pump swashplate through the position sensor and calculates the angle control deviation as the target angle value minus the current actual angle value. The controller uses pulse width modulation technology to control the energization state of the solenoid valve and generate a pulse width modulation signal; The controller uses a proportional control algorithm to calculate the duty cycle, which is equal to the angle deviation multiplied by the proportional gain coefficient. The controller sends the pulse width modulation signal to the solenoid coil of the two-position four-way solenoid valve through the digital output interface.

8. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The mode-specific speed strategy formulation and proportional-integral-derivative parameter adaptive control include: The controller employs a deep reinforcement learning-based parameter adaptive proportional-integral-derivative (PID) control method, using a deep reinforcement learning network for online optimization of the PID parameters. The controller implements closed-loop speed control, calculates the speed control error, and inputs the speed error into the proportional-integral-derivative controller for calculation. The controller implements torque limiting protection and monitors the actual output torque of the servo motor.

9. The method for controlling a plunger pump by a servo motor according to claim 1, characterized in that, The multi-mode performance comparison and coordination effect analysis includes: For variable mode, the controller focuses on monitoring energy-saving effect and load adaptability, and calculates the energy saving rate as the theoretical maximum power consumption minus the actual power consumption and then divided by the theoretical maximum power consumption. For the quantitative mode, the controller focuses on monitoring the flow control accuracy and the linearity of speed and flow, and uses the linear regression method to analyze the relationship between the actual flow and the motor speed; The controller measures mode switching performance, including switching response time and switching process stability, and monitors pressure and flow fluctuations during mode switching.

10. A system for controlling a plunger pump with a servo motor drive, characterized in that, A method for performing a servo motor driven control plunger pump according to any one of claims 1-9 includes: The initialization parameter acquisition module is used to acquire the initialization data and equipment configuration parameters of the servo motor control system. Through the controller, it performs hardware status detection and pressure condition parameter configuration, establishes a quantitative relationship between the servo motor speed and the output flow of the plunger pump, and obtains the coordinated control parameters of the servo motor and the plunger pump. The pressure condition identification module is used to identify and switch modes based on the coordinated control parameters of the servo motor plunger pump, verify the working characteristics of the plunger pump, and obtain a plunger pump working characteristic verification report. The solenoid valve control module, based on the plunger pump working characteristic verification report, performs solenoid valve pulse width modulation control to obtain a variable quantitative conversion verification report; The speed control module is used to determine the current working mode based on the variable quantitative conversion verification report, perform sub-mode speed strategy formulation and proportional-integral-derivative parameter adaptive control, and obtain a motor operating status report. The evaluation module, based on the motor operating status report, performs multi-mode performance comparison and coordination effect analysis to obtain a servo motor plunger pump coordination effect evaluation report.

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