Clutch half-engagement point self-learning method and device, electronic equipment and storage medium
By dynamically acquiring multi-source data in the AMT automatic transmission and performing self-learning of the clutch half-engagement point, the problem of inaccurate clutch half-engagement point control during vehicle dynamic driving is solved, improving the comfort of vehicle starting and shifting processes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FAW JIEFANG AUTOMOTIVE CO
- Filing Date
- 2026-05-14
- Publication Date
- 2026-07-14
AI Technical Summary
Existing AMT automatic transmissions have difficulty accurately controlling the clutch half-engagement point during vehicle dynamic driving, affecting the comfort of vehicle starting and shifting.
By acquiring multi-source data sets and performing multi-level judgments, the system dynamically determines whether the vehicle meets the clutch self-learning conditions. Then, during vehicle operation, it executes the clutch half-engagement point self-learning action to obtain a self-learning value that is more consistent with the actual vehicle's dynamic operating state.
It improves the accuracy of clutch control, enhances the comfort of vehicle starting and shifting, and reduces errors caused by static self-learning and user parking operations.
Smart Images
Figure CN122379554A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle technology, and in particular to a clutch half-engagement point self-learning method, device, electronic device, and storage medium. Background Technology
[0002] The existing AMT automatic transmission is developed from the MT manual transmission by adding various sensors, transmission control unit, electronically controlled shifting mechanism and clutch actuator. Compared with other automatic transmission solutions, it has the advantages of low cost and high transmission efficiency.
[0003] Using pneumatic shift actuators effectively prevents environmental pollution caused by oil leakage from hydraulic actuators. Furthermore, the control medium is air, resulting in lower actuator costs. Therefore, most mainstream AMT automatic transmissions currently employ electronically controlled pneumatic shift actuators. During the automatic transmission shifting process, the TCU controls the shift solenoid valve to open the air circuit, allowing working air to enter the actuator and drive the cylinder piston. This, in turn, drives the connected shift fork, pushing or shifting the shift sleeve to the target gear position.
[0004] Sales of tractor trucks in my country have maintained steady growth year by year along with the development of industries such as logistics. However, the number of trucks equipped with AMT transmissions is far lower than that equipped with manual transmissions. In developed countries such as Europe and the United States, AMT transmissions are already standard equipment on tractor trucks. In recent years, sales of tractor trucks equipped with AMT transmissions in my country have shown steady growth. Therefore, there is a large market potential for AMT transmissions in my country's tractor truck market.
[0005] With the increasing popularity of AMT transmissions, drivers' demands for vehicle comfort are also gradually increasing. Comfort is closely related to the accurate control of the clutch during vehicle start-up and gear shifting. The clutch half-engagement point position is the primary key factor determining the smoothness of clutch control. Therefore, AMT must be able to obtain the most accurate clutch half-engagement point under the most suitable vehicle dynamic operating conditions, thereby ensuring the accuracy of clutch control during start-up and gear shifting. Existing technologies find it difficult to achieve the above goals. Summary of the Invention
[0006] The purpose of this invention is to provide a clutch half-engagement point self-learning method, device, electronic device, and storage medium, which enables the vehicle to perform clutch half-engagement point self-learning under specific conditions during dynamic driving. This helps to ensure that the self-learning value is more consistent with the actual dynamic operating state of the vehicle, making the clutch control during starting and shifting more accurate, thereby improving the overall vehicle comfort.
[0007] To address the aforementioned technical problems, in a first aspect, the present invention provides a clutch half-engagement point self-learning method, comprising at least:
[0008] At least a first vehicle multi-source data set is acquired, and at least based on the first vehicle multi-source data set, it is determined whether the vehicle meets the basic entry conditions for clutch self-learning.
[0009] When the vehicle meets the basic entry conditions for clutch self-learning, at least a second vehicle multi-source data set is acquired, and at least based on the second vehicle multi-source data set, it is determined whether the vehicle meets the necessary entry conditions for clutch self-learning.
[0010] When the vehicle meets the necessary entry conditions for the clutch self-learning, at least a third vehicle multi-source data set is acquired, and at least based on the third vehicle multi-source data set, it is determined whether the vehicle meets the trigger entry conditions for the clutch self-learning.
[0011] When the vehicle meets the triggering entry condition of the clutch self-learning, the preset clutch half-engagement point self-learning action is performed at least during vehicle operation.
[0012] Optionally, the first vehicle multi-source data set includes at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road slope.
[0013] Optionally, the second vehicle multi-source data set includes at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the current gear of the vehicle, the engine speed, and the vehicle's starting status.
[0014] Optionally, the third vehicle multi-source data group includes at least the vehicle's current gear, the vehicle's gear at the previous moment, the cumulative mileage value after the vehicle's clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed.
[0015] Based on the same concept, in a second aspect, the present invention also provides a clutch half-engagement point self-learning device for performing the clutch half-engagement point self-learning method described in any one of the first aspects.
[0016] The clutch half-engagement point self-learning device includes at least:
[0017] The first judgment module is used to acquire at least a first vehicle multi-source data set, and at least based on the first vehicle multi-source data set, determine whether the vehicle meets the basic entry conditions for clutch self-learning.
[0018] The second judgment module is used to acquire at least a second vehicle multi-source data set when the vehicle meets the basic entry conditions for clutch self-learning, and to determine whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set.
[0019] The third judgment module is used to acquire at least a third vehicle multi-source data set when the vehicle meets the necessary entry conditions for the clutch self-learning, and to determine whether the vehicle meets the trigger entry conditions for the clutch self-learning based at least on the third vehicle multi-source data set.
[0020] The self-learning module is used to perform a preset clutch half-engagement point self-learning action at least during vehicle operation when the vehicle meets the triggering entry condition of the clutch self-learning.
[0021] Optionally, the first vehicle multi-source data set includes at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road slope.
[0022] Optionally, the second vehicle multi-source data set includes at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the current gear of the vehicle, the engine speed, and the vehicle's starting status.
[0023] Optionally, the third vehicle multi-source data group includes at least the vehicle's current gear, the vehicle's gear at the previous moment, the cumulative mileage value after the vehicle's clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed.
[0024] Based on the same concept, in a third aspect, the present invention also provides an electronic device including a memory and a processor, the memory storing a computer program executable on the processor, the processor executing the program to implement the steps of the clutch half-engagement point self-learning method according to any one of the first aspects.
[0025] Based on the same concept, in a fourth aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the clutch half-engagement point self-learning method described in any of the first aspects.
[0026] The technical solution provided by this invention firstly acquires at least a first vehicle multi-source data set, and determines whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set; further, when the vehicle meets the basic entry conditions for clutch self-learning, at least a second vehicle multi-source data set is acquired, and determines whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set; further, when the vehicle meets the necessary entry conditions for clutch self-learning, at least a third vehicle multi-source data set is acquired, and determines whether the vehicle meets the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set; finally, when the vehicle meets the trigger entry conditions for clutch self-learning, a preset clutch half-engagement point self-learning action is performed at least during vehicle operation.
[0027] Therefore, the embodiments of the present invention enable the vehicle to perform clutch half-engagement point self-learning under specific conditions during dynamic driving, which helps to ensure that the self-learning value is more consistent with the actual dynamic operation of the vehicle, making the clutch control during starting and shifting more accurate, thereby improving the overall vehicle comfort. Attached Figure Description
[0028] Figure 1 This is a flowchart of a clutch half-engagement point self-learning method provided in an embodiment of the present invention;
[0029] Figure 2 This is a schematic diagram of the structure of a clutch half-engagement point self-learning device provided in an embodiment of the present invention;
[0030] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention;
[0031] Figure 4 This is a schematic diagram of a self-learning process of the clutch half-engagement point during vehicle operation, provided by an embodiment of the present invention. Detailed Implementation
[0032] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0033] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.
[0034] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.
[0035] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.
[0036] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”
[0037] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.
[0038] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.
[0039] Figure 1This is a flowchart of a clutch half-engagement point self-learning method provided by an embodiment of the present invention. This embodiment is applicable to at least any vehicle's automatic transmission clutch half-engagement point self-learning scenario (applicable to, but not limited to, commercial vehicles, engineering vehicles, and passenger vehicles; also not limited to automatic transmissions connected to the engine such as AT, AMT, DCT, CVT, DHT, ECVT, or transmissions with an electric motor as an optional drive power source; also not limited to vehicles driven by traditional gasoline and diesel engines, hybrid vehicles, and pure electric vehicles). This clutch half-engagement point self-learning method can be, but is not limited to, executed by the clutch half-engagement point self-learning device in this embodiment of the present invention as the execution subject, which can be implemented in software and / or hardware. Figure 1 As shown, the clutch half-engagement point self-learning method includes at least the following steps:
[0040] S1. Obtain at least the first vehicle multi-source data set, and determine whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set.
[0041] The first vehicle multi-source data set may include multiple data items. In one specific embodiment, the first vehicle multi-source data set may optionally include at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road gradient.
[0042] For example, the aforementioned step S1 can be specifically described as follows:
[0043] The system acquires battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road gradient via sensors and / or CAN bus. When the battery voltage meets the normal operating voltage limits, the vehicle main air pressure is not lower than the minimum operating air pressure, the output shaft speed is not lower than the minimum dynamic driving speed (e.g., not lower than the minimum output shaft speed allowed for coasting in neutral), the handbrake signal is released, the transmission oil temperature is not lower than the minimum operating temperature, and the road gradient is within the gradient range allowed for self-learning activation, i.e., when all the above conditions are met simultaneously, the vehicle is determined to meet the basic entry conditions for clutch dynamic self-learning. Conversely, if any of the above conditions are not met, the vehicle is determined not to meet the basic entry conditions for clutch dynamic self-learning.
[0044] S2. When the vehicle meets the basic entry conditions for clutch self-learning, at least the second vehicle multi-source data set is acquired, and the vehicle is judged to meet the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set.
[0045] The second vehicle multi-source data set may also consist of multiple data items. In another specific implementation, the second vehicle multi-source data set may optionally include at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the vehicle's current gear, engine speed, and vehicle starting status.
[0046] For example, the aforementioned step S2 can be specifically described as follows:
[0047] Provided that the basic entry conditions described in step S1 are met, if the requested gear of the automatic transmission is not neutral, the current gear is not neutral, the requested gear is equal to the current gear, the engine speed is between the set minimum and maximum speeds (the minimum speed can be below idle speed but above the engine shutdown protection speed, and the maximum speed can be above idle speed but below the upshift point), and the vehicle is not in a state of starting with the accelerator pedal pressed or automatically starting without pressing the accelerator pedal, then the vehicle is determined to have met the necessary entry conditions for clutch self-learning. Simultaneously, after the vehicle meets the necessary entry conditions for clutch self-learning, the maximum and minimum torques during engine operation are recorded. If the difference between the recorded maximum and minimum engine torques exceeds a set torque difference threshold, then even if the vehicle meets the necessary entry conditions for clutch self-learning, it is considered invalid until the vehicle is parked and returned to neutral, at which point the judgment process in step S2 is restarted.
[0048] S3. When the vehicle meets the necessary entry conditions for clutch self-learning, at least a third vehicle multi-source data set is acquired, and the vehicle is judged to meet the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set.
[0049] The third vehicle multi-source data set can also consist of multiple data points. In another specific implementation, optionally, the third vehicle multi-source data set includes at least the vehicle's current gear, the vehicle's previous gear, the cumulative mileage since the clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed. It is understood that the second and third vehicle multi-source data sets can also be obtained through sensors and / or the CAN bus; the trigger entry conditions may include a first trigger entry sub-condition and a second trigger entry sub-condition.
[0050] For example, the aforementioned step S3 can be specifically described as follows:
[0051] Provided that the necessary entry conditions described in step S2 are met, if the vehicle was in neutral at the previous moment and is not in neutral at the current moment, that is, the vehicle exits from coasting in neutral, then the vehicle is determined to meet the first trigger entry sub-condition. The first trigger entry sub-condition will only be reset after the self-learning is completed or failed once it is met. Furthermore, if the vehicle re-enters coasting in neutral, the current gear changes from non-neutral to neutral, the engine speed drops to idle speed, and the cumulative mileage value after the clutch half-engagement self-learning during the last triggered driving reaches the set mileage threshold, then the vehicle is determined to meet the second trigger entry sub-condition.
[0052] S4. When the vehicle meets the triggering conditions for clutch self-learning, the preset clutch half-engagement point self-learning action shall be performed at least during vehicle operation.
[0053] If the first trigger entry sub-condition and the second trigger entry sub-condition are met simultaneously, the vehicle is determined to meet the trigger entry conditions for clutch self-learning, and step S4 is executed.
[0054] For example, the self-learning action of preset clutch half-engagement point may specifically include:
[0055] (4-1) Detect whether the clutch is fully open, for example, by obtaining the actual clutch position x through the clutch displacement sensor; if the actual clutch position x is not less than the set fully open position x1, then the clutch is determined to be fully open; otherwise, it is determined that the clutch is not fully disengaged, and the clutch is controlled to disengage at the set rapid disengagement rate dx1 so that the actual clutch position x is not lower than the clutch release position x2. Here, the clutch release position x2 is slightly lower than the fully open position x1. The deviation between the two depends on the distance that the clutch actuator continues to disengage on its own due to its own mechanical hysteresis after the control is stopped when x2 is the closed-loop control target. x1 can be specifically the disengagement position that ensures that the driven plate will not rotate with the pressure plate when the pressure plate rotates during the clutch disengagement process due to the adhesion between the clutch pressure plate and the driven plate.
[0056] (4-2) Clutch engagement control condition judgment: As determined in step (4-1), the clutch should be fully open, and the triggering entry condition for clutch half-engagement point self-learning during vehicle movement involved in step S3 is met. Furthermore, the input shaft speed is less than the speed threshold n1 for half-engagement point self-learning, and the engine torque is less than the torque threshold tq1 for half-engagement point self-learning. After all the above conditions are met and a set time threshold t1 is reached, it is determined that the vehicle meets the control conditions for clutch engagement. It can be understood that the aforementioned speed threshold n1 for half-engagement point self-learning is at least not lower than idle speed, but lower than idle speed plus a set offset value (e.g., 1100 rpm); the aforementioned torque threshold tq1 for half-engagement point self-learning is at least not lower than the engine idle torque during neutral coasting, but not higher than the idle torque plus a preset offset value (e.g., 70 Nm ~ 250 Nm).
[0057] (4-3) Clutch engagement control
[0058] 1) First-stage control
[0059] Record the input shaft speed nstart when the clutch begins to engage, and control the clutch to engage according to the target position xtg=x+dx2*dt, where dx2 represents the clutch engagement rate set by the clutch self-learning during driving, and dt represents the calculation step size; if the actual clutch position x is less than the set estimated half-engagement point xest, or the absolute value of the difference between the actual clutch position x and the old value of the half-engagement point position stored at the current clutch temperature xct is less than the set difference Δx1, then the first stage of clutch engagement control ends.
[0060] 2) Second-stage control
[0061] After the first stage of clutch engagement control is completed, the second stage of control begins, controlling the clutch to engage according to the target position xtg=x+dx3*dt, where dx3 represents the clutch engagement rate set by the clutch self-learning during driving in the second stage, and dt represents the calculation step size; in addition, the absolute value of dx3 is less than the absolute value of dx2, for example, the absolute value of dx2 is 10 times the absolute value of dx3.
[0062] Figure 4 This is a schematic diagram of a clutch half-engagement point self-learning process during vehicle operation provided by an embodiment of the present invention. The above process can be described as follows: Figure 4 As shown.
[0063] (4-4) Torque observation near the clutch half-engagement point based on engine torque
[0064] After the triggering conditions for self-learning the clutch half-engagement point during vehicle operation involved in step S3 above are met, torque observation near the clutch half-engagement point based on engine torque begins. Timing starts from the moment the observation begins. When the timing reaches the confirmation duration t2, a flag indicating that the average engine torque calculation is complete is issued. Before reaching (t2-Δt), no operation is performed on the observed engine torque. When (t2-Δt) is reached, the observed engine torque value at each moment is accumulated: Engtq=∫engtqdt. When t2 is reached, this accumulated value is recorded, and the average value of the engine torque is calculated from (t2-Δt) to t2, which is used as the torque observation value near the clutch half-engagement point based on engine torque, i.e., cluthtq=Engtq / Δt, until cluthtq is locked when t2 is reached.
[0065] (4-5) Learning the new temporary half-engagement point of the clutch
[0066] During the clutch engagement control phase, if the current input shaft speed ncrut is lower than the set threshold Δn by nstart, and the absolute value of the input shaft deceleration slope is greater than the preset rate threshold, and the engine torque average calculation completion flag is true, and the difference between the current engine torque and the torque observation value cluthtq near the clutch half-engagement point based on the engine torque is less than the preset threshold Δtq, then the actual clutch position at this moment is recorded as the new temporary half-engagement point position Xnew0, a new temporary half-engagement point learning completion flag is issued, and the clutch is fully engaged in open-loop control.
[0067] (4-6) Clutch half-engagement point preservation
[0068] If the difference between the new temporary clutch half-engagement position Xnew0 and the old clutch half-engagement position xct stored at the current clutch temperature is less than a preset value, and the new temporary clutch half-engagement position Xnew0 is less than the difference between the set maximum clutch position and the clutch opening offset value, and the new temporary clutch half-engagement position Xnew0 is greater than the minimum half-engagement limit value, then the updated clutch half-engagement position Xnew, calculated using Xnew = Xnew0*k1 + xct*(1-k1), is used to overwrite the old clutch half-engagement position stored at the current clutch temperature. It can be understood that the coefficient k1 represents the weighting coefficient calculated based at least on the new temporary clutch half-engagement position Xnew0 and the old clutch half-engagement position xct.
[0069] The technical solution provided in this embodiment firstly acquires at least a first vehicle multi-source data set, and determines whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set; further, when the vehicle meets the basic entry conditions for clutch self-learning, at least a second vehicle multi-source data set is acquired, and determines whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set; further, when the vehicle meets the necessary entry conditions for clutch self-learning, at least a third vehicle multi-source data set is acquired, and determines whether the vehicle meets the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set; finally, when the vehicle meets the trigger entry conditions for clutch self-learning, a preset clutch half-engagement point self-learning action is performed at least during vehicle operation.
[0070] Therefore, this embodiment enables the vehicle to perform clutch half-engagement point self-learning under specific conditions during dynamic driving, which helps to ensure that the self-learning value is more consistent with the actual vehicle dynamic operation state, making the clutch control during starting and shifting more accurate, thereby improving the overall vehicle comfort.
[0071] It should be noted that the embodiments of the present invention provide at least one method and flowchart for self-learning the clutch half-engagement point during vehicle operation. Most existing technologies utilize the half-engagement point learned under static conditions as the starting half-engagement point. Dry clutches, due to wear or manufacturing inconsistencies, may experience changes or differences in the half-engagement point position. Static self-learning is often performed when the vehicle has just started or stopped, which differs from the clutch temperature and environmental conditions of a running vehicle. Therefore, performing half-engagement point self-learning during dynamic driving can obtain a self-learning value that more closely matches the actual vehicle operating state, making clutch control more accurate. Furthermore, dynamic learning can reduce unnecessary stopping operations, decrease the number and duration of user stops, and improve driving efficiency.
[0072] Figure 2 This is a schematic diagram of a clutch half-engagement point self-learning device provided in an embodiment of the present invention. This embodiment is applicable to at least any vehicle's automatic transmission clutch half-engagement point self-learning scenario. This clutch half-engagement point self-learning device can be implemented using software and / or hardware. Figure 2 As shown, the clutch half-engagement point self-learning device includes at least:
[0073] The first judgment module 110 is used to acquire at least the first vehicle multi-source data set and determine whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set.
[0074] The second judgment module 120 is used to acquire at least a second vehicle multi-source data set when the vehicle meets the basic entry conditions for clutch self-learning, and to judge whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set.
[0075] The third judgment module 130 is used to acquire at least a third vehicle multi-source data set when the vehicle meets the necessary entry conditions for clutch self-learning, and to determine whether the vehicle meets the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set.
[0076] The self-learning module 140 is used to perform a preset clutch half-engagement point self-learning action at least during vehicle operation when the vehicle meets the triggering conditions for clutch self-learning.
[0077] Optionally, the first vehicle multi-source data set includes at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road gradient.
[0078] Optionally, the second vehicle multi-source data set includes at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the vehicle's current gear, engine speed, and vehicle start-up status.
[0079] Optionally, the third vehicle multi-source data set includes at least the vehicle's current gear, the vehicle's gear at the previous moment, the cumulative mileage value after the vehicle's clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed.
[0080] The technical solution provided in this embodiment firstly acquires at least a first vehicle multi-source data set through a first judgment module, and determines whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set; further, when the vehicle meets the basic entry conditions for clutch self-learning, the second judgment module acquires at least a second vehicle multi-source data set, and determines whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set; further, when the vehicle meets the necessary entry conditions for clutch self-learning, the third judgment module acquires at least a third vehicle multi-source data set, and determines whether the vehicle meets the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set; finally, when the vehicle meets the trigger entry conditions for clutch self-learning, the self-learning module executes a preset clutch half-engagement point self-learning action at least during vehicle operation.
[0081] Therefore, this embodiment enables the vehicle to perform clutch half-engagement point self-learning under specific conditions during dynamic driving, which helps to ensure that the self-learning value is more consistent with the actual vehicle dynamic operation state, making the clutch control during starting and shifting more accurate, thereby improving the overall vehicle comfort.
[0082] This embodiment provides an electronic device. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. See also: Figure 3 The electronic device 1000 includes a processor 1001 and a memory 1002. The memory 1002 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 1001, the steps in any of the above clutch half-engagement point self-learning methods are performed. Through the above technical solution, the processor 1001 and the memory 1002 are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanism (not shown). The memory 1002 stores a computer program that can be executed by the processor. When the electronic device 1000 is running, the processor 1001 executes the computer program to execute the clutch half-engagement point self-learning method in any optional implementation of the above embodiments, so as to at least achieve the following functions: at least acquire a first vehicle multi-source data set, and at least determine whether the vehicle meets the basic entry conditions for clutch self-learning based on the first vehicle multi-source data set; when the vehicle meets the basic entry conditions for clutch self-learning, at least acquire a second vehicle multi-source data set, and at least determine whether the vehicle meets the necessary entry conditions for clutch self-learning based on the second vehicle multi-source data set; when the vehicle meets the necessary entry conditions for clutch self-learning, at least acquire a third vehicle multi-source data set, and at least determine whether the vehicle meets the trigger entry conditions for clutch self-learning based on the third vehicle multi-source data set; when the vehicle meets the trigger entry conditions for clutch self-learning, at least execute a preset clutch half-engagement point self-learning action during vehicle operation.
[0083] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the clutch half-engagement point self-learning method as provided in all embodiments of this application: acquiring at least a first vehicle multi-source data set, and determining whether the vehicle meets the basic entry conditions for clutch self-learning based at least on the first vehicle multi-source data set; when the vehicle meets the basic entry conditions for clutch self-learning, acquiring at least a second vehicle multi-source data set, and determining whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set; when the vehicle meets the necessary entry conditions for clutch self-learning, acquiring at least a third vehicle multi-source data set, and determining whether the vehicle meets the trigger entry conditions for clutch self-learning based at least on the third vehicle multi-source data set; when the vehicle meets the trigger entry conditions for clutch self-learning, performing a preset clutch half-engagement point self-learning action at least during vehicle operation.
[0084] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.
[0085] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.
[0086] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.
[0087] Computer program code for performing the operations of this invention can be written in one or more programming languages or a combination thereof. Programming languages include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. A self-learning method for clutch half-engagement point, characterized in that, At least including: At least a first vehicle multi-source data set is acquired, and at least based on the first vehicle multi-source data set, it is determined whether the vehicle meets the basic entry conditions for clutch self-learning. When the vehicle meets the basic entry conditions for clutch self-learning, at least a second vehicle multi-source data set is acquired, and at least based on the second vehicle multi-source data set, it is determined whether the vehicle meets the necessary entry conditions for clutch self-learning. When the vehicle meets the necessary entry conditions for the clutch self-learning, at least a third vehicle multi-source data set is acquired, and at least based on the third vehicle multi-source data set, it is determined whether the vehicle meets the trigger entry conditions for the clutch self-learning. When the vehicle meets the triggering entry condition of the clutch self-learning, the preset clutch half-engagement point self-learning action is performed at least during vehicle operation.
2. The clutch half-engagement point self-learning method according to claim 1, characterized in that, The first vehicle multi-source data group includes at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road slope.
3. The clutch half-engagement point self-learning method according to claim 1, characterized in that, The second vehicle multi-source data set includes at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the vehicle's current gear, engine speed, and vehicle start-up status.
4. The clutch half-engagement point self-learning method according to claim 1, characterized in that, The third vehicle multi-source data group includes at least the vehicle's current gear, the vehicle's gear at the previous moment, the cumulative mileage value after the vehicle's clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed.
5. A clutch half-engagement point self-learning device, characterized in that, Used to perform the clutch half-engagement point self-learning method according to any one of claims 1-4; The clutch half-engagement point self-learning device includes at least: The first judgment module is used to acquire at least a first vehicle multi-source data set, and at least based on the first vehicle multi-source data set, determine whether the vehicle meets the basic entry conditions for clutch self-learning. The second judgment module is used to acquire at least a second vehicle multi-source data set when the vehicle meets the basic entry conditions for clutch self-learning, and to determine whether the vehicle meets the necessary entry conditions for clutch self-learning based at least on the second vehicle multi-source data set. The third judgment module is used to acquire at least a third vehicle multi-source data set when the vehicle meets the necessary entry conditions for the clutch self-learning, and to determine whether the vehicle meets the trigger entry conditions for the clutch self-learning based at least on the third vehicle multi-source data set. The self-learning module is used to perform a preset clutch half-engagement point self-learning action at least during vehicle operation when the vehicle meets the triggering entry condition of the clutch self-learning.
6. The clutch half-engagement point self-learning device according to claim 5, characterized in that, The first vehicle multi-source data group includes at least the battery voltage, vehicle main air pressure, output shaft speed, handbrake signal, transmission oil temperature, and road slope.
7. The clutch half-engagement point self-learning device according to claim 5, characterized in that, The second vehicle multi-source data set includes at least the requested gear of the automatic transmission, the maximum and minimum torque during engine operation, the vehicle's current gear, engine speed, and vehicle start-up status.
8. The clutch half-engagement point self-learning device according to claim 5, characterized in that, The third vehicle multi-source data group includes at least the vehicle's current gear, the vehicle's gear at the previous moment, the cumulative mileage value after the vehicle's clutch half-engagement self-learning during the last triggered driving, the vehicle's coasting state, and the engine speed.
9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the clutch half-engagement point self-learning method according to any one of claims 1-4.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the clutch half-engagement point self-learning method according to any one of claims 1-4.