Clutch self-learning method, device, and vehicle

Abstract

The disclosed embodiments relate to a clutch self-learning method, device, and vehicle, wherein the method includes: identifying whether the vehicle satisfies a preset vehicle state self-learning condition; when the vehicle satisfies the preset vehicle state self-learning condition, identifying whether the vehicle satisfies a preset parking condition; when the preset parking condition is satisfied, identifying whether the vehicle satisfies a driver departure condition; when the driver departure condition is satisfied, identifying whether the vehicle satisfies a preset self-learning drive mode; when the preset self-learning drive mode is satisfied, controlling the clutch in the vehicle to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation for the control current of the solenoid valve of the clutch in the vehicle and / or to perform time compensation for the oil filling time of the clutch in the vehicle. In this technical solution, the user's perception of self-learning is reduced, and the user experience is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of vehicle control technology, and in particular to a clutch self-learning method, device, and vehicle. Background Art

[0002] With the development of intelligent driving technology, users are increasingly demanding the use and operation of intelligent driving vehicles. Currently, vehicles equipped with intelligent driving technology are primarily hybrid vehicles or new energy vehicles, with some electric vehicles also utilizing intelligent driving technology. As intelligent driving technology matures, the market share of vehicles equipped with intelligent driving features is also gradually increasing. Consequently, the workload of clutch calibration before a vehicle is put into operation is also increasing. To shorten the time it takes for a vehicle to be put into operation, clutch self-learning is becoming increasingly common after the vehicle is put into operation.

[0003] In related technologies, when the self-learning clutch performs pressure control, the entire vehicle may feel something, such as slight abnormal noises, which reduces the user experience. Summary of the Invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a clutch self-learning method, device, and vehicle.

[0005] An embodiment of the present disclosure provides a self-learning method for a clutch, the method comprising: identifying whether a vehicle satisfies a preset vehicle state self-learning condition; when the vehicle satisfies the preset vehicle state self-learning condition, identifying whether the vehicle satisfies a preset parking condition; when the preset parking condition is satisfied, identifying whether the vehicle satisfies a driver departure condition; when the driver departure condition is satisfied, identifying whether the vehicle satisfies a preset self-learning driving mode; when the preset self-learning driving mode is satisfied, controlling the clutch in the vehicle to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation on the oil filling time of the clutch in the vehicle.

[0006] An embodiment of the present disclosure also provides a self-learning device for a clutch, the device comprising: a first identification module for identifying whether a vehicle satisfies a preset vehicle state self-learning condition; a second identification module for identifying whether the vehicle satisfies a preset parking condition when the vehicle satisfies the preset vehicle state self-learning condition; a third identification module for identifying whether the vehicle satisfies a driver departure condition when the preset parking condition is satisfied; a fourth identification module for identifying whether the vehicle satisfies a preset self-learning driving mode when the driver departure condition is satisfied; a self-learning control module for controlling the clutch in the vehicle to perform self-learning to obtain a self-learning result when the preset self-learning driving mode is satisfied, wherein the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation on the oil filling time of the clutch in the vehicle.

[0007] An embodiment of the present disclosure also provides a vehicle, comprising: a processor; a memory for storing executable instructions of the processor; the processor for reading the executable instructions from the memory and executing the instructions to implement the self-learning method of the clutch provided in the embodiment of the present disclosure.

[0008] The technical solution provided by the embodiments of the present disclosure has the following advantages over the prior art:

[0009] The clutch self-learning scheme provided by the embodiment of the present disclosure identifies whether the vehicle meets the preset vehicle state self-learning conditions. When the vehicle meets the preset vehicle state self-learning conditions, it identifies whether the vehicle meets the preset parking conditions. When the preset parking conditions are met, it identifies whether the vehicle meets the driver's departure conditions. When the driver's departure conditions are met, it identifies whether the vehicle meets the preset self-learning driving mode. Then, when the preset self-learning driving mode is met, the clutch in the vehicle is controlled to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation for the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation for the oil filling time of the clutch in the vehicle. In this technical solution, the safety of the vehicle during self-learning is improved, the user's perception of self-learning is reduced, and the user experience is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0011] Figure 1 A schematic flow chart of a clutch self-learning method provided in an embodiment of the present disclosure;

[0012] Figure 2 A schematic flow chart of another clutch self-learning method provided in an embodiment of the present disclosure;

[0013] Figure 3 A schematic flow chart of another clutch self-learning method provided in an embodiment of the present disclosure;

[0014] Figure 4 A schematic structural diagram of a self-learning device for a clutch provided in an embodiment of the present disclosure;

[0015] Figure 5 A schematic structural diagram of a vehicle provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0016] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0017] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0018] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to." The term "based on" means "based, at least in part, on." The term "one embodiment" means "at least one embodiment," the term "another embodiment" means "at least one additional embodiment," and the term "some embodiments" means "at least some embodiments." Other terms are defined in the following description.

[0019] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] In order to solve the above problems, an embodiment of the present disclosure provides a self-learning method for a clutch, which is introduced below in conjunction with specific embodiments.

[0023] Figure 1 This is a flow chart of a clutch self-learning method provided by an embodiment of the present disclosure. This method can be executed by a clutch self-learning device, wherein the device can be implemented using software and / or hardware and can generally be integrated into a vehicle. Figure 1 As shown, the method includes:

[0024] Step 101: Identify whether the vehicle meets the preset vehicle state self-learning conditions.

[0025] In an embodiment of the present disclosure, it is identified whether the vehicle meets a preset vehicle state self-learning condition, that is, it is identified whether the vehicle is in a state capable of self-learning.

[0026] It should be noted that in different application scenarios, the preset vehicle state self-learning conditions are different. In some possible embodiments, the preset vehicle state self-learning conditions include:

[0027] (1) The default self-learning switch is in the on state.

[0028] In this embodiment, a self-learning switch is pre-set. In this embodiment, the state of the self-learning switch can be preset based on the flg_AdptEnBaseAdsa flag. Different from the traditional self-learning mode, when the matching vehicle has the intelligent driving function and the current transmission mechanism requires the self-learning function, and according to the current calibration function requirements, the switch is set to flg_AdptEnBaseAdsa=1. When flg_AdptEnBaseAdsa=1, it indicates that the preset self-learning switch is in the on state. The flg_AdptEnBaseAdsa switch can be turned off or on at any time according to the requirements of the calibration test. This provides convenience and flexibility for testing.

[0029] (2) The intelligent driving function module in the vehicle is in a non-faulty state.

[0030] The intelligent driving function module may include a radar (e.g., a laser radar, a millimeter-wave radar, etc.), a camera module, etc. In this embodiment, the status of the intelligent driving function module may be identified based on flg_AdsaVaild. When flg_AdsaVaild = 1, it indicates that the intelligent driving function module in the vehicle is in a normal state.

[0031] (3) All door sensors, seat sensors and seat belts in the vehicle are in a non-faulty state.

[0032] In this embodiment, it is recognized that all door sensors, seat sensors, and seat belts in the vehicle are in a non-faulty state.

[0033] For example, the vehicle includes four doors, and the four doors of the vehicle are identified based on flg_DriverDoorVaild, flg_FRDoorVaild, flg_RLDoorVaild and flg_RRDoorVaild respectively, when flg_DriverDoorVaild=1, flg_FRDoorVaild=1, flg_RLDoorVaild=1, and flg_RRDoorVaild=1, the door sensors identifying the four doors of the vehicle are all normal.

[0034] For example, when a vehicle includes five seats, there are generally two seat sensors in the front row and three seat sensors in the back row. If these five seat sensors are valid, it means that the seat sensors are all in a non-fault state. Among them, when flg_DriverSeatVaild, flg_FRSeatVaild, flg_FRSeatVaild, flg_RRSeatVaild and flg_RMSeatVaild are used to identify the five seat sensors respectively, when flg_DriverSeatVaild=1, flg_FRSeatVaild=1, flg_RLSeatVaild=1, flg_RRSeatVaild=1, and flg_RMSeatVaild=1, and the communication of the five seat sensors is valid, it is ensured that whether there is someone in the seat can be detected in time.

[0035] In this embodiment, when the vehicle includes five seats, each seat includes a seat belt, and flg_DriverBeltVaild, flg_FRBeltVaild, flg_RLBeltVaild, flg_RRBeltVaild and flg_RRBeltVaild are used to identify the seat belts on the five seats respectively, then when flg_DriverBeltVaild=1, flg_FRBeltVaild=1, flg_RLBeltVaild=1, flg_RRBeltVaild=1, flg_RMBeltVaild=1, it indicates that the seat belt signal is valid.

[0036] (4) The clutch in the vehicle has not completed self-learning.

[0037] In this embodiment, self-learning is required for each sensor. If the self-learning of the current clutch has been completed, there is no need to perform self-learning again, unless the self-learning value of the clutch is reset for a certain clutch and self-learning needs to be performed again.

[0038] In this embodiment, when all clutches in the vehicle have not completed self-learning, it indicates that self-learning of the clutch is required.

[0039] In an embodiment of the present disclosure, whether a preset vehicle state self-learning condition is met may be identified based on flg_AdptBaseAdsaAcTive. When the preset vehicle state self-learning condition=1, it indicates that the preset vehicle state self-learning condition is met.

[0040] Step 102 : When the vehicle satisfies a preset vehicle state self-learning condition, it is identified whether the vehicle satisfies a preset parking condition.

[0041] It is understandable that in order to reduce the user's perception of the self-learning process, the vehicle should be in the parked state. Therefore, in one embodiment of the present disclosure, when the vehicle meets the preset vehicle state self-learning condition, it is identified whether the vehicle meets the preset parking condition.

[0042] In different application scenarios, the preset parking conditions are different. In some possible embodiments, the preset parking conditions include:

[0043] (1) The vehicle’s speed is 0.

[0044] In this embodiment, the vehicle speed may represent the current output shaft speed or the vehicle speed is 0. The vehicle speed of 0 can ensure that the current driver has the intention to stop, and is also for the safety of the vehicle and personnel when the current vehicle is performing self-learning.

[0045] (2) The vehicle is in braking or parking state.

[0046] In this embodiment, the vehicle is currently in the braking or parking state if the driver's brake pedal is in the braking state, or the Electronic Stability Program (ESP) and Anti-lock Brake System (ABS) are in the parking state, or the vehicle has an automatic parking function and the ESP can automatically park the vehicle after the vehicle stops, or the vehicle automatically enters the parking state after the driver unbuckles the seat belt, leaves the seat, or opens the door. This condition determines whether the vehicle is currently in or is in the braking state based on the brake switch and parking conditions.

[0047] (3) The vehicle is in neutral or park.

[0048] In this embodiment, the gear position currently requested by the shift lever is neutral or parking. According to the current driver's driving habits, some drivers are accustomed to keeping the gear in neutral before getting off the vehicle, while some drivers generally control the gear in parking before getting off the vehicle. Therefore, the gear position of the vehicle is identified as neutral or parking.

[0049] In this embodiment, the actual gear position of the transmission must also be consistent with the position of the shift lever. For example, if the shift lever is currently in neutral, the actual gear position of the transmission is neutral. If the current shift lever position request is park, the actual gear position of the transmission should also be park. If the actual gear position of the transmission and the shift lever position are inconsistent and remain inconsistent for a certain period of time (for example, 2000ms), self-learning is prohibited.

[0050] (4) The transmission mechanism in the vehicle is in a non-faulty state.

[0051] Among them, the speed change mechanism may include a transmission, a clutch, a gear, a speed sensor, etc.

[0052] In this embodiment, self-learning is allowed only when the transmission mechanism in the vehicle is in a non-faulty state.

[0053] If the transmission has a clutch, gear, or speed sensor fault, clutch self-learning is prohibited. This is because clutch self-learning requires all transmission components and sensors to be fault-free for proper clutch learning. For example, if the clutch is eroded, the clutch oil pressure control characteristics will change, effectively causing the clutch to be in a faulty state. If self-learning is performed, the result will not be a normal clutch state. For example, if the speed sensor in the transmission is faulty, the current speed cannot be guaranteed to be accurate, and the current speed value will be used during self-learning, preventing self-learning. Therefore, clutch self-learning is not possible if the transmission has a fault.

[0054] Step 103: When the preset parking condition is met, it is identified whether the vehicle meets the driver's departure condition.

[0055] In order to reduce the driver's perception of self-learning, in one embodiment of the present disclosure, when a preset parking condition is met, it is identified whether the vehicle meets a driver's departure condition.

[0056] It should be noted that the driver's leaving conditions may vary in different application scenarios. In some possible embodiments, the driver's leaving conditions may include:

[0057] (1) The driver is wearing a seat belt before getting off the vehicle. If the driver's seat belt changes from a locked state to an open state, it means that the driver has a need to get off the vehicle, and the judgment is made in combination with the following other conditions.

[0058] (2) The driver's seat sensor detects that the driver has left the driver's seat, that is, the seat changes from a state where the driver is sitting to a state where the driver has left the seat, and the driver's departure is confirmed.

[0059] In this embodiment, it can also be ensured that other users are not in the car to further enhance the user experience. If other seats are detected, the same principle is applied until no one is detected in all seats.

[0060] (3) When there is only a driver fatigue detection system in the vehicle, the driver fatigue detection system can be used to detect whether the driver is still in the vehicle. If the driver gets out of the vehicle, the driver will not be detected in the driving seat.

[0061] If the vehicle has a passenger detection system such as a camera or rearview mirror, the system checks whether the passenger in the corresponding seat is still in the seat. If there is no corresponding passenger detection system, the corresponding detection flag is always set (a flag of 0 indicates that the corresponding seat is not occupied), flg_DriverDet = 0, flg_FRPassengerDet = 0, flg_RLPassengerDet = 0, flg_RRPassengerDet = 0, and flg_RMPassengerDet = 0. If the status is 0, the state that the driver and passenger are not in the vehicle is established.

[0062] (4) In addition to detecting whether the driver and passengers in the car are in the car, it is also necessary to identify the driver or passengers in the car through the intelligent driving's external camera to determine whether the current occupants are already outside the car.

[0063] If there is a camera system inside the car to detect the driver, and there is also a corresponding camera detection system for the driver on the driver's side outside the car, and the cameras inside and outside the car have the same recognition of the driver and both are valid, it can be determined that the driver is already outside the car.

[0064] If there is no corresponding driver detection outside the car, this condition does not need to be judged, and it is only necessary to judge whether the driver inside the car is still in the driving seat. The judgment condition of the driver outside the car is mandatory.

[0065] For passenger detection, if there is a detection system inside the car to determine whether the passengers are in their seats, and there is also an intelligent driving detection system for passengers outside the car, this condition will be used for judgment. If there is no detection system inside the car and there is a corresponding camera outside the car, there is no need to judge again. This condition for judging whether the passengers are outside the car is mandatory.

[0066] If there is only a passenger detection system inside the car, it is only necessary to determine whether the passenger is inside the car, and the condition of detecting whether the passenger is already outside the car is mandatory.

[0067] (5) The current driver's door is in the open state and the door status is in the normal state. When flg_DriverDoorVaild identifies the door status, when flg_DriverDoorVaild=1, it indicates that the door status is in the normal state.

[0068] When all the above (1)-(5) conditions are met at the same time, it can be determined that the current occupant is no longer in the car.

[0069] Step 104 : When the driver's departure condition is met, identifying whether the vehicle meets the preset self-learning driving mode.

[0070] In one embodiment of the present disclosure, when the driver's departure condition is met, it is determined whether the vehicle meets the preset self-learning driving mode. The preset self-learning driving mode varies in different application scenarios. In some possible embodiments, if the vehicle is currently in pure electric mode, it is determined that the driver and passenger are already outside the vehicle, and normal clutch self-learning of the transmission mechanism can be performed, and the motor speed can be controlled to a fixed speed value required for self-learning, which can be preset to 850 rpm.

[0071] In some possible embodiments, if the current vehicle is in hybrid mode, the preset self-learning driving mode may include:

[0072] (1) The vehicle is not in charging state.

[0073] In this embodiment, if the vehicle is currently in a charging state, the charging strategy is executed first to ensure the power balance of the power battery or meet the driver's demand for the target power value for pure electric driving. Therefore, self-learning is not performed when the vehicle is in a charging state.

[0074] (2) The vehicle does not contain any device to be cooled.

[0075] In this embodiment, if the vehicle uses a mechanical compressor and the driver requests cooling, or if high-voltage components such as the power battery and motor require cooling, driver cooling and limited cooling of high-voltage components are prioritized. Unless the current vehicle interior temperature reaches the driver's set cooling temperature, or the high-voltage component cooling temperature meets component safety requirements, the engine is allowed to be shut down, and the motor is then used to perform clutch self-learning at a fixed speed.

[0076] However, if the compressor stops working, and the current temperature inside the car rises and is 10°C higher than the temperature set by the driver, or the temperature of the high-voltage components rises to the safe temperature + 10°C, or reaches the upper limit of the components, the current clutch self-learning will be stopped and the engine will be started to continue cooling to cool the car or the high-voltage components.

[0077] Therefore, in this embodiment, it is also necessary to determine that the vehicle does not include a device to be cooled, wherein the device to be cooled is a component that needs to be cooled and whose temperature is not within a preset safe temperature range.

[0078] (3) The vehicle is in engine direct drive mode.

[0079] In this embodiment, when the current driving mode is in engine direct drive mode, the engine can be shut down and the motor can be fixed to a certain speed for learning if a person leaves the vehicle. This engine shutdown in this situation will not cause driver complaints, as the engine direct drive mode has an automatic engine start-stop mode, and since the driver has left the vehicle, the engine can be automatically shut down, saving fuel and improving fuel economy. However, in this case, due to the self-learning shutdown, even after self-learning is complete, the engine does not need to be restarted unless the driver needs to shift gears to start driving.

[0080] (4) The vehicle is not in the preset driving condition.

[0081] In this embodiment, during self-learning, in order to ensure vehicle safety, it is also necessary to determine that the vehicle is not in a preset driving condition.

[0082] In this embodiment, if the vehicle is currently in 4L or 4H four-wheel drive mode, or in a harsh driving mode such as sand, mud, mountain, or snow, clutch self-learning is prohibited. It can also be considered that stopping the currently started engine is prohibited. In this case, the driver generally has a high demand for the vehicle's engine and motor power, or the vehicle may be in the process of rescue. If the engine power is shut down due to self-learning, it is likely to cause inconvenience to the driver.

[0083] Moreover, under such harsh working conditions, when the vehicle is self-learning and the clutch is engaged, if the clutch consistency is poor, the whole vehicle will be greatly impacted, which will bring danger to the whole vehicle if it is on a mountain or snowy mountain at this time.

[0084] Step 105, when a preset self-learning driving mode is met, the clutch in the vehicle is controlled to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation on the oil filling time of the clutch in the vehicle.

[0085] When the preset self-learning driving mode is met, the vehicle's clutch is controlled to self-learn and obtain the self-learning results. This logic allows us to determine that the driver and passengers have left the vehicle and that the vehicle is in a suitable state for self-learning. Self-learning at this time will not be noticeable to the passengers, and the transmission clutch will complete self-learning without them noticing. This improves the previous situation where drivers may have noticed the clutch self-learning process while inside the vehicle.

[0086] In an embodiment of the present disclosure, the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation on the oil filling time of the clutch in the vehicle, so that, in subsequent vehicle control, the control current of the solenoid valve of the clutch in the vehicle can be current compensated based on the self-learning result, and / or the oil filling time of the clutch in the vehicle can be time compensated.

[0087] In summary, the clutch self-learning method of the disclosed embodiment identifies whether the vehicle meets the preset vehicle state self-learning conditions. When the vehicle meets the preset vehicle state self-learning conditions, it identifies whether the vehicle meets the preset parking conditions. When the preset parking conditions are met, it identifies whether the vehicle meets the driver's departure conditions. When the driver's departure conditions are met, it identifies whether the vehicle meets the preset self-learning driving mode. Then, when the preset self-learning driving mode is met, the clutch in the vehicle is controlled to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle, and / or to perform time compensation on the oil filling time of the clutch in the vehicle. In this technical solution, the safety of the vehicle during self-learning is improved, the user's perception of self-learning is reduced, and the user experience is improved.

[0088] The self-learning process of the clutch in the embodiment of the present disclosure is described below with reference to specific embodiments.

[0089] Figure 2 is a flow chart of a self-learning method of a clutch according to another embodiment of the present disclosure, as shown in FIG. Figure 2 As shown, the method includes:

[0090] Step 201 : Determine whether the vehicle meets the conditions for entering the preset parameter calibration self-learning phase.

[0091] In this embodiment, the state bits of a state machine can be used to identify the various states of the vehicle self-learning phase (also known as the P2C phase). P2C self-learning primarily focuses on learning the P2C characteristics of the clutch solenoid valve. The clutch pressure command is controlled by controlling the solenoid valve current. Due to inconsistencies in factors such as the valve plate, solenoid valve, oil pipeline, and clutch characteristics within the transmission, the solenoid valve current in different transmissions may not meet the clutch pressure requirements. Therefore, after learning, the solenoid valve control current of the transmission currently equipped on the vehicle is modified to meet the clutch pressure requirements. The state machine may include three main states: Idle, Work, and Post. The Work phase may include the Pre phase and the P2Cadpt phase. The Pre phase is the initialization phase for parameter calibration, and the P2Cadpt phase is the self-learning phase for preset parameter calibration. POST is the self-learning exit phase, and Idle is the self-learning initial phase.

[0092] In this embodiment, the conditions for the Idle phase to enter the Work phase may include:

[0093] (1) The self-learning entry enabling conditions are met, which may include Figure 1 The conditions shown in .

[0094] (2) The current gear is in neutral, and the shift lever condition is in neutral for a certain period of time. The time here can be preset to 2000ms, etc.

[0095] (3) The self-learning clutch selection is not empty. The self-learning clutch selection is generally carried out in the order of C1, C2, C3, C4, and B1. If the current clutch has completed learning, this clutch will be skipped and the learning of other clutches will be carried out.

[0096] The conditions for the Work phase to enter the POST phase may include one of the following:

[0097] (1) If there is a gear shifting demand, whether it is from the driver or the transmission itself, the self-learning phase will be stopped and the POST phase will be entered, with the gear shifting being performed according to the driver's gear shifting demand.

[0098] (2) The current gear is not in neutral.

[0099] It should be noted that the completion of the self-learning phase of the preset parameter calibration indicates that the self-learning of this phase is completed (Completed) or failed (Failed).

[0100] Step 202 : When a condition for entering a preset parameter calibration self-learning phase is met, a first current offset of a target clutch is determined, wherein the target clutch is a clutch in a vehicle to be self-learned.

[0101] In an embodiment of the present disclosure, when the conditions for entering the preset parameter calibration self-learning phase are met, the first current offset of the target clutch is determined, wherein the target clutch is the clutch to be self-learned in the vehicle, for example, the target clutch is the self-learned clutch among C1, C2, C3, C4, and B1.

[0102] When the target clutch first enters the preset parameter calibration self-learning phase, the first current offset is the pre-calibrated initial value. This current offset can be positive or negative. It is generally negative to minimize the target clutch's slip and force self-learning. The slip value here is the difference between the engine input shaft speed and the transmission input shaft speed.

[0103] Step 203 : Calculate a first sum of the first current offset and the current control current of the solenoid valve of the target clutch, and control the target clutch according to the first sum.

[0104] Step 204 , determining whether the slip of the target clutch falls within a corresponding first preset slip range. If it falls within the first preset slip range, completing the self-learning of the target clutch in the preset parameter calibration self-learning phase.

[0105] Step 205: When it does not fall within the corresponding first preset slip range, query the first preset table according to the slip to obtain a second current offset, calculate a second sum of the second current offset and the current control current of the solenoid valve, and control the target clutch according to the second sum until the target clutch completes self-learning in the preset parameter calibration self-learning stage.

[0106] In this embodiment, a first summation value of a first current offset and a current control current of the solenoid valve of the target clutch is calculated, the target clutch is controlled according to the first summation value, and it is determined whether the slip of the target clutch belongs to a corresponding first preset slip range. When it belongs to the first preset slip range, the self-learning of the target clutch in the preset parameter calibration self-learning stage is completed.

[0107] When the slip does not fall within the corresponding first preset slip range, the first preset table is queried based on the slip to obtain a second current offset. Specifically, the table is queried based on the results of the previous self-learning to obtain the second current offset. A second sum of the second current offset and the current control current of the solenoid valve is calculated. The target clutch is then controlled based on the second sum until the target clutch completes self-learning in the preset parameter calibration self-learning phase. For example, the target clutch is controlled based on the second sum, and it is determined whether the slip of the target clutch falls within the corresponding first preset slip range. If it does fall within the first preset slip range, the target clutch completes self-learning in the preset parameter calibration self-learning phase. If it does not fall within the first preset slip range, the first preset table is queried based on the current slip to obtain a third current offset.

[0108] In this embodiment, there may be two special situations in which the above method may not be used to determine whether the target clutch has completed self-learning:

[0109] (1) When the first learning result (slip) is marked as RangeUnderKP, the second learning result is marked as RangeOverKP, and the third learning result is marked as RangeUnderKP. If the current offset corresponding to RangeOverKP is less than the preset lower limit, and the current offset corresponding to the third learning result is greater than the preset lower limit, it is directly determined that the target clutch preset parameter calibration self-learning stage is successful, and the self-learning of the target clutch is completed.

[0110] (2) Calculate the difference between two adjacent learning results each time. When the difference is greater than a preset difference threshold, the average of the two current offsets corresponding to the two adjacent learning results can be directly used as the self-learning result to determine that the self-learning of the target clutch is completed.

[0111] In one embodiment of the present disclosure, the self-learning stage may also include a preset oil filling self-learning stage, that is, the BoostAdpt stage is included after P2Cadpt in the above-mentioned Work stage. BoostAdpt indicates the preset oil filling self-learning stage. During the oil filling stage, if the clutch is insufficiently filled with oil, the pressure in the clutch-related pipelines will not be fully filled, resulting in insufficient pressure in the clutch during the engagement process. Therefore, in this embodiment, self-learning of the preset oil filling stage is also performed.

[0112] Among them, such as Figure 3 As shown, the method further includes:

[0113] Step 301 : Determine whether the vehicle meets the preset conditions for entering the oil filling self-learning phase.

[0114] In this embodiment, after the self-learning of the preset parameter calibration self-learning phase is completed, it can be directly determined that the vehicle meets the conditions for entering the preset oil filling self-learning phase.

[0115] The completion conditions of the preset parameter calibration self-learning phase may include one of the following:

[0116] (1) The slip of all target clutches to be learned belongs to the corresponding preset slip range.

[0117] That is, all target clutches to be learned have been learned successfully.

[0118] (2) The self-learning coefficients of all target clutches to be learned are greater than or equal to the preset coefficient threshold.

[0119] In this embodiment, after the first self-learning of the preset parameter calibration self-learning stage, the self-learning coefficient of the preset parameter calibration self-learning stage is set to 1. After the self-learning of the preset parameter calibration self-learning stage is not performed for the first time, the absolute value of the difference between the slip of the target clutch after the self-learning of the current preset parameter calibration self-learning stage and the slip of the target clutch after the self-learning of the last preset parameter calibration self-learning stage is calculated. When the absolute value of the difference is less than the preset slip threshold, the self-learning coefficient is updated to the sum of the first preset coefficient value and the self-learning coefficient. When the absolute value of the difference is not less than the preset slip threshold, the self-learning coefficient is updated to the sum of the second preset coefficient value and the self-learning coefficient, wherein the first preset coefficient value is greater than the second preset coefficient value. In some possible embodiments, the first preset coefficient value may be 10, the second preset coefficient value may be 1, and the preset coefficient threshold may be 11.

[0120] If the target clutch's learning result for this stage is Failed, it indicates that the target clutch has failed learning. Since this learning was unsuccessful, the self-learning coefficient is not assigned a value. Since the learning value after P2C self-learning (current offset) was unsuccessful, the result of the last successful learning (current offset) remains unchanged. If all self-learning states (including Idle, Pre, and P2CAdpt) are complete, the self-learning is considered successful. Otherwise, it is considered a failure.

[0121] Step 302 : When a preset oil filling self-learning phase entry condition is met, a first oil filling time offset of the target clutch is determined.

[0122] In this embodiment, when the preset oil filling self-learning phase entry condition is met, the first oil filling time offset of the target clutch is determined. When the target clutch first enters the preset oil filling self-learning phase, the first oil filling time offset of the preset oil filling self-learning phase is a preset initial value.

[0123] Step 303 : Calculate a third sum of the first oil filling time offset and the current oil filling time of the target clutch, and control the oil filling of the target clutch according to the third sum.

[0124] In this embodiment, a third sum of the first oil filling time offset and the current oil filling time of the target clutch is calculated, and the oil filling of the target clutch is controlled according to the third sum.

[0125] Step 304 : When the target clutch enters the engaged state, determine a reference slip of the target clutch in the engaged state and / or a reference time for entering the engaged state.

[0126] In this embodiment, when the target clutch enters the engaged state, that is, when the target clutch enters the KP state, a reference slip of the target clutch in the engaged state and / or a reference time to enter the engaged state (time from the oil filling stage to KP) is determined.

[0127] Step 305 : Determine whether the preset oil filling self-learning phase is successful based on the reference slip and / or reference time.

[0128] In this embodiment, whether the preset oil filling self-learning phase is successful is determined based on the reference slip and / or the reference time.

[0129] That is, it is determined whether the reference slip falls within the second preset slip range and / or whether the time difference (for example, the time difference between the reference time and the preset target time (the target time is the ideal time preset when entering the KP state)) falls within the preset time range. When the reference slip falls within the second preset slip range and / or the time difference falls within the preset time range, it is determined that the preset oil filling self-learning stage is successful.

[0130] Step 306 : If learning is unsuccessful in the preset oil filling self-learning phase, the time difference between the reference time and the preset target time is calculated.

[0131] In this embodiment, when learning is unsuccessful in the preset oil filling self-learning stage, the time difference between the reference time and the preset target time is calculated.

[0132] Step 307: query a second preset table based on the time difference to obtain a second oil filling time offset, calculate a fourth sum of the second oil filling time offset and the current oil filling time of the target clutch, and control the oil filling of the target clutch based on the fourth sum until the target clutch successfully completes self-learning in the preset oil filling self-learning stage.

[0133] In this embodiment, a second preset table is queried based on the time difference to obtain a second oil filling time offset. A fourth summation of the second oil filling time offset and the current oil filling time of the target clutch is calculated. Oil filling of the target clutch is controlled based on the fourth summation until the target clutch successfully completes self-learning in the preset oil filling self-learning phase. Specifically, oil filling of the target clutch is controlled based on the fourth summation. When the target clutch enters the engaged state, a reference slip of the target clutch in the engaged state and / or a reference time for entering the engaged state are determined. Whether the preset oil filling self-learning phase has been successful is determined based on the reference slip and / or the reference time. If learning is unsuccessful, the aforementioned steps are continued until learning is successful.

[0134] Of course, in one embodiment of the present disclosure, it is not necessary for the learning to be successful to be considered as the completion of the preset oil filling self-learning stage. The following two situations are also considered as the completion of the preset oil filling self-learning stage:

[0135] (1) When the first learning result (e.g., reference slip) is marked as RangeUnderFill, the second learning result is marked as RangeOverFill, and the third learning result is marked as RangeUnderFill. If the reference slip corresponding to RangeOverFill is less than the preset lower limit, and the reference slip corresponding to the third learning result (e.g., RangeUnderKP) is greater than the preset lower limit, then it is directly determined that the preset oil filling self-learning stage is successful, and the self-learning of the target clutch is completed.

[0136] (2) Calculate the slip difference between two adjacent learning results each time. When the slip difference is greater than a preset difference threshold, the average of the two oil filling time offsets corresponding to the two adjacent learning results can be directly used as the self-learning result to determine that the self-learning of the target clutch is completed.

[0137] The completion conditions of the preset oil filling self-learning phase may include one of the following:

[0138] (1) All target clutches to be learned have been learned successfully.

[0139] (2) The self-learning coefficients of all target clutches to be learned are greater than or equal to the preset coefficient threshold.

[0140] In this embodiment, after the first self-learning of the preset oil filling self-learning stage, the self-learning coefficient of the preset parameter calibration self-learning stage is set to 1. After the self-learning of the preset parameter calibration self-learning stage is not performed for the first time, the absolute value of the difference between the reference slip of the target clutch after the self-learning of the preset oil filling self-learning stage this time and the reference slip of the target clutch after the self-learning of the last preset oil filling self-learning stage is calculated. When the absolute value of the difference is less than the preset slip threshold, the self-learning coefficient is updated to the sum of the first preset coefficient value and the self-learning coefficient. When the absolute value of the difference is not less than the preset slip threshold, the self-learning coefficient is updated to the sum of the second preset coefficient value and the self-learning coefficient, wherein the first preset coefficient value is greater than the second preset coefficient value. In some possible embodiments, the first preset coefficient value may be 10, the second preset coefficient value may be 1, and the preset coefficient threshold may be 11.

[0141] If the target clutch's learning result for this phase is Failed, it indicates that the target clutch has failed. Since the learning coefficient was unsuccessful, no value is assigned to it. Since the learning value after BoostAdpt's self-learning (oil filling time offset) was unsuccessful, the result from the last successful learning (oil filling time offset) remains unchanged. If all self-learning states (including Idle, Pre, P2Cadpt, and BoostAdpt) are complete, the self-learning is considered successful. Otherwise, it is considered a failure.

[0142] In summary, in the embodiments of the present disclosure, self-learning of the target clutch is performed while ensuring that the user's perception of self-learning is reduced, thereby improving the driving experience.

[0143] In order to implement the above embodiment, the present disclosure also proposes a self-learning device for a clutch.

[0144] Figure 4 FIG. 1 is a schematic structural diagram of a self-learning device for a clutch according to an embodiment of the present disclosure. Figure 4 As shown, the self-learning device of the clutch includes: a first recognition module 410, a second recognition module 420, a third recognition module 430, a fourth recognition module 440, and a self-learning control module 450, wherein:

[0145] A first identification module 410 is used to identify whether the vehicle meets a preset vehicle state self-learning condition;

[0146] The second identification module 420 is used to identify whether the vehicle meets the preset parking condition when the vehicle meets the preset vehicle state self-learning condition;

[0147] The third identification module 430 is used to identify whether the vehicle meets the driver's departure condition when the preset parking condition is met;

[0148] A fourth identification module 440 is configured to identify whether the vehicle satisfies a preset self-learning driving mode when the driver's departure condition is met;

[0149] The self-learning control module 450 is used to control the clutch in the vehicle to perform self-learning to obtain a self-learning result when a preset self-learning driving mode is met, wherein the self-learning result is used to current compensate the control current of the solenoid valve of the clutch in the vehicle, and / or to time compensate the oil filling time of the clutch in the vehicle.

[0150] The self-learning device of the clutch provided in the embodiment of the present disclosure can execute the self-learning method of the clutch provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0151] In order to implement the above embodiments, the present disclosure further proposes a computer program product, including a computer program / instruction, which implements the self-learning method of the clutch in the above embodiments when executed by a processor.

[0152] Figure 5 A schematic diagram of the structure of a vehicle provided in an embodiment of the present disclosure. For example, Figure 5 As shown, the vehicle 500 includes a memory 501 and a processor 502, wherein the memory is used to store the processor-executable instructions 5011, and the processor is used to read the executable instructions 5011 from the memory and execute the executable instructions to implement the above method.

[0153] This embodiment can divide the vehicle into functional modules based on the above-described method example. For example, each functional module can be mapped to a specific function, or two or more functions can be integrated into a single processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used.

[0154] In the case of dividing the functional modules according to the corresponding functions, the vehicle may include: a first identification module, a second identification module, a third identification module, a fourth identification module and a self-learning control module. It should be noted that all relevant contents of the various steps involved in the above method embodiment can be referred to the functional description of the corresponding functional modules and will not be repeated here.

[0155] The vehicle provided in this embodiment is used to execute the above-mentioned self-learning method of the clutch, and thus can achieve the same effect as the above-mentioned implementation method.

[0156] In the case of an integrated unit, the vehicle may include a processing module and a storage module. The processing module may be used to control and manage the vehicle's movements, while the storage module may be used to support the vehicle's execution of program codes and data.

[0157] The processing module may be a processor or a controller that implements or executes various exemplary logic blocks, modules, and circuits described herein. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processing (DSP) and a microprocessor, and the storage module may be a memory.

[0158] This embodiment also provides a computer-readable storage medium, which stores computer program code (including but not limited to disk storage, CD-ROM, optical storage, etc.). When the computer program code runs on a computer, the computer executes the above-mentioned related method steps to implement a self-learning method of a clutch provided in the above embodiment.

[0159] Among them, the beneficial effects of the above embodiments can refer to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0160] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0161] In the embodiments provided in this disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division into modules or units is merely a logical functional division. In actual implementation, other divisions may be employed, such as combining or integrating multiple units or components into another device, or omitting or disabling certain features. Furthermore, the coupling or direct coupling or communication connection shown or discussed between devices or units may be through interfaces, or indirect coupling or communication connection between devices or units, which may be electrical, mechanical, or other forms. The above description is merely a preferred embodiment of this disclosure and an illustration of the underlying technical principles. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the aforementioned technical features, but also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the scope of this disclosure. For example, technical solutions formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

[0162] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details have been included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0163] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

Claims

1. A self-learning method for a clutch, characterized in that: include: Identify whether the vehicle meets the preset vehicle status self-learning conditions; When the vehicle satisfies the preset vehicle state self-learning condition, identifying whether the vehicle satisfies a preset parking condition; When the preset parking condition is met, identifying whether the vehicle meets a driver leaving condition; When the driver's departure condition is met, identifying whether the vehicle meets a preset self-learning driving mode; When the preset self-learning driving mode is satisfied, controlling the clutch in the vehicle to perform self-learning to obtain a self-learning result, wherein the self-learning result is used to perform current compensation on a control current of a solenoid valve of the clutch in the vehicle and / or to perform time compensation on an oil filling time of the clutch in the vehicle, wherein controlling the clutch in the vehicle to perform self-learning to obtain the self-learning result includes: Determine whether the vehicle meets the conditions for entering the preset parameter calibration self-learning phase, When the preset parameter calibration self-learning phase entry condition is met, a first current offset of a target clutch is determined, wherein the target clutch is a clutch in the vehicle to be self-learned, calculating a first summation value of the first current offset and a current control current of the solenoid valve of the target clutch, and controlling the target clutch according to the first summation value; determining whether the slip of the target clutch falls within a corresponding first preset slip range, and completing the self-learning of the target clutch in a preset parameter calibration self-learning phase when the target clutch falls within the first preset slip range; When the current does not fall within the corresponding first preset slip range, querying a first preset table according to the slip to obtain a second current offset, calculating a second sum of the second current offset and a current control current of the solenoid valve, and controlling the target clutch according to the second sum until the self-learning of the target clutch in the preset parameter calibration self-learning stage is completed; After the self-learning of the preset parameter calibration self-learning stage is performed for the first time, setting the self-learning coefficient of the preset parameter calibration self-learning stage to 1; After the self-learning of the preset parameter calibration self-learning stage is not performed for the first time, calculating the absolute value of the difference between the slip of the target clutch after the self-learning of the preset parameter calibration self-learning stage this time and the slip of the target clutch after the self-learning of the preset parameter calibration self-learning stage last time, When the absolute value of the difference is less than a preset slip threshold, updating the self-learning coefficient to the sum of a first preset coefficient value and the self-learning coefficient; When the absolute value of the difference is not less than a preset slip threshold, updating the self-learning coefficient to the sum of a second preset coefficient value and the self-learning coefficient, wherein the first preset coefficient value is greater than the second preset coefficient value; The self-learning of the target clutch in the preset parameter calibration self-learning stage includes: The slips of all target clutches to be learned fall within the corresponding preset slip ranges; and / or, The self-learning coefficients of all target clutches to be learned are greater than or equal to a preset coefficient threshold.

2. The method according to claim 1, wherein The preset vehicle state self-learning conditions include: The preset self-learning switch is in the on state; The intelligent driving function module in the vehicle is in a non-faulty state; All door sensors, seat sensors, and seat belts in the vehicle are in a non-faulty state; The clutch in the vehicle has not been fully self-learned.

3. The method according to claim 1, wherein The preset parking conditions include: The speed of the vehicle is 0; The vehicle is in a braking state or a parking state; The gear position of the vehicle is neutral or parking; The transmission mechanism in the vehicle is in a non-faulty state.

4. The method according to claim 1, wherein When the vehicle is a hybrid mode vehicle, the preset self-learning driving mode includes: The vehicle is not in a charging state; The vehicle does not contain a device to be cooled; The vehicle is in engine direct drive mode; The vehicle is not in a preset driving condition.

5. The method according to claim 1, wherein Also includes: Determining whether the vehicle meets a preset oil filling self-learning phase entry condition; When the preset oil filling self-learning phase entry condition is met, determining a first oil filling time offset of the target clutch; calculating a third sum of the first oil filling time offset and the current oil filling time of the target clutch, and controlling the oil filling of the target clutch according to the third sum; When the target clutch enters an engaged state, determining a reference slip of the target clutch in the engaged state and / or a reference time for entering the engaged state; determining whether the preset oil filling self-learning phase is successful according to the reference slip and / or the reference time; When learning is unsuccessful in the preset oil filling self-learning stage, calculating the time difference between the reference time and the preset target time; A second preset table is queried according to the time difference to obtain a second oil filling time offset, a fourth summation value of the second oil filling time offset and the current oil filling time of the target clutch is calculated, and the oil filling of the target clutch is controlled according to the fourth summation value until the self-learning of the target clutch in the preset oil filling self-learning stage is completed.

6. The method according to claim 5, wherein The determining whether the preset oil filling self-learning phase is successful according to the reference slip and / or the reference time includes: determining whether the reference slip falls within a second preset slip range, and / or determining whether the time difference falls within a preset time range; When the reference slip falls within the second preset slip range, and / or the time difference falls within the preset time range, it is determined that the preset oil filling self-learning phase is successful.

7. A self-learning device for a clutch, characterized in that: include: A first identification module is used to identify whether the vehicle meets the preset vehicle state self-learning conditions; a second identification module, configured to identify whether the vehicle satisfies a preset parking condition when the vehicle satisfies the preset vehicle state self-learning condition; a third identification module, configured to identify whether the vehicle satisfies a driver's leaving condition when the preset parking condition is satisfied; a fourth identification module, configured to identify whether the vehicle satisfies a preset self-learning driving mode when the driver's departure condition is met; A self-learning control module is configured to control the clutch in the vehicle to perform self-learning to obtain a self-learning result when the preset self-learning driving mode is satisfied, wherein the self-learning result is used to perform current compensation on the control current of the solenoid valve of the clutch in the vehicle and / or to perform time compensation on the oil filling time of the clutch in the vehicle. The self-learning control module is configured to determine whether the vehicle meets the conditions for entering the preset parameter calibration self-learning phase, When the preset parameter calibration self-learning phase entry condition is met, a first current offset of a target clutch is determined, wherein the target clutch is a clutch in the vehicle to be self-learned, calculating a first summation value of the first current offset and a current control current of the solenoid valve of the target clutch, and controlling the target clutch according to the first summation value; determining whether the slip of the target clutch falls within a corresponding first preset slip range, and completing the self-learning of the target clutch in a preset parameter calibration self-learning phase when the target clutch falls within the first preset slip range; When the current does not fall within the corresponding first preset slip range, querying a first preset table according to the slip to obtain a second current offset, calculating a second sum of the second current offset and a current control current of the solenoid valve, and controlling the target clutch according to the second sum until the self-learning of the target clutch in the preset parameter calibration self-learning stage is completed; After the self-learning of the preset parameter calibration self-learning stage is performed for the first time, setting the self-learning coefficient of the preset parameter calibration self-learning stage to 1; After the self-learning of the preset parameter calibration self-learning stage is not performed for the first time, calculating the absolute value of the difference between the slip of the target clutch after the self-learning of the preset parameter calibration self-learning stage this time and the slip of the target clutch after the self-learning of the preset parameter calibration self-learning stage last time, When the absolute value of the difference is less than a preset slip threshold, updating the self-learning coefficient to the sum of a first preset coefficient value and the self-learning coefficient; When the absolute value of the difference is not less than a preset slip threshold, updating the self-learning coefficient to the sum of a second preset coefficient value and the self-learning coefficient, wherein the first preset coefficient value is greater than the second preset coefficient value; The self-learning of the target clutch in the preset parameter calibration self-learning stage includes: The slips of all target clutches to be learned fall within the corresponding preset slip ranges; and / or, The self-learning coefficients of all target clutches to be learned are greater than or equal to a preset coefficient threshold.

8. A vehicle, characterized in that: The vehicle includes: processor; a memory for storing instructions executable by the processor; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the self-learning method of the clutch as described in any one of claims 1-6.

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