CN114811032A - Gear self-learning method, device, equipment and storage medium - Google Patents
Gear self-learning method, device, equipment and storage medium Download PDFInfo
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- CN114811032A CN114811032A CN202210599167.9A CN202210599167A CN114811032A CN 114811032 A CN114811032 A CN 114811032A CN 202210599167 A CN202210599167 A CN 202210599167A CN 114811032 A CN114811032 A CN 114811032A
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- 238000000034 method Methods 0.000 title claims abstract description 53
- 230000007935 neutral effect Effects 0.000 claims description 18
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- 230000008569 process Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 4
- 238000012935 Averaging Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
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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
- F16H61/02—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 the signals used
- F16H61/0202—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 the signals used the signals being electric
- F16H61/0204—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 the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal
- F16H61/0213—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 the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal characterised by the method for generating shift signals
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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
- F16H61/02—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 the signals used
- F16H61/0202—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 the signals used the signals being electric
- F16H61/0204—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 the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal
- F16H61/0213—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 the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal characterised by the method for generating shift signals
- F16H2061/0216—Calculation or estimation of post shift values for different gear ratios, e.g. by using engine performance tables
Abstract
The invention discloses a gear self-learning method, a gear self-learning device, gear self-learning equipment and a storage medium, and belongs to the technical field of vehicle gear shifters. The invention receives an input self-learning instruction; switching the gear to a preset gear according to the self-learning instruction; powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located; after the whole vehicle is electrified again, acquiring a target position of the gear after gear return is completed, and taking the target position as a self-learning position of a preset gear; the positions of other gears are determined according to the target position to complete gear self-learning, the positions of the preset gears are learned in a power-off and fall-back re-electrifying mode, and then the positions of the other gears are learned according to the positions of the preset gears, so that multiple gear shifting and frequent positive and negative rotation of a motor are avoided, the gear self-learning efficiency is improved, meanwhile, the abrasion of vehicle parts is reduced, and the service life of the vehicle parts is prolonged.
Description
Technical Field
The invention relates to the technical field of vehicle gear shifters, in particular to a gear self-learning method, a gear self-learning device, gear self-learning equipment and a storage medium.
Background
The electronic gear shifting actuator controller receives a gear shifting operation instruction of the gear shifter, and controls the gear shifting motor to actuate to complete gear shifting by calculating and outputting a pulse width modulation wave corresponding to a required gear. Compared with the traditional mechanical gear shifting, the electronic gear shifting almost has no pause/big complaint of operating force, the mechanical structure is simpler, the reliability is stronger, and the integration level is higher. However, since the hall sensor near the actuator motor has an accuracy error, and the gear shifting system also has a mechanical dimension error, and the fixed duty ratio range preset in the prior art does not cover the errors, the hall sensor preset value needs to be corrected through gear self-learning when the vehicle leaves the factory.
In the prior art, most of gears are independently learned, approximate values of the center duty ratio of each gear are obtained and stored according to a method of averaging for multiple gear shifts (generally more than 4 times), and the range of the duty ratio value corresponding to each gear is determined according to the center value, so that the self-learning efficiency of the gears is low. Moreover, for a fixed whole vehicle, under the condition of known vehicle parameters, the operations are redundant and have poor timeliness, the motor is controlled to rotate forward and backward for a plurality of times too frequently in a short time, the risk of excessive heating and even breakdown of the motor and a driving circuit formed by the motor and semiconductor components can be caused, and the service life of vehicle components is reduced by the current gear self-learning mode.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a gear self-learning method, a gear self-learning device, gear self-learning equipment and a storage medium, and aims to solve the technical problems that in the prior art, the self-learning efficiency is low and the service life of vehicle components is shortened.
In order to achieve the purpose, the invention provides a gear self-learning method, which comprises the following steps:
receiving an input self-learning instruction;
switching the gear to a preset gear according to the self-learning instruction;
powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located;
after the whole vehicle is electrified again, acquiring a target position of the gear after gear return is completed, and taking the target position as a self-learning position of a preset gear;
and determining the positions of other gears according to the target position so as to complete gear self-learning.
Optionally, predetermine the fender position and be the neutral gear, carry out the outage to whole car, so that the fender position is followed predetermine the position that keeps off the position and carry out fender position fallback, include:
powering off the whole vehicle to enable the gear to fall back from the position of the neutral gear for the first time;
after the whole vehicle is electrified again, acquiring the current position of the gear after the gear falls back for the first time;
when the current position is not at the preset position, carrying out secondary power-off on the whole vehicle so as to enable the gear to carry out secondary gear falling from the current position;
the acquiring of the target position of the gear after gear return is completed comprises:
and acquiring the target position of the gear after the secondary gear falling is completed.
Optionally, the gear self-learning method further includes:
when the current position is at a preset position, controlling the gear to reversely rotate according to a calibration angle, and acquiring a new current position of the gear;
and carrying out secondary power-off on the whole vehicle so as to enable the gear to fall back from the new current position for the secondary gear.
Optionally, the determining the positions of the other gears according to the target position includes:
acquiring a gear angle difference between the gear and other gears;
and determining the positions of other gears according to the gear angle difference and the target position.
Optionally, the gear self-learning method further includes:
detecting whether the current gear is a parking gear;
and when the current gear is a parking gear, performing secondary gear self-learning on the gear and other gears, and outputting a corresponding gear self-learning prompt.
Optionally, before performing secondary gear self-learning on the gear and the other gears and outputting a corresponding gear self-learning prompt, the method further includes:
detecting whether a secondary self-learning command is received;
and when the secondary self-learning command is received, executing the step of carrying out secondary gear self-learning on the gear and other gears and outputting corresponding gear self-learning prompts.
Optionally, before performing secondary gear self-learning on the gear and the other gears and outputting a corresponding gear self-learning prompt, the method further includes:
acquiring the current driving mileage of the whole vehicle;
when the current driving mileage reaches a preset mileage, executing the steps of carrying out secondary gear self-learning on the gears and other gears and outputting corresponding gear self-learning prompts
In addition, in order to achieve the above object, the present invention further provides a gear self-learning apparatus, including:
the receiving module is used for receiving an input self-learning instruction;
the control module is used for switching the gear to a preset gear according to the self-learning instruction;
the control module is also used for powering off the whole vehicle so as to enable the gear to fall back from the position where the preset gear is located;
the reading module is used for acquiring a target position of the gear after gear return is finished after the whole vehicle is electrified again;
and the calculation module is used for determining the positions of other gears according to the target position so as to complete gear self-learning.
In addition, in order to achieve the above object, the present invention further provides a gear self-learning apparatus, including: a memory, a processor, and a gear self-learning program stored on the memory and running on the processor, the gear self-learning program configured to implement the gear self-learning method as described above.
In addition, to achieve the above object, the present invention further provides a storage medium having a gear self-learning program stored thereon, wherein the gear self-learning program, when executed by a processor, implements the gear self-learning method as described above.
The invention receives an input self-learning instruction; switching the gear to a preset gear according to the self-learning instruction; powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located; after the whole vehicle is electrified again, acquiring a target position of the gear after gear return is completed, and taking the target position as a self-learning position of a preset gear; the positions of other gears are determined according to the target position to complete gear self-learning, the positions of the preset gears are learned in a power-off and fall-back re-electrifying mode, and then the positions of the other gears are learned according to the positions of the preset gears, so that multiple gear shifting and frequent positive and negative rotation of a motor are avoided, the gear self-learning efficiency is improved, meanwhile, the abrasion of vehicle parts is reduced, and the service life of the vehicle parts is prolonged.
Drawings
FIG. 1 is a schematic structural diagram of a gear self-learning device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a first embodiment of the gear self-learning method of the present invention;
FIG. 3 is a schematic flow chart of a gear self-learning method according to a second embodiment of the present invention;
FIG. 4 is a schematic gear self-learning diagram of an embodiment of the gear self-learning method of the present invention;
FIG. 5 is a schematic flow chart of a third embodiment of the gear self-learning method of the present invention;
FIG. 6 is a block diagram of the first embodiment of the gear self-learning apparatus according to the present invention.
The implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a gear self-learning device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the gear self-learning apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001 described previously.
It will be appreciated by those skilled in the art that the configuration shown in FIG. 1 does not constitute a limitation of the gear self-learning apparatus and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, the memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a gear self-learning program.
In the gear self-learning apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the gear self-learning device of the present invention may be disposed in the gear self-learning device, and the gear self-learning device calls the gear self-learning program stored in the memory 1005 through the processor 1001 and executes the gear self-learning method provided by the embodiment of the present invention.
An embodiment of the invention provides a gear self-learning method, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of the gear self-learning method.
In this embodiment, the gear self-learning method includes the following steps:
step S10: and receiving an input self-learning instruction.
In this embodiment, the execution main body of this embodiment may be a gear self-learning device, the gear self-learning device has functions of data processing, data communication, program operation and the like, and the gear self-learning device may be an electronic gear shift actuator. Of course, other devices with similar functions may be used, and the present embodiment is not limited thereto. For convenience of explanation, the present embodiment will be described taking an electronic shifter actuator as an example.
It should be noted that, in the current gear self-learning, separate learning is performed on all gears, an approximate central duty ratio value of each gear is obtained and stored according to a method of averaging for multiple gear shifts (generally more than 4 times), and then a duty ratio value range corresponding to each gear is determined according to the central duty ratio value, so that the gear self-learning efficiency is low. Moreover, for a fixed whole vehicle, under the condition of known vehicle parameters, the operations are redundant and have poor timeliness, the motor is controlled to rotate forward and backward for a plurality of times too frequently in a short time, the risk of excessive heating and even breakdown of the motor and a driving circuit formed by the motor and semiconductor components can be caused, and the service life of vehicle components is reduced by the current gear self-learning mode.
Aiming at the technical problems, the positions of the preset gears are learned by self, then the positions of other gears are learned according to the learned positions of the gears and the angle relation among the gears, the positions of the gears are not required to be obtained in a self-learning mode of multiple gear shifting, the gear self-learning efficiency is improved, and meanwhile the safety of vehicle parts is guaranteed.
In specific implementation, in order to ensure the accuracy of self-learning, in this embodiment, before gear self-learning is performed, a gear needs to be adjusted to a preset gear, and then subsequent gear self-learning is performed, and before the preset gear is switched, a self-learning instruction needs to be received.
Step S20: and switching the gear to a preset gear according to the gear shifting operation instruction.
In a specific implementation, after the self-learning instruction is received, the gear is switched to the preset gear according to the received self-learning instruction. The preset gear in this embodiment may be set to a neutral gear, that is, N gear, and of course, other gears may be selected as the preset gear according to the actual condition.
Step S30: and powering off the whole vehicle so as to enable the gears to fall back from the positions where the preset gears are located.
In the concrete implementation, after the gear is switched to the preset gear, the whole vehicle is powered off in the embodiment, after the whole vehicle is powered off, the gear falls back from the position where the preset gear is located, and the gear falls back automatically after the power is off of the whole vehicle without additional control operation.
Step S40: and after the whole vehicle is electrified again, acquiring the target position of the gear after gear return is completed.
In specific implementation, the gear can fall back to other positions after the power failure of the whole vehicle, and after the falling process of the whole gear is completed, the vehicle can be powered on again in the embodiment, and then the position of the current gear is obtained, that is, the target position where the gear is located after the gear falls back is completed.
It should be noted that the self-learning position of the gear, that is, the target position in this embodiment, may be obtained by powering on again after power-off and falling.
Step S50: and determining the positions of other gears according to the target position so as to complete gear self-learning.
In this embodiment, the target position is a self-learning position of the gear, and since the gear falling is started from the preset gear in this embodiment, the target position is also a self-learning position of the preset gear, for example, assuming that the preset gear is N gear, that is, the target position is a self-learning position of N gear, after the target position is determined, based on a relationship between each gear, the self-learning positions of other gears may be obtained based on the target position in this embodiment, thereby completing the self-learning of all gears of the entire vehicle. For example, after the self-learning position of the N gear is obtained, the positions of other gears, such as P gear, N gear, D gear and R gear, can be obtained according to the self-learning position of the N gear.
The embodiment is realized by receiving an input gear shifting operation instruction; switching the gear to a preset gear according to the gear shifting operation instruction; powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located; acquiring a target position of the gear after gear return is completed; the positions of other gears are determined according to the target position to complete gear self-learning, the positions of the preset gears are obtained through learning in a power-off falling mode, then the positions of the other gears are obtained through learning according to the positions of the preset gears, multiple gear shifting and frequent positive and negative rotation of a motor are avoided, gear self-learning efficiency is improved, meanwhile, abrasion of vehicle parts is reduced, and the service life of the vehicle parts is prolonged.
Referring to fig. 3, fig. 3 is a schematic flow chart of a gear self-learning method according to a second embodiment of the present invention.
Based on the first embodiment, in the gear self-learning method according to this embodiment, the step S30 specifically includes:
step S301: and powering off the whole vehicle so as to enable the gears to fall back from the positions where the neutral gears are located for the first time.
It should be noted that, in this embodiment, power-off gear drop-back and power-on again after gear drop-back are performed twice, that is, the first gear drop-back and the second gear drop-back in this embodiment.
In specific implementation, after the gear is switched to the preset gear, the whole vehicle is powered off in the embodiment, then the gear starts to fall back from the position where the preset gear is located for the first time, after the first gear fall back is completed, the whole vehicle is powered on again in the embodiment, then the whole vehicle is powered off again, then the preset gear starts to fall back for the second time, and finally the whole vehicle is powered on again, so that the self-learning process of the preset gear is completed.
Step S302: and after the whole vehicle is electrified again, acquiring the current position of the gear after the gear falls back for the first time.
In specific implementation, the preset gear is set as a neutral gear in this embodiment, before the first fall-back, the gear is switched to the position where the neutral gear is located, then the whole vehicle is powered off, after the first fall-back of the gear is completed, the whole vehicle is powered on again, and at this time, the current position where the gear is located is obtained.
Step S303: when the current position is not located at the preset position, the whole vehicle is powered off for the second time, so that the gear is located at the current position and is subjected to secondary gear falling.
It should be noted that after the gear falls back, the gear may fall back to other positions from the initial position where the neutral gear is located, and for different positions where the gear falls back, in this embodiment, the judgment is performed through a preset position, and then the self-learning position of the neutral gear is finally obtained based on different judgment results.
In fig. 4, the preset position in this embodiment is a D-shift position, that is, positions 3 and 4 shown in fig. 4 are positions, and the current position is not in the D-shift position, and the shift positions are positions 1 and 2 at this time. In addition, in the shift 1 position, P or R range information may be received but N range information may not be received, in the shift 2 or 3 position, P, R and N range information may not be received but D range information may be received, and in the shift 4 position, P, R, N and D range information may be received.
In specific implementation, in this embodiment, the current position of the neutral gear after the first gear falling is completed is compared with a preset position, and if the current position is not located at the preset position, in this case, the power of the entire vehicle is further turned off in this embodiment, and then the secondary gear falling is directly started, at this time, the neutral gear will continue to fall back to other positions from the current position located after the first gear falling, and it needs to be emphasized that the position where the neutral gear is located after the secondary gear falling is completed is the target position in this embodiment, which is also the neutral self-learning position.
Further, if the shift position at this time is in the D-shift position, in this case, in this embodiment, the shift position is controlled to rotate in the reverse direction according to the calibration angle, and then the shift position is rotated to the new current position, and then the power of the entire vehicle is cut off for the second time, so that the shift position starts to fall back for the second time from the new current position. Likewise, the position of the gear after the completion of the secondary fall-back is the target position described in the present embodiment, which is also the neutral self-learning position. In this embodiment, the calibration angle may be set according to the mechanical structure of the gear control of different vehicles, which is not limited in this embodiment.
Further, in this embodiment, the step S50 specifically includes:
step S501: and acquiring a gear angle difference between the preset gear and other gears.
It should be noted that each gear has a corresponding gear angle difference, which is determined by the mechanical structure of the gear control of the vehicle itself and can be directly obtained. It should be noted that in this embodiment, the gears fall back from the preset gears, and the target position where the gears fall back is the self-learning position of the preset gears, so that when determining the positions of other gears, the gear angle difference between the preset gears and other gears needs to be obtained. For example, assuming that the preset gear is the N gear, the gear angle differences between the N gear and the P gear, the D gear, and the R gear are obtained respectively.
Step S502: and determining the positions of other gears according to the gear angle difference and the target position.
In this embodiment, after determining the gear angle difference between each gear, the target position is added or subtracted with the gear angle difference to obtain the positions of other gears, thereby completing self-learning of each gear.
In the embodiment, the power of the whole vehicle is cut off, so that the gear falls back from the position of the neutral gear for the first time; acquiring the current position of the gear after the gear falls back for the first time; when the current position is not at the preset position, carrying out secondary power-off on the whole vehicle so as to enable the gear to carry out secondary gear falling from the current position; when the current position is at a preset position, controlling the gear to reversely rotate according to a calibration angle, and acquiring a new current position of the gear; it is right the whole car carries out the secondary outage, so that keep off the position and follow new current position carries out the secondary and keeps off the position and fall back, through twice outage fall back and take corresponding mode to the fender position after the first fall back to adjust to the fender position after the first fall back to different positions after the first fall back, can more accurately obtain predetermine the self-learning position of keeping off the position, thereby improved the accuracy that keeps off the position and learn by oneself.
Referring to fig. 5, fig. 5 is a schematic flow chart of a third embodiment of the gear self-learning method according to the present invention.
Based on the first or second embodiment, a third embodiment of the gear self-learning method of the present invention is provided.
Taking the first embodiment as an example, in this embodiment, the step S40 is followed by:
step S60: and detecting whether the current gear is a parking gear.
In addition, each part of the vehicle is worn away with long-term use, and in this embodiment, the gear shifter is self-learned twice when the user uses the vehicle daily. When the second self-learning is carried out, the current gear needs to be guaranteed to be the parking gear.
Step S70: and when the current gear is a parking gear, performing secondary gear self-learning on the gear and other gears, and outputting a corresponding gear self-learning prompt.
In a specific implementation, when it is detected that the current gear is the parking gear, it is described that a condition for performing self-learning is satisfied at this time, in this case, the gear of the vehicle is controlled to perform secondary gear self-learning in this embodiment, and a gear self-learning prompt is output at the same time to inform a user that the vehicle is performing gear self-learning. The process of the gear self-learning in this embodiment is similar to the process in the above embodiment, and is not described here again.
Further, in this embodiment, it is necessary to detect whether a secondary self-learning command is received or whether the current driving mileage of the entire vehicle is acquired, in addition to ensuring that the current gear is the parking gear, and after the current gear is the parking gear, gear self-learning can be started when the two conditions are met. Specifically, when the current gear is the parking gear, if a secondary self-learning command is received, the vehicle is controlled to start gear self-learning. Or when the current gear is the parking gear, if the current driving mileage reaches a preset mileage, controlling the vehicle to start gear self-learning, where the preset mileage may be set according to an actual gear self-learning requirement, which is not limited in this embodiment.
Whether this embodiment is the parking fender position through detecting current fender position to when the current mileage of receiving self-learning order or whole car reaches preset mileage, it is right fender position and other fender positions carry out the secondary and keep off the position self-learning to export corresponding fender position self-learning suggestion, avoid leading to each part of vehicle to produce wearing and tearing along with the long-time use of vehicle, cause the position of keeping off the position inaccurate, through at the follow-up in-process of using the car of user, can also self-learn the fender position of the executor of shifting of vehicle, promoted user experience.
Furthermore, an embodiment of the present invention further provides a storage medium, where a gear self-learning program is stored, and the gear self-learning program, when executed by a processor, implements the steps of the gear self-learning method described above.
Since the storage medium adopts all technical solutions of all the embodiments, at least all the beneficial effects brought by the technical solutions of the embodiments are achieved, and no further description is given here.
Referring to fig. 6, fig. 6 is a block diagram illustrating a first embodiment of the gear self-learning apparatus according to the present invention.
As shown in fig. 6, the gear self-learning apparatus according to the embodiment of the present invention includes:
and the receiving module 10 is used for receiving an input self-learning instruction.
And the control module 20 is used for switching the gear to a preset gear according to the self-learning instruction.
The control module 20 is further configured to power off the entire vehicle, so that the gear falls back from the position where the preset gear is located.
And the reading module 30 is used for acquiring the target position of the gear after gear return is completed after the whole vehicle is powered on again.
And the calculation module 40 is used for determining the positions of other gears according to the target position so as to complete gear self-learning.
The embodiment receives an input self-learning instruction; switching the gear to a preset gear according to the self-learning instruction; powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located; after the whole vehicle is electrified again, acquiring a target position of the gear after gear return is completed, and taking the target position as a self-learning position of a preset gear; the positions of other gears are determined according to the target position to complete gear self-learning, the positions of the preset gears are learned in a power-off and fall-back re-electrifying mode, and then the positions of the other gears are learned according to the positions of the preset gears, so that multiple gear shifting and frequent positive and negative rotation of a motor are avoided, the gear self-learning efficiency is improved, meanwhile, the abrasion of vehicle parts is reduced, and the service life of the vehicle parts is prolonged.
In an embodiment, the preset gear is a neutral gear, and the control module 20 is further configured to power off the entire vehicle, so that the gear falls back from the position where the neutral gear is located for the first time; after the whole vehicle is electrified again, acquiring the current position of the gear after the gear falls back for the first time; when the current position is not at the preset position, carrying out secondary power-off on the whole vehicle so as to enable the gear to carry out secondary gear falling from the current position;
the reading module 30 is further configured to obtain a target position where the gear is located after the secondary gear falling is completed.
In an embodiment, the control module 20 is further configured to control the gear to rotate reversely according to a calibration angle when the current position is at a preset position, and obtain a new current position of the gear; and carrying out secondary power-off on the whole vehicle so as to enable the gear to fall back from the new current position for the secondary gear.
In an embodiment, the calculation module 40 is further configured to obtain a gear angle difference between the gear and another gear; and determining the positions of other gears according to the gear angle difference and the target position.
In one embodiment, the gear self-learning apparatus further includes: a detection module;
the detection module is used for detecting whether the current gear is a parking gear;
and the control module 20 is further configured to perform secondary gear self-learning on the gear and other gears when the current gear is the parking gear, and output a corresponding gear self-learning prompt.
In an embodiment, the detection module is further configured to detect whether a secondary self-learning command is received;
and the control module 20 is further configured to execute the step of performing secondary gear self-learning on the gear and other gears and outputting a corresponding gear self-learning prompt when receiving the secondary self-learning command.
In an embodiment, the detection module is further configured to obtain a current driving mileage of the entire vehicle;
the control module 20 is further configured to execute the step of performing secondary gear self-learning on the gear and the other gears and outputting a corresponding gear self-learning prompt when the current driving mileage reaches a preset mileage.
Since the gear self-learning device adopts all technical solutions of all the embodiments, at least all the beneficial effects brought by the technical solutions of the embodiments are achieved, and no further description is given here.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may refer to the gear self-learning method provided in any embodiment of the present invention, and are not described herein again.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A gear self-learning method is characterized by comprising the following steps:
receiving an input self-learning instruction;
switching the gear to a preset gear according to the self-learning instruction;
powering off the whole vehicle to enable the gear to fall back from the position where the preset gear is located;
after the whole vehicle is electrified again, acquiring a target position of the gear after gear return is completed, and taking the target position as a self-learning position of a preset gear;
and determining the positions of other gears according to the target position so as to complete gear self-learning.
2. The gear self-learning method according to claim 1, wherein the preset gear is a neutral gear, and the power failure of the whole vehicle to enable the gear to be shifted back from the position where the preset gear is located comprises:
powering off the whole vehicle to enable the gear to fall back from the position of the neutral gear for the first time;
after the whole vehicle is electrified again, acquiring the current position of the gear after the gear falls back for the first time;
when the current position is not at the preset position, carrying out secondary power-off on the whole vehicle so as to enable the gear to carry out secondary gear falling from the current position;
the acquiring of the target position of the gear after gear return is completed comprises:
and acquiring the target position of the gear after the secondary gear falling is completed.
3. The gear self-learning method of claim 2, further comprising:
when the current position is at a preset position, controlling the gear to reversely rotate according to a calibration angle, and acquiring a new current position of the gear;
and carrying out secondary power-off on the whole vehicle so as to enable the gear to fall back from the new current position for the secondary gear.
4. The gear self-learning method of claim 1, wherein the determining the positions of the other gears based on the target position comprises:
acquiring a gear angle difference between the gear and other gears;
and determining the positions of other gears according to the gear angle difference and the target position.
5. The gear self-learning method according to any one of claims 1 to 4, further comprising:
detecting whether the current gear is a parking gear;
and when the current gear is a parking gear, performing secondary gear self-learning on the gear and other gears, and outputting a corresponding gear self-learning prompt.
6. The gear self-learning method according to claim 5, wherein before performing secondary gear self-learning on the gear and other gears and outputting corresponding gear self-learning prompts, the method further comprises:
detecting whether a secondary self-learning command is received;
and when the secondary self-learning command is received, executing the step of carrying out secondary gear self-learning on the gear and other gears and outputting corresponding gear self-learning prompts.
7. The gear self-learning method according to claim 5, wherein before performing secondary gear self-learning on the gear and other gears and outputting corresponding gear self-learning prompts, the method further comprises:
acquiring the current driving mileage of the whole vehicle;
and when the current driving mileage reaches a preset mileage, executing the step of carrying out secondary gear self-learning on the gears and other gears, and outputting corresponding gear self-learning prompts.
8. A gear self-learning device, characterized in that, gear self-learning device includes:
the receiving module is used for receiving an input self-learning instruction;
the control module is used for switching the gear to a preset gear according to the self-learning instruction;
the control module is also used for powering off the whole vehicle so as to enable the gear to fall back from the position where the preset gear is located;
the reading module is used for acquiring a target position of the gear after gear return is finished after the whole vehicle is electrified again;
and the calculation module is used for determining the positions of other gears according to the target position so as to complete gear self-learning.
9. A gear self-learning device, characterized in that the gear self-learning device comprises: a memory, a processor, and a gear self-learning program stored on the memory and running on the processor, the gear self-learning program configured to implement the gear self-learning method of any of claims 1-7.
10. A storage medium having stored thereon a gear self-learning program which, when executed by a processor, implements a gear self-learning method according to any one of claims 1 to 7.
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| CN202210599167.9A CN114811032A (en) | 2022-05-30 | 2022-05-30 | Gear self-learning method, device, equipment and storage medium |
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| CN202210599167.9A CN114811032A (en) | 2022-05-30 | 2022-05-30 | Gear self-learning method, device, equipment and storage medium |
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