Intelligent variable pump control method of engineering vehicle hydraulic system

Abstract

The invention relates to the technical field of high-pressure large-flow hydraulic system control, and discloses an intelligent variable pump control method for an engineering vehicle hydraulic system, which comprises the following steps of: in a single operation cycle, respectively measuring two response times of loading pressure boosting and unloading pressure reduction by utilizing a single pressure switch signal, and calculating the pressure of the hydraulic system on the basis of the inherent asymmetry of the two response times; according to the high-frequency-response electro-hydraulic proportional valve control method, the two time-varying factors, namely the temperature and the load which are originally confused with each other, in a hydraulic system are successfully decoupled, opening adjustment of a key valve can be matched with the real operation environment and task requirements, and the high-frequency-response electro-hydraulic proportional valve control instruction is generated. Response delay or impact caused by state misjudgment is avoided, and adaptability and stability of the control system are improved.

Description

Technical Field

[0001] This invention relates to an intelligent variable pump control method for a hydraulic system of engineering vehicles, belonging to the field of high-pressure, high-flow hydraulic system control technology. Background Technology

[0002] Currently, hydraulic control systems for engineering vehicles are typically built on the premise that the working characteristics of the hydraulic system are relatively stable and that the control parameters rarely change once set. However, the actual operating environment of engineering vehicles is full of dynamic changes. Among these, the temperature fluctuation of hydraulic oil is the most widespread and unavoidable core factor. Drastic changes in oil temperature directly alter its viscosity, thereby disturbing the dynamic response characteristics of the entire system. This results in a sluggish and weak system response during cold starts at low temperatures, while continuous high-load operation leading to excessively high oil temperatures can cause the system to respond too quickly or even generate shocks. This performance drift caused by temperature changes is an inherent challenge faced by all hydraulic equipment.

[0003] To address this issue, an obvious approach in the industry is to add a temperature sensor to the system and adjust the control parameters based on the real-time measured oil temperature. However, this seemingly straightforward solution introduces new problems in the harsh application scenarios of engineering vehicles. On the one hand, the introduction of high-precision sensors significantly increases the hardware cost, wiring complexity, and software algorithm complexity of the system. On the other hand, each new sensor and its connecting lines become a potential high-failure point in the high-vibration and high-pollution environment. This makes the pursuit of greater adaptability sacrifice the operational reliability that is most valued in the field of engineering machinery.

[0004] Specifically, existing technologies suffer from the following shortcomings: 1. Control models are generally based on static or ideal operating conditions, failing to inherently adapt to the time-varying effects of hydraulic oil's physical properties, resulting in poor system performance consistency across the entire temperature range; 2. Attempts to acquire system state information by adding external sensors contradict the fundamental requirements of engineering machinery for low cost and high reliability, limiting the practical application and widespread adoption of advanced control strategies; 3. System response speed is affected not only by temperature but also by the magnitude of external load. Existing simplified models struggle to effectively distinguish between these two effects without adding more sensors, leading to insufficient accuracy in control compensation. Therefore, the technical problem this invention aims to solve is how to enable the pump's control system to acquire an inherent environmental perception and state discrimination capability without adding extra sensors or sacrificing the system's inherent reliability, thereby automatically compensating for the combined effects of time-varying factors such as oil temperature and external load. Summary of the Invention

[0005] This invention provides an intelligent variable pump control method for hydraulic systems of engineering vehicles. Its main purpose is to solve the problem of insufficient control adaptability and stability caused by the inability of existing control methods to effectively cope with time-varying factors such as oil temperature and external load without sacrificing system reliability.

[0006] To achieve the above objectives, the present invention provides an intelligent variable pump control method for a hydraulic system of an engineering vehicle, comprising the following steps:

[0007] Step a: Install a pressure switch on the outlet side of the variable pump. The pressure switch is used to generate a binary pressure signal that characterizes whether the outlet pressure has reached a preset threshold.

[0008] Step b: In a single hydraulic operation cycle of the engineering vehicle, using a timer within the edge control unit, measure the pressure boost response time Δt experienced by the binarized pressure signal during the transition from the first state to the second state during the loading process. rise And the buck response time Δt experienced during the transition from the second state back to the first state during the unloading process. drop ;

[0009] Step c, the edge control unit uses the pressure drop response time Δt, which is the main factor characterizing the hydraulic oil temperature effect, as the basis for the pressure drop response time. drop The temperature compensation coefficient K is determined according to the preset first mapping relationship. temp Furthermore, the edge control unit is based on the boost response time Δt. rise With the voltage drop response time Δt drop The relationship between the two is used to determine the load compensation coefficient K based on the preset second mapping relationship. load ;

[0010] Step d: The edge control unit generates basic valve port commands based on the vehicle's operational requirements, and combines the basic valve port commands with the temperature compensation coefficient K. temp and load compensation coefficient K load Multiplication is performed to generate the final valve control command, and the high-frequency electro-hydraulic proportional valve in the main circuit of the system is adjusted according to the final valve control command, so as to precisely control the high-pressure, high-flow hydraulic oil from the variable pump.

[0011] Preferably, the first mapping relationship in step c is established based on the physical correlation between hydraulic oil viscosity and system pressure response time, and is used to map different pressure reduction response times Δt. drop The different temperature compensation coefficients K correspond to different interval ranges. temp value.

[0012] Preferably, in step c, the load compensation coefficient K is determined. load Specifically, the calculation is based on the following formula: Where f is a preset function used to characterize the relationship between the ratio of boost response time to buck response time and the magnitude of the external load, and the output of the function is the load compensation coefficient K. load .

[0013] Preferably, the method further includes a fault diagnosis step, which includes: the edge control unit also pre-stores a maximum allowable response time Δt. max ; and before executing step c, a judgment is made if the boost response time Δt measured in step b is... rise Exceeding Δt max If so, steps c and d are terminated, and a predefined fail-safe procedure is activated.

[0014] Preferably, the method further includes a filter health status monitoring step, which includes: when the hydraulic system is identified to enter a steady-state operating condition where the pressure value remains stable, the edge control unit counts the number of state transitions of the binarized pressure signal within a preset time window to obtain the jitter frequency; and if the jitter frequency exceeds the preset health status reference frequency, a filter blockage maintenance early warning signal is generated.

[0015] Preferably, the method further includes a pump health status self-diagnosis step, which includes: when the vehicle is detected to have entered a preset standby condition, controlling the outlet of the variable pump to form a closed dead load chamber; instructing the variable pump to briefly load the dead load chamber to a preset pressure and then stop; and measuring the pressure decay time Δt experienced by the pressure in the dead load chamber naturally decaying from the preset pressure to a preset threshold of the pressure switch. decay This is used to characterize the degree of internal leakage in variable pumps.

[0016] Preferably, the method further includes an efficiency compensation step, which includes: the edge control unit based on the pressure decay time Δt decay When determining the pump health factor H and generating the final displacement control command in step d, the calculation result is further divided by the pump health factor H to compensate for the decrease in volumetric efficiency of the variable pump due to wear.

[0017] Preferably, both the first mapping relationship and the second mapping relationship are stored in one or more human-dimensional lookup tables of the edge control unit.

[0018] Preferably, the edge control unit also pre-stores a normal temperature reference time, if the voltage drop response time Δt drop If the time is longer than the normal temperature reference time, then the temperature compensation coefficient K temp If the voltage drop response time Δt is greater than 1, drop If the time is shorter than the normal temperature reference time, then the temperature compensation coefficient K temp Less than 1.

[0019] Preferably, the pressure switch is an industrial-grade mechanical pressure switch or an electronic pressure switch, the edge control unit is a general-purpose microcontroller, and the timer is a built-in hardware timer module of the general-purpose microcontroller.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] 1. This invention establishes a control method that can simultaneously distinguish the hydraulic oil temperature effect and the external load effect using only a single pressure switch signal. By measuring the pressure increase response time during the loading process and the pressure decrease response time during the unloading process in a single working cycle, the temperature effect is evaluated using the pressure decrease response time, which is an intrinsic indicator that more purely reflects the viscosity characteristics of the oil. Furthermore, the magnitude of the external load is inferred by using the asymmetric relationship between the pressure increase and pressure decrease response times. This successfully decouples the two variables of temperature and load that are confused in traditional control, enabling the displacement adjustment of the variable pump to adapt to both changes in ambient temperature and actual working load requirements, avoiding response lag or action shock caused by misjudgment.

[0022] 2. This invention also provides an operating mechanism that integrates adaptive control and health management of the pump. When the system is in dynamic operation, it performs adaptive adjustment to temperature and load. When the system enters a condition where the pressure value remains stable, it switches roles to monitor minute fluctuations in the pressure signal and uses them as an early basis for judging the filter clogging status. Furthermore, when it detects that the vehicle has entered a standby state, it can actively control the pump outlet to form a closed cavity. Through the natural pressure decay process after a brief loading, it can quantitatively assess the degree of internal leakage of the pump itself. By seamlessly integrating operation control, status monitoring, and health self-diagnosis into the same set of relatively simple hardware, the hydraulic system gains a protection capability throughout its entire life cycle.

[0023] 3. By deeply exploring and applying the fundamental physical quantity of pressure response time in multiple dimensions, this invention can not only perceive the working condition by comparing the pressure rise and fall times, but also distinguish between normal slow response and systemic faults by setting an upper limit threshold for the response time, thereby providing fault diagnosis function for the entire adaptive control logic. At the same time, by quantitatively assessing the wear of the pump itself and feeding it back to the displacement control command for compensation, it ensures that the engineering vehicle can maintain stable operating efficiency even after long-term use. Attached Figure Description

[0024] Figure 1 This is a logic flowchart of an intelligent variable pump control method for a hydraulic system of an engineering vehicle according to the present invention.

[0025] Figure 2 This is a graph showing the relationship between the response time and oil temperature of the present invention.

[0026] Figure 3 This is a schematic diagram of the system operating state machine for the control method of the present invention.

[0027] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of this application can be combined with each other.

[0029] This invention discloses an intelligent variable displacement pump control method for a hydraulic system of an engineering vehicle. The method requires only an industrial-grade pressure switch and an edge control unit on the outlet side of the variable displacement pump. The core of this method lies in performing multi-dimensional time-series analysis on the binary pressure signal generated by this single pressure switch. In a single hydraulic operation cycle, the influence of two time-varying factors—hydraulic oil temperature and external load—is simultaneously analyzed. Combined with online diagnosis of the system's health status, a variable displacement pump control command that accurately adapts to the current working conditions and equipment status is ultimately generated. The operation process mainly includes: multi-dimensional state perception based on the asymmetry of pressure rise and fall timing; generation of composite compensation coefficients based on the perception results; and dynamic construction and execution of the final displacement control command incorporating health status factors. During parameter calibration, the first and second mapping relationships are quantified and stored as specific function models, where the load compensation coefficient K is used to determine... load The second mapping relationship is achieved by mapping multiple data points measured during the offline calibration phase to... The least squares method is used to fit a pre-defined continuous function model, which takes the form of a sigmoid saturated function. Here, x represents the ratio. A, B, C, and D are coefficients determined by fitting calibration data. The sigmoid saturation function, as a mathematical tool that can characterize the smooth transition of the system response from the linear growth region to the saturation plateau region, has its output stored in the memory of the edge control unit. Similarly, it is used to determine the temperature compensation coefficient K. temp The first mapping relationship is also achieved by mapping data pairs (Δt) drop ,K temp Piecewise linear interpolation or polynomial fitting is performed to generate a value for any input Δt. drop All of the following can output a uniquely determined K. tempThe value is a continuous function or a high-density lookup table, which transforms the original discrete calibration points into a control law covering the entire operating range; the thresholds in fault diagnosis and health status monitoring are determined by statistical analysis of the original time-series data collected during the calibration phase, among which the maximum allowable response time Δt max The value is obtained by collecting multiple boost response times Δt measured under extreme but normal operating conditions, such as the highest oil temperature and the maximum load. rise For the sample, calculate its mean μ and standard deviation σ, and then use Δt max The value is set to μ+4σ, where μ and σ are statistical measures describing the central tendency and dispersion of the sample data. The value of μ+4σ ensures coverage of extremely low-probability normal events with an occurrence probability of less than 63 per million. The jitter frequency of the filter health status monitoring is obtained by performing spectral analysis on the binarized pressure signal sequence under steady-state conditions using Fast Fourier Transform (FFT), and the health status reference frequency f is set. base The signal energy integral value is set within the 1 Hz to 10 Hz frequency band. Here, the Fast Fourier Transform (FFT) is a standard algorithm for converting a time-domain signal into a frequency-domain signal to analyze its frequency components. The alarm threshold is then set to this f value. base 2.5 times; while the triggering of pump health status self-diagnosis requires, in addition to the conditions of engine idling, zero handle signal and zero vehicle speed, these conditions must be met continuously for a time window of more than 30 seconds, and the parking brake signal of the vehicle bus must be in an effective engagement state. At the same time, the system pressure detected instantaneously before starting the diagnosis is lower than 5 bar, in order to confirm that the hydraulic system is in a true standby state of no load and no pressure holding.

[0030] In a typical application scenario, such as when an engineering vehicle is performing a work cycle, the hydraulic system's pressure response characteristics continuously drift due to the dual dynamic changes in oil temperature and work load, thus affecting the accuracy and smoothness of the operation. To address this challenge, this method is configured to perform a complete state self-sensing and control self-calibration in each independent hydraulic work cycle of the vehicle. During loading, the edge control unit uses its built-in timer module to measure the pressure boost response time Δt experienced when the pressure switch signal switches from a first state representing pressure below a threshold to a second state representing pressure reaching the threshold. rise Correspondingly, during the unloading process, the unit again measures the pressure drop response time Δt experienced by the pressure switch signal switching from the second state back to the first state. drop Given that the pressure reduction process is mainly controlled by the viscous resistance during oil reflux, its response time Δt drop It is basically insensitive to changes in external load, therefore, Δt drop It was used as an endogenous index that could purely characterize the current hydraulic oil viscosity, i.e., the temperature effect, while the boost response time Δt riseThis is the result of the combined effects of temperature and external load. By utilizing the asymmetry in the physical causes of these two response times, this method provides an intrinsic information basis for distinguishing between the two time-varying factors.

[0031] To convert raw time measurements into quantifiable parameters that can be used for control, the edge control unit internally stores two mapping relationships in the form of one-dimensional lookup tables. The first mapping relationship is used to determine the temperature compensation coefficient K. temp The calibration process follows a deterministic offline calibration procedure: the hydraulic system is placed under no-load conditions, and the hydraulic oil is regulated within a preset operating temperature range using an external temperature control device. During this process, the stable pressure drop response time Δt corresponding to a series of key temperature points is recorded. drop And set a compensation coefficient value corresponding to the target performance response, for example, Δt corresponding to room temperature. drop Based on this, K temp Set to 1.0; at low temperature, the measured Δt drop If extended, then set K. temp Greater than 1; at high temperatures, the measured Δt drop If shortened, then set K. temp Less than 1, thus generating a value that will reduce Δt drop Interval range and K temp The lookup table corresponding to the value, and the second mapping relationship are used to determine the load compensation coefficient K. load The calibration is performed with the hydraulic oil at the aforementioned ambient temperature reference condition. By applying a series of known standard loads to the system, the boost response time Δt at each load level is measured. rise And according to the formula Calculate the ratio, and then compare this ratio with the K required to achieve a specific dynamic response. load The values ​​are correlated to construct a function lookup table representing the relationship between the ratio and the load size. Thus, during real-time vehicle operation, the edge control unit measures Δt... rise With Δt drop Then, by consulting these two preset lookup tables, the K value matching the current oil temperature and load can be determined. temp With K load .

[0032] When generating the final control command, the edge control unit first generates a basic displacement command based on the vehicle's operational requirements, and then combines this basic displacement command with the determined temperature compensation coefficient K. temp and load compensation coefficient K loadMultiplication is performed to generate the final displacement control command, and the displacement of the variable pump is adjusted according to this command. To improve the robustness of the system, this method also integrates a health status self-diagnosis and compensation mechanism. To cope with faults such as hydraulic pipeline leakage that may cause pressure to fail to build up, a maximum allowable response time Δt is pre-stored in the system. max This threshold is determined based on the system's pressure settling time under acceptable extreme operating conditions, with added safety redundancy. Before performing routine compensation calculations, the system first measures the Δt. rise Make a judgment; if its value exceeds Δt max The system then suspends the regular instruction generation process and activates a predefined fail-safe procedure, such as forcibly setting the pump displacement to zero and issuing a fault alarm signal, thereby providing a fault identification and safety assurance mechanism for the adaptive control logic. Furthermore, when the hydraulic system is detected to have entered a steady-state condition with stable pressure, the edge control unit counts the number of state transitions of the binarized pressure signal within a preset time window to obtain a jitter frequency. If this jitter frequency continuously exceeds the reference frequency recorded when the system is healthy, a filter blockage maintenance warning signal is generated to prompt the operator to perform preventative checks. Further, to address the decrease in volumetric efficiency caused by long-term wear of the pump body, the method also includes a pump health self-diagnosis step. When the system detects that the vehicle has entered a preset standby condition, a test process is automatically triggered: first, the relevant valves are controlled to form a closed dead-load chamber at the pump outlet; then, the pump is instructed to briefly load the chamber until the pressure rises to a preset value and stops. Subsequently, the edge control unit measures the pressure decay time Δt experienced by the pressure in the closed chamber naturally decaying to the pressure switch threshold due to internal leakage of the pump. decay , the Δt decay The value is inversely proportional to the degree of internal leakage of the pump, and the system is based on this Δt. decay A pump health factor H is determined, and when generating the final displacement control command, the original calculation result is further divided by the pump health factor H to compensate for the decrease in volumetric efficiency caused by pump wear, thereby maintaining the stability of vehicle operating performance.

[0033] Example 1: This example is a specific operational instance of the general technical solution described in a particular industrial scenario, aiming to illustrate the synergistic relationship between the various technical features in the solution and their comprehensive technical effects in dealing with complex working conditions. In a high-altitude mining area, a heavy engineering vehicle starts in the early morning of winter, when the ambient temperature is -25°C. Due to the low temperature, the viscosity of the hydraulic oil increases dramatically, causing the entire hydraulic system to respond slowly. When the operating handle issues a full-load lifting command, the system needs to avoid the gravitational load of the material and the high viscous resistance of the oil itself. Under this condition, the performance of any control system based on static parameters deviates from the preset working range. When the vehicle performs its first loading operation cycle, its intelligent variable pump control system begins to intervene. During the boom lifting process, the edge control unit measures an extended pressure response time Δt. rise During the subsequent unloading phase, the unit also measured a prolonged pressure drop response time Δt due to oil viscosity. drop The system did not extend Δt rise This is attributed to a generalized slowdown in system response, rather than utilizing Δt. drop This time-series characteristic, which is insensitive to load and strongly correlated only with oil viscosity, was used as the basis for judging the current oil temperature state. By consulting the pre-stored first mapping relationship, a temperature compensation coefficient K greater than 1 was determined. temp Furthermore, the system will use Δt rise With Δt drop The comparison revealed that, after the temperature effect was separated, the ratio indicated that the operation was under heavy load. Based on this, the system determined the corresponding load compensation coefficient K using the second mapping relationship. load Here, for Δt drop The measurement provides a prerequisite for accurately assessing the temperature effect, while the quantification of the temperature effect allows for the analysis of the mixed signal Δt. rise Decoupling load information becomes possible, and the two steps work together to resolve the technical contradiction of temperature and load effects being confused in single-parameter control.

[0034] As sunlight intensified and continuous operation continued, by midday, the hydraulic oil temperature had risen to 110°C, and the oil viscosity had decreased significantly. At this point, when the vehicle performed the same loading operation again, the system measured Δt... rise With Δt drop All have been significantly shortened, and the edge control unit is based on the shortened Δt. drop A temperature compensation coefficient K less than 1 was determined. temp At the same time, based on Δt at this moment rise With Δt drop The ratio determines K that matches the current load. loadThe final displacement control command is generated by multiplying the basic command by two dynamic compensation coefficients. This command enhances the pump's displacement output under low-temperature heavy loads and suppresses it under high temperatures, thus maintaining consistent operational response across the entire temperature range and dynamic load range. Furthermore, if the hydraulic pump develops internal leakage due to wear during long-term use of the vehicle, this variable representing the equipment's health status will also be included in the control closed loop. In the vehicle's standby condition, the system actively performs pump health status self-diagnosis by measuring the pressure decay time Δt. decay To quantify the degree of internal leakage of the pump and generate the pump health factor H, the aforementioned control logic for compensating for changes in the external environment and tasks, together with the internal health status diagnosis logic here, constitute a multi-level adaptive system; K temp With K load The adjustment focuses on the performance of the current work cycle, while the introduction of the pump health factor H compensates for the efficiency decline caused by physical wear and tear on a longer time scale. Its architecture integrates instantaneous condition adaptation and long-term efficiency compensation, realizing multi-dimensional and multi-time scale adjustment of the system state. This control method uses the response time sequence of the hydraulic system itself as an information source to construct an endogenous perception and self-calibration loop that does not rely on external sensors. This allows the system to quantitatively track and compensate for the evolution of the health status of its core components while responding to changes in the external environment and tasks.

[0035] Example 2: To objectively verify the effectiveness of the control method of the present invention in dealing with dual changes in hydraulic oil temperature and external load, a hydraulic system performance test platform was built. The core of the platform is a variable pump controlled by the edge control unit under test. A pressure switch as the sole pressure feedback element is installed on its outlet side. The pump output is connected to an electro-hydraulic proportional loading valve group that can simulate different load levels. At the same time, the entire hydraulic circuit is immersed in a thermodynamic control box with active heating and cooling functions to set and maintain the hydraulic oil temperature. For data comparison, the platform is also equipped with high-precision reference sensors that do not participate in the control closed loop, including pressure transmitters and temperature sensors, to record the actual response process of the system. The experiment aims to quantitatively compare the differences in system response under two control modes: Mode A, enabling the complete adaptive control method of the present invention based on the asymmetric decoupling of the boost and pull-up timing; Mode B, as a control group, disabling adaptive compensation, i.e., setting the temperature compensation coefficient K. temp With load compensation coefficient K loadThe test conditions were kept constant at 1.0, executing only the basic displacement command. The selected test conditions aimed to cover the typical working range that engineering vehicles might encounter. The hydraulic oil temperature was set to three levels: low temperature (-20℃), normal temperature (50℃), and high temperature (110℃). The external load was also set to three levels: light load (20% of maximum load), medium load (60% of maximum load), and heavy load (100% of maximum load). The test procedure was as follows: For the above nine working condition combinations, a standard load-unload cycle was run in both Mode A and Mode B. In each cycle, the edge control unit recorded its measured boost response time Δt. rise , Voltage drop response time Δt drop And K calculated accordingly temp With K load Meanwhile, the reference pressure transmitter records the system pressure peak during the loading phase to calculate the pressure overshoot. This indicator is used to evaluate the impact and stability of the system response. Table 1 shows the test data records for some representative operating points.

[0036] Table 1: Comparison of response data for the two control modes under different operating conditions.

[0037]

[0038] Table 1 shows the experimental data for different control modes. Under low-temperature heavy-load conditions, control group B, lacking compensation, exhibits a slow system response and low pressure overshoot; while mode A, based on the measured length Δt... drop With length Δt rise K was generated that is greater than 1. temp With K load By actively increasing the pump's displacement output to overcome oil viscosity, the pressure overshoot was raised to a level similar to that under normal operating conditions. Under high-temperature conditions, control group B experienced a pressure overshoot of up to 35.6% due to excessively fast system response caused by thinner oil; while mode A, based on the measured short Δt... drop A K less than 1 was generated. temp This suppressed the pump's displacement output, controlling the pressure overshoot to 13.2%, restoring it to the baseline level. Furthermore, comparing operating conditions 6 and 8 shows that, under the same high temperature and different loads, mode A can also achieve better performance through Δt... rise With Δt drop Adjusting K by changing the ratio load Optimize the response under different loads.

[0039] Example 3: This example combines Figures 1 to 3 The method for controlling intelligent variable pumps in the hydraulic system of engineering vehicles is explained, such as... Figure 1As shown, the process begins with the acquisition of a single pressure switch signal, and then the boost response time Δt during the loading process is measured by a multi-dimensional timing signal acquisition module. rise The pressure drop response time Δt during the unloading process drop After obtaining the measured value, the system first enters the fault diagnosis stage to determine the measured boost response time Δt. rise Does it exceed the preset maximum allowable response time Δt? max If the judgment result is yes, that is, Δt rise If the limit is exceeded, a predefined fault-safe procedure is activated; otherwise, the system enters the core decoupling stage. In this stage, the system utilizes the asymmetry of the boost / buck timing to separate the intertwined temperature effects from the load effects, thereby obtaining the temperature compensation coefficient K. temp With load compensation coefficient K load Meanwhile, the system can also independently trigger the pump health status self-diagnosis function when it detects that the vehicle has entered a preset standby condition, by measuring the pressure decay time Δt. decay This characterizes the degree of internal leakage in the pump and generates a pump health factor H based on it. Finally, in the instruction dynamic construction module that integrates the health factor, the system will use the basic displacement instruction D... base Temperature compensation coefficient K temp Load compensation coefficient K load And the pump health factor H is calculated according to the formula. Generate the final displacement control command and output it to the variable pump.

[0040] like Figure 2 As shown in the figure, the horizontal axis represents the oil temperature in °C, and the vertical axis represents the response time in milliseconds. The curve clearly shows the boost response time Δt. rise The solid line indicates the voltage drop response time Δt. drop The graph uses a dashed line to indicate the evolution of oil viscosity as the temperature changes from -30℃ to 120℃. It shows that as the oil temperature increases, its viscosity decreases, leading to a change in Δt. rise With Δt drop All exhibit a non-linear decreasing trend, and throughout the entire temperature range, Δt rise The value is always greater than Δt drop The value of , this inherent asymmetry, provides a physical basis for the subsequent decoupling of temperature and load effects.

[0041] like Figure 3As shown, the system is typically in a standby state that continuously monitors trigger events. When a hydraulic operation command is received, the system transitions from standby to dynamic operation and compensation. In this state, it performs core tasks such as measuring pressure rise and fall response times, decoupling and calculating temperature and load compensation coefficients, and generating and sending the final displacement command. After the operation cycle ends, it returns to standby. If the pressure rise response time exceeds the limit during dynamic operation, the system immediately switches to fault-safe mode, performing operations such as suspending normal control logic, activating predefined safety programs, and issuing fault alarm signals. In addition, when the system is in standby and a standby condition is detected, it triggers a pump health self-diagnosis process, performing tasks such as forming a closed dead load chamber at the control outlet, measuring the natural pressure decay time, and updating health factors. After the diagnosis is completed, it returns to standby. Similarly, if a steady-state condition is detected during dynamic operation, the system triggers a filter health monitoring process, performing tasks such as counting pressure signal state transitions, calculating jitter frequency, and comparing with a benchmark to determine the risk of blockage. After monitoring is completed or the steady-state condition ends, it returns to dynamic operation and compensation.

[0042] Example 4: This example aims to illustrate the offline calibration and setting procedures for a series of key parameters and mapping relationships required before the specific engineering deployment of the aforementioned technical solution, in order to solve the parameter mismatch problem that may occur when applying a general control model to a specific type of engineering vehicle. On a prototype of a specific type of engineering vehicle, before its mass production, a one-time calibration of the control system parameters is performed on a dedicated hydraulic test bench. This test bench has the function of accurately controlling the hydraulic oil temperature and simulating different levels of external loads. The purpose of the calibration is to generate a lookup table and threshold parameters that match the inherent characteristics of the hydraulic system for the edge control unit of this type of vehicle. The calibration process first enters the temperature compensation coefficient K. temp In the mapping relationship establishment phase, the vehicle's hydraulic system was placed under no-load conditions. Using the thermodynamic control unit of the test bench, the hydraulic oil temperature was gradually increased from the vehicle's designed minimum operating temperature of -30°C to the maximum operating temperature of 120°C in 10°C increments. At each temperature step point, after the oil temperature stabilized, multiple standard unloading cycles were executed, and the pressure drop response time Δt was recorded. drop The average value was then used, followed by Δt measured at the system's normal operating temperature of 50°C. drop Using K as the reference point, temp The value is set to 1.0. For other temperature points, it is determined based on their Δt. drop The degree of deviation from the reference value is used to set a K value to compensate for viscosity changes at that temperature. temp These values ​​are sequentially stored in the first one-dimensional lookup table within the edge control unit.

[0043] After completing the temperature calibration, proceed to the load compensation factor K. load During the mapping relationship establishment phase, the hydraulic oil temperature was stabilized at the aforementioned reference temperature of 50°C. Using the load simulation unit of the test bench, a series of known loads from zero load to the maximum design load were applied to the hydraulic system. At each load step point, a complete loading-unloading cycle was executed, and the pressure boost response time Δt was measured. rise And calculate its pressure drop response time Δt at the current reference temperature. drop The ratio is determined by setting a corresponding K based on the requirements of achieving the preset response objectives under this load, such as minimizing pressure overshoot and response time. load The value, and the ratio of that value to K load The values ​​are stored as data pairs in a second one-dimensional lookup table; after the above two core lookup tables are generated, the diagnostic and safety-related thresholds in the system are determined, including the maximum permissible response time Δt. max The setting is to take the longest Δt measured in all the aforementioned calibration conditions. rise The value is multiplied by a fixed safety factor of 1.5, and the result is written into the control unit as a fixed fault judgment boundary, which is the reference jitter frequency f required for filter health monitoring. base During the entire calibration process, when the hydraulic system is in any period of pressure stability, the number of pressure switch signal transitions is continuously collected, and the average frequency is calculated. This average value is then set as the f-value for the new system. base .

[0044] Finally, the mapping relationship of the pump health factor H was calibrated. In the brand-new condition of the prototype, a pump health self-diagnosis step was performed, and the pressure decay time was measured and recorded. This value was defined as Δt for a brand-new pump. decaynew This corresponds to H = 1.0. Simultaneously, based on the pump's design life and failure data, a pressure decay time characterizing severe pump wear is determined, defined as Δt. decayeol This value corresponds to a minimum acceptable health factor H. min The lookup table within a cell is based on a linear relationship. By filling in the gaps, Δt was established. decay A deterministic mapping relationship between H and H.

[0045] Example 5: This example aims to illustrate an adaptive baseline calibration and parameter fine-tuning procedure executed when the aforementioned technical solution encounters changes in key media or components of the hydraulic system, demonstrating the adaptability and maintenance convenience of the control system throughout its entire lifecycle. When an engineering vehicle that has completed offline calibration undergoes routine maintenance and has had its hydraulic oil changed to a different grade, or a pressure switch with individual differences in response characteristics replaced, its hydraulic response baseline characteristics may drift. In this case, a field baseline calibration procedure can be initiated through the maintenance diagnostic interface. After the procedure is triggered, the vehicle needs to perform several standard unloading actions under no-load conditions at the current ambient temperature. During this process, the edge control unit measures and records the stable pressure reduction response time Δt under the current conditions. drop The average value is calculated and set as the new ambient temperature reference time. Then, the control unit compares this new reference time with the original reference time stored during offline calibration, and calculates a global temperature compensation scaling factor. In subsequent routine operations, all real-time measured Δt values ​​are used as the scaling factor. drop The values ​​will first be multiplied by the scaling factor, and then entered into the original one-dimensional lookup table to look up the temperature compensation coefficient K. temp .

[0046] After completing temperature baseline calibration, the system enters a load response fine-tuning phase during the initial recovery cycle. In this phase, the system utilizes its calibrated temperature compensation capability to continuously analyze the correlation between the temperature-compensated boost response time and the external load during each actual load and unload cycle. If the system identifies a persistent unidirectional deviation between this correlation and the mapping relationship stored in the original lookup table, it will adjust the load compensation coefficient K. load The corresponding one-dimensional lookup table is iteratively corrected in small increments until the deviation converges to the preset range. Through this online fine-tuning based on actual operating data, the control system can match its internal model with the changed hardware or media characteristics, thereby restoring its control stability without relying on a large test bench.

[0047] Example 6: This example aims to supplement the explanation of the triggering conditions, internal logic, and preprocessing and validity self-verification procedures of the aforementioned online diagnostic functions, so as to ensure the stability and reliability of the diagnostic results under the working conditions of the engineering vehicle throughout its entire life cycle. The pump health status self-diagnosis step is triggered by a deterministic logic gate, which requires the following three conditions to be met simultaneously within a time window of more than a preset duration: First, the engine speed data obtained from the vehicle bus is continuously within the preset idle speed range; second, all hydraulic operation command signals transmitted from the operating handles are zero; third, the vehicle's driving speed is zero. Only after this logic gate is activated will the system enter the subsequent self-diagnosis process.

[0048] Before officially starting to measure the pressure decay time Δt decay Previously, the system would also perform a sealing verification of the lock-up valve used to create a dead-load closed chamber. In this verification procedure, the edge control unit first instructs the lock-up valve to close, then instructs the variable pump to output at a fixed low displacement and starts timing. In a properly sealed chamber, the pressure should quickly build up and trigger the pressure switch. The system compares the time taken for this process with a maximum allowable pressure build-up time, measured during offline calibration, representing the normal closure of the valve. If the measured pressure build-up time exceeds this maximum allowable time, it indicates that the lock-up valve itself has a leak and cannot provide effective test conditions for pump health diagnosis. At this time, the system will abort the diagnosis and generate a specific fault code for the lock-up valve, thereby avoiding incorrect assessment of the pump's health status due to test condition failure. For filter clogging monitoring, the generation of its alarm threshold includes an adaptive adjustment mechanism. The system obtains a reference jitter frequency f during initial calibration. base However, during long-term vehicle operation, the edge control unit will continuously calculate the moving average of the system's jitter frequency in non-alarm states using a relatively long time constant. The final alarm trigger threshold is the initial reference frequency f. base This weighted combination with the moving average allows the alarm threshold to slowly adapt to the overall drift of the background noise level in the entire hydraulic system due to normal aging, thereby improving the signal-to-noise ratio of the warning signal in long-term use.

[0049] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for controlling an intelligent variable pump in a hydraulic system of an engineering vehicle, characterized in that, Includes the following steps: Step a: Install a pressure switch on the outlet side of the variable pump. The pressure switch is used to generate a binary pressure signal that characterizes whether the outlet pressure has reached a preset threshold. Step b: In a single hydraulic operation cycle of the engineering vehicle, using a timer within the edge control unit, measure the pressure boost response time Δt experienced by the binarized pressure signal during the transition from the first state to the second state during the loading process. rise And the buck response time Δt experienced during the transition from the second state back to the first state during the unloading process. drop ; Step c, the edge control unit uses the pressure drop response time Δt, which is the main factor characterizing the hydraulic oil temperature effect, as the basis for the pressure drop response time. drop The temperature compensation coefficient K is determined according to the preset first mapping relationship. temp Furthermore, the edge control unit is based on the boost response time Δt. rise With the voltage drop response time Δt drop The relationship between the two is used to determine the load compensation coefficient K based on the preset second mapping relationship. load ; Step d: The edge control unit generates basic valve port commands based on the vehicle's operational requirements, and combines the basic valve port commands with the temperature compensation coefficient K. temp and load compensation coefficient K load Multiplication is performed to generate the final valve control command, and the high-frequency electro-hydraulic proportional valve in the main circuit of the system is adjusted according to the final valve control command to control the high-pressure, high-flow hydraulic oil from the variable pump.

2. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, The first mapping relationship in step c is established based on the physical correlation between hydraulic oil viscosity and system pressure response time, and is used to map different pressure drop response times Δt. drop The different temperature compensation coefficients K correspond to different interval ranges. temp value.

3. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, In step c, the load compensation coefficient K is determined. load Specifically, the calculation is based on the following formula: Where f is a preset function used to characterize the relationship between the ratio of boost response time to buck response time and the magnitude of the external load, and the output of the function is the load compensation coefficient K. load .

4. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, The method also includes a fault diagnosis step, which includes: the edge control unit also pre-stores the maximum allowable response time Δt. max ; and before executing step c, a judgment is made if the boost response time Δt measured in step b is... rise Exceeding Δt max If so, steps c and d will be terminated, and a predefined fail-safe procedure will be activated.

5. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, The method also includes a filter health status monitoring step, which includes: when the hydraulic system enters a steady-state operating condition where the pressure value remains stable, the edge control unit counts the number of state transitions of the binarized pressure signal within a preset time window to obtain the jitter frequency; and if the jitter frequency exceeds the preset health status reference frequency, a filter clogging maintenance early warning signal is generated.

6. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, The method also includes a pump health status self-diagnosis step, which includes: when the vehicle is detected to have entered a preset standby condition, controlling the variable pump outlet to form a closed dead load chamber; instructing the variable pump to briefly load the dead load chamber to a preset pressure and then stop; and measuring the pressure decay time Δt experienced by the pressure in the dead load chamber naturally decaying from the preset pressure to the preset threshold of the pressure switch. decay This is used to characterize the degree of internal leakage in variable pumps.

7. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 6, characterized in that, The method also includes an efficiency compensation step, which includes: the edge control unit based on the pressure decay time Δt decay When determining the pump health factor H and generating the final displacement control command in step d, the calculation result is further divided by the pump health factor H to compensate for the decrease in volumetric efficiency of the variable pump due to wear.

8. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, Both the first and second mapping relationships are stored in one or more human-dimensional lookup tables of the edge control unit.

9. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 2, characterized in that, The edge control unit also has a pre-stored ambient temperature reference time. If the buck response time Δt drop If the time is longer than the normal temperature reference time, then the temperature compensation coefficient K temp If the voltage drop response time Δt is greater than 1, drop If the time is shorter than the normal temperature reference time, then the temperature compensation coefficient K temp Less than 1.

10. The intelligent variable pump control method for a hydraulic system of an engineering vehicle according to claim 1, characterized in that, The pressure switch is an industrial-grade mechanical pressure switch or an electronic pressure switch, the edge control unit is a general-purpose microcontroller, and the timer is the built-in hardware timer module of the general-purpose microcontroller.

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