CN112923051B - Self-learning detection method for position of EOL shifting fork - Google Patents
Self-learning detection method for position of EOL shifting fork Download PDFInfo
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- CN112923051B CN112923051B CN202110069132.XA CN202110069132A CN112923051B CN 112923051 B CN112923051 B CN 112923051B CN 202110069132 A CN202110069132 A CN 202110069132A CN 112923051 B CN112923051 B CN 112923051B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H63/00—Control outputs from the control unit to change-speed- or reversing-gearings for conveying rotary motion or to other devices than the final output mechanism
- F16H63/02—Final output mechanisms therefor; Actuating means for the final output mechanisms
- F16H63/30—Constructional features of the final output mechanisms
- F16H63/32—Gear shift yokes, e.g. shift forks
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16H—GEARING
- F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
- F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
- F16H2061/0087—Adaptive control, e.g. the control parameters adapted by learning
Abstract
The invention particularly relates to a self-learning detection method for an EOL shifting fork position, which comprises the following steps of: writing the original shifting fork position during the assembly of the transmission into a memory, and reading and recording the current assembly position of the shifting fork as the neutral position of the shifting fork on the basis of the original shifting fork position; a limiting position step: pushing a shifting fork to move to the extreme position of the shifting fork by preset pressure, and waiting for a first preset time; if the moving speed of the shifting fork is 0, the shifting fork is considered to move successfully; otherwise, the self-learning of the shifting fork position is determined to fail; a gear position step: after the shifting fork successfully moves, releasing the pressure acting on the shifting fork for a second preset time; if the moving speed of the shifting fork is 0 and the position of the shifting fork is within the position range of the gear, the current shifting fork position is considered to be the gear position of the shifting fork; otherwise, the shift fork position is determined to be failed to learn, and the shift fork or the transmission needs to be maintained. Therefore, the shifting fork position self-learning can be efficiently completed, and the accuracy of the self-learning result is high.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a self-learning detection method for an EOL shifting fork position.
Background
The double-clutch transmission has the advantage that the power cannot be interrupted in the gear shifting process, and is valued by various domestic enterprises. The synchronizer is a core component of the double-clutch transmission, and the shifting fork drives the synchronizer to move so as to realize gear shifting action.
In the prior art, different gear engaging forces are calculated on the basis of a target position and a rotating speed difference of a synchronizer to realize gear disengagement and gear engagement, and after each action is finished, a neutral position and an on-gear position of a shifting fork are acquired. However, due to external factors such as assembling differences and burrs, the normal gear engaging force may cause the gear disengaging and engaging process to be blocked, and the self-learning failure rate of the shifting fork is high.
Disclosure of Invention
The invention aims to provide a self-learning detection method for the position of an EOL shifting fork, which can efficiently complete the self-learning of the position of the shifting fork and has high accuracy of the self-learning result.
Embodiments of the invention may be implemented as follows:
in a first aspect, the invention provides a self-learning detection method for the position of an EOL shifting fork, which is used for self-learning of the shifting fork of a double-clutch transmission and comprises the following steps:
neutral position step: writing the original shifting fork position during the assembly of the transmission into a memory, and reading and recording the current assembly position of the shifting fork as the neutral position of the shifting fork on the basis of the original shifting fork position;
a limiting position step: pushing a shifting fork to move to the extreme position of the shifting fork by preset pressure, and waiting for a first preset time; if the moving speed of the shifting fork is 0, the shifting fork is considered to move successfully; otherwise, the self-learning of the shifting fork position is determined to fail;
a gear position step: after the shifting fork successfully moves, releasing the pressure acting on the shifting fork for a second preset time; if the shifting fork moving speed is 0 and the position of the shifting fork is within the position range of the gear, the current shifting fork position is considered to be the gear position of the shifting fork; otherwise, the shift fork position is determined to be failed to learn, and the shift fork or the transmission needs to be maintained.
According to the method, the original shifting fork position of the transmission assembly is recorded as the neutral position of the shifting fork, and the original position of the shifting fork is set and configured accurately through the tool clamp and the inspection equipment when the transmission is assembled, so that the accuracy of the neutral position of the shifting fork during self-learning of the position of the shifting fork can be guaranteed, the accuracy of the limiting position and the shifting fork of the subsequent shifting fork in the gear position is further guaranteed, and the accuracy of the whole self-learning result is further improved. And extreme position step promotes the shift fork to extreme position with predetermineeing pressure, so can enlarge the removal stroke of shift fork, eliminate assembly error and the first gear shifting jamming of derailleur that little burr leads to, further improved the success rate of self-learning of shift fork. The gear position step is to obtain the gear position of the shifting fork by testing the speed of the shifting fork after the second preset force release time, and the detection mode is combined with the extreme position step, so that the gear return of the shifting fork is avoided, the learning time is shortened, the gear engaging and disengaging failure rate is reduced, and the gear position of the shifting fork can be obtained efficiently and accurately. In conclusion, the EOL shifting fork position self-learning detection method has the characteristics of convenience in operation, short learning time and high accuracy of a self-learning result, and is remarkable in economic benefit.
In an optional embodiment, the EOL shift fork position self-learning detection method includes a right gear step:
pushing the shifting fork to a right limit position with preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork is located in the range of the right gear position, the current shifting fork position is considered as the right gear position, and the current shifting fork position is stored, otherwise, the self-learning of the shifting fork position fails.
In an optional embodiment, the EOL shift fork position self-learning detection method comprises a left gear step:
pushing the shifting fork to a left limit position at a preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork position is in the range of the left gear position, the current shifting fork position is considered as the left gear position, and the current shifting fork position is stored, otherwise, the self-learning of the shifting fork position fails.
In an alternative embodiment, in the left gear step: pushing the shifting fork to move from the right side to the left limit position at the gear position under preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, the self-learning of the shifting fork position is determined to fail.
In an alternative embodiment, the EOL shift fork position self-learning detection method includes a writing step:
if the neutral position step, the right gear step and the left gear step of the shifting fork are successful, writing the neutral position, the left gear position and the right gear position of the shifting fork into a storage; and if any one of the neutral position step, the right gear step and the left gear step fails, not writing into a memory.
In an optional embodiment, the EOL shift fork position self-learning detection method includes a back-empty step:
and calling a neutral gear position step, a right gear step and a left gear step in the storage device, operating the shifting fork to move, if the shifting fork returns to the range of the neutral gear position within a third preset time, considering that the self-learning of all the positions of the shifting fork is successful, otherwise, failing to self-learn the position of the shifting fork.
In an alternative embodiment, the position of the next fork is self-learned after the emptying step of the previous fork is completed.
In an alternative embodiment, the predetermined pressure is between 1000kPa and 1200 kPa.
In an alternative embodiment, the predetermined pressure is 1100 kPa.
In an alternative embodiment, the memory is a non-volatile memory.
The beneficial effects of the embodiment of the invention include, for example:
the self-learning detection method for the position of the EOL shifting fork comprises a neutral gear position step, a limit position step and a gear position step. The original shifting fork position of the transmission assembly is recorded as the neutral position of the shifting fork, and the original position of the shifting fork is accurately set and configured through the tool clamp and the inspection equipment during transmission assembly, so that the accuracy of the neutral position during self-learning of the shifting fork position can be guaranteed, the accuracy of the limiting position and the shifting fork position of the subsequent shifting fork is guaranteed, and the accuracy of the whole self-learning result is improved.
The limiting position step is to push the shifting fork to the limiting position by preset pressure, so that the moving stroke of the shifting fork can be enlarged, the assembly error and the primary gear engaging and clamping stagnation of the transmission caused by small burrs are eliminated, and the self-learning success rate of the shifting fork is further improved.
The gear position step is to obtain the gear position of the shifting fork by testing the speed of the shifting fork after the second preset force release time, and the detection mode is combined with the extreme position step, so that the gear return of the shifting fork is avoided, the learning time is shortened, the gear engaging and disengaging failure rate is reduced, and the gear position of the shifting fork can be obtained efficiently and accurately.
In conclusion, the EOL shifting fork position self-learning detection method has the characteristics of convenience in operation, short learning time and high accuracy of a self-learning result, and is remarkable in economic benefit.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic representation of a prior art dual clutch transmission;
FIG. 2 is a schematic illustration of a neutral mechanical position of a shift fork of the dual clutch transmission;
FIG. 3 is a logic diagram of a shifting fork position self-learning sequence according to an embodiment of the present invention;
FIG. 4 is a self-learning test chart of the shift fork position according to the embodiment of the invention;
fig. 5 is a schematic diagram of an EOL shift fork position self-learning detection method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.
Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
Fig. 1 is a schematic diagram of a conventional dual clutch transmission. Referring to fig. 1, the dual clutch transmission is valued by various domestic enterprises because of the advantage that power is not interrupted during the gear shifting process. The synchronizer is a core component of the dual clutch transmission, and stable and reliable operation of the synchronizer is an essential condition for stable operation of the whole vehicle.
In the process of assembling the transmission, if impurities, unqualified parts, unqualified assembly and other factors exist, gear shifting can be failed, and a vehicle cannot run normally.
In the prior art, different gear engaging forces are calculated in different stages before synchronization, in the synchronization process, after synchronization and the like on the basis of a target position and a rotating speed difference of a synchronizer, gear picking and gear engaging are realized by controlling the opening degree of an electromagnetic valve, and after each action is finished, a neutral position and an on-gear position of a shifting fork are acquired.
However, due to external factors such as assembling differences and burrs, the normal gear engaging force may cause the gear disengaging and engaging process to be blocked, and the self-learning failure rate of the shifting fork is high.
Fig. 2 is a schematic illustration of the neutral mechanical position of the shift forks of a dual clutch transmission, and it can be seen from fig. 2 that the middle wave-shaped grooves are all ranges of neutral, wherein point B is the correct neutral position.
If the shifting fork returns to the point A from the left gear or returns to the point C from the right gear, the shifting fork is considered to return to the zero, and the position of the point A or the position of the point C is not suitable as the neutral position, so that the gear picking and engaging failure rate is high. The difference of the numerical values of the neutral positions after the shifting fork left side gear and right side gear return to the neutral is large, so that the neutral position is difficult to judge, and the accuracy of a self-learning result is influenced.
In order to improve the above technical problem, a self-learning detecting method for the position of the shifting fork is provided in the following embodiments.
Fig. 3 is a logic diagram of a shift fork position self-learning sequence in the embodiment of the present invention, fig. 4 is a data test diagram of shift fork position self-learning in the embodiment of the present invention, and fig. 5 is a schematic diagram of the EOL shift fork position self-learning detection method in the embodiment of the present invention. Referring to fig. 3, 4 and 5, the embodiment provides a self-learning detection method for the position of an EOL shift fork, which is used for self-learning of a shift fork of a dual clutch transmission, and includes the following steps:
neutral position step S1: writing the original shifting fork position during the assembly of the transmission into a memory, and reading and recording the current assembly position of the shifting fork as the neutral position of the shifting fork on the basis of the original shifting fork position;
limit position step S2: pushing a shifting fork to move to the extreme position of the shifting fork by preset pressure, and waiting for a first preset time; if the moving speed of the shifting fork is 0, the shifting fork is considered to move successfully; otherwise, confirming that the self-learning of the shifting fork position fails;
at the shift position step S3: after the shifting fork successfully moves, releasing the pressure acting on the shifting fork for a second preset time; if the moving speed of the shifting fork is 0 and the position of the shifting fork is within the position range of the gear, the current shifting fork position is considered to be the gear position of the shifting fork; otherwise, the shift fork position is determined to be failed to learn, and the shift fork or the transmission needs to be maintained.
According to the detection method, the original shifting fork position of the transmission assembly is recorded as the neutral position of the shifting fork, and the original position of the shifting fork is accurately set and configured through a tooling clamp and inspection equipment during transmission assembly, so that the accuracy of the neutral position during self-learning of the shifting fork position can be guaranteed, the accuracy of the limiting position and the shifting fork position of the subsequent shifting fork is guaranteed, and the accuracy of the whole self-learning result is improved.
Because the neutral position of the shifting fork and the gear position are learned when the transmission is off line, the neutral position is directly read, the accuracy of the neutral position is guaranteed, and the method can be used as a basis for judging whether the final gear picking is successful or not, so that the accuracy of a self-learning result is improved.
The limiting position step is that the shifting fork is pushed to the limiting position by preset pressure, and the shifting is carried out by larger (preset pressure) shifting force, so that the moving stroke of the shifting fork can be enlarged, the assembly error and the primary shifting clamping stagnation of the transmission caused by small burrs are eliminated, and the self-learning success rate of the shifting fork is further improved.
The gear position step is to obtain the gear position of the shifting fork by testing the speed of the shifting fork after the second preset force release time, and the detection mode is combined with the extreme position step, so that the gear return of the shifting fork is avoided, the learning time is shortened, the gear engaging and disengaging failure rate is reduced, and the gear position of the shifting fork can be obtained efficiently and accurately. Therefore, the EOL shifting fork position self-learning detection method has the characteristics of convenience in operation, short learning time and high accuracy of a self-learning result, and is remarkable in economic benefit.
It can be understood that the eol (end of Line Testing tool) offline detector is an offline detection device used in an automobile production Line, and is used for satisfying the function detection and product configuration before the product is offline.
Further, in this embodiment, the EOL shift fork position self-learning detection method includes the step of right-side shift:
pushing the shifting fork to a right limit position with preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork is located in the range of the right gear position, the current shifting fork position is considered as the right gear position, and the current shifting fork position is stored, otherwise, the self-learning of the shifting fork position fails.
It will be understood that the right shift step includes a limit position step S2 when the shift fork is moved right and an at-shift step S3. The right-hand range position range here is a preset range value that has been obtained during the design, manufacturing and experimental stages of the transmission.
Further, in this embodiment, the method for self-learning detecting the position of the EOL shift fork includes the step of left-side gear:
pushing the shifting fork to a left limit position at a preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork position is within the range of the left gear position, the current shifting fork position is considered as the left gear position, and the position is stored, otherwise, the self-learning of the shifting fork position fails.
It will be understood that the left shift step includes a limit position step S2 when the shift fork is moved to the left and an in-shift step S3. The left range position range is here a preset range value that has been obtained during the design, manufacturing and experimental stages of the transmission.
Specifically, in the left-side gear step: pushing the shifting fork to move from the right side to the left limit position at the gear position under preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, the self-learning of the shifting fork position is determined to fail.
It should be noted that the shifting fork is directly pushed from the right side to the left limit position, the gear engaging control stage is simplified, the step of returning to the air between gears is omitted, the self-learning time is shortened, and the gear disengaging failure rate is reduced.
Further, in the embodiment of the present invention, the method for detecting the position self-learning of the EOL shift fork includes a writing step S4:
if the neutral position step, the right gear step and the left gear step of the shifting fork are successful, writing the neutral position, the left gear position and the right gear position of the shifting fork into a storage; and if any one of the neutral position step, the right side gear step and the left side gear step fails, not writing into the memory.
In the embodiment of the invention, the self-learning detection method for the position of the EOL shifting fork comprises a step of emptying S5:
and calling a neutral gear position step, a right gear step and a left gear step in the storage, operating the shifting fork to move, and if the shifting fork returns to the range of the neutral gear position (namely between the point A and the point C) within a third preset time, considering that the self-learning of all the positions of the shifting fork is successful, otherwise, failing to self-learn the position of the shifting fork.
In the emptying step, after the neutral position, the left side gear position and the right side gear position are stored, gear picking is performed, so that the accuracy of the self-learned gears is verified, and the shifting fork position is in the neutral position when the shifting fork is off the line.
In the embodiment of the invention, after the last fork is emptied, the position of the next fork is self-learned. That is, after the neutral position step S1, the limit position step S2, the shift position step S3, the write step S4, and the return to neutral step S5 are completed, the position self-learning of the next fork can be performed.
Furthermore, the self-learning of each shifting fork is independent, and the self-learning of a certain shifting fork fails, so that the self-learning of the next shifting fork cannot be influenced.
Optionally, in this embodiment, the memory is a nonvolatile memory. NVM (non Valitalmememory- -non-volatile memory).
The NVM typically includes an EEPROM or Data-Flash integrated in its TCU chip for storing Data and a Code-Flash/Program-Flash for storing Program Code/Data and a TPU extended off-chip NOR Flash or NAND-Flash. The stability and reliability of the data of the transmission can be guaranteed.
Optionally, in this embodiment of the present invention, the preset pressure is 1000kPa to 1200 kPa. Preferably, in the present embodiment, the preset pressure is 1100 kPa.
In this embodiment, the neutral position, the limit position, and the shift position of the shift fork are values obtained by mathematical model conversion/calculation. Alternatively, the shift fork position is a value converted from a voltage value. For example, the value may be a voltage value such as a high level, a low level, etc., which is merely an example and is not limited.
Further, referring to fig. 4, the current value in fig. 4 is the valve body current corresponding to the gear engaging pressure found according to the valve body characteristic PI curve, and the gear position learning stage and the gear disengaging verification stage can be distinguished according to the difference of the current shapes. Therefore, a clearer and more straight shifting fork position self-learning checking result can be obtained.
According to the detection method for self-learning the position of the EOL shifting fork, when the transmission is off-line, the gear can be shifted by using larger shifting force through software logic, the neutral assembly initial position of the shifting fork and the gear position of the shifting fork in gear can be learned, and meanwhile, the abnormal shifting fork can be detected, so that the normal transmission can be smoothly shifted in driving according to the learned position of the off-line, and the abnormal transmission can be checked out for further detection. Fig. 3 shows the position self-learning logic of each fork, and fig. 4 shows the test process when four forks respectively complete self-learning.
As shown in fig. 3, the software control steps are as follows (the four forks are respectively subjected to the following steps):
step 1: writing the original shifting fork position into the NVM, reading and recording the current assembly position of the shifting fork as the neutral position of the shifting fork on the basis, and as shown in FIG. 2, during offline assembly, the neutral position is required to be at the point B;
and 2, step: pushing the shifting fork to a right limit position with 1100kPa force, waiting for a period of time, considering that the pushing is successful if the shifting speed of the shifting fork is basically 0, otherwise, the self-learning of the position of the shifting fork fails, and at the moment, the mechanical structure is deformed, so that the right limit position is not the gear position on the right side;
and 3, step 3: force is relieved, a period of time is waited, if the moving speed of the shifting fork is basically 0 and the shifting fork is positioned in the range of the right gear position, the current shifting fork position is considered as the right gear position, and the position is stored, otherwise, the self-learning of the shifting fork position fails;
and 4, step 4: directly pushing the shifting fork from the right side to the left limit position with 1100kPa force, waiting for a period of time, considering that pushing is successful if the shifting speed of the shifting fork is basically 0, otherwise, failing self-learning of the position of the shifting fork, and deforming a mechanical structure at the moment, so that the left limit position is not the left side in the shift position;
and 5: force is relieved, a period of time is waited, if the moving speed of the shifting fork is basically 0 and the position is within the range of the left gear position, the current shifting fork position is considered as the left gear position, and the position is stored, otherwise, the self-learning of the shifting fork position fails;
step 6: if the steps are successful, writing NVM in the neutral position, the left side and the right side of the shifting fork, and if the steps fail, not writing the NVM;
and 7: and calling normal emptying logic, if the shifting fork returns to the neutral range within a certain time, considering that the self-learning of the position of the shifting fork is successful, otherwise, failing to self-learn the position of the shifting fork.
And 8: and starting the self-learning of the position of the next shifting fork. The self-learning of each shifting fork is independent, and the self-learning of a certain shifting fork fails, so that the self-learning of the next shifting fork cannot be influenced.
In summary, the embodiment of the invention provides a self-learning detection method for the position of an EOL shifting fork, which at least has the following advantages:
1. learning the neutral position and the gear position of the shifting fork when the transmission is off-line, and directly reading the neutral position for judging whether the gear is successfully picked or not;
2. the shifting is carried out by a large shifting force, the moving stroke of a shifting fork can be enlarged, the clamping stagnation of the primary shifting of the transmission caused by assembly errors and small burrs is eliminated, and the success rate of self-learning is improved;
3. the shifting fork is directly pushed to the right limit position by a large gear engaging force, and the shifting fork is directly pushed to the left limit position from the right side in the gear position, so that the gear engaging control stage is simplified, the step of returning to the air between gears is omitted, the self-learning time is shortened, and the gear disengaging failure rate is reduced;
4. after the neutral position, the left side gear position and the right side gear position are stored, the gear is picked, the accuracy of the self-learned gears is verified, and the shifting fork position is in the neutral position when the wire is off;
5. if the gear can not be successfully engaged by using larger engaging force, or the shifting fork can not be kept at the gear position, or the shifting fork acts overtime, the shifting fork has a fault, and the detected fault transmission needs to be further detected, so that the offline quality of the transmission and the driving performance of a vehicle are ensured.
The method can be used for learning the shifting fork position with higher consistency and accuracy through repeated tests of different transmissions.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. The self-learning detection method for the position of the EOL shifting fork is used for self-learning of the shifting fork of a double-clutch transmission and is characterized by comprising the following steps of:
neutral position step: writing the original shifting fork position during the assembly of the transmission into a memory, and reading and recording the current assembly position of the shifting fork as the neutral position of the shifting fork on the basis of the original shifting fork position;
a limiting position step: pushing a shifting fork to move to a shifting fork extreme position by preset pressure, and waiting for a first preset time; if the moving speed of the shifting fork is 0, the shifting fork is considered to move successfully; otherwise, confirming that the self-learning of the shifting fork position fails;
a gear position step: after the shifting fork successfully moves, releasing the pressure acting on the shifting fork for a second preset time; if the shifting fork moving speed is 0 and the position of the shifting fork is within the position range of the gear, the current shifting fork position is considered to be the gear position of the shifting fork; otherwise, confirming that the shifting fork position fails to learn, and the shifting fork or the transmission needs to be maintained;
the EOL shifting fork position self-learning detection method comprises the steps of:
pushing the shifting fork to a right limit position with preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork position is within the range of the right gear position, the current shifting fork position is considered as the right gear position, and the position is stored, otherwise, the self-learning of the shifting fork position fails;
the EOL shifting fork position self-learning detection method comprises the following steps of:
pushing the shifting fork to a left limit position at a preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, confirming that the self-learning of the shifting fork position fails;
releasing force after the shifting fork is successfully pushed, and waiting for a second preset time; if the shifting fork moving speed is 0 and the shifting fork position is within the range of the left gear position, the current shifting fork position is considered as the left gear position, and the current shifting fork position is stored, otherwise, the self-learning of the shifting fork position fails;
the EOL shifting fork position self-learning detection method comprises the following writing steps:
if the neutral gear position step, the right gear step and the left gear step of the shifting fork are successful, writing the neutral gear position, the left gear position and the right gear position of the shifting fork into a storage; if any of the neutral position step, the right gear step and the left gear step fails, not writing into a memory;
the EOL shifting fork position self-learning detection method comprises the following steps:
and calling a neutral gear position step, a right gear step and a left gear step in the storage device, operating the shifting fork to move, if the shifting fork returns to the range of the neutral gear position within a third preset time, considering that the self-learning of all the positions of the shifting fork is successful, otherwise, failing to self-learn the position of the shifting fork.
2. An EOL shift fork position self-learning detection method according to claim 1, characterized in that:
the left gear step: pushing the shifting fork to move from the right side to the left limit position at the gear position under preset pressure, and waiting for a first preset time; if the shifting speed of the shifting fork is 0, the shifting fork is judged to be successfully pushed; otherwise, the self-learning of the shifting fork position is determined to fail.
3. An EOL shift fork position self-learning detection method as claimed in claim 1, wherein:
and after the emptying step of the previous shifting fork is completed, carrying out self-learning of the position of the next shifting fork.
4. An EOL shift fork position self-learning detection method according to claim 1, characterized in that:
the preset pressure is 1000kPa-1200 kPa.
5. An EOL shift fork position self-learning detection method as claimed in claim 4, wherein:
the preset pressure is 1100 kPa.
6. An EOL shift fork position self-learning detection method as claimed in claim 1, wherein:
the memory is a non-volatile memory.
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| CN105626851B (en) * | 2014-12-01 | 2018-03-13 | 比亚迪股份有限公司 | Searching method, system and the vehicle of the neutral bit positions of automatic transmission |
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| CN110207582B (en) * | 2019-06-11 | 2021-03-02 | 中国第一汽车股份有限公司 | Shifting fork position testing method, system, equipment and storage medium |
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