A clutch pressure self-learning method, device, equipment and medium

Abstract

The application discloses a clutch pressure self-learning method and device, equipment and medium. The method comprises the following steps: determining a current theoretical pressure of a target clutch at a current time, and determining a historical theoretical pressure of the target clutch at a historical time; the historical time is determined based on the current time and a preset period; determining a theoretical pressure slope absolute value of the target clutch according to the current theoretical pressure and the historical theoretical pressure; determining a slope threshold value associated with the current theoretical pressure; if it is determined that the slope threshold value is smaller than the theoretical pressure slope, the target clutch is prohibited from self-learning; if it is determined that the slope threshold value is greater than or equal to the theoretical pressure slope absolute value, the target clutch is controlled to perform self-learning. Through the execution of the scheme, the accuracy of self-learning of the clutch near the half combination point can be improved, and then the driving stability coefficient is improved, and the riding experience of the user is improved.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and in particular to a clutch pressure self-learning method, device, equipment and medium. Background Art

[0002] In transmission systems, clutch pressure is typically regulated by controlling the current flowing through the clutch solenoid valve. Since consistency is difficult to achieve during solenoid valve production, and individual solenoid valve characteristics vary, each solenoid valve undergoes off-line testing to determine the relationship between current and actual clutch pressure. However, this relationship may fluctuate significantly throughout the lifecycle of the valve body and its transmission-equipped vehicle, necessitating clutch pressure self-learning to adjust the clutch pressure when deviations occur.

[0003] The current pressure-current self-learning method is primarily as follows: When the command pressure is within a certain range, and the command pressure and actual pressure are greater than a certain value, the current is compensated within this pressure range to ensure that the actual pressure follows the command pressure. However, actual clutch pressure tracking deteriorates near the half-engagement point. If the command pressure rises too rapidly within a certain range, the actual pressure will not be able to keep up, causing the system to believe the actual pressure is too low and initiate an erroneous self-learning. This leads to an incorrect correspondence between the pressure point and the current value, resulting in inaccurate clutch pressure self-learning results, abnormal control, and serious impact on driving. Summary of the Invention

[0004] The present invention provides a clutch pressure self-learning method, device, equipment and medium, which can improve the accuracy of clutch self-learning near the semi-engagement point, thereby helping to improve the driving stability coefficient and enhance the user's riding experience.

[0005] According to one aspect of the present invention, a clutch pressure self-learning method is provided, the method comprising:

[0006] Determining a current theoretical pressure of a target clutch at a current moment, and determining a historical theoretical pressure of the target clutch at a historical moment; the historical moment being determined based on the current moment and a preset period;

[0007] determining an absolute value of a theoretical pressure slope of the target clutch according to the current theoretical pressure and the historical theoretical pressure;

[0008] determining a slope threshold associated with the current theoretical pressure;

[0009] If it is determined that the slope threshold is less than the theoretical pressure slope absolute value, prohibiting the target clutch from performing self-learning;

[0010] If it is determined that the slope threshold value is greater than or equal to the theoretical pressure slope absolute value, the target clutch is controlled to perform self-learning.

[0011] According to another aspect of the present application, there is provided a clutch pressure self-learning device, comprising:

[0012] A current and historical theoretical pressure determination module is configured to determine a current theoretical pressure of a target clutch at a current time and determine a historical theoretical pressure of the target clutch at a historical time; the historical time is determined based on the current time and a preset period;

[0013] A theoretical pressure slope determination module is configured to determine a theoretical pressure slope absolute value of the target clutch according to the current theoretical pressure and the historical theoretical pressure;

[0014] A slope threshold value determination module is configured to determine a slope threshold value associated with the current theoretical pressure;

[0015] A first determination module is configured to, if it is determined that the slope threshold value is less than the theoretical pressure slope absolute value, prohibit the target clutch from performing self-learning;

[0016] A second determination module is configured to, if it is determined that the slope threshold value is greater than or equal to the theoretical pressure slope, control the target clutch to perform self-learning.

[0017] According to another aspect of the present application, there is provided an electronic device, comprising:

[0018] At least one processor; and

[0019] A memory in communication connection with the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the clutch pressure self-learning method according to any one of the embodiments of the present application.

[0021] According to another aspect of the present application, there is provided a computer readable storage medium, which stores computer instructions for enabling a processor to execute the clutch pressure self-learning method according to any one of the embodiments of the present application when executed by the processor.

[0022] The technical scheme of the embodiment of the present application determines a current theoretical pressure of the target clutch at a current moment and determines a historical theoretical pressure of the target clutch at a historical moment; the historical moment is determined based on the current moment and a preset period; a theoretical pressure slope absolute value of the target clutch is determined according to the current theoretical pressure and the historical theoretical pressure; a slope threshold value associated with the current theoretical pressure is determined; if it is determined that the slope threshold value is less than the theoretical pressure slope absolute value, the target clutch is prohibited from self-learning; and if it is determined that the slope threshold value is greater than or equal to the theoretical pressure slope absolute value, the target clutch is controlled to perform self-learning. By executing the present scheme, the accuracy of self-learning of the clutch near the half combination point can be improved, and thus the driving stability coefficient can be improved, and the user's ride experience can be improved.

[0023] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0025] Figure 1 is a flowchart of a clutch pressure self-learning method provided by the embodiment of the present application;

[0026] Figure 2 is a flowchart of another clutch pressure self-learning method provided by the embodiment of the present application;

[0027] Figure 3 is a structural schematic diagram of a clutch pressure self-learning device provided by the embodiment of the present application;

[0028] Figure 4 is a structural schematic diagram of an electronic device for implementing the clutch pressure self-learning method of the embodiment of the present application. DETAILED DESCRIPTION

[0029] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second", and the like in the description and in the claims of the present application and above-described accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the data thus used can be interchanged under appropriate circumstances so that the embodiments of the application described herein can be implemented in other than the order illustrated or described herein. Moreover, 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 includes a list of steps or units not necessarily limited to those clearly identified as such, but can include other not clearly recited steps or units inherent in such process, method, product, or apparatus.

[0031] It can be understood that, before using the technical solutions disclosed in the embodiments of the present application, the type, applicable scope, and use scenarios of the personal information involved in the present application should be informed to the user and the authorization of the user should be obtained in accordance with relevant laws and regulations.

[0032] For example, in response to receiving the active request of the user, prompt information is sent to the user to explicitly prompt the user that the operation requested to be performed will require the acquisition and use of personal information of the user. Thus, the user can voluntarily choose whether to provide personal information to the software or hardware such as electronic device, application program, server, or storage medium, etc. performing the operation of the technical solutions of the present application according to the prompt information.

[0033] As an optional but non-limiting implementation manner, in response to receiving the active request of the user, the manner of sending prompt information to the user may, for example, be the manner of pop-up window, and the prompt information may, for example, be presented in the form of text in the pop-up window. In addition, the pop-up window may, for example, also carry selection controls for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0034] It can be understood that the above-mentioned notification and acquisition of user authorization process is only illustrative and does not limit the implementation manner of the present application, and other manners meeting the relevant laws and regulations can also be applied to the implementation manner of the present application.

[0035] It can be understood that the data (including but not limited to the data itself, the acquisition or use of the data) involved in the present technical solution should comply with the requirements of the relevant laws and regulations and the relevant provisions.

[0036] Figure 1is a flowchart of a clutch pressure self-learning method provided by an embodiment of the present application. The embodiment can be applicable to the case where a DCT clutch performs self-learning near a half engagement point. The method can be performed by a clutch pressure self-learning device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device for clutch pressure self-learning. As shown in Figure 1 the method includes the following steps.

[0037] S110: Determine a current theoretical pressure of a target clutch at a current time and a historical theoretical pressure of the target clutch at a historical time.

[0038] The historical time is determined based on the current time and a preset period.

[0039] The theoretical pressure can be determined by calculating a target clutch torque according to a vehicle state, and then converting the target clutch torque value to obtain the theoretical pressure of the target clutch. The theoretical pressure can be obtained by using an existing demand pressure acquisition method, and the embodiment will not be described in detail. The preset period can be set according to actual needs, for example, 3 periods. The length of one period can be set according to actual needs, for example, 10 ms. The present scheme can determine the current theoretical pressure of the target clutch at the current time and the historical theoretical pressure of the target clutch at the historical time.

[0040] S120: Determine a theoretical pressure slope absolute value of the target clutch according to the current theoretical pressure and the historical theoretical pressure.

[0041] Specifically, the present scheme can take the ratio of the difference between the current theoretical pressure and the historical theoretical pressure to the period length (for example, 10 s) as the theoretical pressure slope of the target clutch at the current time. Alternatively, the present scheme can take the difference between the current theoretical pressure and the historical theoretical pressure as the theoretical pressure slope of the target clutch at the current time, and determine the theoretical pressure slope absolute value.

[0042] S130: Determine a slope threshold value associated with the current theoretical pressure, and determine whether the slope threshold value is less than the theoretical pressure slope absolute value.

[0043] If yes, perform S140, and if no, perform S150.

[0044] Among them, the present solution pre-stores a correspondence table between the theoretical pressure of the target clutch and the slope threshold. For example, when the theoretical pressure is 0 bar, the slope threshold is 0.15 bar / s. When the theoretical pressure is 2 bar, the slope threshold is 0.15 bar / s. When the theoretical pressure is 3 bar, the slope threshold is 0.15 bar / s. When the theoretical pressure is 4 bar, the slope threshold is 0.15 bar / s. When the theoretical pressure is 5 bar, the slope threshold is 1 bar / s. When the theoretical pressure is 10 bar, the slope threshold is 1 bar / s. When the theoretical pressure is 20 bar, the slope threshold is 1 bar / s. This solution can determine the slope threshold associated with the current theoretical pressure, and compare the slope threshold associated with the current theoretical pressure with the absolute value of the theoretical pressure slope at the current moment.

[0045] S140: The target clutch is prohibited from performing self-learning.

[0046] If the slope threshold associated with the current theoretical pressure is determined to be less than the absolute value of the theoretical pressure slope at the current moment, this indicates that the theoretical pressure of the target clutch is changing rapidly. To avoid clutch self-learning errors, the target clutch is prohibited from self-learning. This allows for the identification of erroneous learning scenarios and the termination of self-learning after identification, thus preventing clutch self-learning errors.

[0047] S150: Control the target clutch to perform self-learning.

[0048] Among them, if this scheme determines that the slope threshold associated with the current theoretical pressure is greater than or equal to the absolute value of the theoretical pressure slope at the current moment, it means that the theoretical pressure mutation of the target clutch is small, the target clutch has the conditions for self-learning, and the target clutch can be controlled to perform self-learning.

[0049] The technical solution of the embodiment of the present invention determines the current theoretical pressure of the target clutch at the current moment and determines the historical theoretical pressure of the target clutch at historical moments; the historical moments are determined based on the current moment and a preset period; the absolute value of the theoretical pressure slope of the target clutch is determined based on the current theoretical pressure and the historical theoretical pressure; a slope threshold associated with the current theoretical pressure is determined; if it is determined that the slope threshold is less than the absolute value of the theoretical pressure slope, the target clutch is prohibited from self-learning; if it is determined that the slope threshold is greater than or equal to the absolute value of the theoretical pressure slope, the target clutch is controlled to perform self-learning. By implementing this solution, the accuracy of clutch self-learning near the half-engagement point can be improved, which in turn helps to improve the driving stability factor and enhance the user's riding experience.

[0050] Figure 2 This is a flow chart of the clutch pressure self-learning method provided by an embodiment of the present invention. This embodiment is optimized based on the above embodiment.Figure 2 As shown, the clutch pressure self-learning method in the embodiment of the application can include:

[0051] S210: determining a current theoretical pressure of a target clutch at a current time and determining a historical theoretical pressure of the target clutch at a historical time.

[0052] S220: determining an absolute value of a theoretical pressure slope of the target clutch according to the current theoretical pressure and the historical theoretical pressure.

[0053] S230: determining a slope threshold value associated with the current theoretical pressure and determining whether the slope threshold value is less than the absolute value of the theoretical pressure slope.

[0054] If yes, S240 is performed, and if no, S250 is performed.

[0055] S240: prohibiting the target clutch from performing self-learning.

[0056] S250: determining a target delay time according to the current theoretical pressure and an association between a theoretical pressure and a delay time. S260 is performed.

[0057] In the present scheme, a corresponding relationship table between a theoretical pressure and a delay time is pre-stored, and the target delay time corresponding to the current theoretical pressure can be determined according to the current theoretical pressure and the corresponding relationship table between the theoretical pressure and the delay time. For example, when the theoretical pressure is 0 bar, the delay time is 1.15 s. When the theoretical pressure is 2 bar, the delay time is 1.15 s. When the theoretical pressure is 3 bar, the delay time is 1.15 s. When the theoretical pressure is 4 bar, the delay time is 0.5 s. When the theoretical pressure is 5 bar, the delay time is 0 s. When the theoretical pressure is 10 bar, the delay time is 0 s. When the theoretical pressure is 20 bar, the delay time is 0 s.

[0058] S260: determining a target time according to the current time and the target delay time. S270 is performed.

[0059] In the present scheme, the sum of the current time and the target delay time is determined as the target time.

[0060] S270: for each delay time between the current time and the target time, determining an actual pressure and a theoretical pressure of the target clutch at the delay time. S280 is performed.

[0061] The actual pressure of the target clutch can be obtained by a clutch pressure sensor. The delay time can be determined every 10ms starting from the current time. This solution can determine the actual pressure and theoretical pressure of the target clutch at each delay time between the current time and the target time.

[0062] S280: Determine a stable follow-up result of the actual pressure according to the actual pressure at each delay time and the theoretical pressure. Execute S290.

[0063] The stable following result may be that the actual pressure stably follows the theoretical pressure, or the stable following result may be that the actual pressure stably follows the theoretical pressure. This solution can determine whether the actual pressure stably follows the theoretical pressure based on the theoretical pressure and the actual pressure of the target clutch at each delay moment.

[0064] S290: If it is determined that the stable following result is stable following, the target clutch is controlled to perform self-learning at the target moment.

[0065] In this scheme, if it is determined that the actual pressure of the target clutch stably follows the theoretical pressure, and the rate of change of the theoretical pressure of the target clutch at the target time is less than the slope threshold associated with the theoretical pressure at the target time, it indicates that the target clutch meets the conditions for self-learning, and the target clutch can be controlled to perform self-learning at the target time. If it is determined that the actual pressure of the target clutch does not stably follow the theoretical pressure, and / or the rate of change of the theoretical pressure of the target clutch at the target time is greater than or equal to the slope threshold associated with the theoretical pressure at the target time, it indicates that the target clutch does not meet the conditions for self-learning, the target clutch is prohibited from performing self-learning, and the process returns to S210.

[0066] In this embodiment, optionally, the stable following result of the actual pressure is determined based on the actual pressure and the theoretical pressure at each of the delay moments, including: determining the actual pressure slope and the theoretical pressure slope at each of the delay moments based on the actual pressure and the theoretical pressure; determining the average value of the theoretical pressure slope based on each of the theoretical pressure slopes; if the absolute value of the difference between the actual pressure slope and the theoretical pressure slope at each of the delay moments is less than a first preset threshold, and the absolute value of the difference between each of the actual pressure slopes and the average value of the theoretical pressure slope is less than a second preset threshold, then determining the stable following result of the actual pressure to be stable following.

[0067] Among them, for each delay moment, this solution can use the difference between the actual pressure of the target clutch at the delay moment and the actual pressure of the target clutch at the previous moment as the actual pressure slope of the target clutch at the delay moment. Alternatively, this solution can also use the ratio of the difference between the actual pressure of the target clutch at the delay moment and the actual pressure of the target clutch at the previous moment and the time period as the actual pressure slope of the target clutch at the delay moment. Similarly, for each delay moment, this solution can use the difference between the theoretical pressure of the target clutch at the delay moment and the theoretical pressure of the target clutch at the previous moment as the theoretical pressure slope of the target clutch at the delay moment. Alternatively, this solution can also use the ratio of the difference between the theoretical pressure of the target clutch at the delay moment and the theoretical pressure of the target clutch at the previous moment and the time period as the theoretical pressure slope of the target clutch at the delay moment. Then, the theoretical pressure slope average value is determined based on each theoretical pressure slope. In this solution, if the absolute value of the difference between the actual pressure slope and the theoretical pressure slope at each delay moment within the target delay time is less than a first preset threshold, and the absolute value of the difference between each actual pressure slope and the average of the theoretical pressure slopes is less than a second preset threshold, then the actual pressure trend is consistent with the theoretical pressure trend, and the actual pressure stable following result is determined to be stable following. The first and second preset thresholds can be set as needed. By comparing the changing trends of the actual pressure of the target clutch with the theoretical pressure within the target delay time, the accuracy of clutch self-learning can be reliably guaranteed.

[0068] In this embodiment, optionally, the target clutch is controlled to perform self-learning at the target moment, including: determining the pressure compensation value of the theoretical pressure of the target clutch at the target moment based on the theoretical pressure, actual pressure and preset pressure step at each of the delay moments, and controlling the target clutch to perform self-learning based on the pressure compensation value.

[0069] Clutch self-learning does not directly compensate the actual clutch pressure to the theoretical pressure, but rather slowly increases the actual pressure to the theoretical pressure through learning. After determining that the actual pressure of the target clutch stably follows the theoretical pressure, this solution then determines the pressure compensation value for the theoretical pressure of the target clutch at the target moment based on the theoretical pressure, actual pressure, and preset pressure step size at each delay moment. Based on the mapping relationship between different clutch pressures and solenoid valve currents in the valve body project's end-of-life (EOL) data table, the solenoid valve current corresponding to the pressure compensation value for the theoretical pressure of the target clutch at the target moment is determined. Based on the solenoid valve current, the clutch pedal opening is controlled to self-learn the target clutch. The preset pressure step size can be set according to actual needs.

[0070] In the embodiment, optionally, the pressure compensation value of the target clutch at the target time is determined according to the theoretical pressure, the actual pressure and the preset pressure step of each delay time, comprising: determining the average theoretical pressure of the target clutch in the target delay time according to the theoretical pressure of each delay time; determining the average actual pressure of the target clutch in the target delay time according to the actual pressure of each delay time; and determining the pressure compensation value according to the average theoretical pressure, the average actual pressure and the preset pressure step.

[0071] In the embodiment, optionally, the pressure compensation value of the target clutch at the target time is determined according to the theoretical pressure, the actual pressure and the preset pressure step of each delay time, comprising: determining the average theoretical pressure of the target clutch in the target delay time according to the theoretical pressure of each delay time; determining the average actual pressure of the target clutch in the target delay time according to the actual pressure of each delay time; and determining the pressure compensation value according to the average theoretical pressure, the average actual pressure and the preset pressure step.

[0072] In the embodiment, optionally, the pressure compensation value of the target clutch at the target time is determined according to the theoretical pressure, the actual pressure and the preset pressure step of each delay time, comprising: determining the average theoretical pressure of the target clutch in the target delay time according to the theoretical pressure of each delay time; determining the average actual pressure of the target clutch in the target delay time according to the actual pressure of each delay time; and determining the pressure compensation value according to the average theoretical pressure, the average actual pressure and the preset pressure step.

[0073] In the embodiment, optionally, the pressure compensation value of the target clutch at the target time is determined according to the theoretical pressure, the actual pressure and the preset pressure step of each delay time, comprising: determining the average theoretical pressure of the target clutch in the target delay time according to the theoretical pressure of each delay time; determining the average actual pressure of the target clutch in the target delay time according to the actual pressure of each delay time; and determining the pressure compensation value according to the average theoretical pressure, the average actual pressure and the preset pressure step.

[0074] In the embodiment, optionally, the pressure compensation value of the target clutch at the target time is determined according to the theoretical pressure, the actual pressure and the preset pressure step of each delay time, comprising: determining the average theoretical pressure of the target clutch in the target delay time according to the theoretical pressure of each delay time; determining the average actual pressure of the target clutch in the target delay time according to the actual pressure of each delay time; and determining the pressure compensation value according to the average theoretical pressure, the average actual pressure and the preset pressure step.

[0075] If it is determined that the average pressure difference absolute value is less than the preset pressure step, the average pressure difference absolute value is taken as a pressure compensation value, a current corresponding to the average pressure difference absolute value is determined, the controller controls power to the electromagnetic valve, and the electromagnetic valve outputs pressure to compensate the actual pressure of the target clutch at the target moment. The problem of non-convergence and inaccuracy of self-learning of the clutch can be avoided.

[0076] The technical scheme of the embodiment of the application determines a current theoretical pressure of the target clutch at a current moment and a historical theoretical pressure of the target clutch at a historical moment, determines a theoretical pressure slope absolute value of the target clutch according to the current theoretical pressure and the historical theoretical pressure, determines a slope threshold value associated with the current theoretical pressure, prohibits self-learning of the target clutch if it is determined that the slope threshold value is less than the theoretical pressure slope absolute value, determines a target delay time according to the current theoretical pressure and an association relationship between the theoretical pressure and the delay time if it is determined that the slope threshold value is greater than or equal to the theoretical pressure slope absolute value, determines a target moment according to the current moment and the target delay time, determines an actual pressure and a theoretical pressure of the target clutch at each delay moment between the current moment and the target moment, determines a stable following result of the actual pressure according to the actual pressure and the theoretical pressure at each delay moment, and controls the target clutch to perform self-learning at the target moment if it is determined that the stable following result is stable following. By executing the scheme, the accuracy of self-learning of the clutch near the half-coupling point can be improved, and the driving stability coefficient can be improved, and the ride experience of the user can be improved.

[0077] Figure 3 is a structural schematic diagram of a clutch pressure self-learning device provided by the embodiment of the application. As shown in the figure, the device comprises: Figure 3

[0078] A current and historical theoretical pressure determination module 310 is configured to determine a current theoretical pressure of a target clutch at a current moment and determine a historical theoretical pressure of the target clutch at a historical moment, wherein the historical moment is determined based on the current moment and a preset period;

[0079] A theoretical pressure slope determination module 320 is configured to determine a theoretical pressure slope absolute value of the target clutch according to the current theoretical pressure and the historical theoretical pressure;

[0080] A slope threshold value determination module 330 is configured to determine a slope threshold value associated with the current theoretical pressure;

[0081] A first judgment module 340 is configured to prohibit self-learning of the target clutch if it is determined that the slope threshold value is less than the theoretical pressure slope absolute value;

[0082] ​The second judgment module 350 is configured to control the target clutch to perform self-learning if it is determined that the slope threshold is greater than or equal to the absolute value of the theoretical pressure slope.

[0083] Optionally, the device also includes a delay module, including a target delay time determination unit, which is used to determine the target delay time according to the current theoretical pressure, the correlation between the theoretical pressure and the delay time after determining that the slope threshold is greater than or equal to the absolute value of the theoretical pressure slope; a target moment determination unit, which is used to determine the target moment according to the current moment and the target delay time; an actual pressure and theoretical pressure determination unit, which is used to determine the actual pressure and theoretical pressure of the target clutch at the delay moment for each delay moment between the current moment and the target moment; a stable following result determination unit, which is used to determine the stable following result of the actual pressure according to the actual pressure and theoretical pressure at each delay moment; and a second judgment module 350, which is specifically used to control the target clutch to perform self-learning at the target moment if it is determined that the stable following result is stable following.

[0084] Optionally, the stable following result determination unit includes an actual pressure slope and theoretical pressure slope determination subunit, which is used to determine the actual pressure slope and theoretical pressure slope at each delay moment based on the actual pressure and theoretical pressure at each delay moment; a theoretical pressure slope average value determination subunit, which is used to determine the theoretical pressure slope average value based on each theoretical pressure slope; and a stable following result determination subunit, which is used to determine that the stable following result of the actual pressure is stable following if the absolute value of the difference between the actual pressure slope and the theoretical pressure slope at each delay moment is less than a first preset threshold, and the absolute value of the difference between each actual pressure slope and the theoretical pressure slope average value is less than a second preset threshold.

[0085] Optionally, the second judgment module 350 is specifically used to determine the pressure compensation value of the theoretical pressure of the target clutch at the target moment based on the theoretical pressure, actual pressure and preset pressure step at each of the delay moments, and control the target clutch to perform self-learning according to the pressure compensation value.

[0086] Optionally, the second judgment module 350 includes an average theoretical pressure determination subunit, which is used to determine the average theoretical pressure of the target clutch within the target delay time based on the theoretical pressure at each of the delay moments; an average actual pressure determination subunit, which is used to determine the average actual pressure of the target clutch within the target delay time based on the actual pressure at each of the delay moments; and a pressure compensation value determination subunit, which is used to determine the pressure compensation value based on the average theoretical pressure, the average actual pressure and the preset pressure step.

[0087] Optionally, a pressure compensation value determination subunit is specifically used to determine the absolute value of the average pressure difference based on the difference between the average theoretical pressure and the average actual pressure; if it is determined that the absolute value of the average pressure difference is greater than the preset pressure step, the preset pressure step is used as the pressure compensation value.

[0088] Optionally, the pressure compensation value determination subunit is further specifically used to, after determining the average pressure difference based on the difference between the average theoretical pressure and the average actual pressure, use the absolute value of the average pressure difference as the pressure compensation value if it is determined that the absolute value of the average pressure difference is less than or equal to the preset pressure step.

[0089] The clutch pressure self-learning device provided in the embodiment of the present invention can execute the clutch pressure self-learning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0090] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0091] like Figure 4 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., which is communicatively connected to the at least one processor 41. The memory stores a computer program that can be executed by the at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 into the random access memory (RAM) 43. Various programs and data required for the operation of the electronic device 40 can also be stored in the RAM 43. The processor 41, ROM 42, and RAM 43 are connected to each other via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0092] Multiple components in the electronic device 40 are connected to the I / O interface 45, including an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a magnetic disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0093] Processor 41 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 41 executes the various methods and processes described above, such as the clutch pressure self-learning method.

[0094] In some embodiments, the clutch pressure self-learning method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the clutch pressure self-learning method described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to execute the clutch pressure self-learning method in any other suitable manner (e.g., via firmware).

[0095] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package and partially on a remote machine or entirely on a remote machine or server.

[0097] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0099] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0100] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0101] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0102] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A clutch pressure self-learning method, characterized in that: include: determining a current theoretical pressure of a target clutch at a current moment, and determining a historical theoretical pressure of the target clutch at a historical moment; The historical moment is determined based on the current moment and a preset period; determining an absolute value of a theoretical pressure slope of the target clutch according to the current theoretical pressure and the historical theoretical pressure; determining a slope threshold associated with the current theoretical pressure; If it is determined that the slope threshold is less than the theoretical pressure slope absolute value, prohibiting the target clutch from performing self-learning; If it is determined that the slope threshold is greater than or equal to the theoretical pressure slope absolute value, controlling the target clutch to perform self-learning; After determining that the slope threshold is greater than or equal to the theoretical pressure slope absolute value, the method further includes: determining a target delay time according to the current theoretical pressure and a correlation between the theoretical pressure and the delay time; Determine a target time according to the current time and the target delay time; For each delayed moment between the current moment and the target moment, determining the actual pressure and the theoretical pressure of the target clutch at the delayed moment; Determining a stable following result of the actual pressure according to the actual pressure at each of the delay moments and the theoretical pressure; Controlling the target clutch to perform self-learning includes: If it is determined that the stable following result is stable following, controlling the target clutch to perform self-learning at the target time; The step of determining the stable following result of the actual pressure according to the actual pressure at each of the delay moments and the theoretical pressure includes: Determining the actual pressure slope and the theoretical pressure slope at each delay moment according to the actual pressure and the theoretical pressure at each delay moment; Determining a theoretical pressure slope average value based on each of the theoretical pressure slopes; If the absolute value of the difference between the actual pressure slope and the theoretical pressure slope at each of the delay moments is less than a first preset threshold, and the absolute value of the difference between each of the actual pressure slopes and the average value of the theoretical pressure slopes is less than a second preset threshold, then the stable following result of the actual pressure is determined to be stable following.

2. The method according to claim 1, characterized in that Controlling the target clutch to perform self-learning at the target time includes: According to the theoretical pressure, actual pressure and preset pressure step at each of the delay moments, a pressure compensation value of the theoretical pressure of the target clutch at the target moment is determined, and the target clutch is controlled to perform self-learning according to the pressure compensation value.

3. The method according to claim 2, characterized in that Determining a pressure compensation value of the theoretical pressure of the target clutch at the target moment according to the theoretical pressure, the actual pressure, and the preset pressure step at each of the delay moments includes: determining an average theoretical pressure of the target clutch within a target delay time according to the theoretical pressure at each delay moment; determining an average actual pressure of the target clutch within the target delay time according to the actual pressure at each delay moment; The pressure compensation value is determined according to the average theoretical pressure, the average actual pressure, and a preset pressure step.

4. The method according to claim 3, characterized in that Determining the pressure compensation value according to the average theoretical pressure, the average actual pressure, and a preset pressure step size includes: Determining an absolute value of an average pressure difference according to a difference between the average theoretical pressure and the average actual pressure; If it is determined that the absolute value of the average pressure difference is greater than the preset pressure step length, the preset pressure step length is used as the pressure compensation value.

5. The method according to claim 4, further comprising, after determining the average pressure difference according to the difference between the average theoretical pressure and the average actual pressure: If it is determined that the absolute value of the average pressure difference is less than or equal to the preset pressure step, the absolute value of the average pressure difference is used as the pressure compensation value.

6. A clutch pressure self-learning device, characterized in that: include: a current and historical theoretical pressure determination module, configured to determine a current theoretical pressure of a target clutch at a current moment, and determine a historical theoretical pressure of the target clutch at a historical moment; The historical moment is determined based on the current moment and a preset period; a theoretical pressure slope determination module, configured to determine an absolute value of a theoretical pressure slope of the target clutch according to the current theoretical pressure and the historical theoretical pressure; a slope threshold determination module, configured to determine a slope threshold associated with the current theoretical pressure; a first judgment module, configured to prohibit the target clutch from performing self-learning if it is determined that the slope threshold is less than the theoretical pressure slope absolute value; a second judgment module, configured to control the target clutch to perform self-learning if it is determined that the slope threshold is greater than or equal to the theoretical pressure slope absolute value; The device further comprises: a delay module, comprising a target delay time determining unit, for determining the target delay time according to the current theoretical pressure, the correlation between the theoretical pressure and the delay time after determining that the slope threshold is greater than or equal to the absolute value of the theoretical pressure slope; a target moment determining unit, for determining the target moment according to the current moment and the target delay time; an actual pressure and theoretical pressure determining unit, for determining, for each delay moment between the current moment and the target moment, the actual pressure and theoretical pressure of the target clutch at the delay moment; a stable following result determining unit, for determining a stable following result of the actual pressure according to the actual pressure and theoretical pressure at each delay moment; a second judgment module, specifically for controlling the target clutch to perform self-learning at the target moment if it is determined that the stable following result is stable following; The stable following result determination unit includes an actual pressure slope and theoretical pressure slope determination subunit, which is used to determine the actual pressure slope and theoretical pressure slope at each delay moment based on the actual pressure and theoretical pressure at each delay moment; a theoretical pressure slope average value determination subunit, which is used to determine the theoretical pressure slope average value based on each theoretical pressure slope; and a stable following result determination subunit, which is used to determine that the stable following result of the actual pressure is stable following if the absolute value of the difference between the actual pressure slope and the theoretical pressure slope at each delay moment is less than a first preset threshold, and the absolute value of the difference between each actual pressure slope and the theoretical pressure slope average value is less than a second preset threshold.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the clutch pressure self-learning method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the clutch pressure self-learning method according to any one of claims 1 to 5 when executed.

Images