Intelligent hydraulic oil tank system, control method thereof and vehicle control unit

Abstract

The invention provides an intelligent hydraulic oil tank system, a control method thereof and a vehicle control unit, and relates to the technical field of intelligent control. The method comprises the steps that system state parameters of the intelligent hydraulic oil tank system are obtained; inputting the system state parameters into a preset neural network model, and predicting the system state; and the intelligent hydraulic oil tank system is intelligently controlled according to the prediction result. According to the method, intelligent control and management of the hydraulic oil tank can be achieved, and therefore the stability and maintenance convenience of a hydraulic system are improved.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, and in particular to an intelligent hydraulic tank system and its control method, and a vehicle controller. Background Technology

[0002] In the field of construction machinery, hydraulic systems are core power transmission and control components, widely used in equipment such as loaders, excavators, and bulldozers. The hydraulic oil tank, as the "heart" of the hydraulic system, undertakes the crucial functions of storing hydraulic oil, dissipating heat, filtering contaminants, and maintaining stable system operation.

[0003] As the construction machinery industry transforms towards electrification and intelligentization, equipment places higher demands on the stability, energy efficiency, and ease of maintenance of hydraulic systems. In related technologies, the structure of a hydraulic oil tank mainly includes basic components such as the tank body, inlet and outlet ports, oil filter, and level gauge, offering limited functionality. Furthermore, the control of the hydraulic oil tank relies heavily on manual operation, such as replacing the filter element in the oil filter and separating contaminants from the tank. This is inefficient, prone to omissions, and can accelerate the wear of hydraulic components, potentially leading to system failures.

[0004] Therefore, there is a need for an intelligent hydraulic tank solution that can achieve intelligent control and management of hydraulic tanks, thereby improving the stability and ease of maintenance of hydraulic systems. Summary of the Invention

[0005] This application provides an intelligent hydraulic oil tank system and its control method, as well as a vehicle controller, which can realize intelligent control and management of the hydraulic oil tank, thereby improving the stability and maintenance convenience of the hydraulic system.

[0006] In a first aspect, embodiments of this application provide a control method for an intelligent hydraulic tank system, comprising:

[0007] Obtain the system status parameters of the intelligent hydraulic oil tank system;

[0008] The system state parameters are input into a preset neural network model to predict the system state.

[0009] The intelligent hydraulic tank system is intelligently controlled based on the prediction results.

[0010] In one possible implementation, the intelligent hydraulic tank system includes a filtration system and an intelligent hydraulic tank. The outlet of the filtration system is connected to the inlet of the intelligent hydraulic tank. The filtration system includes an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter.

[0011] When the system state parameter is the pressure value of the bypass valve, the step of inputting the system state parameter into a preset neural network model to predict the system state includes:

[0012] When the pressure value of the bypass valve is detected to exceed the preset pressure threshold, the pressure value of the bypass valve is input into the preset first neural network model to predict the remaining service time of the filter element in the oil filter.

[0013] or,

[0014] When the pressure value of the bypass valve exceeds a preset pressure threshold, the pressure value of the bypass valve is input into a preset first neural network model to predict the first remaining usage time of the filter element in the oil filter; the pressure value of the bypass valve is sent to a back-end terminal, and the second remaining usage time of the filter element sent by the back-end terminal is received; if the difference between the first remaining usage time and the second remaining usage time is less than a preset time difference threshold, then the first remaining usage time / the second remaining usage time is taken as the remaining usage time of the filter element; if the difference between the first remaining usage time and the second remaining usage time is greater than or equal to the time difference threshold, then the second remaining usage time is taken as the remaining usage time of the filter element.

[0015] The first neural network model is trained based on historical replacement data of the filter cartridges in the filtration system.

[0016] The second remaining service time of the filter element is predicted by the back-end terminal by inputting the pressure value of the bypass valve into a preset second neural network model. The second neural network model is trained based on the historical replacement data of filter elements in multiple filtration systems of the same model.

[0017] In one possible implementation, before inputting the pressure value of the bypass valve into a preset first neural network model, the method further includes:

[0018] Acquire the temperature information of the bypass valve collected by the temperature sensor;

[0019] Determine the target pressure range corresponding to the temperature information, and determine whether the pressure value of the bypass valve is within the target pressure range;

[0020] If the pressure value of the bypass valve is within the target pressure range, then continue to execute the step of inputting the pressure value of the bypass valve into the preset first neural network model;

[0021] If the pressure value of the bypass valve is not within the target pressure range, then the pressure value of the bypass valve is deleted, and the pressure value of the bypass valve in the intelligent hydraulic tank system is reacquired.

[0022] In one possible implementation, the intelligent control of the intelligent hydraulic tank system based on the prediction results includes:

[0023] When the remaining usage time of the filter element is detected to have reached a preset usage time threshold, one or more of the following actions are performed:

[0024] The vehicle-mounted equipment outputs a filter replacement reminder message.

[0025] Output a filter replacement reminder message to the backend terminal;

[0026] Output filter replacement reminder information to the user terminal;

[0027] The filter replacement prompt information includes one or more of the following: text information, image information, sound information, and light information.

[0028] In one possible implementation, when the system state parameter is an oil quality parameter or a blowdown cycle, the step of inputting the system state parameter into a preset neural network model to predict the system state includes:

[0029] The oil quality parameters are input into a preset third neural network model to predict the target sewage discharge time corresponding to the oil quality parameters.

[0030] or,

[0031] Obtain the drainage parameters of the intelligent hydraulic oil tank system, including one or more of the historical drainage time, temperature parameters, pressure parameters, and oil quality parameters of the intelligent hydraulic oil tank; input the drainage parameters and the drainage cycle into a preset fourth neural network model to obtain the adjusted drainage cycle;

[0032] The third neural network model is trained based on the historical oil quality parameters and corresponding drainage times of the intelligent hydraulic oil tank; the fourth neural network model is trained based on the historical drainage parameters and corresponding drainage cycles of the intelligent hydraulic oil tank.

[0033] In one possible implementation, the base plate of the intelligent hydraulic tank is inclined / semi-inclined, and a one-way valve is provided at the lowest point of the base plate, the one-way valve being connected to the reservoir; the intelligent control of the intelligent hydraulic tank system based on the prediction results includes:

[0034] When the current time is detected to have reached the target sewage discharge time / sewage discharge cycle / adjusted sewage discharge cycle, the one-way valve is controlled to open so that the contaminated oil at the bottom of the intelligent hydraulic oil tank flows into the reservoir through the one-way valve.

[0035] Secondly, embodiments of this application provide a vehicle controller, including:

[0036] The acquisition module is used to acquire the system status parameters of the intelligent hydraulic oil tank system;

[0037] The processing module is used to input the system state parameters into a preset neural network model to predict the system state; and to perform intelligent control of the intelligent hydraulic tank system based on the prediction results.

[0038] Thirdly, embodiments of this application provide another vehicle controller, including:

[0039] The processor, and the memory that is in communication with the processor;

[0040] Memory is used to store instructions that the computer executes;

[0041] The processor is configured to execute computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0042] Fourthly, this application provides an intelligent hydraulic oil tank system, including: a filtration system and an intelligent hydraulic oil tank, wherein the outlet of the filtration system is connected to the inlet of the intelligent hydraulic oil tank;

[0043] The filtration system includes an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter. A differential pressure sensor is provided between the inlet and outlet of the bypass valve, and the differential pressure sensor is connected to the vehicle controller as described in claim 7.

[0044] In one possible implementation, the base plate of the intelligent hydraulic tank is inclined / semi-inclined, and a one-way valve is provided at the lowest point of the base plate.

[0045] The one-way valve includes a one-way valve seat, a steel ball, and a spring. The steel ball and the spring are connected, and the one-way valve seat is fixedly connected to the base plate via a flange.

[0046] The one-way valve seat has a flow hole in the middle, and the intelligent hydraulic oil tank has a control device on the outside. One end of the control device is connected to the steel ball through the flow hole, and the flow hole is also connected to the reservoir.

[0047] When the one-way valve is in the open state, one end of the control device lifts the steel ball away from the one-way valve seat, so that the oil at the bottom of the intelligent hydraulic oil tank flows into the reservoir through the flow hole.

[0048] When the one-way valve is in the closed state, the spring presses the steel ball against the one-way valve seat to block the flow hole, preventing the oil at the bottom of the intelligent hydraulic oil tank from flowing into the reservoir through the flow hole.

[0049] In one possible implementation, the control device includes any one of the following: a piston, a solenoid valve, or a piston with a solenoid valve or a drive device;

[0050] The reservoir includes one or more of the following: a reservoir between the one-way valve seat and the control device, a reservoir inside the control device, a reservoir inside the flange, and a reservoir outside the intelligent hydraulic tank.

[0051] Fifthly, embodiments of this application provide an engineering machinery, including a vehicle controller as described in the third aspect and an intelligent hydraulic tank system as described in the fourth aspect.

[0052] In a sixth aspect, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect described above.

[0053] In a seventh aspect, embodiments of this application provide a computer program product, including a computer program, which, when executed by a processor, is used to implement the first aspect and / or various possible implementations of the first aspect described above.

[0054] This application provides an intelligent hydraulic tank system and its control method, as well as a vehicle controller. By acquiring the system state parameters of the intelligent hydraulic tank system in real time, it achieves accurate, all-time, and blind-spot-free perception of the system state. Subsequently, a preset neural network model is used to analyze the system state parameters. Utilizing the nonlinear fitting and feature learning capabilities of the neural network, the implicit correlations and changing trends between system state parameters can be accurately captured, significantly improving the prediction accuracy of system states such as oil deterioration and abnormal faults. By predicting abnormal system states in advance and taking targeted measures, proactive and intelligent control and management of the hydraulic tank system are achieved, effectively reducing the cost of manual intervention and the risk of human error. It can promptly avoid faults such as hydraulic component wear, achieving refined utilization of oil resources, thereby improving the stability and maintenance convenience of the hydraulic system. Attached Figure Description

[0055] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0056] Figure 1This is a schematic diagram of the structure of an intelligent hydraulic oil tank system according to an embodiment of this application;

[0057] Figure 2 This is a schematic diagram of the structure of a filtration system according to an embodiment of this application;

[0058] Figure 3 This is a schematic diagram of the structure of an intelligent hydraulic oil tank according to an embodiment of this application;

[0059] Figure 4 This is a schematic diagram of the bottom structure of a hydraulic oil tank in related technologies;

[0060] Figure 5 This is a flowchart of a control method for an intelligent hydraulic oil tank system according to an embodiment of this application;

[0061] Figure 6 This is a schematic diagram of the structure of a vehicle controller according to an embodiment of this application;

[0062] Figure 7 This is a schematic diagram of the structure of a vehicle controller according to another embodiment of this application.

[0063] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0064] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0065] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0066] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0067] It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0068] The intelligent hydraulic tank system and its control method, as well as the vehicle controller of this application, can be used in the field of intelligent control, or in any field other than intelligent control, such as the field of construction machinery. The application fields of the intelligent hydraulic tank system and its control method, as well as the vehicle controller of this application, are not limited.

[0069] The intelligent hydraulic tank system and its control method, as well as the vehicle controller of this application, can be applied to the hydraulic systems of construction machinery, especially the intelligent control and system status management of hydraulic tanks. As long as a hydraulic tank exists in the hydraulic system of construction machinery, the intelligent hydraulic tank system and its control method, as well as the vehicle controller of this application, can be applied.

[0070] In the field of construction machinery, hydraulic systems are core power transmission and control components, widely used in equipment such as loaders, excavators, and bulldozers. The hydraulic oil tank, as the "heart" of the hydraulic system, undertakes the crucial functions of storing hydraulic oil, dissipating heat, filtering contaminants, and maintaining stable system operation.

[0071] As the construction machinery industry transforms towards electrification and intelligentization, equipment places higher demands on the stability, energy efficiency, and ease of maintenance of hydraulic systems. In related technologies, the structure of a hydraulic oil tank mainly includes basic components such as the tank body, inlet and outlet ports, oil filter, and level gauge, offering limited functionality. Furthermore, the control of the hydraulic oil tank relies heavily on manual operation, such as replacing the filter element in the oil filter and separating contaminants from the tank. This is inefficient, prone to omissions, and can accelerate the wear of hydraulic components, potentially leading to system failures.

[0072] Based on the above-mentioned technical problems, the inventive concept of this application is to provide an intelligent hydraulic oil tank solution that can realize intelligent control and management of hydraulic oil tanks, thereby improving the stability and maintenance convenience of hydraulic systems.

[0073] This application provides an intelligent hydraulic tank system and its control method, as well as a vehicle controller. By acquiring the system state parameters of the intelligent hydraulic tank system in real time, it achieves accurate, all-time, and blind-spot-free perception of the system state. Subsequently, a preset neural network model is used to analyze the system state parameters. Utilizing the nonlinear fitting and feature learning capabilities of the neural network, the implicit correlations and changing trends between system state parameters can be accurately captured, significantly improving the prediction accuracy of system states such as oil deterioration and abnormal faults. By predicting abnormal system states in advance and taking targeted measures, proactive and intelligent control and management of the hydraulic tank system are achieved, effectively reducing the cost of manual intervention and the risk of human error. It can promptly avoid faults such as hydraulic component wear, achieving refined utilization of oil resources, thereby improving the stability and maintenance convenience of the hydraulic system.

[0074] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0075] Figure 1 This is a schematic diagram of the structure of an intelligent hydraulic oil tank system according to an embodiment of this application, as shown below. Figure 1 As shown, the intelligent hydraulic oil tank system may include a filtration system and an intelligent hydraulic oil tank, with the outlet of the filtration system connected to the inlet of the intelligent hydraulic oil tank.

[0076] Figure 2 This is a schematic diagram of the structure of a filtering system according to an embodiment of this application, as shown below. Figure 2 As shown, the filtration system may include an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter. A differential pressure sensor is provided between the inlet and outlet of the bypass valve, and the differential pressure sensor is connected to the vehicle controller of the construction machinery.

[0077] In this embodiment, the filtration system can be installed in the oil inlet pipe of the intelligent hydraulic oil tank to filter the oil entering the intelligent hydraulic oil tank.

[0078] In this embodiment, the oil filter includes a filter element, which is used to filter the oil flowing into the oil filter.

[0079] In this embodiment, a bypass valve can be installed between the inlet and outlet of the oil filter. The bypass valve and the oil filter are connected in parallel. When the filter element of the oil filter can filter the oil normally, the bypass valve is in the closed state. As the filter element becomes more clogged, the pressure of the bypass valve gradually increases. When the pressure reaches the opening threshold, the bypass valve opens, and the oil flows into the oil tank through the bypass valve (at this time, the filter element is basically clogged, and the oil cannot flow into the oil tank through the filter element). That is, priority is given to ensuring that the oil in the oil tank can support the operation of the equipment.

[0080] However, bypass valves cannot filter hydraulic fluid, and fluid contamination can affect the service life of hydraulic systems and equipment. Therefore, a differential pressure sensor can be installed between the inlet and outlet of the bypass valve. The differential pressure sensor is connected in parallel with the bypass valve, and it can collect the pressure values ​​at both ends of the bypass valve and transmit these values ​​to the vehicle controller.

[0081] In this embodiment, after receiving the pressure value from the bypass valve, the vehicle controller can monitor it as a system status parameter. Before the bypass valve pressure reaches the opening threshold, it uses neural network models and AI technology to analyze and predict the pressure, accurately determining the degree of filter clogging and remaining lifespan. When the remaining lifespan of the filter is detected to be low, a replacement reminder can be sent to the user via various means such as instrument indicator lights, mobile app, or SMS. This setup ensures timely filter replacement before complete clogging, keeping the bypass valve pressure below the opening threshold and preventing oil contamination caused by filter failure and bypass valve opening.

[0082] In this embodiment, a temperature sensor can also be installed between the inlet and outlet of the bypass valve. The temperature sensor is connected in parallel with the bypass valve, and it can collect the temperature values ​​at both ends of the bypass valve and transmit these values ​​to the vehicle controller. The vehicle controller can then use the temperature values ​​to make a reasonable judgment on the pressure values ​​transmitted by the differential pressure sensor. Generally, in a closed system, temperature and pressure are positively correlated; that is, the higher the temperature, the greater the pressure. If the pressure value transmitted by the differential pressure sensor is large, but the temperature value transmitted by the temperature sensor is small, it may be due to an error in the pressure value transmitted by the differential pressure sensor. The vehicle controller can then discard this pressure value and make a combined judgment based on the pressure and temperature values ​​of the bypass valve at the next time period.

[0083] In this embodiment, a pressure switch can also be provided between the inlet and outlet of the bypass valve. The pressure switch is connected in parallel with the bypass valve and can provide overpressure protection for the filtration system.

[0084] In this embodiment, a differential pressure sensor can be installed between the inlet and outlet of the bypass valve. The differential pressure sensor can collect the pressure values ​​at both ends of the bypass valve and transmit the pressure values ​​to the vehicle controller. After receiving the pressure values ​​from the bypass valve, the vehicle controller analyzes them using a preset neural network model. Utilizing the nonlinear fitting and feature learning capabilities of the neural network, it accurately determines the degree of filter element blockage and remaining lifespan. This configuration allows the user to be notified to replace the filter element before it becomes completely clogged, ensuring that the pressure value of the bypass valve remains below the opening threshold. This avoids oil contamination caused by filter element failure and bypass valve opening, mitigates hydraulic component wear and other malfunctions, and achieves proactive and intelligent control of the hydraulic oil tank system.

[0085] In one possible implementation, Figure 3 This is a schematic diagram of the structure of an intelligent hydraulic oil tank according to an embodiment of this application, as shown below. Figure 3 As shown, the base plate of the intelligent hydraulic oil tank is tilted / semi-tilted, and a one-way valve is installed at the lowest point of the base plate.

[0086] A one-way valve includes a one-way valve seat, a steel ball, and a spring. The steel ball and spring are connected together, and the one-way valve seat is fixedly connected to the base plate via a flange.

[0087] A flow hole is provided in the middle of the one-way valve seat, and a control device is provided on the outside of the intelligent hydraulic oil tank. One end of the control device is connected to the steel ball through the flow hole, and the flow hole is also connected to the reservoir.

[0088] When the check valve is in the open state, one end of the control device lifts the steel ball away from the check valve seat, allowing the oil at the bottom of the intelligent hydraulic oil tank to flow into the reservoir through the flow hole.

[0089] When the check valve is closed, the spring presses the steel ball against the check valve seat to block the flow hole, preventing the oil at the bottom of the intelligent hydraulic tank from flowing into the reservoir through the flow hole.

[0090] Figure 4 This is a schematic diagram of the structure of the bottom of a hydraulic oil tank in related technologies, such as... Figure 4 As shown, the bottom plate of the hydraulic oil tank is flat, and a drain port is provided on the bottom plate. The drain port is fitted onto a fixing ring, and the fixing ring fixes the fixing ring to the bottom plate. The external piston blocks the drain port through the fixing ring.

[0091] When the hydraulic fluid in the tank becomes contaminated, the only way to drain the fluid is to pull out the retaining ring from the external piston, resulting in significant waste and high maintenance costs. Otherwise, the contaminated fluid will wear down the hydraulic system. Furthermore, because the base plate is flat and the retaining ring and retaining ring extend above the drain port on the base plate, the fluid in the tank cannot be completely drained. The remaining fluid in the tank reduces the quality of newly injected fluid, leading to frequent fluid changes and further increasing costs.

[0092] In this embodiment, the bottom plate of the intelligent hydraulic oil tank can be tilted / semi-tilted, so that larger impurities, contaminants, and contaminated oil can be concentrated at the lowest point of the bottom plate of the intelligent hydraulic oil tank, i.e., at the check valve.

[0093] In this embodiment, such as Figure 3 As shown, the one-way valve seat can be fixedly connected to the flange, and the flange can be fixed to the base plate with bolts. Both the flange and the bolts are located on the outside of the base plate (opposite to the area where the oil is located).

[0094] In this embodiment, such as Figure 3 As shown, the spring of the one-way valve can be connected to a fixed structure, which can be connected to a base plate. The receiving cavity of the fixed structure can house the spring and steel ball, fixing the spring and steel ball above the one-way valve seat. A flow channel (either on one side or around the base plate) can be provided at the connection point between the fixed structure and the base plate, allowing the oil (containing impurities and contaminants) at the bottom of the intelligent hydraulic oil tank to flow into the flow hole of the one-way valve seat through the flow channel.

[0095] In this embodiment, such as Figure 3 As shown, when the check valve is in the open state, the control device moves upward, and one end of the control device lifts the steel ball, causing the steel ball to separate from the check valve seat. The oil at the bottom of the intelligent hydraulic oil tank flows into the flow hole of the check valve seat through the flow channel, and then flows into the reservoir through the flow hole.

[0096] In this embodiment, when the check valve is in the closed state, the control device moves down, and the spring presses the steel ball against the check valve seat and blocks the flow hole. After the oil at the bottom of the intelligent hydraulic oil tank flows into the flow tank, it cannot flow into the reservoir through the flow hole of the check valve seat.

[0097] In this embodiment, CFD fluid simulation technology can be used to design the internal bottom plate, baffles, inlet and outlet positions, sensor positions, etc. of the oil tank to eliminate dead zones and eddies and promote oil circulation and heat exchange.

[0098] In this embodiment, the bottom plate of the intelligent hydraulic oil tank can be tilted / semi-tilted, allowing larger contaminants to concentrate at the check valve and flow through the flow channel to the check valve seat. This efficient sedimentation of contaminants is unobstructed. When drainage is required, the check valve is opened via a control device. One end of the control device lifts a steel ball, disengaging it from the check valve seat. This allows contaminated oil at the bottom of the intelligent hydraulic oil tank to flow into the flow hole on the check valve seat and then into the reservoir, thus discharging the contaminated oil. When drainage is not required, the check valve is closed via the control device, blocking the flow hole on the check valve seat with the steel ball, preventing further flow of oil from the tank into the reservoir. This design enables automatic control of hydraulic oil tank drainage using a check valve. Efficient sedimentation and timely drainage significantly extend oil life, reduce oil loss, substantially lower maintenance costs, ensure long-term stable operation of the hydraulic system, and greatly improve reliability.

[0099] In one possible implementation, the control device may include any of the following: a piston, a solenoid valve, or a piston with a solenoid valve or a drive mechanism.

[0100] The reservoir may include one or more of the following: a reservoir between a one-way valve seat and a control device, a reservoir within the control device, a reservoir within a flange, or a reservoir outside the intelligent hydraulic tank.

[0101] In this embodiment, the control device may include, but is not limited to, a piston, a solenoid valve, or a piston with a solenoid valve or a drive device, as long as the control device can control the opening and closing of the one-way valve.

[0102] In this embodiment, when the control device is a piston, the user can control the opening and closing of the one-way valve by means of the piston based on experience.

[0103] In this embodiment, when the control device is a solenoid valve, a piston with a solenoid valve, or a piston with a drive device, the solenoid valve / drive device can be connected to the vehicle controller, and the vehicle controller can automatically control the opening and closing of the check valve through the solenoid valve / drive device.

[0104] In this embodiment, such as Figure 3 As shown, a liquid storage chamber can be provided between the one-way valve seat and the control device. The oil (containing impurities, contaminants, etc.) at the bottom of the intelligent hydraulic oil tank can flow into this liquid storage chamber through the flow hole on the one-way valve seat. A magnetic ring can also be provided on the side of the control device that contacts the liquid storage chamber. The magnetic ring can attract impurities such as iron filings in the liquid in the liquid storage chamber to avoid component wear or blockage.

[0105] In this embodiment, the liquid reservoir may include, but is not limited to: a liquid reservoir between the one-way valve seat and the control device, a liquid reservoir inside the control device, a liquid reservoir inside the flange, or a liquid reservoir outside the intelligent hydraulic oil tank. Any liquid reservoir that can store the liquid flowing out of the one-way valve seat can be used as a liquid reservoir.

[0106] In this embodiment, when the liquid reservoir is a liquid storage chamber between the one-way valve seat and the control device, if the control device controls the one-way valve to close, the liquid in the liquid storage chamber can flow out directly.

[0107] In this embodiment, when the reservoir is a reservoir chamber inside the control device (piston), a reservoir chamber inside the flange, or a reservoir outside the intelligent hydraulic oil tank, the reservoir can be connected to the reservoir chamber between the one-way valve seat and the control device through a guide port / guide pipe, etc., to guide the liquid in the reservoir chamber to the reservoir.

[0108] In this embodiment, when the reservoir is a reservoir chamber inside the control device (piston), a reservoir chamber inside the flange, or a reservoir outside the intelligent hydraulic oil tank, the reservoir can be made transparent so that the user can intuitively see the amount of liquid in the reservoir and the degree of contamination, thereby timely draining the liquid in the reservoir or replacing the oil in the tank.

[0109] In this embodiment, when the reservoir is a reservoir chamber inside the control device (piston), a reservoir chamber inside the flange, or a reservoir outside the intelligent hydraulic oil tank, a solenoid valve can be installed on the reservoir. The solenoid valve can be connected to the vehicle controller, and the vehicle controller can automatically control whether the liquid in the reservoir flows out through the solenoid valve.

[0110] In this embodiment, the control device can be a piston, which is used to manually control the sewage discharge. Alternatively, the control device can be a solenoid valve, a piston with a solenoid valve, or a piston with a drive device, which is used to automatically control the sewage discharge, thereby realizing active and intelligent control of the hydraulic oil tank system.

[0111] Figure 5 This is a flowchart of a control method for an intelligent hydraulic oil tank system according to an embodiment of this application, applied to... Figure 1 This embodiment describes the control method of the intelligent hydraulic oil tank system, with the vehicle controller as the executing entity. For example... Figure 5 As shown, the control method for this intelligent hydraulic tank system may include the following steps:

[0112] S501: Obtain system status parameters of the intelligent hydraulic oil tank system.

[0113] In this embodiment, the system status parameters can be parameters that characterize the status of the intelligent hydraulic tank system, such as the pressure value of the bypass valve, oil quality parameters, preset drainage cycle, oil temperature, bubble content, etc., without any restrictions.

[0114] In this embodiment, the hydraulic oil tank may be equipped with a temperature sensor, an oil quality sensor, a bubble sensor, etc. The temperature sensor can collect the oil tank temperature and transmit it to the vehicle controller, the oil quality sensor can collect oil quality parameters and transmit them to the vehicle controller, and the bubble sensor can collect oil tank bubble parameters and transmit them to the vehicle controller.

[0115] S502: Input the system state parameters into the preset neural network model to predict the system state.

[0116] In this embodiment, when the system status parameter is the pressure value of the bypass valve, the remaining life and replacement time of the filter element in the oil filter can be predicted by a neural network model.

[0117] In this embodiment, when the system status parameter is the oil quality parameter or the preset sewage discharge cycle, the sewage discharge time, i.e. the opening time of the bottom check valve, can be predicted by the neural network model.

[0118] In this embodiment, when the system state parameter is the oil temperature, the start-up time of the oil tank heating / cooling device can be predicted based on this parameter using a neural network model.

[0119] In this embodiment, when the system state parameter is the bubble content, the start time of the oil tank gas collection device can be predicted by a neural network model.

[0120] In this embodiment, a neural network model or AI algorithm can be introduced to perform big data analysis and fault prediction on the operating status of the hydraulic system, realizing the transformation from passive maintenance to predictive maintenance, enabling the hydraulic system to have self-learning, self-diagnosis and self-prediction capabilities, achieving more intelligent working condition identification and energy management, and improving energy efficiency to a new level.

[0121] In this embodiment, system status parameters can also be uploaded to the backend, allowing professionals to remotely diagnose faults and optimize performance, thereby reducing downtime.

[0122] S503: Intelligent control of the intelligent hydraulic tank system based on the prediction results.

[0123] In this embodiment, a heating device (and / or cooling device) may be installed inside / outside the hydraulic oil tank. The heating device (and / or cooling device) is connected to the vehicle controller, and the vehicle controller can use the heating device (and / or cooling device) to actively manage the temperature of the oil.

[0124] In this embodiment, an air collection device can be installed inside the hydraulic oil tank. The air collection device is connected to the vehicle controller, and the vehicle controller can use the air collection device to actively manage the air bubbles in the oil tank.

[0125] In this embodiment, based on the prediction results, a filter element replacement reminder can be output, and / or the drain can be activated, and / or the oil tank heating / cooling device can be activated, and / or the oil tank air collection device can be activated. This allows for proactive and intelligent control and management of the intelligent hydraulic oil tank system, achieving intelligent pollution control and oil temperature management, reducing oil loss, significantly extending oil life, and substantially reducing maintenance costs and downtime. System reliability is significantly enhanced, reducing contaminant wear, lowering the hydraulic system failure rate by more than 50%, and resulting in more stable operation.

[0126] In this embodiment, the system status parameters of the intelligent hydraulic tank system can be acquired in real time, enabling precise, all-time, and blind-spot-free perception of the system status. Subsequently, a pre-defined neural network model is used to analyze the system status parameters. Utilizing the nonlinear fitting and feature learning capabilities of the neural network, the implicit correlations and changing trends between system status parameters can be accurately captured, significantly improving the prediction accuracy of system states such as oil deterioration and abnormal faults. By predicting abnormal system states in advance and taking targeted measures, proactive and intelligent control of the hydraulic tank system is achieved, effectively reducing the cost of manual intervention and the risk of human error. It can also promptly avoid faults such as hydraulic component wear, achieving refined utilization of oil resources, thereby improving the stability and maintenance convenience of the hydraulic system.

[0127] In one possible implementation, the intelligent hydraulic tank system may include a filtration system and an intelligent hydraulic tank. The outlet of the filtration system is connected to the inlet of the intelligent hydraulic tank. The filtration system includes an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter.

[0128] When the system state parameter is the pressure value of the bypass valve, step S502 above inputs the system state parameter into a preset neural network model to predict the system state, which may include:

[0129] When the pressure value of the bypass valve exceeds the preset pressure threshold, the pressure value of the bypass valve is input into the preset first neural network model to predict the remaining service time of the filter element in the oil filter.

[0130] The first neural network model was trained based on historical replacement data of the filter cartridges in the filtration system.

[0131] In this embodiment, the preset pressure threshold can be flexibly set by those skilled in the art according to actual conditions, as long as it is less than the opening threshold of the bypass valve, for example, it can be 80% of the opening threshold, and no restrictions are imposed here.

[0132] In this embodiment, the historical replacement data of the filter element may include the filter element replacement time, replacement frequency, and the pressure value of the bypass valve before replacement.

[0133] In this embodiment, a first neural network model can be trained in advance based on the historical replacement data of the filter element. By inputting the pressure value of the bypass valve into the first neural network model, the remaining service life of the filter element can be accurately predicted.

[0134] In one possible implementation, when the system state parameter is the pressure value of the bypass valve, step S502 above, which inputs the system state parameter into a preset neural network model to predict the system state, may further include:

[0135] S11: When the pressure value of the bypass valve is detected to exceed the preset pressure threshold, the pressure value of the bypass valve is input into the preset first neural network model to predict the first remaining service time of the filter element in the oil filter.

[0136] S12: Send the pressure value of the bypass valve to the back-end terminal and receive the second remaining usage time of the filter element sent by the back-end terminal.

[0137] S13: If the difference between the first remaining usage time and the second remaining usage time is less than the preset time difference threshold, then the first remaining usage time / the second remaining usage time shall be taken as the remaining usage time of the filter element.

[0138] S14: If the difference between the first remaining usage time and the second remaining usage time is greater than or equal to the time difference threshold, then the second remaining usage time shall be taken as the remaining usage time of the filter element.

[0139] The second remaining service time of the filter element is predicted by the back-end terminal by inputting the pressure value of the bypass valve into the preset second neural network model. The second neural network model is trained based on the historical replacement data of filter elements in multiple filtration systems of the same model.

[0140] In this embodiment, when the monitoring personnel obtain the pressure value of the bypass valve sent by the vehicle controller through the back-end terminal, they can determine whether the pressure value of the bypass valve is reasonable and monitor the system status based on the pressure value of the bypass valve.

[0141] In this embodiment, the preset time difference threshold can be flexibly set by those skilled in the art according to actual needs, and no restrictions are imposed here.

[0142] In this embodiment, multiple filtration systems of the same model can be multiple filtration systems of the same model as the filtration system in the device.

[0143] In this embodiment, the first neural network model is trained only based on historical replacement data of the filter system in the device, which may contain errors. Therefore, after predicting the first remaining usage time using the first neural network model, the pressure value of the bypass valve needs to be sent to the back-end terminal, where the second neural network model predicts the second remaining usage time. Since the second remaining usage time is trained based on historical replacement data of multiple filter systems of the same model, its prediction result is more accurate. Therefore, the second remaining usage time can be used to correct the first remaining usage time, improving the accuracy of the filter element remaining usage time prediction.

[0144] In one possible implementation, before inputting the pressure value of the bypass valve into the preset first neural network model as described above, the following may also be included:

[0145] S21: Obtain the temperature information of the bypass valve collected by the temperature sensor.

[0146] S22: Determine the target pressure range corresponding to the temperature information, and determine whether the pressure value of the bypass valve is within the target pressure range.

[0147] S23: If the pressure value of the bypass valve is within the target pressure range, continue to execute the step of inputting the pressure value of the bypass valve into the preset first neural network model.

[0148] S24: If the pressure value of the bypass valve is not within the target pressure range, delete the pressure value of the bypass valve and re-acquire the pressure value of the bypass valve in the intelligent hydraulic tank system.

[0149] In this embodiment, a temperature sensor can also be installed between the inlet and outlet of the bypass valve. The temperature sensor is connected in parallel with the bypass valve. The temperature sensor can collect the temperature values ​​at both ends of the bypass valve and transmit the temperature values ​​of the bypass valve to the vehicle controller.

[0150] In this embodiment, those skilled in the art can pre-set the pressure range corresponding to each temperature and store it in the vehicle controller.

[0151] In this embodiment, the temperature information of the bypass valve can be used to make a reasonable judgment on the pressure value of the bypass valve, so as to avoid obtaining incorrect results based on unreasonable pressure values, which would affect the normal operation of the system.

[0152] In one possible implementation, when the system state parameter is the pressure value of the bypass valve, the above step S503, which performs intelligent control of the intelligent hydraulic tank system based on the prediction result, may include:

[0153] When the remaining usage time of the filter cartridge is detected to have reached a preset usage time threshold, perform one or more of the following:

[0154] A: The filter replacement reminder is output through the vehicle's onboard equipment.

[0155] B: Output filter replacement prompts to the backend terminal.

[0156] C: Output filter replacement prompts to the user terminal.

[0157] The filter replacement prompts include one or more of the following: text, image, sound, and light.

[0158] In this embodiment, the preset usage time threshold can be flexibly set by those skilled in the art according to actual needs, and no restrictions are imposed here.

[0159] In this embodiment, filter replacement reminders can be output via the vehicle's dashboard, such as by illuminating a dashboard indicator light. The dashboard can also output text prompts, visual prompts, etc. Additionally, filter replacement reminders can also be output via the vehicle's audio system.

[0160] In this embodiment, the back-end terminal can be a manufacturer platform, an operation and maintenance platform, etc., to promptly remind operation and maintenance personnel to replace the filter element.

[0161] In this embodiment, filter replacement reminders can be sent to user terminals via various means such as mobile apps or SMS.

[0162] In this embodiment, filter replacement reminders can be output through various means such as vehicle-mounted devices, back-end terminals, and user terminals to promptly remind users or maintenance personnel to replace the filter and avoid oil contamination caused by filter failure.

[0163] In one possible implementation, when the system state parameter is an oil quality parameter, step S502 above, which inputs the system state parameter into a preset neural network model to predict the system state, may include:

[0164] The oil quality parameters are input into a preset third neural network model to predict the target sewage discharge time corresponding to the oil quality parameters.

[0165] The third neural network model was trained based on the historical oil quality parameters of the intelligent hydraulic tank and the corresponding drainage time.

[0166] In this embodiment, an oil quality sensor can be installed inside the hydraulic oil tank. The oil quality sensor can collect oil quality parameters and transmit them to the vehicle controller.

[0167] In this embodiment, the third neural network model can also be trained based on historical data (historical oil quality parameters and corresponding drainage times) of multiple smart hydraulic tanks of the same model as the smart hydraulic tank.

[0168] In this embodiment, a third neural network model can be trained in advance based on historical oil quality parameters and corresponding sewage discharge times. By inputting the collected oil quality parameters into the third neural network model, the target sewage discharge time corresponding to the oil quality parameters can be accurately predicted.

[0169] In one possible implementation, when the system state parameter is the sewage discharge cycle, step S502 above, which inputs the system state parameter into a preset neural network model to predict the system state, may include:

[0170] S31: Obtain the drainage parameters of the intelligent hydraulic oil tank system. The drainage parameters include one or more of the following: historical drainage time of the intelligent hydraulic oil tank, temperature parameters, pressure parameters, and oil quality parameters.

[0171] S32: Input the sewage discharge parameters and sewage discharge cycle into the preset fourth neural network model to obtain the adjusted sewage discharge cycle.

[0172] The fourth neural network model was trained based on the historical sewage discharge parameters and corresponding sewage discharge cycles of the intelligent hydraulic oil tank.

[0173] In this embodiment, the drainage parameters may include, but are not limited to: the historical drainage time of the intelligent hydraulic oil tank, temperature parameters, pressure parameters, oil quality parameters, etc. Any parameters related to the drainage of the oil tank can be used as drainage parameters, such as bubble parameters.

[0174] In this embodiment, the fourth neural network model can also be trained based on historical data (historical sewage discharge parameters and corresponding sewage discharge cycles of the intelligent hydraulic tank) from multiple intelligent hydraulic tanks of the same model as the intelligent hydraulic tank.

[0175] In this embodiment, the vehicle controller can pre-store a drainage cycle, which is fixed. The drainage cycle can be adjusted according to the current drainage parameters of the intelligent hydraulic tank system, so that the adjusted drainage cycle is more adapted to the current working conditions of the intelligent hydraulic tank system and improves the accuracy of the drainage cycle.

[0176] In one possible implementation, the base plate of the intelligent hydraulic tank is inclined / semi-inclined, and a check valve is provided at the lowest point of the base plate, which is connected to the reservoir.

[0177] When the system status parameters are oil quality parameters or drain cycle, the above step S503, which performs intelligent control of the intelligent hydraulic tank system based on the prediction results, may include:

[0178] When the target sewage discharge time / sewage discharge cycle / adjusted sewage discharge cycle is detected, the one-way valve is opened to allow the contaminated oil at the bottom of the intelligent hydraulic oil tank to flow into the reservoir through the one-way valve.

[0179] In this embodiment, the closing time of the one-way valve can be controlled by the user based on experience, or predicted using big data analysis or neural network models.

[0180] In this embodiment, when the target drainage time / drainage cycle / adjusted drainage cycle is detected, the check valve is opened, allowing contaminated oil at the bottom of the intelligent hydraulic tank to flow into the reservoir through the check valve. This setup enables automatic control of hydraulic tank drainage, significantly extending oil life and reducing oil loss through efficient sedimentation and timely drainage. It also significantly lowers maintenance costs, ensures long-term stable operation of the hydraulic system, and greatly improves reliability.

[0181] The application process of the intelligent hydraulic tank system of this application is described below with a specific embodiment.

[0182] like Figure 1 , Figure 2 and Figure 3 As shown, the intelligent hydraulic oil tank system includes a filtration system and an intelligent hydraulic oil tank, with the outlet of the filtration system connected to the inlet of the intelligent hydraulic oil tank.

[0183] The filtration system includes an oil filter, and a bypass valve is installed between the inlet and outlet of the oil filter. A differential pressure sensor and a temperature sensor are respectively installed between the inlet and outlet of the bypass valve, and both the differential pressure sensor and the temperature sensor are connected to the vehicle controller of the construction machinery. A pressure switch is also installed between the inlet and outlet of the bypass valve.

[0184] An oil filter includes a filter element, which is used to filter the oil flowing into the filter.

[0185] The intelligent hydraulic oil tank has a tilted / semi-tilted base plate, and a check valve is installed at the lowest point of the base plate.

[0186] A one-way valve includes a one-way valve seat, a steel ball, and a spring. The steel ball and spring are connected together, and the one-way valve seat is fixedly connected to the base plate via a flange.

[0187] A flow hole is provided in the middle of the one-way valve seat, and a control device is provided on the outside of the intelligent hydraulic oil tank. One end of the control device is connected to the steel ball through the flow hole, and the flow hole is also connected to the reservoir.

[0188] When the check valve is in the open state, one end of the control device lifts the steel ball away from the check valve seat, allowing the oil at the bottom of the intelligent hydraulic oil tank to flow into the reservoir through the flow hole.

[0189] When the check valve is closed, the spring presses the steel ball against the check valve seat to block the flow hole, preventing the oil at the bottom of the intelligent hydraulic tank from flowing into the reservoir through the flow hole.

[0190] The intelligent control process of this intelligent hydraulic oil tank system is as follows:

[0191] (a) Filter element replacement control:

[0192] The first step is for the vehicle controller to acquire the pressure value of the bypass valve. When the pressure value of the bypass valve exceeds the preset pressure threshold, the controller acquires the temperature information of the bypass valve collected by the temperature sensor, determines the target pressure range corresponding to the temperature information, and confirms that the pressure value of the bypass valve is within the target pressure range.

[0193] The second step involves the vehicle controller inputting the pressure value of the bypass valve into a preset first neural network model to predict the remaining usage time of the filter element in the oil filter.

[0194] The third step is that when the vehicle controller detects that the remaining usage time of the filter element has reached the preset usage time threshold, it outputs a filter element replacement prompt message through the on-board equipment, and also outputs the filter element replacement prompt message to the back-end terminal and the user terminal respectively.

[0195] (ii) Automatic control of sewage discharge:

[0196] The first step is for the vehicle controller to obtain the preset sewage discharge cycle and the sewage discharge parameters of the intelligent hydraulic oil tank system. The sewage discharge parameters include one or more of the following: historical sewage discharge time of the intelligent hydraulic oil tank, temperature parameters, pressure parameters, and oil quality parameters.

[0197] The second step involves the vehicle controller inputting the sewage discharge parameters and sewage discharge cycle into the preset fourth neural network model to obtain the adjusted sewage discharge cycle.

[0198] Third, when the vehicle controller detects that the current time has reached the adjusted sewage discharge cycle, it controls the one-way valve to open so that the contaminated oil at the bottom of the intelligent hydraulic oil tank flows into the reservoir through the one-way valve.

[0199] Figure 6 This is a schematic diagram of the structure of a vehicle controller according to an embodiment of this application, as shown below. Figure 6 As shown, the vehicle controller includes: an acquisition module 61 for acquiring system state parameters of the intelligent hydraulic tank system; a processing module 62 for inputting the system state parameters into a preset neural network model to predict the system state; and intelligent control of the intelligent hydraulic tank system based on the prediction results.

[0200] The vehicle controller provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be repeated here.

[0201] Figure 7 This is a schematic diagram of the structure of a vehicle controller according to another embodiment of this application, as shown below. Figure 7 As shown, the vehicle controller includes a processor 701 and a memory 702 communicatively connected to the processor 701; the memory 702 stores computer-executed instructions; the processor 701 executes the computer-executed instructions stored in the memory 702 to implement the steps of the control method of the intelligent hydraulic tank system in the above-described method embodiments.

[0202] In the aforementioned vehicle controller, the memory 702 and the processor 701 are electrically connected directly or indirectly to enable data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines, such as a bus connection. The memory 702 stores computer-executable instructions for implementing data access control methods, including at least one software function module that can be stored in the memory 702 in the form of software or firmware. The processor 701 executes various functional applications and data processing by running the software programs and modules stored in the memory 702.

[0203] The memory 702 may be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 702 stores programs, which are executed by the processor 701 upon receiving execution instructions. Furthermore, the software programs and modules within the memory 702 may include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components.

[0204] The processor 701 can be an integrated circuit chip with signal processing capabilities. The processor 701 described above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0205] One embodiment of this application also provides an engineering machinery, which may include: such as Figure 6 The vehicle controller shown, and as Figure 1 The intelligent hydraulic oil tank system shown.

[0206] An embodiment of this application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the steps of the various method embodiments of this application.

[0207] An embodiment of this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the various method embodiments of this application.

[0208] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0209] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0210] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0211] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0212] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0213] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

[0214] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A control method for an intelligent hydraulic oil tank system, characterized in that, include: Obtain the system status parameters of the intelligent hydraulic oil tank system; The system state parameters are input into a preset neural network model to predict the system state. The intelligent hydraulic tank system is intelligently controlled based on the prediction results.

2. The control method for the intelligent hydraulic oil tank system according to claim 1, characterized in that, The intelligent hydraulic oil tank system includes a filtration system and an intelligent hydraulic oil tank. The outlet of the filtration system is connected to the inlet of the intelligent hydraulic oil tank. The filtration system includes an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter. When the system state parameter is the pressure value of the bypass valve, the step of inputting the system state parameter into a preset neural network model to predict the system state includes: When the pressure value of the bypass valve is detected to exceed the preset pressure threshold, the pressure value of the bypass valve is input into the preset first neural network model to predict the remaining service time of the filter element in the oil filter. or, When the pressure value of the bypass valve exceeds a preset pressure threshold, the pressure value of the bypass valve is input into a preset first neural network model to predict the first remaining usage time of the filter element in the oil filter; the pressure value of the bypass valve is sent to a back-end terminal, and the second remaining usage time of the filter element sent by the back-end terminal is received; if the difference between the first remaining usage time and the second remaining usage time is less than a preset time difference threshold, then the first remaining usage time / the second remaining usage time is taken as the remaining usage time of the filter element; if the difference between the first remaining usage time and the second remaining usage time is greater than or equal to the time difference threshold, then the second remaining usage time is taken as the remaining usage time of the filter element. The first neural network model is trained based on historical replacement data of the filter cartridges in the filtration system. The second remaining service time of the filter element is predicted by the back-end terminal by inputting the pressure value of the bypass valve into a preset second neural network model. The second neural network model is trained based on the historical replacement data of filter elements in multiple filtration systems of the same model.

3. The control method for the intelligent hydraulic oil tank system according to claim 2, characterized in that, Before inputting the pressure value of the bypass valve into the preset first neural network model, the method further includes: Acquire the temperature information of the bypass valve collected by the temperature sensor; Determine the target pressure range corresponding to the temperature information, and determine whether the pressure value of the bypass valve is within the target pressure range; If the pressure value of the bypass valve is within the target pressure range, then continue to execute the step of inputting the pressure value of the bypass valve into the preset first neural network model; If the pressure value of the bypass valve is not within the target pressure range, then the pressure value of the bypass valve is deleted, and the pressure value of the bypass valve in the intelligent hydraulic tank system is reacquired.

4. The control method for the intelligent hydraulic oil tank system according to claim 2, characterized in that, The intelligent control of the intelligent hydraulic tank system based on the prediction results includes: When the remaining usage time of the filter element is detected to have reached a preset usage time threshold, one or more of the following actions are performed: The vehicle-mounted equipment outputs a filter replacement reminder message. Output a filter replacement reminder message to the backend terminal; Output filter replacement reminder information to the user terminal; The filter replacement prompt information includes one or more of the following: text information, image information, sound information, and light information.

5. The control method for the intelligent hydraulic oil tank system according to any one of claims 2-4, characterized in that, When the system state parameter is an oil quality parameter or a sewage discharge cycle, the step of inputting the system state parameter into a preset neural network model to predict the system state includes: The oil quality parameters are input into a preset third neural network model to predict the target sewage discharge time corresponding to the oil quality parameters. or, Obtain the drainage parameters of the intelligent hydraulic oil tank system, including one or more of the historical drainage time, temperature parameters, pressure parameters, and oil quality parameters of the intelligent hydraulic oil tank; input the drainage parameters and the drainage cycle into a preset fourth neural network model to obtain the adjusted drainage cycle; The third neural network model is trained based on the historical oil quality parameters and corresponding drainage times of the intelligent hydraulic oil tank; the fourth neural network model is trained based on the historical drainage parameters and corresponding drainage cycles of the intelligent hydraulic oil tank.

6. The control method for the intelligent hydraulic oil tank system according to claim 5, characterized in that, The intelligent hydraulic tank has a base plate that is inclined / semi-inclined, and a check valve is installed at the lowest point of the base plate, the check valve being connected to the reservoir; the intelligent control of the intelligent hydraulic tank system based on the prediction results includes: When the current time is detected to have reached the target sewage discharge time / sewage discharge cycle / adjusted sewage discharge cycle, the one-way valve is controlled to open so that the contaminated oil at the bottom of the intelligent hydraulic oil tank flows into the reservoir through the one-way valve.

7. A vehicle controller, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory is used to store computer-executed instructions; The processor is used to execute computer execution instructions stored in the memory, causing the processor to perform the control method of the intelligent hydraulic tank system as described in any one of claims 1-6.

8. An intelligent hydraulic oil tank system, characterized in that, include: A filtration system and an intelligent hydraulic oil tank, wherein the outlet of the filtration system is connected to the inlet of the intelligent hydraulic oil tank; The filtration system includes an oil filter, and a bypass valve is provided between the inlet and outlet of the oil filter. A differential pressure sensor is provided between the inlet and outlet of the bypass valve, and the differential pressure sensor is connected to the vehicle controller as described in claim 7.

9. The intelligent hydraulic oil tank system according to claim 8, characterized in that, The base plate of the intelligent hydraulic oil tank is inclined / semi-inclined, and a one-way valve is provided at the lowest point of the base plate. The one-way valve includes a one-way valve seat, a steel ball, and a spring. The steel ball and the spring are connected, and the one-way valve seat is fixedly connected to the base plate via a flange. The one-way valve seat has a flow hole in the middle, and the intelligent hydraulic oil tank has a control device on the outside. One end of the control device is connected to the steel ball through the flow hole, and the flow hole is also connected to the reservoir. When the one-way valve is in the open state, one end of the control device lifts the steel ball away from the one-way valve seat, so that the oil at the bottom of the intelligent hydraulic oil tank flows into the reservoir through the flow hole. When the one-way valve is in the closed state, the spring presses the steel ball against the one-way valve seat to block the flow hole, preventing the oil at the bottom of the intelligent hydraulic oil tank from flowing into the reservoir through the flow hole.

10. The intelligent hydraulic oil tank system according to claim 9, characterized in that, The control device includes any one of the following: a piston, a solenoid valve, or a piston equipped with a solenoid valve or a drive device; The reservoir includes one or more of the following: a reservoir between the one-way valve seat and the control device, a reservoir inside the control device, a reservoir inside the flange, and a reservoir outside the intelligent hydraulic tank.

Images