A selection self-learning method and device for a wet clutch automatic transmission

Abstract

The application discloses a selection self-learning method and device for a wet clutch automatic transmission, and the method comprises the following steps: determining the theoretical displacement of each position in a selection actuator and the theoretical total stroke of a selection slider; performing a first selection operation when an electromagnet is in a preset state; if the difference between the actual displacement of the last position and the actual displacement of the first position in the first selection operation is greater than or equal to the theoretical total stroke, then self-learning the relationship among the pulse width modulation signal, the power supply voltage and the current of the electromagnet; determining the preferred state of the electromagnet according to the self-learning result, and obtaining the fine selection displacement of all positions based on the current-displacement relationship curve obtained by performing a second selection operation in the preferred state; performing a gear engagement operation based on the fine selection displacement; and if the gear engagement operation of all positions is successful, then taking the fine selection displacement of each position as the corresponding displacement setting value. The application can quickly and accurately select the correct and suitable selection position displacement point.

Description

Technical Field

[0001] This application relates to the field of transmission technology, and more specifically, to a method and apparatus for self-learning gear selection in a wet clutch automatic transmission. Background Technology

[0002] Currently, in the commercial vehicle market, the gear selection actuators of automatic transmissions (AMT) are mainly powered by hydraulics, pneumatics, or electric motors. With the trend towards electrification, hydraulic and pneumatic systems will gradually be phased out, and while electric motor shifting offers better control precision, it is less efficient. To meet the demands of commercial vehicle applications, some wet clutch automatic transmissions are adopting electromagnet shifting, which aligns with the electrification trend, improves efficiency, and reduces costs.

[0003] like Figure 1 As shown, the gear selection system of the wet clutch automatic transmission consists of a gear selection actuator, a displacement sensor 20, and an electromagnet 10. The gear selection actuator has four positions (positions 1-4), distinguished by springs with different stiffness coefficients (e.g., springs 40-60). The gear selection control objective is to quickly and accurately control the gear selection slider 30 to achieve the corresponding position displacement according to the gear selection requirements. Simultaneously, the output torque of the electromagnet 10 is strongly correlated with the displacement; therefore, the accuracy of the four position displacements is crucial to achieving the gear shifting objective.

[0004] Since the target accuracy of gear selection displacement is affected by errors in the actuator, displacement sensor, and electromagnet output torque, it is necessary to learn from these errors in the system. However, current learning methods only learn from the relevant hardware errors and cannot account for the impact of errors in the power source control. Summary of the Invention

[0005] This application provides a gear selection self-learning method and device for a wet clutch automatic transmission. Based on the relationship between the pulse width modulation signal of the control electromagnet, the supply voltage and the current obtained through self-learning, the method controls the change of the electromagnet current during the gear selection process, quickly and accurately selects the correct and appropriate gear selection position displacement point, improves the software control precision, and the accurate gear selection displacement can also ensure the consistency, reliability, safety and stability of the wet clutch automatic transmission and the finished vehicle.

[0006] This application provides a self-learning method for gear selection in a wet clutch automatic transmission, including:

[0007] Based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission, the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider are determined. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position.

[0008] The first gear selection operation is performed when the electromagnet is in the preset state;

[0009] If the difference between the actual displacement of the last position and the actual displacement of the first position in the first gear selection operation is greater than or equal to the theoretical total stroke, then the relationship between the pulse width modulation signal, the power supply voltage and the current of the self-learning control electromagnet is established.

[0010] The optimal state of the electromagnet is determined based on the self-learning results, and the selected displacement of all positions is obtained based on the current-displacement relationship curve obtained by performing the second gear selection operation under the optimal state.

[0011] Gear shifting is performed based on carefully selected displacement;

[0012] If all gear shifting operations are successful, the selected displacement for each position will be used as the corresponding displacement setting value.

[0013] Preferably, the preset state is that the pulse width modulation signal controlling the electromagnet is 100%, and the power supply voltage is at its maximum value.

[0014] Preferably, the selected displacement for all positions is obtained based on the current-displacement relationship curve obtained by performing the second gear selection operation under the preferred state, specifically including:

[0015] Determine the initial displacement value at each position based on the current-displacement relationship curve;

[0016] The optimal displacement is determined based on the initial displacement value at each location and the corresponding gear selection design tolerance.

[0017] Preferably, the correspondence between the pulse width modulation signal, supply voltage, and current of the self-learning control electromagnet specifically includes:

[0018] Based on historical data, a preliminary determination has been made of the relationship between the pulse width modulation signal and the supply voltage while maintaining a linear change in current.

[0019] The relationship between pulse width modulation signal and supply voltage was verified through practical operation to obtain the correspondence between pulse width modulation signal, supply voltage and current.

[0020] Preferably, the relationship between the pulse width modulation signal and the supply voltage is verified through practical operation to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current, specifically including:

[0021] Based on the initial state, keep the pulse width modulation signal unchanged, adjust the supply voltage in a gradient, and keep the current changing linearly;

[0022] Based on the relationship between the pulse width modulation signal and the supply voltage, the supply voltage and the pulse width modulation signal are adjusted simultaneously to make the current continue to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

[0023] This application also provides a gear selection self-learning device for a wet clutch automatic transmission, including a theoretical parameter determination module, a first gear selection operation module, a self-learning module, a gear selection displacement acquisition module, a gear engagement operation module, and a confirmation module;

[0024] The theoretical parameter determination module is used to determine the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position.

[0025] The first gear selection operation module is used to perform the first gear selection operation when the electromagnet is in a preset state;

[0026] The self-learning module is used to learn the relationship between the pulse width modulation signal, supply voltage, and current of the electromagnet when the difference between the actual displacement of the last position and the actual displacement of the first position is greater than or equal to the theoretical total stroke during the first gear selection operation.

[0027] The selected displacement acquisition module is used to determine the preferred state of the electromagnet based on the self-learning results, and obtain the selected displacement of all positions based on the current-displacement relationship curve obtained by performing the second gear selection operation under the preferred state;

[0028] The gear shifting module is used to perform gear shifting operations based on the selected displacement;

[0029] The confirmation module is used to set the selected displacement for each position as the corresponding displacement setting value when the gear shifting operation is successful in all positions.

[0030] Preferably, the preset state is that the pulse width modulation signal controlling the electromagnet is 100%, and the power supply voltage is at its maximum value.

[0031] Preferably, the selected displacement acquisition module includes an initial value determination module and a selected displacement determination module;

[0032] The initial value determination module is used to determine the initial displacement value at each position based on the current-displacement relationship curve;

[0033] The selected displacement determination module is used to determine the corresponding selected displacement based on the initial displacement value at each position and the corresponding gear selection design tolerance.

[0034] Preferably, the self-learning module includes a preliminary determination module and a practical confirmation module;

[0035] The preliminary determination module is used to preliminarily determine the relationship between the pulse width modulation signal and the supply voltage while maintaining linear current variation based on historical data;

[0036] The practical verification module is used to verify the relationship between the pulse width modulation signal and the supply voltage, and to obtain the correspondence between the pulse width modulation signal, the supply voltage and the current.

[0037] Preferably, the practical verification module includes a first adjustment module and a second adjustment module;

[0038] The first adjustment module is used to maintain the pulse width modulation signal unchanged from the initial state, adjust the supply voltage in a gradient, and maintain the linear change of current.

[0039] The second adjustment module is used to simultaneously adjust the supply voltage and the pulse width modulation signal based on the relationship between the pulse width modulation signal and the supply voltage, so that the current continues to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

[0040] Other features and advantages of this application will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the present application and, together with their description, serve to explain the principles of the present application.

[0042] Figure 1 This is a structural diagram of the gear selection system for a wet clutch automatic transmission.

[0043] Figure 2 A flowchart of the gear selection self-learning method for the wet clutch automatic transmission provided in this application;

[0044] Figure 3 The current-displacement relationship curve obtained for the first gear selection operation provided in this application;

[0045] Figure 4 The relationship between the pulse width modulation signal for controlling the electromagnet, the supply voltage and the current obtained through self-learning, and the current-displacement relationship curve obtained by the second gear selection operation are provided in this application.

[0046] Figure 5 A schematic diagram illustrating the principle of obtaining selected displacements at all positions, provided for this application;

[0047] Figure 6 A structural diagram of the gear selection self-learning device for the wet clutch automatic transmission provided in this application. Detailed Implementation

[0048] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0049] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0050] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0051] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0052] This application provides a gear selection self-learning method and device for a wet clutch automatic transmission. Based on the relationship between the pulse width modulation signal of the control electromagnet, the supply voltage and the current obtained through self-learning, the method controls the change of the electromagnet current during the gear selection process to quickly and accurately select the correct and appropriate gear selection position displacement point. At the same time, it corrects the relationship between the control current and displacement of the electromagnet, improves the software control accuracy, and the accurate gear selection displacement can also ensure the consistency, reliability, safety and stability of the wet clutch automatic transmission and the finished vehicle.

[0053] like Figure 2 As shown, the gear selection self-learning method for a wet clutch automatic transmission provided in this application includes:

[0054] S210: Based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission, determine the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position.

[0055] exist Figure 1 In the embodiment shown, the theoretical displacement of each position is the displacement of the mechanical center point of that position relative to the base point, denoted as S11, S21, S31 and S41. The theoretical total stroke S is the difference between the theoretical displacement S41 of position 4 (the last position) and the theoretical displacement S11 of position 1 (the first position).

[0056] S220: Perform the first gear selection operation when the electromagnet is in the preset state.

[0057] As an example, the preset state is that the pulse-width modulation (PWM) signal controlling the electromagnet is 100% and the supply voltage V is at its maximum value, so as to eliminate the resistance of the movement path.

[0058] Under these conditions, the gear selection slider is pushed to move through its full stroke, achieving the first gear selection operation. During the gear selection operation, the signal and current feedback value from the displacement sensor are recorded to obtain... Figure 3 The current-displacement relationship curve is shown. Figure 3 As shown, the current exhibits a trend of first rising, then falling, then rising again, and finally holding steady. The displacement linearity between positions 1-4 is good, with no issues such as stuttering. The actual displacements of positions 1-4 are denoted as S12, S22, S32, and S42.

[0059] S230: If the difference between the actual displacement S42 of the last position and the actual displacement S12 of the first position in the first gear selection operation is greater than or equal to the theoretical total stroke S (i.e., S42-S12≥S), then the relationship between the pulse width modulation signal, the power supply voltage and the current of the self-learning control electromagnet is determined.

[0060] As an example, the correspondence between the pulse width modulation signal, supply voltage, and current of the self-learning control electromagnet specifically includes:

[0061] S2301: Based on historical data, the relationship between the pulse width modulation signal and the supply voltage is initially determined while maintaining linear current variation, in order to learn the relationship between different supply voltages, different PWM signals, and current. Learning from historical data can improve the learning efficiency of self-learning.

[0062] S2302: Conduct practical verification of the relationship between the pulse width modulation signal and the supply voltage to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current.

[0063] As an example, the relationship between the pulse width modulation signal and the supply voltage is verified through practical operation to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current, specifically including:

[0064] P1: Based on the initial state, keep the pulse width modulation signal unchanged, adjust the supply voltage in a gradient, and keep the current changing linearly.

[0065] As an example, such as Figure 4 As shown, the electromagnet is initially controlled with a small PWM (15%) and a small supply voltage (6V). The PWM is kept constant, and the supply voltage is increased in increments of 1V to keep the current changing linearly.

[0066] P2: Based on the relationship between the pulse width modulation signal and the supply voltage, the supply voltage and the pulse width modulation signal are adjusted simultaneously to make the current continue to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

[0067] Based on step P1, according to the relationship between the pulse width modulation signal and the supply voltage, the supply voltage and PWM are continuously increased at a certain gradient, while maintaining a linear change in current, until the relationship between different allowable supply voltages and PWM is confirmed. Figure 4 As shown, the black curve represents the PWM and voltage control profile, the blue rectangle reflects the PWM and voltage changes, and the red curve represents the current curve.

[0068] As an example, the maximum PWM is 60%.

[0069] Preferably, before self-learning, the gear selection system needs to be checked. Self-learning can only be performed if the system power supply meets the design requirements and there are no other faults in the system that would affect self-learning.

[0070] S240: Determine the optimal state of the electromagnet based on the self-learning results, and obtain the selected displacement for all positions based on the current-displacement relationship curve obtained by performing the second gear selection operation under the optimal state.

[0071] Specifically, based on the correspondence between the pulse width modulation signal, the supply voltage, and the current in the self-learning results, a specific supply voltage and a specific PWM with a corresponding relationship are determined as the preferred state of the electromagnet.

[0072] As an example, the specific supply voltage is 24V, and the specific PWM is 60%. Under these conditions, the gear selection slider is pushed to move through its full stroke to achieve the second gear selection operation. During the gear selection operation, the signal and current feedback value of the displacement sensor are recorded, and the obtained current-displacement relationship curve is shown below. Figure 4 The curves within the green rectangle are shown, with the purple curve representing the displacement curve. (See image.) Figure 4 As shown, due to the gear selection operation, the current curve fluctuates (i.e., changes non-linearly) from the point corresponding to position 1. At positions 2, 3, and 4, there is a trough in the current curve.

[0073] As one embodiment, the selected displacement for all positions is obtained based on the current-displacement relationship curve obtained by performing the second gear selection operation under the preferred state, specifically including:

[0074] S2401: Determine the initial displacement value at each position based on the current-displacement relationship curve.

[0075] like Figure 5As shown, the point where the current begins to change nonlinearly corresponds to position 1, and the corresponding value on the displacement curve is the initial displacement value S13 for position 1. The first trough of the current fluctuation corresponds to position 2, and the corresponding value on the displacement curve is the initial displacement value S23 for position 2. The second trough of the current fluctuation corresponds to position 3, and the corresponding value on the displacement curve is the initial displacement value S33 for position 3. The third trough of the current fluctuation corresponds to position 4, and the corresponding value on the displacement curve is the initial displacement value S43 for position 4.

[0076] S2402: Determine the corresponding selected displacement based on the initial displacement value at each position and the corresponding gear selection design tolerance.

[0077] like Figure 5 As shown, the design tolerance for position 1 is ΔS1. Therefore, S13 + ΔS1 is taken as the selected displacement for position 1, as follows: Figure 5 The self-learning position 1 displacement is shown. The selection design tolerance for position 2 is ΔS2, then S23 - ΔS2 is taken as the selected displacement for position 2, as shown... Figure 5 The self-learning position 2 displacement is shown. The selection design tolerance for position 3 is ΔS3, then S33-ΔS3 is taken as the selected displacement of position 3, as shown. Figure 5 The self-learning position 3 displacement is shown. The selection design tolerance for position 4 is ΔS4, then S43-ΔS4 is taken as the selected displacement for position 4, as shown. Figure 5 The self-learning position 4 displacement is shown in the figure.

[0078] S250: Gear shifting operation is based on selected displacement.

[0079] S260: If all gear shifting operations are successful, the selected displacement for each position will be used as the corresponding displacement setting value.

[0080] After obtaining the selected displacement, it is stored and retrieved, and the gear shifting in the four positions is verified and confirmed. If the gear shifting is successful, it means that the gear selection self-learning is successful. If the gear shifting in any position is unsuccessful, the self-learning is restarted.

[0081] Based on the above, this application also provides a gear selection self-learning device for a wet clutch automatic transmission. For example... Figure 6 As shown, the gear selection self-learning device includes a theoretical parameter determination module 610, a first gear selection operation module 620, a self-learning module 630, a selected displacement acquisition module 640, a gear engagement operation module 650, and a confirmation module 660.

[0082] The theoretical parameter determination module 610 is used to determine the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position.

[0083] The first gear selection operation module 620 is used to perform the first gear selection operation when the electromagnet is in a preset state.

[0084] The self-learning module 630 is used to learn the relationship between the pulse width modulation signal, supply voltage, and current of the control electromagnet when the difference between the actual displacement of the last position and the actual displacement of the first position in the first gear selection operation is greater than or equal to the theoretical total stroke.

[0085] The selected displacement acquisition module 640 is used to determine the preferred state of the electromagnet based on the self-learning results, and to obtain the selected displacement of all positions based on the current-displacement relationship curve obtained by performing the second gear selection operation under the preferred state.

[0086] The gear shifting module 650 is used for gear shifting operations based on selected displacement.

[0087] The confirmation module 660 is used to set the selected displacement of each position as the corresponding displacement setting value when the gear shifting operation is successful in all positions.

[0088] Preferably, the preset state is that the pulse width modulation signal controlling the electromagnet is 100%, and the power supply voltage is at its maximum value.

[0089] Preferably, the selected displacement acquisition module 640 includes an initial value determination module 6401 and a selected displacement determination module 6402.

[0090] The initial value determination module 6401 is used to determine the initial displacement value at each position based on the current-displacement relationship curve.

[0091] The selected displacement determination module 6402 is used to determine the corresponding selected displacement based on the initial displacement value at each position and the corresponding gear selection design tolerance.

[0092] Preferably, the self-learning module 630 includes a preliminary determination module 6301 and a practical confirmation module 6302.

[0093] The preliminary determination module 6301 is used to preliminarily determine the relationship between the pulse width modulation signal and the supply voltage while maintaining the linear change of the current, based on historical data.

[0094] The practical verification module 6302 is used to perform practical verification of the relationship between the pulse width modulation signal and the supply voltage, and to obtain the correspondence between the pulse width modulation signal, the supply voltage and the current.

[0095] Preferably, the practical confirmation module 6302 includes a first adjustment module and a second adjustment module.

[0096] The first adjustment module is used to maintain the pulse width modulation signal unchanged from the initial state, adjust the supply voltage in a gradient, and maintain the linear change of current.

[0097] The second adjustment module is used to simultaneously adjust the supply voltage and the pulse width modulation signal based on the relationship between the pulse width modulation signal and the supply voltage, so that the current continues to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

[0098] This application utilizes the current change during the full stroke of the gear selector slider to determine the precise displacement at each position. By leveraging the relationship between current and displacement changes, it achieves self-learning of mechanical position displacement, integrating the errors of hardware and software control, improving the accuracy of software control and gear selector displacement, and ensuring the consistency, reliability, safety, and stability of the wet clutch automatic transmission and the finished vehicle.

[0099] While specific embodiments of this application have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and are not intended to limit the scope of this application. Those skilled in the art should understand that modifications can be made to the above embodiments without departing from the scope and spirit of this application. The scope of this application is defined by the appended claims.

Claims

1. A self-learning method for gear selection in a wet clutch automatic transmission, characterized in that, include: Based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission, the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider are determined. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position. The first gear selection operation is performed when the electromagnet is in the preset state; If the difference between the actual displacement of the last position and the actual displacement of the first position in the first gear selection operation is greater than or equal to the theoretical total stroke, then the relationship between the pulse width modulation signal, the power supply voltage and the current of the self-learning control electromagnet is established. The optimal state of the electromagnet is determined based on the self-learning results, and the optimal displacement for all positions is obtained by performing a second gear selection operation based on the optimal state to obtain the current-displacement relationship curve. The self-learning results include the correspondence between the pulse width modulation signal controlling the electromagnet, the supply voltage, and the current. Specifically, based on historical data, the relationship between the pulse width modulation signal and the supply voltage is initially determined while maintaining linear current change. The relationship between the pulse width modulation signal and the supply voltage is then experimentally verified to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current. The gear shifting operation is performed based on the selected displacement; If all gear shifting operations are successful, the selected displacement for each position will be used as the corresponding displacement setting value.

2. The self-learning method for gear selection of a wet clutch automatic transmission according to claim 1, characterized in that, The preset state is that the pulse width modulation signal of the control electromagnet is 100% and the power supply voltage is at its maximum value.

3. The gear selection self-learning method for a wet clutch automatic transmission according to claim 1, characterized in that, Based on the current-displacement relationship curve obtained by performing the second gear selection operation under the preferred state, the selected displacement at all positions is obtained, specifically including: The initial displacement value at each position is determined based on the current-displacement relationship curve. The optimal displacement is determined based on the initial displacement value at each location and the corresponding gear selection design tolerance.

4. The gear selection self-learning method for a wet clutch automatic transmission according to claim 1, characterized in that, The relationship between the pulse width modulation signal and the supply voltage was verified through practical operation to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current, specifically including: Based on the initial state, keep the pulse width modulation signal unchanged, adjust the supply voltage in a gradient, and keep the current changing linearly; Based on the relationship between the pulse width modulation signal and the supply voltage, the supply voltage and the pulse width modulation signal are adjusted simultaneously so that the current continues to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

5. A gear selection self-learning device for a wet clutch automatic transmission, characterized in that, It includes a theoretical parameter determination module, a first gear selection operation module, a self-learning module, a fine displacement acquisition module, a gear shifting operation module, and a confirmation module; The theoretical parameter determination module is used to determine the theoretical displacement of each position in the gear selection actuator and the theoretical total stroke of the gear selection slider based on the structure and characteristics of the gear selection system of the wet clutch automatic transmission. The theoretical total stroke is the difference between the theoretical displacement of the last position and the theoretical displacement of the first position. The first gear selection module is used to perform the first gear selection operation when the electromagnet is in a preset state; The self-learning module is used to learn the relationship between the pulse width modulation signal, power supply voltage, and current of the control electromagnet when the difference between the actual displacement of the last position and the actual displacement of the first position in the first gear selection operation is greater than or equal to the theoretical total stroke. The selected displacement acquisition module is used to determine the preferred state of the electromagnet based on the self-learning results, and to obtain the selected displacement for all positions based on the current-displacement relationship curve obtained by performing a second gear selection operation under the preferred state. The self-learning results include the correspondence between the pulse width modulation signal controlling the electromagnet, the supply voltage, and the current. Specifically, it involves: initially determining the relationship between the pulse width modulation signal and the supply voltage while maintaining linear current change based on historical data; and then verifying the relationship between the pulse width modulation signal and the supply voltage through practical operation to obtain the correspondence between the pulse width modulation signal, the supply voltage, and the current. The gear shifting module is used to perform gear shifting operations based on the selected displacement. The confirmation module is used to set the selected displacement of each position as the corresponding displacement setting value when the gear shifting operation is successful in all positions.

6. The gear selection self-learning device for a wet clutch automatic transmission according to claim 5, characterized in that, The preset state is that the pulse width modulation signal of the control electromagnet is 100% and the power supply voltage is at its maximum value.

7. The gear selection self-learning device for a wet clutch automatic transmission according to claim 5, characterized in that, The selected displacement acquisition module includes an initial value determination module and a selected displacement determination module; The initial value determination module is used to determine the initial displacement value at each position based on the current-displacement relationship curve. The selected displacement determination module is used to determine the corresponding selected displacement based on the initial displacement value at each position and the corresponding gear selection design tolerance.

8. The gear selection self-learning device for a wet clutch automatic transmission according to claim 5, characterized in that, The self-learning module includes a preliminary determination module and a practical confirmation module; The preliminary determination module is used to preliminarily determine the relationship between the pulse width modulation signal and the supply voltage while maintaining linear change in current, based on historical data. The practical verification module is used to perform practical verification of the relationship between the pulse width modulation signal and the supply voltage, and to obtain the correspondence between the pulse width modulation signal, the supply voltage and the current.

9. The gear selection self-learning device for a wet clutch automatic transmission according to claim 8, characterized in that, The practical operation confirmation module includes a first adjustment module and a second adjustment module; The first adjustment module is used to maintain the pulse width modulation signal unchanged, adjust the supply voltage in a gradient, and maintain the linear change of current based on the initial state; The second adjustment module is used to simultaneously adjust the supply voltage and the pulse width modulation signal based on the relationship between the pulse width modulation signal and the supply voltage, so that the current continues to change linearly until the correspondence between all supply voltages and all pulse width modulation signals is determined.

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