CN113917839B - Engine flywheel irregularity self-learning system and method - Google Patents
Engine flywheel irregularity self-learning system and method Download PDFInfo
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- CN113917839B CN113917839B CN202111033254.XA CN202111033254A CN113917839B CN 113917839 B CN113917839 B CN 113917839B CN 202111033254 A CN202111033254 A CN 202111033254A CN 113917839 B CN113917839 B CN 113917839B
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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Abstract
The invention provides a self-learning system and a self-learning method for irregularities of an engine flywheel, which relate to the technical field of engines and comprise the following steps: the diagnosis module is used for inputting a self-learning command by an operator; the engine control module is respectively connected with the diagnosis module, a brake pedal and an engine, and is used for carrying out self-learning on the flywheel irregularity of the engine according to the self-learning command when receiving the self-learning command and continuously receiving a brake signal of the brake pedal, feeding back the self-learning state in the self-learning process in real time, and storing the flywheel irregularity obtained by self-learning after the self-learning of the flywheel irregularity of the engine is completed; the diagnostic module is also used for receiving and displaying the self-learning state. The system and the method have the beneficial effects that the interference of manual operation on the self-learning process is eliminated, the self-learning success rate is effectively improved, and the self-learning requirement that the traditional operation cannot adapt to part of the engine flywheel of the hybrid electric vehicle is solved.
Description
Technical Field
The invention relates to the technical field of engines, in particular to a self-learning system and method for irregularities of an engine flywheel.
Background
The self-learning of the irregularity among the flywheel teeth of the traditional gasoline vehicle internal combustion engine has important reference significance for the fire judgment of the engine (specific requirements for the fire judgment in national standards), and the engine controller realizes the function of engine fire monitoring by learning the irregularity among the flywheel teeth, so that the success rate of the self-learning of the irregularity among the flywheel teeth by the engine controller needs to be ensured.
The existing self-learning of the irregularity among flywheel teeth requires an operator to step on an accelerator to the fuel cut-off rotating speed for a plurality of seconds and then return to an idle speed and repeat for a plurality of times, and in the process, the fault tolerance and the self-learning success rate are greatly reduced due to the fact that great uncertainty is brought by manual operation.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an engine flywheel irregularity self-learning system, which comprises:
the diagnosis module is used for inputting a self-learning command by an operator;
The engine control module is respectively connected with the diagnosis module, a brake pedal and an engine, and is used for carrying out self-learning on the flywheel irregularity of the engine according to the self-learning command when receiving the self-learning command and continuously receiving a brake signal of the brake pedal, feeding back the self-learning state in the self-learning process in real time, and storing the flywheel irregularity obtained by self-learning after the self-learning of the flywheel irregularity of the engine is completed;
the diagnostic module is also configured to receive and display the self-learning state.
Preferably, the engine control module includes:
The self-learning unit is used for receiving the self-learning command and directly transmitting at least one preset torque demand to the engine, the engine rotates at corresponding rotating speeds according to the torque demands, monitors the rotating process of each rotating speed of the engine to learn the flywheel irregularity corresponding to each rotating speed of the engine, and outputs a corresponding self-learning result to the diagnosis module after the self-learning is completed;
the state monitoring unit is connected with the self-learning unit and used for monitoring the self-learning process of the self-learning unit, obtaining the self-learning state and feeding the self-learning state back to the diagnosis module in real time;
And the storage unit is connected with the self-learning unit and is used for storing the irregularities of the flywheel of each rotating speed of the engine.
Preferably, the engine control module further includes a notification unit connected to the self-learning unit, and configured to output a first notification signal when the self-learning unit performs self-learning of the flywheel irregularity, and output a second notification signal when the self-learning unit completes self-learning of the flywheel irregularity.
Preferably, the engine control module is connected to at least one vehicle controller, and each vehicle controller stops operating when receiving the first notification signal, and enters an operating state when receiving the second notification signal.
Preferably, the engine control module further comprises a control unit connected with the self-learning unit, and when the control unit continuously receives the braking signal, the self-learning unit is controlled to perform self-learning of the flywheel irregularity;
when the control unit does not receive the braking signal, the self-learning unit is controlled not to perform self-learning of the flywheel irregularity;
And when the control unit does not continuously receive the braking signal in the self-learning process, controlling the self-learning unit to stop self-learning of the flywheel irregularity.
Preferably, the engine control module further includes an analysis unit connected to the self-learning unit and the control unit, and when the self-learning result output by the self-learning unit indicates failure and the control unit does not continuously receive the braking signal in the self-learning process, the control unit interrupts the braking signal received in the self-learning process and outputs the interrupt to the diagnosis module as prompt information for display;
When the self-learning result output by the self-learning unit indicates failure but the control unit continuously receives the braking signal in the self-learning process, the control unit continuously receives the braking signal in the self-learning process and outputs the braking signal as prompt information to the diagnosis module for display.
Preferably, the state monitoring unit includes:
The first monitoring subunit is used for outputting an initial state as the self-learning state when the self-learning unit does not complete or does not perform the self-learning of the irregularity of the flywheel;
a second monitoring subunit configured to output an idle state as the self-learning state when the engine does not receive each of the torque demands;
A third monitoring subunit for outputting a climbing state as the self-learning state when the engine rotates at a corresponding rotation speed according to each torque requirement
Preferably, the state monitoring unit further includes:
and the fourth monitoring subunit is used for outputting a waiting state as the self-learning state when the engine control module does not receive the self-learning command or the braking signal.
The self-learning method for the irregularity of the engine flywheel is applied to the self-learning system for the irregularity of the engine flywheel, and the self-learning system for the irregularity of the engine flywheel is connected with an engine, so that the self-learning method for the irregularity of the engine flywheel specifically comprises the following steps:
Step S1, the engine flywheel irregularity self-learning system receives a self-learning command input by an operator and a braking signal input by the operator by stepping on a brake pedal;
and S2, when the self-learning system continuously receives the braking signal, performing self-learning of the flywheel irregularity of the engine according to the self-learning command, feeding back the self-learning state in the self-learning process in real time, and storing the self-learned flywheel irregularity after the self-learning of the flywheel irregularity of the engine is completed.
Preferably, the step S2 specifically includes the following steps:
step S21, the engine flywheel irregularity self-learning system directly sends at least one preset torque demand to the engine according to the self-learning command, and the engine rotates at a corresponding rotating speed according to each torque demand;
Step S22, the engine flywheel irregularity self-learning system monitors the rotation process of each rotating speed of the engine so as to learn the flywheel irregularity corresponding to each rotating speed of the engine;
And S23, the self-learning process is monitored by the self-learning system of the engine flywheel irregularity, the self-learning state is obtained and fed back in real time, and after the self-learning is finished, the flywheel irregularity is stored and the corresponding self-learning result is output.
The technical scheme has the following advantages or beneficial effects: the system and the method eliminate the interference of manual operation on the self-learning process, effectively improve the self-learning success rate and solve the problem that the traditional operation cannot adapt to the self-learning requirement of part of the engine flywheel of the hybrid electric vehicle.
Drawings
FIG. 1 is a schematic diagram of the system according to the preferred embodiment of the present invention;
FIG. 2 is a flow chart showing the steps of the method according to the preferred embodiment of the present invention;
FIG. 3 is a flowchart showing the steps S2 in a preferred embodiment of the present invention;
FIG. 4 is a flow chart showing the implementation of the system and method according to the preferred embodiment of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present invention is not limited to the embodiment, and other embodiments may fall within the scope of the present invention as long as they conform to the gist of the present invention.
In a preferred embodiment of the present invention, based on the above-mentioned problems existing in the prior art, there is now provided a self-learning system for irregularities of an engine flywheel, as shown in fig. 1, comprising:
A diagnosis module 1 for an operator to input a self-learning command;
The engine control module 2 is respectively connected with the diagnosis module 1, a brake pedal 3 and an engine 4, and is used for carrying out self-learning on the flywheel irregularity of the engine 4 according to the self-learning command when receiving the self-learning command and continuously receiving a brake signal of the brake pedal 3, feeding back the self-learning state in the self-learning process in real time, and storing the flywheel irregularity obtained by self-learning after the self-learning of the flywheel irregularity of the engine 4 is completed;
the diagnostic module 1 is also used to receive and display the self-learning status.
Specifically, in this embodiment, the self-learning process of the irregularities between the teeth of the conventional flywheel is as follows:
Step A1, after a driver starts the off-line vehicle, the engine 4 is operated to be warmed up;
step A2, placing the vehicle in a neutral position or a parking position, and enabling the engine 4 to be in an idle state;
Step A3, the driver steps on the accelerator to a throttle after the engine 4 has cut-off speed (6000 rpm), and the engine 4 is stabilized for a few seconds after the cut-off speed falls back to the idle speed;
And step A4, after repeating the step A3 for three times, the engine controller should normally learn irregularities among the teeth of the engine flywheel into the memory for permanent storage, and the engine controller should normally have the fire monitoring function.
Preferably, in the method, the driver only needs to operate the diagnostic apparatus (i.e. the diagnostic module 1) to send a self-learning command and continuously tread the brake pedal 3 in the self-learning process, so that complex operation is not required, the interference of human factors is reduced, and the self-learning success rate is improved.
In a preferred embodiment of the present invention, the engine control module 2 includes:
A self-learning unit 21, configured to receive a self-learning command and directly send at least one preset torque request to the engine 4, where the engine 4 rotates at a corresponding rotation speed according to each torque request, and the self-learning unit 21 monitors a rotation process of each rotation speed of the engine 4 to learn a flywheel irregularity corresponding to each rotation speed of the engine 4, and outputs a corresponding self-learning result to the diagnostic module 1 after the self-learning is completed;
A state monitoring unit 22 connected to the self-learning unit 21 for monitoring the self-learning process of the self-learning unit 21, obtaining a self-learning state and feeding back to the diagnosis module 1 in real time;
a storage unit 23 connected to the self-learning unit 21 for storing flywheel irregularities for each rotational speed of the engine 4.
Specifically, in this embodiment, a corresponding logic calculation is added to the self-learning unit 21, and the engine control module 2 performs automatic control after receiving the self-learning command sent by the diagnostic module 1, so that the vehicle is not limited by the hybrid architecture of the vehicle, and other controllers of the vehicle are notified of the self-learning unit 21 entering a self-learning state.
Preferably, during self-learning, the engine control module 2 directly sends a torque request to the engine 4, monitors the rotational speed state, the drive train state, the brake state, the water temperature of the engine 4 and the self-learning state, and feeds back the self-learning state and the self-learning result after the self-learning is completed.
In the preferred embodiment of the present invention, the engine control module 2 further includes a notification unit 24 connected to the self-learning unit 21 for outputting a first notification signal when the self-learning unit 21 performs the self-learning of the flywheel irregularity, and outputting a second notification signal when the self-learning unit 21 completes the self-learning of the flywheel irregularity.
In a preferred embodiment of the present invention, the engine control module 2 is connected to at least one vehicle controller 5, and each vehicle controller 5 stops operating when receiving the first notification signal and enters an operating state when receiving the second notification signal.
In the preferred embodiment of the present invention, the engine control module 2 further includes a control unit 25 connected to the self-learning unit 21, and when the control unit 25 continuously receives the braking signal, the self-learning unit 21 is controlled to perform self-learning of the flywheel irregularity;
when the control unit 25 does not receive the brake signal, the self-learning unit 21 is controlled not to perform the self-learning of the flywheel irregularity;
When the control unit 25 does not continuously receive the brake signal during the self-learning, the self-learning unit 21 is controlled to stop the self-learning of the flywheel irregularity.
Specifically, in the present embodiment, when the self-learning unit 21 receives the self-learning command but the control unit 25 does not receive the brake signal, the self-learning unit 21 cannot perform self-learning, and also when the control unit 25 receives the brake signal but the self-learning unit 21 does not receive the self-learning command, the self-learning unit 21 cannot perform self-learning when the self-learning unit 21 receives the self-learning command and the control unit 25 continuously receives the brake signal, and during self-learning, if the control unit 25 does not continuously receive the brake signal, that is, the brake signal is interrupted, the self-learning unit 21 stops performing self-learning.
In the preferred embodiment of the present invention, the engine control module 2 further includes an analysis unit 26 connected to the self-learning unit 21 and the control unit 25, and when the self-learning result output by the self-learning unit 21 indicates failure and the control unit 25 does not continuously receive the braking signal during the self-learning process, the analysis unit outputs the interrupt of the braking signal received by the control unit 25 during the self-learning process as a prompt message to the diagnosis module 1 for display;
When the self-learning result output by the self-learning unit 21 indicates failure but the control unit 25 continuously receives the brake signal in the self-learning process, the control unit 25 continuously receives the brake signal in the self-learning process as prompt information and outputs the prompt information to the diagnostic module 1 for display.
Specifically, in this embodiment, if the self-learning unit 21 does not complete self-learning in a special case, such as when the driver releases the brake pedal 3 or the engine 4 has a related failure, the analysis unit 26 outputs a corresponding failure cause of self-learning to the diagnostic module 1 for display.
In a preferred embodiment of the present invention, the status monitor unit 22 includes:
A first monitoring subunit 221, configured to output an initial state as a self-learning state when the self-learning unit 21 does not complete or does not perform self-learning of the flywheel irregularity;
A second monitoring subunit 222, configured to output an idle state as a self-learning state when the engine 4 does not receive each torque request;
The third monitoring subunit 223 is configured to output a climbing state as a self-learning state when the engine 4 rotates at a corresponding rotation speed according to each torque request.
In the preferred embodiment of the present invention, the status monitor unit 22 further comprises:
the fourth monitoring subunit 224 is configured to output a waiting state as a self-learning state when the engine control module 2 does not receive the self-learning command or the brake signal.
Specifically, in this embodiment, the initial state indicates that self-learning is not completed or is about to be performed, the idle state indicates that the engine 4 has no torque requirement and is in a stable idle closed-loop state, the climb state indicates that the engine 4 starts to climb at the rotation speed, the target torque reaches the vicinity of the calibratable maximum fuel cut-off rotation speed, the engine 4 enters the idle state after entering the fuel cut-off state and falling normally through realizing the target negative torque, and the waiting state indicates that the self-learning condition is temporarily not satisfied due to the influence of the external environment or the engine control module 2 does not receive a self-learning command or a braking signal, and the idle state is re-entered after the self-learning condition is satisfied to wait for a new round of learning, if the self-learning condition is still not satisfied after the calibrated long-term time, the whole self-learning process is forcedly exited.
In a preferred embodiment of the present invention, an engine flywheel irregularity self-learning method is applied to an engine flywheel irregularity self-learning system, and the engine flywheel irregularity self-learning system is connected to an engine 4, as shown in fig. 2, and the engine flywheel irregularity self-learning method specifically includes the following steps:
step S1, the engine flywheel irregularity self-learning system receives a self-learning command input by an operator and a braking signal input by the operator by stepping on a brake pedal 3;
And S2, when the self-learning system continuously receives a braking signal, the self-learning system of the flywheel irregularity of the engine 4 carries out self-learning of the flywheel irregularity of the engine 4 according to a self-learning command, feeds back the self-learning state in the self-learning process in real time, and stores the self-learned flywheel irregularity after the self-learning of the flywheel irregularity of the engine 4 is completed.
In a preferred embodiment of the present invention, as shown in fig. 3, step S2 specifically includes the following steps:
step S21, the engine flywheel irregularity self-learning system directly sends at least one preset torque demand to the engine 4 according to the self-learning command, and the engine 4 rotates at a corresponding rotation speed according to each torque demand;
step S22, the engine flywheel irregularity self-learning system monitors the rotation process of each rotating speed of the engine to learn the flywheel irregularity corresponding to each rotating speed of the engine 4;
Step S23, the engine flywheel irregularity self-learning system monitors the self-learning process, obtains a self-learning state and feeds back the self-learning state in real time, and stores the flywheel irregularity after the self-learning is completed and outputs a corresponding self-learning result.
Specifically, in this embodiment, as shown in fig. 4, the system and the method are applied to the vehicle off-line station, and are performed after the vehicle has been assembled and the vehicle fault checking and warming up are completed, and the specific steps are as follows:
step B1, a finished automobile offline personnel enters a vehicle cockpit to operate, and a brake pedal 3 is stepped on by feet;
step B2, a finished automobile offline personnel sends a self-learning command of an engine flywheel through an operation diagnostic instrument;
Step B3, the engine controller automatically performs flywheel self-learning, feeds back the self-learning state, the self-learning result and the self-learning failure reason in real time through the diagnostic instrument, and simultaneously informs other vehicle controllers 5 that the self-learning is in progress;
And step B4, judging whether to enter the next process or not by the whole car offline personnel according to the self-learning result fed back by the diagnostic instrument:
entering the next procedure when the self-learning result shows success;
if the self-learning result indicates failure, if the diagnostic apparatus displays that the control unit 25 continuously receives the brake signal during the self-learning process, the process goes to step B5;
If the diagnostic apparatus indicates that the control unit 25 does not continuously receive the braking signal in the self-learning process, the process goes to step B1;
Step B5, judging whether the problem of the vehicle is solved:
if the vehicle is in question, the vehicle is withdrawn and the vehicle is simply overhauled;
if it is not a problem in the vehicle itself, the process goes to step B1.
Preferably, the system and method are applied to the self-learning of irregularities of an engine controller or an engine flywheel and other related components of a vehicle after the flywheel is replaced.
The foregoing description is only illustrative of the preferred embodiments of the present invention and is not to be construed as limiting the scope of the invention, and it will be appreciated by those skilled in the art that equivalent substitutions and obvious variations may be made using the description and drawings, and are intended to be included within the scope of the present invention.
Claims (10)
1. An engine flywheel irregularity self-learning system, comprising:
the diagnosis module is used for inputting a self-learning command by an operator;
The engine control module is respectively connected with the diagnosis module, a brake pedal and an engine, and is used for carrying out self-learning on the flywheel irregularity of the engine according to the self-learning command when receiving the self-learning command and continuously receiving a brake signal of the brake pedal, feeding back the self-learning state in the self-learning process in real time, and storing the flywheel irregularity obtained by self-learning after the self-learning of the flywheel irregularity of the engine is completed;
The diagnosis module is also used for receiving and displaying the self-learning state;
The engine control module includes:
The self-learning unit is used for receiving the self-learning command and directly sending at least one preset torque demand to the engine, the engine rotates at a corresponding rotating speed according to each torque demand, monitors the rotating process of each rotating speed of the engine to learn the flywheel irregularity corresponding to each rotating speed of the engine, and outputs a corresponding self-learning result to the diagnosis module after the self-learning is completed.
2. The engine flywheel irregularity self-learning system of claim 1, wherein the engine control module comprises:
the state monitoring unit is connected with the self-learning unit and used for monitoring the self-learning process of the self-learning unit, obtaining the self-learning state and feeding the self-learning state back to the diagnosis module in real time;
And the storage unit is connected with the self-learning unit and is used for storing the irregularities of the flywheel of each rotating speed of the engine.
3. The engine flywheel irregularity self-learning system of claim 2 wherein the engine control module further comprises a notification unit coupled to the self-learning unit for outputting a first notification signal when the self-learning unit performs the flywheel irregularity self-learning and outputting a second notification signal when the self-learning unit completes the flywheel irregularity self-learning.
4. The engine flywheel irregularity self-learning system of claim 3 wherein the engine control module is connected to at least one vehicle controller, each of the vehicle controllers stopping operation upon receipt of the first notification signal and entering an operational state upon receipt of the second notification signal.
5. The engine flywheel irregularity self-learning system of claim 2, wherein the engine control module further comprises a control unit connected to the self-learning unit for controlling the self-learning unit to perform the flywheel irregularity self-learning when the control unit continuously receives the brake signal;
when the control unit does not receive the braking signal, the self-learning unit is controlled not to perform self-learning of the flywheel irregularity;
And when the control unit does not continuously receive the braking signal in the self-learning process, controlling the self-learning unit to stop self-learning of the flywheel irregularity.
6. The engine flywheel irregularity self-learning system of claim 5, wherein the engine control module further comprises an analysis unit respectively connected to the self-learning unit and the control unit, and when the self-learning result output by the self-learning unit indicates failure and the control unit does not continuously receive the braking signal during the self-learning process, the control unit outputs the braking signal received by the control unit during the self-learning process to the diagnosis module as prompt information for display;
When the self-learning result output by the self-learning unit indicates failure but the control unit continuously receives the braking signal in the self-learning process, the control unit continuously receives the braking signal in the self-learning process and outputs the braking signal as prompt information to the diagnosis module for display.
7. The engine flywheel irregularity self-learning system of claim 2, wherein the state monitoring unit comprises:
The first monitoring subunit is used for outputting an initial state as the self-learning state when the self-learning unit does not complete or does not perform the self-learning of the irregularity of the flywheel;
a second monitoring subunit configured to output an idle state as the self-learning state when the engine does not receive each of the torque demands;
And the third monitoring subunit is used for outputting a climbing state as the self-learning state when the engine rotates at the corresponding rotating speed according to each torque demand.
8. The engine flywheel irregularity self-learning system of claim 7, wherein the condition monitoring unit further comprises:
and the fourth monitoring subunit is used for outputting a waiting state as the self-learning state when the engine control module does not receive the self-learning command or the braking signal.
9. The engine flywheel irregularity self-learning method is characterized by being applied to the engine flywheel irregularity self-learning system according to any one of claims 1-8, wherein the engine flywheel irregularity self-learning system is connected with an engine, and the engine flywheel irregularity self-learning method specifically comprises the following steps:
Step S1, the engine flywheel irregularity self-learning system receives a self-learning command input by an operator and a braking signal input by the operator by stepping on a brake pedal;
Step S2, when the self-learning system continuously receives the braking signal, the self-learning system performs self-learning of the flywheel irregularity of the engine according to the self-learning command, feeds back the self-learning state in the self-learning process in real time, and stores the self-learned flywheel irregularity after the self-learning of the flywheel irregularity of the engine is completed;
the step S2 specifically includes the following steps:
step S21, the engine flywheel irregularity self-learning system directly sends at least one preset torque demand to the engine according to the self-learning command, and the engine rotates at a corresponding rotating speed according to each torque demand;
Step S22, the engine flywheel irregularity self-learning system monitors the rotation process of each rotation speed of the engine to learn the flywheel irregularity corresponding to each rotation speed of the engine.
10. The engine flywheel irregularity self-learning method of claim 9, wherein after executing step S22, continuing to execute:
And S23, the self-learning process is monitored by the self-learning system of the engine flywheel irregularity, the self-learning state is obtained and fed back in real time, and after the self-learning is finished, the flywheel irregularity is stored and the corresponding self-learning result is output.
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| CN111577476A (en) * | 2020-04-26 | 2020-08-25 | 东风汽车集团有限公司 | Hybrid power engine gear information learning method |
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| DE4133679A1 (en) * | 1991-10-11 | 1993-04-22 | Bosch Gmbh Robert | METHOD FOR ADAPTING MECHANICAL TOLERANCES OF A SENSOR WHEEL |
| JP4339347B2 (en) * | 2006-10-30 | 2009-10-07 | 本田技研工業株式会社 | Crank angular velocity detection device for internal combustion engine |
| CN107100947B (en) * | 2017-05-15 | 2019-01-08 | 上海汽车变速器有限公司 | Wet-type dual-clutch half hitch chalaza self-learning optimization method and system |
| CN112113771B (en) * | 2019-06-21 | 2023-01-06 | 联合汽车电子有限公司 | Method and system for measuring misfire signal |
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| CN111177867A (en) * | 2019-12-31 | 2020-05-19 | 中国第一汽车股份有限公司 | Method, system, computer equipment and medium for learning tooth difference |
| CN111577476A (en) * | 2020-04-26 | 2020-08-25 | 东风汽车集团有限公司 | Hybrid power engine gear information learning method |
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