Gear self-learning method and device
By dynamically adjusting the control coefficient during the gear self-learning process of the automatic mechanical transmission, the impact problem caused by continuous output torque during self-learning after the transmission is installed on the vehicle is solved, efficient gear self-learning is achieved, the learning success rate is improved and the self-learning time is shortened.
Patent Information
- Application Number
- CN202510877145.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-27
- Publication Date
- 2025-09-19
AI Technical Summary
During the gear self-learning process of the automatic mechanical transmission, the continuous output torque causes obvious impact when the transmission is installed on the vehicle and performs self-learning, affecting the shifting quality and product life.
By controlling the shift actuator to move in the direction of the target gear, and dynamically adjusting the control coefficient of the preset controller during the process, the movement is stopped until the control coefficient reaches 0, and the limit stall position of the target gear is recorded as the self-learning result.
It solves the impact problem of the gearbox self-learning after installation due to continuous output torque, realizes the timely operation of the drive motor during gear self-learning, reduces the disturbance of the learning process, improves the learning success rate and shortens the self-learning time.
Smart Images
Figure CN120667530A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of data processing technology, and in particular to a gear self-learning method and device. Background Art
[0002] An automatic mechanical transmission, also known as an automated manual transmission, combines the features of a traditional manual transmission and an automatic transmission.
[0003] Throughout the lifecycle of an automated mechanical transmission (AMT), gear positions change due to machining, installation deviations, and wear during operation. Therefore, AMT control strategies must include the ability to self-learn gear positions to ensure shift quality and extend product life.
[0004] In related technologies, when the gear shift fork drives the sliding sleeve to the KP position or the gear position, the gearbox output shaft still outputs a certain torque to the subsequent transmission device, thereby causing the vehicle body to shake to a certain extent, making the impact of the gearbox self-learning after installation obvious. Summary of the Invention
[0005] In view of this, the purpose of the present disclosure is to propose a gear self-learning method and device, which can specifically solve the existing problems.
[0006] Based on the above-mentioned purpose, in the first aspect, the present disclosure proposes a gear self-learning method, comprising: for the target gear to be learned by the vehicle, controlling the gear shift actuator to move in the gear-engaging direction of the target gear, if the gear shift actuator has entered the target gear, adjusting the speed or torque of the drive motor to 0, and the target gear is a non-zero gear; in the process of moving in the gear-engaging direction of the target gear, for the gear value, dynamically adjusting the control coefficient of the preset controller according to the relationship between the actual value and the target value of the gear; if the control coefficient reaches 0, controlling the gear shift actuator to stop moving at the first current position; based on the first current position, determining and recording the limit stall position of the target gear as the result of gear self-learning.
[0007] In the second aspect, a gear self-learning device is also provided for executing the gear self-learning method in the first aspect, and the device includes: a judgment unit, configured to judge whether the current vehicle state of the vehicle meets the self-learning conditions; a drive motor and a control unit thereof, configured to control the drive motor to operate based on a speed control mode or a torque control mode; an execution unit of an actuator, configured to drive the shift finger to move; a control unit of the actuator, configured to control the control current of the actuator, monitor the actual value and target value of the gear to which the actuator moves, and record the results of gear self-learning.
[0008] On the third aspect, a gear self-learning device is also provided, including: a first control unit, configured to control the gear shift actuator to move in the gear-engaging direction of the target gear to be learned by the vehicle, and if the gear shift actuator has entered the target gear, adjust the speed or torque of the drive motor to 0, and the target gear is a non-zero gear; an adjustment unit, configured to dynamically adjust the control coefficient of the preset controller according to the relationship between the actual value and the target value of the gear during the movement in the gear-engaging direction of the target gear; a second control unit, configured to control the gear shift actuator to stop moving at the first current position if the control coefficient reaches 0; a determination unit, configured to determine and record the extreme stall position of the target gear as the result of gear self-learning based on the first current position.
[0009] In a fourth aspect, an electronic device is also provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.
[0010] In a fifth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program is executed by a processor to implement any method described in the first aspect.
[0011] In a sixth aspect, a computer program product is also provided, comprising a computer program, wherein the computer program is executed by a processor to implement any of the methods described in the first aspect.
[0012] In summary, the present disclosure has at least the following beneficial effects: During the gear self-learning process, the present disclosure changes the driving state of continuous torque output, resolving the significant impact during gear self-learning after the transmission is installed on the vehicle, which is caused by the need for continuous torque output at the output end. Furthermore, the present disclosure ensures that the drive motor can operate at the right time during gear self-learning, minimizing disturbances during the learning process. This shortens the self-learning time while increasing the learning success rate. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar components or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present disclosure and should not be regarded as limiting the scope of the present disclosure.
[0014] Figure 1 A flow chart of a gear self-learning method according to an embodiment of the present disclosure is shown;
[0015] Figure 2aA flowchart of neutral position self-learning according to an embodiment of the present disclosure is shown;
[0016] Figure 2b A flowchart of self-learning of the stall position at the gear limit according to an embodiment of the present disclosure is shown;
[0017] Figure 2c A flowchart showing the self-learning of the gear engagement point position according to an embodiment of the present disclosure is shown.
[0018] Figure 3 A schematic diagram of a gear self-learning device according to an embodiment of the present disclosure is shown;
[0019] Figure 4 Another schematic diagram of the gear self-learning device according to an embodiment of the present disclosure is shown;
[0020] Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure is shown;
[0021] Figure 6 A schematic diagram of a storage medium provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION
[0022] The present disclosure will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are intended only to illustrate the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.
[0023] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.
[0024] Figure 1 The gear self-learning method disclosed in the present invention is shown. In an embodiment of the present invention, the method includes:
[0025] Step S101, for the target gear to be learned by the vehicle, control the vehicle's shift actuator to move in the gear-engaging direction of the target gear. If the shift actuator has entered the target gear, adjust the speed or torque of the drive motor to 0, and the target gear is a non-zero gear.
[0026] Step S102 , during the movement toward the target gear, dynamically adjusting the control coefficient of the preset controller according to the relationship between the actual value and the target value of the gear.
[0027] Step S103: If the control coefficient reaches 0, the shift actuator is controlled to stop moving at the first current position.
[0028] Step S104: determining and recording the limit stall position of the target gear as a result of gear self-learning based on the first current position.
[0029] Various methods can be used to determine and record the target gear's limit stall position based on the first current position. For example, a numerical interval within which the first current position falls is used as the limit stall position. The size of the numerical interval can be preset. The gear self-learning result includes the target gear's limit stall position.
[0030] This embodiment can be performed in various control modes, such as a speed control mode.
[0031] The disclosed gear self-learning process changes the driving state of continuous torque output, resolving the significant impact during gear self-learning after the transmission is installed, which is caused by the need for continuous torque output at the output end. This ensures that the drive motor can operate at the right time during gear self-learning, minimizing disturbances during the learning process. This shortens the self-learning time while increasing the learning success rate.
[0032] In some optional implementations of any embodiment of the present disclosure, the control coefficient of the preset controller is dynamically and adaptively adjusted according to the relationship between the actual value of the gear and the target value, including: when the actual value of the gear is less than the target value, if the difference between the actual value of the gear and the target value is in a preset large difference interval, the control coefficient is adaptively increased; when the actual value of the gear is less than the target value, if the difference between the actual value of the gear and the target value is in a preset small difference interval, the control coefficient is adaptively decreased; when the actual value of the gear is greater than the target value, the control coefficient is adaptively adjusted to a negative value.
[0033] When the difference between the actual value and the target value of the gear position includes a first difference and a second difference, if the first difference is greater than the second difference, the control coefficient corresponding to the first difference is greater than or equal to the control coefficient corresponding to the second difference.
[0034] In some optional implementations of any embodiment of the present disclosure, for the target gear to be learned by the vehicle, the shift actuator is controlled to move in the gear-engaging direction of the target gear, including: in response to each shift actuator of the vehicle being in a neutral position, and controlling the drive motor to rotate in a first rotation direction at a preset low speed, if the drive motor feedback operation is normal, then for the target gear to be learned by the vehicle, the shift actuator is controlled to move in the gear-engaging direction of the target gear.
[0035] The first rotation direction of the preset low speed is reverse.
[0036] In some optional implementations of any embodiment of the present disclosure, controlling the shift actuator to stop moving at the current position includes: judging the change of the signal of the gear position; if the change is that the signal no longer changes and lasts for a preset time, controlling the shift actuator to stop moving at the current position.
[0037] In some optional implementations of any embodiment of the present disclosure, the method further includes: controlling the drive motor to enter a torque control mode, and if the torque reaches a preset torque, an adaptive fuzzy control method is used to control the shift actuator to move toward the engagement point position of the transmission, and the preset torque is the torque corresponding to the preset low speed; if it is determined by detecting the actual speed of the drive motor that the current gear has reached the disengagement position from the engaged position, the control coefficient of the preset controller is dynamically adjusted according to the difference between the actual value of the speed and the target value; if the difference between the actual value of the speed and the target value is 0, the shift actuator stops moving at the second current position by controlling the control coefficient to 0; based on the second current position, the gear engagement point position of the target gear is determined and recorded as the result of gear self-learning.
[0038] The gear engagement point position of the target gear can be determined and recorded in various ways based on the second current position, for example, the numerical interval of the second current position is used as the gear engagement point position. The size of the numerical interval here can be preset.
[0039] This implementation is still being done towards the target gear.
[0040] Optionally, the control coefficient of the preset controller is dynamically adjusted according to the size of the difference between the actual value of the speed and the target value, including: if the difference between the actual value of the speed and the target value is in a preset large difference interval, an adaptive fuzzy control method is adopted to increase the control coefficient; when the actual value of the speed is less than the target value, if the difference between the actual value of the speed and the target value is in a preset small difference interval, an adaptive fuzzy control method is adopted to reduce the control coefficient.
[0041] In these implementations, the actual value of the rotational speed currently corresponds to a rotational speed direction that is positive, and the adaptive control process is performed when the actual value of the rotational speed is less than the target value.
[0042] In some optional implementations of any embodiment of the present disclosure, the method further includes: in response to the shift finger having moved to the theoretical neutral position, controlling the preset drive motor to enter a speed control mode, and determining whether the no-load operation condition of the preset drive motor is met; if met, executing the neutral recording step: determining and recording the neutral position according to the position indicated by the shift finger.
[0043] Specifically, the drive motor can be controlled to enter a speed control mode and run at a preset low speed. The no-load running condition can include whether the speed can reach 30 rpm (second rotation direction) and whether the torque is less than the no-load torque of 15 Nm.
[0044] Optionally, the method further includes: if not satisfied, moving the shift finger to the right, and again judging whether the preset no-load running condition of the drive motor is satisfied; if satisfied, executing the neutral recording step; if still not satisfied, moving the shift finger to the left, and again judging whether the preset no-load running condition of the drive motor is satisfied; if satisfied, executing the neutral recording step.
[0045] The present disclosure also provides a gear self-learning method, comprising:
[0046] Step 1: First learn the neutral position;
[0047] Step 2: Learn the limit stall position after first gear is engaged and store the information of the position;
[0048] Step 3: Learn the engagement point position of the first gear disengagement, i.e., the KP position, and store the information of the position;
[0049] Step 4: Repeat steps 2-3 to learn the limit stall position and gear engagement point position of the second gear, third gear and fourth gear respectively, and store the information of these positions respectively.
[0050] The specific steps are as follows:
[0051] 1. (e.g. Figure 2a Neutral position learning includes:
[0052] 1. Determine whether the vehicle has the conditions for self-learning (handbrake applied, key powered on, self-learning command received).
[0053] 2. First, move the shift finger to the designed theoretical neutral position. Judgment condition: If the neutral position is valid, the drive motor can run without load.
[0054] 3. Control the drive motor to enter the speed control mode and run at a low speed (30 rpm) to check whether it can run normally without load. That is, first, the speed can reach 30 rpm. If it can be reached, check whether the torque is less than 15 Nm (no-load torque). If both conditions are met, the current position is the neutral position, and the information of this position is recorded.
[0055] 4. If the no-load running condition of the drive motor cannot be met, move the shift finger to the right for a certain distance (2%-5% of the total stroke, which can be calibrated), and repeat steps 2-3. If both conditions are met, the current position is the neutral position, and the information of this position is recorded.
[0056] 5. If the no-load running condition of the drive motor is still not met, move the shift finger to the left for a distance (4%-10% of the total stroke, which can be calibrated), and repeat steps 2-3. If both conditions are met, the current position is the neutral position, and the information of this position is recorded.
[0057] 6. If the drive motor no-load operation condition is still not met after the above actions are completed, it indicates that the neutral position error of the gearbox has exceeded the design redundancy value and an alarm message needs to be issued. Please ask calibration or maintenance personnel to handle it.
[0058] 2. (e.g. Figure 2b The limit stall position (shown) is also the limit position of the gear:
[0059] 1. The shift actuators A2 (controlling the engagement and disengagement of first and second gears) and A1 (controlling the engagement and disengagement of third and fourth gears) are both in the neutral position.
[0060] 2. In speed control mode, the drive motor M1 rotates at a low speed of -30rpm. After the drive motor feedback runs normally, proceed to the next step.
[0061] 3. Using adaptive fuzzy-PID control, the A2 shift actuator moves toward first gear. When the drive motor torque exceeds 15 Nm (no-load torque) or the drive motor speed reaches 0, indicating that the A2 actuator has entered first gear, the speed demand for the drive motor M1 is stopped. In other words, the speed and torque demand for the drive motor are both 0 (to prevent the drive motor from being blocked for a long time and burning out). The A2 actuator continues to move toward the first gear limit position.
[0062] 4. Learning the extreme stall position after first gear engagement: Continue to control the A2 shift mechanism, moving it in the gear engagement direction. Use the adaptive fuzzy PID control method to control the PWM duty cycle. The controlled target is the voltage value of the angle position sensor. Establish fuzzy rules:
[0063] When the actual value of the angle position sensor is far from the target value, the KP coefficient and KI coefficient of the PID controller are also large, so that the actuator can quickly approach the target position;
[0064] When the actual value of the angle position sensor is close to the target value, the KP coefficient and KI coefficient of the PID controller are also small, so that the actuator can move closer to the target position to prevent overshoot;
[0065] When the actual value of the angle position sensor reaches the target value, the KP coefficient and KI coefficient of the PID controller are 0, so that the actuator can stop accurately at the target position;
[0066] When the actual value of the angular position sensor exceeds the target value due to overshoot, the KP coefficient and KI coefficient of the PID controller are negative, causing the actuator to run back and approach the target value. When the target value is reached, the two coefficients are 0, and the actuator can stop accurately at the target position.
[0067] 5. Observe whether the angle position sensor continues to change. When the position signal stops changing and lasts for more than 3 seconds, stop the PWM drive of the actuator (to prevent long-term stalling and burning of the actuator motor) and record the current position information. The current position is the limit stall position after entering gear 1.
[0068] 6. Record and store the first gear limit position information, and the first gear limit position learning is completed. This limit stall position is the gear limit stall position, also known as the gear limit stall position.
[0069] 3. (e.g. Figure 2c (As shown) Gear engagement point KP position learning:
[0070] 1. After completing the learning of the gear limit position, proceed to the learning of the gear engagement point KP position.
[0071] 2. Control the drive motor to enter the torque control mode. The torque demand value is 15Nm when the no-load speed reaches 30rpm. (When in gear, although the drive motor has torque demand and actual torque, because it is in gear (the parking brake is applied, the vehicle cannot move, and the transmission output shaft speed is 0, the drive motor is temporarily blocked), so its drive motor speed is 0). After the actual torque of the motor reaches the set torque, proceed to the next step.
[0072] 3. Based on the adaptive fuzzy PID control method, the shift actuator is controlled to move to the KP point position. The control target is that the actual speed of the drive motor reaches 30 rpm, which means that the gear has moved from the engaged position to the disengaged position.
[0073] Establish adaptive fuzzy rules:
[0074] When the actual speed of the drive motor is far from the target value, the KP coefficient and KI coefficient of the PID controller are also large, so that the actuator can quickly approach the target position;
[0075] When the actual speed of the drive motor is closer to the target value, the KP coefficient and KI coefficient of the PID controller are also smaller, so that the actuator can move closer to the target position to prevent overshoot;
[0076] When the actual speed of the drive motor reaches the target value, the KP coefficient and KI coefficient of the PID controller are 0, so that the actuator can stop accurately at the target position;
[0077] Record the current location information and KP location learning is completed.
[0078] 4. Repeat the above steps to learn the limit positions and KP positions of 2nd gear, 3rd gear, and 4th gear respectively.
[0079] like Figure 3 As shown, a gear self-learning device is shown.
[0080] The present disclosure provides another gear self-learning device, which is used to execute the gear self-learning method described in the above embodiment. Figure 4 As shown, the device includes: a first control unit 401, which is configured to control the shift actuator to move in the gear-engaging direction of the target gear to be learned by the vehicle, and if the shift actuator has entered the target gear, adjust the speed or torque of the drive motor to 0, and the target gear is a non-zero gear; an adjustment unit 402, which is configured to dynamically adjust the control coefficient of the preset controller according to the relationship between the actual value and the target value of the gear during the movement toward the gear-engaging direction of the target gear; a second control unit 403, which is configured to control the shift actuator to stop moving at the first current position if the control coefficient reaches 0; a determination unit 404, which is configured to determine and record the extreme stall position of the target gear as a result of gear self-learning based on the first current position.
[0081] The gear self-learning device provided in the above-mentioned embodiment of the present disclosure and the gear self-learning method provided in the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, run or implemented by the application programs stored therein.
[0082] The embodiment of the present disclosure further provides an electronic device corresponding to the gear position self-learning method provided in the above embodiment, so as to execute the above gear position self-learning method.
[0083] Please refer to Figure 5, which shows a schematic diagram of an electronic device provided by some embodiments of the present disclosure. Figure 5 As shown, the electronic device 50 includes: a processor 500, a memory 501, a bus 502 and a communication interface 503, and the processor 500, the communication interface 503 and the memory 501 are connected via the bus 502; the memory 501 stores a computer program that can be run on the processor 500, and when the processor 500 runs the computer program, it executes the method provided in any of the aforementioned embodiments of the present disclosure.
[0084] The memory 501 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. The system network element and at least one other network element are connected via at least one communication interface 503 (which may be wired or wireless), and may use the Internet, a wide area network, a local area network, a metropolitan area network, or the like.
[0085] Bus 502 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. Memory 501 is used to store programs, and processor 500 executes the programs upon receiving execution instructions. The gear self-learning method disclosed in any of the aforementioned embodiments of the present disclosure may be applied to processor 500 or implemented by processor 500.
[0086] The processor 500 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method may be completed by hardware integrated logic circuits or software instructions in the processor 500. The processor 500 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present disclosure may be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 501 , and the processor 500 reads the information in the memory 501 and completes the steps of the above method in combination with its hardware.
[0087] The electronic device provided by the embodiment of the present disclosure and the gear self-learning method provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented by them.
[0088] The present disclosure also provides a computer-readable storage medium corresponding to the gear self-learning method provided in the above embodiment. Figure 6 The computer-readable storage medium shown is a CD 60 on which a computer program (ie, a program product) is stored. When the computer program is run by the processor, it will execute the gear self-learning method provided by any of the aforementioned embodiments.
[0089] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.
[0090] The computer-readable storage medium provided by the above-mentioned embodiment of the present disclosure and the gear self-learning method provided by the embodiment of the present disclosure are based on the same inventive concept and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.
[0091] It should be noted that:
[0092] In the above text, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present disclosure is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.
[0093] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present disclosure.
[0094] The embodiments of the present disclosure are described above in conjunction with the accompanying drawings, which are only specific implementation methods of the present disclosure. However, the present disclosure is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present disclosure, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present disclosure and the claims, which are all within the protection of the present disclosure.
Claims
1. A gear self-learning method, characterized in that: include: For the target gear to be learned by the vehicle, controlling the shift actuator corresponding to the target gear to move in the gear-engaging direction of the target gear, and if the shift actuator has entered the target gear, adjusting the speed or torque of the drive motor to 0, and the target gear is a non-zero gear; During the movement toward the target gear, the control coefficient of the preset controller is dynamically adjusted according to the relationship between the actual value and the target value of the gear. If the control coefficient reaches 0, the shift actuator is controlled to stop moving at the first current position; According to the first current position, the limit stall position of the target gear is determined and recorded as a result of gear self-learning.
2. The method according to claim 1, characterized in that The dynamically and adaptively adjusting the control coefficient of the preset controller according to the relationship between the actual value and the target value of the gear position includes: In the case where the actual value of the gear position is less than the target value, if the difference between the actual value of the gear position and the target value is within a preset large difference range, an adaptive fuzzy control method is adopted to increase the control coefficient; In the case where the actual value of the gear position is less than the target value, if the difference between the actual value of the gear position and the target value is within a preset small difference range, an adaptive fuzzy control method is adopted to adaptively reduce the control coefficient; When the actual value of the gear position is greater than the target value, an adaptive fuzzy control method is adopted to adjust the control coefficient to a negative value.
3. The method according to claim 1, characterized in that For the target gear position to be learned by the vehicle, controlling the shift actuator to move toward the gear engagement direction of the target gear position includes: In response to all the shift actuators of the vehicle being in the neutral position and controlling the drive motor to rotate at a preset low speed in the first rotation direction, if the drive motor feedback is operating normally, then for the target gear to be learned by the vehicle, the shift actuator corresponding to the target gear is controlled to move in the gear engagement direction of the target gear.
4. The method according to claim 1, wherein The controlling the shift actuator to stop moving at the first current position includes: Determine the change of the gear position signal; If the change condition is that the signal no longer changes and continues for a preset time period, the shift actuator is controlled to stop moving at the current position.
5. The method according to claim 1, wherein The method further comprises: Controlling the drive motor to enter a torque control mode, and adopting an adaptive fuzzy control method to control the shift actuator to move toward the meshing point of the transmission if the torque reaches a preset torque corresponding to a preset low speed; If it is determined by detecting the actual speed of the drive motor that the current gear has reached the disengaged position from the engaged position, the control coefficient of the preset controller is dynamically adjusted according to the difference between the actual value and the target value of the speed; If the difference between the actual value and the target value of the rotational speed is 0, the shift actuator stops moving at the second current position by controlling the control coefficient to 0; According to the second current position, the gear engagement point position of the target gear is determined and recorded as a result of gear self-learning.
6. The method according to claim 5, characterized in that Dynamically adjusting the control coefficient of the preset controller according to the difference between the actual value and the target value of the speed includes: When the actual value of the speed is less than the target value, if the difference between the actual value of the speed and the target value is within a preset large difference range, an adaptive fuzzy control method is adopted to increase the control coefficient; In the case where the actual value of the rotational speed is less than the target value, if the difference between the actual value of the rotational speed and the target value is within a preset small difference interval, an adaptive fuzzy control method is adopted to reduce the control coefficient.
7. The method according to claim 1, characterized in that The method further comprises: In response to the shift finger having moved to the theoretical neutral position, controlling the preset drive motor to adopt a speed control mode to determine whether a no-load operation condition of the preset drive motor is met; If the conditions are met, the neutral gear recording step is performed: according to the position indicated by the shift finger, the neutral gear position is determined and recorded as the result of the gear self-learning.
8. The method according to claim 7, characterized in that The method further comprises: If not, the shift finger is moved to the right to determine again whether the preset no-load running condition of the drive motor is met; If the condition is still not satisfied, the shift finger is moved to the left, and it is determined again whether the preset no-load running condition of the drive motor is satisfied. If so, the neutral gear recording step is executed.
9. A gear self-learning device, characterized in that: The device for executing the gear self-learning method according to any one of claims 1 to 8 comprises: a judging unit configured to judge whether a current vehicle state of the vehicle satisfies a self-learning condition; A drive motor and a control unit thereof, configured to control the drive motor to operate based on a speed control mode or a torque control mode; an actuator unit of the actuator, configured to drive the shift finger to move; The control unit of the actuator is configured to control the control current of the actuator, monitor the actual value and target value of the gear to which the actuator moves, and record the result of gear self-learning.
10. A gear self-learning device, characterized in that: include: a first control unit configured to control the shift actuator to move in a gear-engaging direction of the target gear to be learned by the vehicle, and to adjust the speed or torque of the drive motor to 0 if the shift actuator has entered the target gear, and the target gear is a non-zero gear; an adjusting unit configured to dynamically adjust a control coefficient of the preset controller according to a relationship between an actual value of the gear and a target value during the movement toward the target gear engagement direction; a second control unit configured to control the shift actuator to stop moving at a first current position if the control coefficient reaches 0; The determining unit is configured to determine and record the limit stall position of the target gear as a result of gear self-learning based on the first current position.