CN108223114B - Online self-learning method and system for flow characteristics of control valve of supercharger - Google Patents
Online self-learning method and system for flow characteristics of control valve of supercharger Download PDFInfo
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- CN108223114B CN108223114B CN201711406112.7A CN201711406112A CN108223114B CN 108223114 B CN108223114 B CN 108223114B CN 201711406112 A CN201711406112 A CN 201711406112A CN 108223114 B CN108223114 B CN 108223114B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02B—INTERNAL-COMBUSTION PISTON ENGINES; COMBUSTION ENGINES IN GENERAL
- F02B39/00—Component parts, details, or accessories relating to, driven charging or scavenging pumps, not provided for in groups F02B33/00 - F02B37/00
- F02B39/16—Other safety measures for, or other control of, pumps
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D23/00—Controlling engines characterised by their being supercharged
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/04—Introducing corrections for particular operating conditions
- F02D41/12—Introducing corrections for particular operating conditions for deceleration
- F02D41/123—Introducing corrections for particular operating conditions for deceleration the fuel injection being cut-off
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/14—Introducing closed-loop corrections
- F02D41/1401—Introducing closed-loop corrections characterised by the control or regulation method
- F02D41/1402—Adaptive control
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/12—Improving ICE efficiencies
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Abstract
The invention provides an online self-learning method for flow characteristics of a control valve of a supercharger, which comprises the following steps: judging the working condition of the engine according to a preset period; when the engine is determined to be in a preset working condition which does not affect the normal operation of the engine, the following self-learning operation of the flow characteristic of the supercharger control valve is executed: self-learning the pressure of the air source flowing into the supercharger control valve to enable the outlet pressure of the supercharger control valve to be used as the air source pressure; self-learning the characteristics of the supercharger control valve to obtain a relation table between actual outlet pressure and duty ratio of the supercharger control valve under different duty ratios; the supercharger characteristic table in the supercharger control algorithm is updated using the obtained relationship table. The invention can make the control of the supercharger control algorithm more effective and timely, avoid the problem of poor control effect caused by inconsistency of component characteristic parameters and component actual characteristics in the traditional control algorithm, and improve the control precision and speed of the supercharger control.
Description
Technical Field
The invention relates to an online self-learning method and system for the flow characteristic of a supercharger control valve, in particular to an online self-learning method and system for the flow characteristic of a supercharger control valve of a natural gas engine of a commercial vehicle.
Background
For the control of the natural gas engine supercharger taking an external pressure-stabilizing air source as a working air source for controlling the supercharger, a supercharger control valve is taken as a key execution component in the control of the supercharger, whether the flow characteristics are stable and consistent or not is directly related to the control speed and the control precision of the control of the supercharging pressure of the engine, and the control valve plays a very important role in ensuring the performance of the engine. However, due to the problems of production consistency and abrasion in the use process, the flow characteristic of the control valve of the supercharger often deviates from the set value, if the problem that the flow characteristic of the control valve deviates in the use process cannot be identified, the problems of the control speed and the control precision of the control of the supercharging pressure of the supercharger can be directly caused, and the control divergence can be seriously caused, or the supercharging pressure cannot reach the set value, so that the performance of an engine is influenced.
Therefore, if the method for the on-line self-learning of the flow characteristic of the supercharger control valve of the natural gas engine can be provided, the flow characteristic of the supercharger control valve can be recognized in a self-learning mode in time in the using process, the flow characteristic parameter of the supercharger control valve in the supercharger control algorithm is updated, the control parameter is made to be consistent with the controlled object, and the control speed and the control precision of the supercharger control can be improved.
Disclosure of Invention
In order to solve the technical problems, the invention provides an online self-learning method and system for the flow characteristic of a supercharger control valve, so that the flow characteristic of the supercharger control valve is self-learned and identified in time in the use process of the supercharger control valve, and the flow characteristic parameter of the supercharger control valve in a supercharger control algorithm is updated, so that the control parameter is consistent with a controlled object, and the control speed and the control precision of supercharger control are improved.
The technical scheme adopted by the invention is as follows:
the embodiment of the invention provides an online self-learning method for flow characteristics of a control valve of a supercharger, which comprises the following steps: judging the working condition of the engine according to a preset period; when the engine is determined to be in a preset working condition which does not affect the normal operation of the engine, the following self-learning operation of the flow characteristic of the supercharger control valve is executed: setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of an air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve obtained after the self-learning as the air source pressure; the duty ratio of the supercharger control valve is increased progressively from 0 by a preset gradient to self-learn the characteristics of the supercharger control valve, and a relation table between actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios is obtained; the supercharger control valve characteristic table in the supercharger control algorithm is updated using the obtained relationship table.
Optionally, the preset working condition is a deceleration fuel cut-off working condition.
Optionally, the setting of the duty ratio of the supercharger control valve to 0 to perform self-learning on the pressure of the air supply flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve obtained after the self-learning as the air supply pressure specifically includes: setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve; judging the stability of the collected outlet pressure; and after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
Optionally, the determining the stability of the collected outlet pressure comprises: and performing low-pass filtering processing on the acquired outlet pressure, and determining that the acquired outlet pressure is stable if the difference value between the outlet pressure after the low-pass filtering processing and the outlet pressure before the low-pass filtering processing is smaller than a preset threshold value.
Optionally, the step of increasing the duty ratio of the supercharger control valve from 0 by a preset gradient to self-learn the characteristic of the supercharger control valve to obtain a relationship table between actual outlet pressure and the duty ratio of the supercharger control valve at different duty ratios specifically includes: increasing the duty ratio of the control valve of the supercharger from 0 by a preset gradient until the duty ratio reaches 100%; in the increasing process, judging the stability of the outlet pressure after each increasing, and after determining that the outlet pressure after each increasing is stable, recording the outlet pressure after the increasing and increasing the duty ratio of the next time; and performing data fitting processing on each duty ratio of the supercharger control valve and the corresponding outlet pressure to obtain a relation table between the actual outlet pressure and the duty ratio.
Optionally, the preset gradient is 5%; the preset period is 10 ms.
Another embodiment of the present invention provides an online self-learning system for flow characteristics of a control valve of a supercharger, comprising: the judging module is used for judging the working condition of the engine according to a preset period; the self-learning module is used for executing the following self-learning operation of the flow characteristic of the supercharger control valve when the judging module determines that the engine is in the preset working condition which does not influence the normal operation of the engine: setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of an air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve after self-learning as the air source pressure; the duty ratio of the supercharger control valve is increased progressively from 0 by a preset gradient to self-learn the characteristics of the supercharger control valve, and a relation table between actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios is obtained; the supercharger control valve characteristic table in the supercharger control algorithm is updated using the obtained relationship table.
Optionally, the preset working condition is a deceleration fuel cut-off working condition.
Optionally, the setting of the duty ratio of the supercharger control valve to 0 to perform self-learning on the pressure of the air supply flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve obtained after the self-learning as the air supply pressure specifically includes: setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve; judging the stability of the collected outlet pressure; and after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
Optionally, the step of increasing the duty ratio of the supercharger control valve from 0 by a preset gradient to self-learn the characteristic of the supercharger control valve to obtain a relationship table between actual outlet pressure and the duty ratio of the supercharger control valve at different duty ratios specifically includes: increasing the duty ratio of the control valve of the supercharger from 0 by a preset gradient until the duty ratio reaches 100%; in the increasing process, judging the stability of the outlet pressure after each increasing, and after determining that the outlet pressure after each increasing is stable, recording the outlet pressure after the increasing and increasing the duty ratio of the next time; and performing data fitting processing on each duty ratio of the supercharger control valve and the corresponding outlet pressure to obtain a relation table between the actual outlet pressure and the duty ratio.
According to the online self-learning method and the online self-learning system for the flow characteristic of the supercharger control valve, when the engine is in the preset working condition which does not affect the normal operation of the engine, the self-learning operation of the flow characteristic of the supercharger control valve is executed, and after the self-learning of the characteristic of the supercharger control valve is updated, the characteristic table of the supercharger control valve in the supercharger control algorithm is consistent with the characteristic of the component, so that the supercharger control algorithm can be controlled more effectively and timely, the problem of poor control effect caused by the fact that the characteristic parameters of the component in the conventional control algorithm are inconsistent with the actual characteristic of the component is solved, and the control speed of supercharger control is improved.
Drawings
FIG. 1 is a supercharger control system according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of an online self-learning method for flow characteristics of a control valve of a supercharger according to an embodiment of the invention;
FIG. 3 is a detailed flow chart of a method for online self-learning of flow characteristics of a control valve of a supercharger according to an embodiment of the present invention;
FIG. 4 is a block diagram of an online self-learning system for flow characteristics of a control valve of a supercharger according to an embodiment of the invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The online self-learning method of the flow characteristic of the supercharger control valve provided by the embodiment of the invention is used for self-learning identification of the flow characteristic of the supercharger control valve of a natural gas engine supercharger control system and updating the flow characteristic parameter of the supercharger control valve in a supercharger control algorithm, so that the control parameter is consistent with a controlled object, and the control speed and the control precision of supercharger control are improved.
As shown in fig. 1, the natural gas engine supercharger control system according to the embodiment of the present invention may include a compressed air cylinder 1, a decompressor 2, a supercharger control valve 3, a waste gas bypass (WGP) pressure sensor 4, an engine control unit ECU5, a supercharging pressure sensor 6, a supercharger waste gas bypass control diaphragm valve 7, and a supercharger 11; the supercharger 11 comprises a supercharger waste gas bypass valve 8, a supercharger turbine 9 and a supercharger compressor 10.
Wherein, compressed air gas bomb 1 is the brake that commercial car generally equipped with and uses high-pressure air gas bomb, and the high-pressure air who stores in compressed air gas bomb 1 sends booster control valve 3 after reducing pressure through pressure reducer 2, the air supply pressure who is called booster control valve 3. The air pressure decompressed by the decompressor 2 changes due to production variations of the decompressor 2 and aging during use, and therefore, it is necessary to learn the air pressure decompressed by the decompressor 2.
The booster control valve 3 is a three-way valve with a control valve, which in one example is a solenoid valve. As shown in fig. 1, a passage below the booster control valve 3 is an air inlet and is connected with air decompressed by the decompressor 2; the right channel of the supercharger control valve 3 is an air outlet and is connected with a supercharger bypass control diaphragm valve 7; the left channel of the supercharger control valve 3 is communicated with the atmosphere; an electromagnetic valve is arranged on a left channel of the supercharger control valve 3 and is used for controlling the outlet pressure of the supercharger control valve 3; and a pressure sensor 4 is arranged on the right air outlet channel of the supercharger control valve 3 and used for measuring the air pressure at the outlet of the supercharger control valve 3.
The boost pressure sensor 6 is arranged on an engine intake pipeline in front of the throttle valve and used for measuring the boost pressure of the supercharger.
In the running process of the engine, the ECU5 acquires the actual supercharging pressure of the current working condition through the supercharging pressure sensor 6, compares the actual supercharging pressure with the set supercharging pressure of the current working condition, and calculates the required outlet pressure of the supercharger control valve 3 according to the deviation of the actual supercharging pressure and the set supercharging pressure; the ECU5 collects the actual outlet air pressure of the supercharger control valve 3 according to the WGP pressure sensor 4, compares the actual outlet air pressure with the required outlet pressure, and calculates the target duty ratio of the electromagnetic valve of the supercharger control valve 3 according to the deviation of the actual outlet air pressure and the required outlet pressure; then, the ECU5 controls the solenoid valve of the supercharger control valve 3 to execute according to the calculated target duty parameter.
Since the air outlet passage of the supercharger control valve 3 is connected to the supercharger exhaust gas bypass control diaphragm valve 7, the outlet pressure of the supercharger control valve 3 is different, which results in a difference in the stroke of the push rod of the supercharger exhaust gas bypass control diaphragm valve 7. The push rod of the supercharger waste gas bypass control diaphragm valve 7 can control the opening degree of the supercharger waste gas bypass valve 8 through a set of lever mechanism, and is used for controlling the amount of waste gas flowing through the supercharger turbine 9, and finally the supercharging pressure after supercharging through the supercharger compressor 10 is changed.
The control principle of the supercharger control system of the embodiment is as follows: the high-pressure air from a compressed air storage cylinder for vehicle braking is decompressed by a decompressor and then sent to a supercharger control valve, the air pressure flowing through the supercharger control valve and entering a vacuum diaphragm valve is controlled by controlling the opening degree of an electromagnetic valve of the supercharger control valve, meanwhile, the air pressure at the outlet of the supercharger control valve is collected by using a pressure sensor, when the pressure on a diaphragm in the vacuum diaphragm valve is greater than the elastic force of a spring at the right side of the diaphragm, a push rod of the vacuum diaphragm valve is pushed, the push rod opens a supercharger waste gas bypass valve through a lever mechanism, and the ECU can realize the control of the opening degree of the supercharger bypass valve by controlling the air pressure at the outlet of the supercharger control valve.
According to the online self-learning method for the flow characteristic of the supercharger control valve, when an engine is in a preset working condition which does not affect normal work, such as a deceleration fuel cut-off working condition, the opening of the supercharger control valve is gradually changed by adjusting the duty ratio of the supercharger control valve, then the outlet pressure of the supercharger control valve under different duty ratios is collected through a WGP pressure sensor, so that the outlet pressure of the control valve under different duty ratios can be obtained through calculation, and then the supercharger characteristic table in a supercharger control algorithm is updated through the learned parameters.
Specifically, as shown in fig. 2, an embodiment of the present invention provides an online self-learning method for flow characteristics of a control valve of a supercharger, including:
and S101, judging the working condition of the engine according to a preset period.
When the engine is determined to be in a preset working condition which does not affect the normal operation of the engine, self-learning operation of the flow characteristic of the control valve of the supercharger is executed, and steps S102 to S104 are executed:
and S102, setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of the air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve obtained after self-learning as the air source pressure.
S103, increasing the duty ratio of the supercharger control valve from 0 by a preset gradient to self-learn the characteristics of the supercharger control valve to obtain a relation table between the actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios.
And S104, updating a supercharger characteristic table in a supercharger control algorithm by using the obtained relation table.
In this embodiment, the preset working condition is a deceleration fuel cut-off working condition that does not affect the normal operation of the engine, that is, the deceleration fuel cut-off working condition in the operation process of the engine, the preset gradient is 5%, and the preset period is 10 ms. Step S103 is performed after the air supply pressure self-learning in step S102 is completed.
In addition, the step S102 of obtaining the outlet pressure of the supercharger control valve after the self-learning as the air supply pressure means that the pressure communicated to the atmosphere by the supercharger control valve 3 is adjusted to 0, and at this time, the outlet pressure of the supercharger control valve detected by the WGP pressure sensor 4 is the air supply pressure, and specifically, the step S102 may include:
step one, setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve at the moment;
and step two, judging the stability of the collected outlet pressure.
The specific judgment process of the step comprises the following steps: and performing low-pass filtering processing on the acquired outlet pressure, and if the difference value between the outlet pressure after the low-pass filtering processing and the outlet pressure before the low-pass filtering processing is smaller than a preset threshold value in a preset time, determining that the acquired outlet pressure is stable. The preset time and the preset threshold value may be determined according to actual conditions, and the present invention is not particularly limited. In one non-limiting embodiment, the predetermined time may be 0.2 seconds, and the predetermined pressure stability threshold may be 20 hPa.
And step three, after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
Further, step S103 includes:
the method comprises the following steps that firstly, the duty ratio of a booster control valve is increased from 0 by a preset gradient such as 5% until the duty ratio reaches 100%; in the increasing process, the stability of the outlet pressure after each increasing is judged, and after the outlet pressure after each increasing is determined to be stable, the outlet pressure after the increasing is recorded and the increasing of the duty ratio is carried out next time.
In this step, if the fluctuation range of the outlet pressure after each increment in the preset time is smaller than the preset fluctuation range value, the outlet pressure after the current increment is considered to be stable. The preset time for the outlet pressure to reach the stability after each increment and the preset fluctuation range value can be determined according to actual conditions, and the invention is not particularly limited. In one non-limiting embodiment, the predetermined time to reach stability may be 1 second, and the predetermined fluctuation range value may be 20 hPa.
And secondly, performing data fitting processing on each duty ratio of the supercharger control valve and corresponding outlet pressure to obtain a relation table between actual outlet pressure and the duty ratio.
In this step, each duty ratio of the supercharger control valve and the corresponding outlet pressure may be plotted in a rectangular coordinate system, and the discrete points are connected by a curve to perform data fitting processing, so as to obtain a relationship table between the target outlet pressure and the duty ratio, in which the outlet pressure is an input and the duty ratio is an output.
Furthermore, in an embodiment of the present invention, the method further includes: and if the engine is determined not to be in the preset working condition, stopping executing the self-learning operation of the flow characteristic of the control valve of the supercharger. That is, if the engine is not in the deceleration fuel cut-off condition during execution of the self-learning operation, the self-learning operation is immediately exited.
Further, in embodiments of the present invention, a self-learning success flag may be used to indicate a self-learning operation of the flow characteristic of the booster control valve. If the supercharger characteristic table in the supercharger control algorithm is updated, the self-learning success mark is 1; if the self-learning operation of the flow characteristic of the supercharger control valve is stopped, the self-learning success flag is made 0.
In one embodiment, as shown in fig. 3, the method for online self-learning of the flow characteristic of the control valve of the supercharger according to the embodiment of the present invention may include the following steps:
s201, judging whether the current working condition is in a deceleration fuel cut-off working condition or not by the engine ECU in 10ms week, if so, activating a self-learning function of the flow characteristic of the supercharger control valve, and executing the steps S202 to S209; if the two working conditions exit, the self-learning function exits immediately, and meanwhile, the self-learning success flag is set to be 0;
s202, after the self-learning function is activated, self-learning of air source pressure is firstly carried out. The method comprises the following steps that an engine control unit ECU sets the duty ratio of a supercharger control valve to be 0, and collects the outlet pressure of the supercharger control valve;
s203, judging whether the outlet pressure of the supercharger control valve acquired in the step S202 is stable, if so, executing a step S204, otherwise, circulating the step;
s204, taking the outlet pressure of the supercharger control valve judged to be stable in the step S203 as air source pressure; step S205 is executed;
s205, an engine control unit ECU increases the duty ratio of a supercharger control valve by a gradient of 5%, and collects the outlet pressure of the supercharger control valve after the duty ratio is increased; step S206 is executed;
s206, judging whether the outlet pressure acquired in the step S205 is stable, if so, executing the step S207, otherwise, circulating the step;
s207, taking the outlet pressure judged to be stable in the step S206 as the outlet pressure under the current duty ratio; executing step S208;
s208, judging whether the current duty ratio reaches 100%, if so, executing a step S209, otherwise, returning to the step S205;
s209, obtaining a relation table (outlet pressure is input, duty ratio is output) between target outlet pressure and duty ratio after data fitting processing is carried out on the collected data of each duty ratio and outlet pressure of the supercharger control valve, and updating a supercharger characteristic table in a supercharger control algorithm by using the relation table.
Namely, the online self-learning method for the flow characteristic of the control valve of the supercharger provided by the embodiment of the invention firstly self-learns the pressure of an air source, after the self-learning of the air source pressure is finished, the characteristic of the control valve of the supercharger is learned, in the learning process of the characteristic of the control valve of the supercharger, the duty ratio of the control valve of the supercharger is started from 0, the steps are increased by 5 percent until the duty ratio reaches 100 percent, and each time the duty ratio is increased, when the pressure at the outlet of the supercharger control valve is stable, the current pressure at the outlet of the supercharger control valve is recorded, namely, the stability of the outlet pressure of the control valve of the supercharger needs to be judged every time the duty ratio is increased, the next increase is carried out only after the stability, therefore, the acquired outlet pressure of the supercharger control valve is stable, the control parameter is consistent with the controlled object, and the control speed and the control precision of supercharger control can be improved.
The present embodiment takes a certain 8.6L natural gas engine as an example to illustrate the beneficial effects of the present invention. In a certain road endurance test of an engine, the supercharging pressure of the engine is found to be stable for a long time during acceleration and oscillate before being stable, the supercharging pressure is not consistent with engine bench test data, then monitoring data related to supercharger control is checked, the actual value of the outlet pressure of a supercharger control valve is found to be delayed from a desired value, then related pipeline devices of the supercharger control valve are checked, firstly, the pressure of a gas source for the supercharger control is found to deviate from the design value, the design value is 2.3bar, the actual pressure is only 2.15bar, then, the deviation of the output pressure curve of the supercharger control valve under the inlet pressure of 2.15bar and the response curve under the inlet pressure of 2.3bar is found to exceed 5%, and then, after characteristic parameters of the supercharger control valve are updated, the response curve of the supercharging pressure of the engine is consistent with the bench. Meanwhile, other supercharger control valves are checked, and the fact that even if the pressure of an inlet air source is the same, the output pressure curve is different proves that the characteristic curve of the supercharger control valve needs to be learned by self.
Based on the same inventive concept, the embodiment of the invention also provides an online self-learning system for the flow characteristic of the control valve of the supercharger, and as the principle of the problem solved by the system is similar to the online self-learning method for the flow characteristic of the control valve of the supercharger, the implementation of the system can refer to the implementation of the method, and repeated details are omitted.
As shown in fig. 4, an on-line self-learning system for flow characteristics of a control valve of a supercharger according to an embodiment of the present invention includes:
the judging module 301 is used for judging the working condition of the engine in a preset period;
a self-learning module 302, configured to perform the following self-learning operation of the flow characteristic of the supercharger control valve when the determination module determines that the engine is in a preset operating condition that does not affect normal operation of the engine:
setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of an air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve after self-learning as the air source pressure;
the duty ratio of the supercharger control valve is increased progressively from 0 by a preset gradient so as to carry out self-learning on the characteristics of the supercharger control valve and obtain a relation table between the actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios;
the supercharger control valve characteristic table in the supercharger control algorithm is updated using the obtained relationship table.
Further, the preset working condition is a deceleration fuel cut-off working condition in the running process of the engine.
Further, self-learning the air supply pressure flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve after the self-learning as the air supply pressure specifically comprises:
setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve;
judging the stability of the collected outlet pressure;
and after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
Further, the judging the stability of the collected outlet pressure includes: and performing low-pass filtering on the acquired outlet pressure, and if the difference value between the outlet pressure after the low-pass filtering and the outlet pressure before the low-pass filtering is smaller than a preset threshold value in a preset time, determining that the acquired outlet pressure is stable.
Further, self-learning the characteristics of the supercharger control valve to obtain a relation table between the actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios comprises the following steps:
increasing the duty ratio of the control valve of the supercharger from 0 by a preset gradient until the duty ratio reaches 100%; in the increasing process, judging the stability of the outlet pressure after each increasing, and after determining that the outlet pressure after each increasing is stable, recording the outlet pressure after the increasing and increasing the duty ratio of the next time;
and performing data fitting processing on each duty ratio of the supercharger control valve and the corresponding outlet pressure to obtain a relation table between the actual outlet pressure and the duty ratio.
Further, the preset gradient is 5%; the preset period is 10 ms.
Further, the self-learning module 302 is further configured to: and if the engine is determined not to be in the preset working condition, stopping executing the self-learning operation of the flow characteristic of the control valve of the supercharger.
Further, the self-learning module 302 uses a self-learning success flag to indicate a self-learning operation of the supercharger control valve flow characteristic; if the supercharger characteristic table in the supercharger control algorithm is updated, the self-learning success mark is 1; if the self-learning operation of the flow characteristic of the supercharger control valve is stopped, the self-learning success flag is made 0.
The above modules may be disposed in the engine control unit of the supercharger control system according to the foregoing embodiment, and the functions of the modules may correspond to the corresponding processing steps in the flowcharts shown in fig. 2 to 3, which are not described herein again.
The above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A method of online self-learning of flow characteristics of a control valve of a supercharger, the method comprising:
judging the working condition of the engine according to a preset period;
when the engine is determined to be in a preset working condition which does not affect the normal operation of the engine, the following self-learning operation of the flow characteristic of the supercharger control valve is executed:
setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of an air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve obtained after the self-learning as the air source pressure;
the duty ratio of the supercharger control valve is increased progressively from 0 by a preset gradient to self-learn the characteristics of the supercharger control valve, and a relation table between actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios is obtained;
updating a supercharger control valve characteristic table in a supercharger control algorithm by using the obtained relation table;
the preset working condition is a deceleration fuel cut-off working condition.
2. The method according to claim 1, wherein the setting the duty ratio of the supercharger control valve to 0 to self-learn the pressure of the air supply flowing into the supercharger control valve and the self-learning outlet pressure of the supercharger control valve is used as the air supply pressure specifically comprises:
setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve;
judging the stability of the collected outlet pressure;
and after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
3. The method of claim 2, wherein determining the stability of the collected outlet pressure comprises: and performing low-pass filtering processing on the acquired outlet pressure, and determining that the acquired outlet pressure is stable if the difference value between the outlet pressure after the low-pass filtering processing and the outlet pressure before the low-pass filtering processing is smaller than a preset threshold value.
4. The method according to claim 1, wherein the step-up of the duty ratio of the supercharger control valve from 0 by a preset gradient is performed to self-learn the characteristics of the supercharger control valve, and the table of the relationship between the actual outlet pressure and the duty ratio of the supercharger control valve at different duty ratios is obtained, and specifically comprises the following steps:
increasing the duty ratio of the control valve of the supercharger from 0 by a preset gradient until the duty ratio reaches 100%; in the increasing process, judging the stability of the outlet pressure after each increasing, and after determining that the outlet pressure after each increasing is stable, recording the outlet pressure after the increasing and increasing the duty ratio of the next time;
and performing data fitting processing on each duty ratio of the supercharger control valve and the corresponding outlet pressure to obtain a relation table between the actual outlet pressure and the duty ratio.
5. The method according to claim 1, wherein the preset gradient is 5%; the preset period is 10 ms.
6. An online self-learning system of flow characteristics of a booster control valve, comprising:
the judging module is used for judging the working condition of the engine according to a preset period;
the self-learning module is used for executing the following self-learning operation of the flow characteristic of the supercharger control valve when the judging module determines that the engine is in the preset working condition which does not influence the normal operation of the engine:
setting the duty ratio of the supercharger control valve to be 0 so as to self-learn the pressure of an air source flowing into the supercharger control valve, and taking the outlet pressure of the supercharger control valve after self-learning as the air source pressure;
the duty ratio of the supercharger control valve is increased progressively from 0 by a preset gradient to self-learn the characteristics of the supercharger control valve, and a relation table between actual outlet pressure and the duty ratio of the supercharger control valve under different duty ratios is obtained;
updating a supercharger control valve characteristic table in a supercharger control algorithm by using the obtained relation table;
the preset working condition is a deceleration fuel cut-off working condition.
7. The system of claim 6, wherein the setting of the duty cycle of the supercharger control valve to 0 to self-learn the pressure of the air supply flowing into the supercharger control valve and the self-learning outlet pressure of the supercharger control valve as the air supply pressure comprises:
setting the duty ratio of a supercharger control valve to be 0, and collecting the outlet pressure of the supercharger control valve;
judging the stability of the collected outlet pressure;
and after the acquired outlet pressure is determined to be stable, taking the stable outlet pressure as the air source pressure.
8. The system of claim 6, wherein the step-up of the duty cycle of the supercharger control valve from 0 by a preset gradient to self-learn the supercharger control valve characteristics to obtain the relationship table between the actual outlet pressure and the duty cycle of the supercharger control valve at different duty cycles comprises:
increasing the duty ratio of the control valve of the supercharger from 0 by a preset gradient until the duty ratio reaches 100%; in the increasing process, judging the stability of the outlet pressure after each increasing, and after determining that the outlet pressure after each increasing is stable, recording the outlet pressure after the increasing and increasing the duty ratio of the next time;
and performing data fitting processing on each duty ratio of the supercharger control valve and the corresponding outlet pressure to obtain a relation table between the actual outlet pressure and the duty ratio.
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