CN115750116A - VVT phase closed-loop self-adaptive control method, device and storage medium - Google Patents
VVT phase closed-loop self-adaptive control method, device and storage medium Download PDFInfo
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Abstract
The invention discloses a VVT phase closed-loop self-adaptive control method, which comprises the following steps of: judging whether a phase closed-loop control self-learning activation condition is met or not according to the working condition of the engine, and if the phase closed-loop control self-learning activation condition is met, keeping the self-learning activation condition stable; judging whether the condition of stabilizing the self-learning activation condition is established or not, and entering a self-learning activation stage if the condition is established; calculating and updating the I item control duty ratio storage value; repeating the self-learning process until the self-learning activation condition is not met any more, and determining the final I-term control duty ratio learning value; and adding the learning value of the I item control duty ratio to the PID control duty ratio to serve as the final phase closed-loop control duty ratio. The invention also discloses VVT phase closed-loop self-adaptive control equipment and a storage medium. The invention can self-learn the VVT phase control under any working condition on the premise of not influencing the normal operation of the engine, accurately control the phase and solve the problems of economy, dynamic property and the like.
Description
Technical Field
The invention belongs to the technical field of engine control, and particularly relates to a VVT phase closed-loop self-adaptive control method, VVT phase closed-loop self-adaptive control equipment and a storage medium.
Background
With the development of the automobile industry and the increasing importance of people on the living environment, the requirements on the performance, the oil consumption and the emission of an engine are higher and higher. Research has shown that VVT (Variable Valve Timing) technology has great advantages in terms of both fuel consumption and dynamics. The VVT technology determines a target phase according to the running condition of an engine, calculates the deviation between the target phase and the actual phase, uses the deviation value as a feedback signal to carry out closed-loop control, and adjusts the amount of air intake (exhaust) and the opening and closing time and angle of an air valve through the adjustment of the cam phase, so that the air quantity entering the engine is optimal, the combustion efficiency of the fuel oil of the engine is improved, the power of the engine is improved, and the oil consumption is saved. Therefore, VVT technology is becoming widely used and has been changed from the past as an engine-specific technology to the standard of fuel-powered engines. In order to meet the increasingly strict emission standard and the high requirement on the thermal efficiency of the engine in modern society, the design of the engine is more and more complex, and the working condition of the engine is continuously variable, so that the control requirement on the VVT phase is higher and higher. How to improve the accuracy of VVT phase control becomes an urgent problem to be solved.
Disclosure of Invention
The invention aims to provide a VVT phase closed-loop self-adaptive control method, which is used for self-learning VVT phase control and realizing accurate phase control.
To achieve the above object, according to an aspect of the present invention, there is provided a VVT phase closed-loop adaptive control method, including the steps of:
judging whether a phase closed-loop control self-learning activation condition is met or not according to the working condition of the engine, and if the phase closed-loop control self-learning activation condition is met, keeping the self-learning activation condition stable;
judging whether the condition of stabilizing the self-learning activation condition is established or not, and entering a self-learning activation stage if the condition is established;
accumulating target VVT phase sum, engine oil temperature sum, engine oil pressure sum, engine target load sum, engine actual load sum and I control duty ratio sum in the T time period in the self-learning activation stage;
entering a self-learning storage stage, and calculating a target VVT phase average value phi in the T time period DsrdAvg Average value of engine oil temperature T OilAvg Average value of engine oil pressure p OilAvg Target engine load average rho DsrdAvg Average actual engine load rho ActAvg Average value pct of I control duty ratio InteAvg The average value of the I item control duty ratio is limited within a certain range, and the calculation result is updated into the I item control duty ratio storage value;
repeating the self-learning process until the self-learning activation condition is not met any more, and determining a final I-term control duty ratio learning value;
and adding the PID control duty cycle and the I item of control duty cycle learning value as a final phase closed-loop control duty cycle.
Further, the phase closed-loop control self-learning activation condition comprises:
the engine is in a running state;
the carbon tank is not opened;
the rotating speed of the engine is in a certain range, and the fluctuation of the rotating speed of the engine entering the phase closed-loop control self-learning is small;
the target VVT phase is in a certain range, and the engine target VVT phase entering the phase closed-loop control self-learning has small fluctuation;
the actual VVT phase is in a certain range, and the actual VVT phase of the engine entering the phase closed-loop control self-learning has small fluctuation;
the target load of the engine is in a certain range, and the target load of the engine entering the phase closed-loop control self-learning has small fluctuation;
the actual load of the engine is in a certain range, and the actual load of the engine entering the phase closed-loop control self-learning has small fluctuation;
the temperature of the engine oil is in a certain range, and the temperature fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
the engine oil pressure is in a certain range, and the pressure fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
the voltage of the storage battery is in a certain range, and the voltage of the storage battery entering the phase closed-loop control self-learning has small fluctuation;
the difference between the target load and the actual load of the engine is always greater than 0 and is within a certain range or the difference between the target load and the actual load of the engine is always less than 0 and is within a certain range, and the fluctuation of the difference between the target load and the actual load of the engine entering the phase closed-loop control self-learning is small;
the water temperature of the engine is in a certain range;
the VVT control enters a closed loop control activation phase.
Further, in any self-learning stage, when any one of the self-learning activation conditions is not met, the self-learning non-activation stage is exited.
Further, the condition that the self-learning activation condition is stable is as follows:
the phase control self-learning non-updating time exceeds the preset time;
the self-learning activation conditions are all satisfied for exceeding the preset time;
at least one of the working conditions has a meeting time exceeding a preset time;
the working condition comprises the following steps:
condition 1: the ratio of the engine requested gas circuit torque to the maximum gas circuit torque capacity exceeds a preset value;
condition 2: the ignition efficiency exceeds a preset value;
condition 3: the throttle is in a fully open mode;
condition 4: the throttle is in a non-wide open mode.
Further, the updating the calculation result to the I term control duty cycle storage value includes: and sequentially judging whether the working condition is met or not according to the priority of each condition in the working condition, and if so, updating the current average target VVT phase, the average engine oil temperature, the average engine oil pressure, the average engine target load and the average I item control duty ratio under the average engine actual load into an I item control duty ratio storage area under the corresponding condition.
Further, the determining the final I term control duty cycle learning value includes: and sequentially judging whether the working condition conditions are met or not according to the priority of each condition in the working condition conditions, and if so, extracting the learning values of the corresponding storage area and the working condition as the final I-item control duty ratio learning value.
Further, when the working condition changes, the change rate of the I term control duty ratio learning value is limited, and the maximum value of the absolute value of the change rate of the I term control duty ratio learning value is determined according to the following formula:
wherein rho DsrdAvg As an average value of the target engine load, rho ActAvg As the average value of the actual engine load, phi DsrdAvg K1, k2, D are constants for the target VVT phase average.
Further, the repeating the self-learning process until the self-learning activation condition is no longer satisfied includes: and after the self-learning storage stage is finished, if the self-learning times are plus 1 and the self-learning activation condition is still met, returning to the self-learning activation stage to start a new round of self-learning.
According to another aspect of the present invention, there is provided a VVT phase closed-loop adaptive control apparatus, comprising a memory and a processor, the memory having stored thereon a control program, the control program being loaded and executed by the processor to implement the VVT phase closed-loop adaptive control method as described above.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing a control program for implementing the VVT phase closed-loop adaptive control method as described above when executed by a processor.
In general, compared with the prior art, the above technical solutions conceived by the present invention can achieve the following beneficial effects:
1. the invention can carry out self-learning on the VVT phase closed-loop control under any working condition on the premise of not influencing the normal operation of the engine, accurately control the phase, solve the problems of economy, dynamic property and the like of the engine, and do not influence the self-learning process even if the difference of the working performance of the VVT, the difference of the manufacturing of the engine or the difference of the life cycle of the engine exists.
2. The invention limits the change rate of the I item control duty ratio learning value when the working condition changes, and avoids the influence of overlarge air quantity fluctuation on VVT phase control precision.
Drawings
Fig. 1 is a flowchart of a VVT phase closed-loop adaptive control method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The camshaft phase Control system mainly comprises a cam phaser, a camshaft position sensor, a water temperature sensor, an Oil Control Valve (OCV), a crankshaft position sensor and an Electronic Control Unit (ECU). The cam phaser is mainly composed of a rotor blade, a stator and a return spring. Wherein the rotor blade is fixed on the air inlet camshaft, and the stator and the driven timing chain wheel are integrated. The ECU calculates the valve timing angle (namely the target phase) required by the engine under each working condition, calculates the actual phase of the camshaft according to feedback signals transmitted by a crankshaft position sensor and a cam position sensor, compares the target phase with the actual phase, and sends a control signal to a timing hydraulic control valve according to the deviation value of the target phase and the actual phase. When the engine oil in the oil circuit of the system is controlled by the timing hydraulic control valve to generate pressure, the engine oil extrudes the rotor and drives the air inlet cam shaft to rotate, so that the phase of the cam shaft is advanced, lagged or kept, and the opening and closing time of the air inlet valve is changed. The phaser forms two hydraulic chambers, a valve timing advance chamber and a valve timing retard chamber, during movement of the rotor. Additionally, an oil pressure sensor that reads the oil pressure of the main oil gallery and/or a variable displacement oil pump that adjusts the oil pressure may be added to the camshaft phase control system.
The common VVT phase control adopts a PID control algorithm, and the invention stores the I-item duty ratio of the phase control for improving the control response precision.
As shown in fig. 1, an embodiment of the present invention provides a VVT phase closed-loop adaptive control method, including the following steps:
step one, judging whether a phase closed-loop control self-learning activation condition is met or not according to the working condition of the engine, and if the phase closed-loop control self-learning activation condition is met, keeping the self-learning activation condition stable.
The phase closed-loop control self-learning needs to be carried out when the working condition of the engine is stable so as to ensure the accuracy of the self-learning. The activation condition of the phase closed-loop control self-learning is the most basic premise for the phase closed-loop control to enter the self-learning. The self-learning process can only be started if the most basic preconditions are met.
The activation conditions of the phase closed loop control self-learning comprise:
1. the engine is in a running state;
2. the carbon tank is not opened;
3. the rotating speed of the engine is in a certain range, and the fluctuation of the rotating speed of the engine entering the phase closed-loop control self-learning is small;
4. the target VVT phase is in a certain range, and the engine target VVT phase entering the phase closed-loop control self-learning has small fluctuation;
5. the actual VVT phase is in a certain range, and the actual VVT phase of the engine entering the phase closed-loop control self-learning has small fluctuation;
6. the target load of the engine is in a certain range, and the target load of the engine entering the phase closed-loop control self-learning has small fluctuation;
7. the actual load of the engine is in a certain range, and the actual load of the engine entering the phase closed-loop control self-learning has small fluctuation;
8. the temperature of the engine oil is in a certain range, and the temperature fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
9. the pressure of the engine oil is in a certain range, and the pressure fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
10. the voltage of the storage battery is in a certain range, and the voltage of the storage battery entering the phase closed-loop control self-learning has small fluctuation;
11. the difference between the target load and the actual load of the engine is always greater than 0 and within a certain range, or the difference between the target load and the actual load of the engine is always less than 0 and within a certain range, and the fluctuation of the difference between the target load and the actual load of the engine entering the phase closed-loop control self-learning is small;
12. the water temperature of the engine is in a certain range, so that the combustion condition of the engine is better;
and 13, the VVT control enters a closed loop control activation phase.
And after the self-learning activation conditions are all met, entering a self-learning stabilization stage to keep the self-learning activation conditions stable. And in any stage of self-learning, when any one of the self-learning activation conditions is not met, exiting to a self-learning inactivated state.
And step two, judging whether the condition of stabilizing the self-learning activation condition is satisfied, and entering a self-learning activation stage if the condition is satisfied.
The conditions for stabilizing the self-learning activation condition are as follows:
1. the phase control self-learning non-updating time exceeds the preset time, namely the phase control self-learning times do not update the preset time, so that the problem that the self-learning updating is too frequent, and the accuracy of the learning value is reduced on the contrary is avoided.
2. The self-learning activation conditions are all satisfied for exceeding a preset time T0.
3. At least one of the working condition conditions has the satisfaction time exceeding the preset time T1, wherein T1 is less than T0;
the working condition comprises the following steps:
condition 1: the ratio of the engine request gas circuit torque to the maximum gas circuit torque capacity exceeds a preset value, and the preset value is 0.95 in the embodiment;
condition 2: the ignition efficiency exceeds a preset value, and the preset value is 0.8 in the embodiment;
condition 3: the throttle valve is in a full-open mode, namely the ratio of the pressure at the outlet of the throttle valve to the pressure at the inlet of the throttle valve exceeds a preset value, and the preset value is 0.994 in the embodiment;
condition 4: the throttle is in a non-wide open mode, i.e. when the ratio of the throttle outlet and inlet pressures does not exceed a predetermined value, in this embodiment the predetermined value is 0.994.
If the condition that the self-learning activation condition is stable is not established but the activation condition is met, the self-learning activation condition is maintained in the self-learning stabilization stage, and the self-learning activation condition is continuously kept stable. And if the condition that the self-learning activation condition is stable is not established and the self-learning activation condition is not met, returning to the self-learning inactivated stage. And after the self-learning activation condition is met and the condition that the self-learning activation condition is stable is met, entering the next stage, namely a VVT phase closed-loop control self-learning activation stage.
And step three, accumulating the target VVT phase sum, the engine oil temperature sum, the engine oil pressure sum, the engine target load sum, the engine actual load sum and the I control duty ratio sum in the T time period in the self-learning activation stage.
And in the self-learning activation phase, lasting for a certain time T (T is not more than T1), accumulating the target VVT phase sum, the engine oil temperature sum, the engine oil pressure sum, the engine target load sum, the engine actual load sum and the I control duty ratio sum in the T time period. And after the time T is met, entering the next phase, namely a VVT phase closed-loop control self-learning storage phase.
Step four, entering intoA learning storage stage, calculating a target VVT phase average value phi in the T time period DsrdAvg Average value of engine oil temperature T OilAvg Average value of engine oil pressure p OilAvg Target engine load average rho DsrdAvg Average actual engine load rho ActAvg I term control duty cycle average value pct InteAvg And the average value of the I item of control duty ratio is limited in a certain range, and the calculation result is updated into the storage value of the I item of control duty ratio.
And in the phase closed-loop control self-learning storage stage, the stored value of the VVT phase closed-loop control steady-state error is updated. The I control duty ratios under different target VVT phases, oil temperatures, oil pressures, engine target loads and engine actual loads are stored in a nonvolatile memory EEPROM. The EEPROM has an initial default I item control duty ratio, and the stored value in the EEPROM is updated after the VVT phase closed loop control self-learning is completed.
The phase closed-loop control self-learning storage stage mainly completes the following work:
(1) Calculating a target VVT phase average value phi in the T time period according to the target VVT phase sum, the engine oil temperature sum, the engine oil pressure sum, the engine target load sum, the engine actual load sum and the I item control duty ratio sum in the T time period DsrdAvg Average value of engine oil temperature T OilAvg Average value of engine oil pressure p OilAvg Target engine load average rho DsrdAvg Average actual engine load rho ActAvg I term control duty cycle average value pct InteAvg The average value of the I control duty ratio is limited within a certain range, and the average value of the I control duty ratio in the embodiment does not exceed +/-10%;
(2) And updating the current average target VVT phase, the average engine oil temperature, the average engine oil pressure, the average engine target load and the average I term control duty ratio value under the average engine actual load into the EEPROM.
And (3) storing the I-item control duty ratio average value in an EEPROM in a separated manner, specifically, dividing the EEPROM into 4 storage areas according to 4 conditions in the working condition, sequentially judging whether the working condition conditions are met or not according to the priority of the 4 conditions, and if so, updating the I-item control duty ratio average value into the storage areas under the corresponding conditions. Condition 1 has the highest priority, followed by condition 2, and so on, and condition 4 has the lowest priority. If the condition 1 is satisfied, storing the learned value in the storage area under the condition 1; if the condition 1 is not met, judging whether the condition 2 is met, and if the condition 2 is met, storing the learning value in a storage area under the condition 2; if condition 2 is still not satisfied, then it is determined whether condition 3 is satisfied, and so on.
The working condition comprises the following steps:
condition 1: the ratio of the engine request gas circuit torque to the maximum gas circuit torque capacity exceeds a preset value, and the preset value is 0.95 in the embodiment;
condition 2: the ignition efficiency exceeds a preset value, and the preset value is 0.8 in the embodiment;
condition 3: the throttle valve is in a full-open mode, namely the ratio of the pressure at the outlet of the throttle valve to the pressure at the inlet of the throttle valve exceeds a preset value, and the preset value is 0.994 in the embodiment;
condition 4: the throttle is in a non-wide open mode, i.e. when the ratio of the throttle outlet and inlet pressures does not exceed a predetermined value, in this embodiment the predetermined value is 0.994.
The specific updating method of the I item control duty ratio learning value is as follows:
initial value of learning value pct LrnRaw ＝pct InteAvg ，pct InteAvg Controlling the average value of the duty ratio for the I term in the T time period;
supposing that the current VVT phase closed-loop control self-learning in the Nth same storage area is the same, the learning value of the VVT phase self-learning in the Nth same storage area is pct Lrn (N) then:
pct Lrn (N)＝r 1 ×[pct LrnRaw (N)-pct Lrn (N-1)]+pct Lrn (N-1) wherein N =1,2,3 \ 8230;, pct LrnRaw (N) is the initial value of VVT phase self-learning value of the Nth same storage region, pct Lrn (N-1) is a VVT phase self-learning value of the same storage region at the N-1 st time,r 1 for coefficients, take between 0 and 1.
And after the updating is finished, the VVT phase closed-loop control self-learning storage phase is ended, and the updated I item control duty ratio learning value is stored in the EEPROM.
And step five, repeating the self-learning process until the self-learning activation condition is not met any more, and determining the final I-term control duty ratio learning value.
And after the self-learning storage stage is finished, the self-learning times are +1. And if the self-learning activation condition of the phase closed-loop control is still met, returning to the self-learning activation stage, counting again by accumulating the time T, and starting a new round of self-learning. And if the self-learning activation condition of the phase closed-loop control is not met any more, entering a self-learning inactivated state.
The method for determining the final I control duty cycle learning value is as follows:
and (3) judging whether the working condition conditions are met or not in sequence from condition 1 to condition 4 according to the priorities of 4 conditions in the working condition conditions from high to low, and if so, extracting learning values under the corresponding storage region and the working condition (target VVT phase, engine oil temperature, engine oil pressure, engine target load and engine actual load) as final I item control duty ratio learning values.
The working condition comprises the following steps:
condition 1: the ratio of the torque of the engine request gas circuit to the maximum gas circuit torque capacity exceeds a preset value, and the preset value is 0.95 in the embodiment;
condition 2: the ignition efficiency exceeds a preset value, and the preset value is 0.8 in the embodiment;
condition 3: the throttle valve is in a full-open mode, namely the ratio of the pressure at the outlet and the pressure at the inlet of the throttle valve exceeds a preset value, and the preset value is 0.994 in the embodiment;
condition 4: the throttle is in a non-wide open mode, i.e. when the ratio of the throttle outlet and inlet pressures does not exceed a predetermined value, in this embodiment the predetermined value is 0.994.
If the working condition changes in the above region, limiting the change rate of the I term control duty ratio learning value, wherein the maximum value of the absolute value of the change rate of the I term control duty ratio learning value is determined according to the following formula:
wherein rho DsrdAvg As an average value of the target engine load, rho ActAvg As the average of the actual engine load, phi DsrdAvg In order to obtain the target VVT phase average value, k1, k2, and D are constants, in this embodiment, k1 is 0.0258, k2 is-0.03894, and D is 0.1234, which is designed to avoid fluctuation of the gas amount and ensure that the fluctuation of the difference between the target gas amount and the actual gas amount is within ± 2% when the operating condition changes.
And step six, adding the learning value of the I item control duty ratio to the PID control duty ratio to serve as the final phase closed-loop control duty ratio.
The embodiment of the present invention further provides a VVT phase closed-loop adaptive control apparatus, which includes a memory and a processor, where the memory stores a control program, and the control program is loaded and executed by the processor to implement the VVT phase closed-loop adaptive control method described above, and the processor may be a CPU, a controller, a microcontroller, a microprocessor, or another data processing chip.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a control program, and the control program is used for implementing the VVT phase closed-loop control method as described above when executed by a processor. The technical solution of the present invention may be substantially implemented or partially implemented in the prior art, and the technical solution may be implemented in the form of a software product, which is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the method embodiments of the present invention. The computer-readable storage medium includes various media capable of carrying computer program code, such as a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a Random Access Memory (RAM), and the like.
In this patent, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrases "comprising 8230; \8230;" comprises 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A VVT phase closed-loop adaptive control method is characterized by comprising the following steps:
judging whether a phase closed-loop control self-learning activation condition is met or not according to the working condition of the engine, and if the phase closed-loop control self-learning activation condition is met, keeping the self-learning activation condition stable;
judging whether the condition of stabilizing the self-learning activation condition is established or not, and entering a self-learning activation stage if the condition is established;
accumulating target VVT phase sum, engine oil temperature sum, engine oil pressure sum, engine target load sum, engine actual load sum and I control duty ratio sum in the T time period in the self-learning activation stage;
entering a self-learning storage stage, and calculating a target VVT phase average value phi in the T time period DsrdAvg Average value of engine oil temperature T OilAvg Average value p of engine oil pressure OilAvg Target engine load average rho DsrdAvg Average actual engine load rho ActAvg I term control duty cycle average value pct InteAvg And the average value of the I control duty ratio is limited toUpdating the calculation result to the I item control duty ratio storage value within a certain range;
repeating the self-learning process until the self-learning activation condition is not met any more, and determining a final I-term control duty ratio learning value;
and adding the learning value of the I item control duty ratio to the PID control duty ratio to serve as the final phase closed-loop control duty ratio.
2. The VVT phase closed-loop adaptive control method of claim 1, wherein the phase closed-loop control self-learning activation condition comprises:
the engine is in a running state;
the carbon tank is not opened;
the rotating speed of the engine is in a certain range, and the fluctuation of the rotating speed of the engine entering the phase closed-loop control self-learning is small;
the target VVT phase is in a certain range, and the engine target VVT phase entering the phase closed-loop control self-learning has small fluctuation;
the actual VVT phase is in a certain range, and the actual VVT phase of the engine entering the phase closed-loop control self-learning has small fluctuation;
the target load of the engine is in a certain range, and the target load of the engine entering the phase closed-loop control self-learning has small fluctuation;
the actual load of the engine is in a certain range, and the actual load of the engine entering the phase closed-loop control self-learning has small fluctuation;
the temperature of the engine oil is in a certain range, and the temperature fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
the engine oil pressure is in a certain range, and the pressure fluctuation of the engine oil entering the phase closed-loop control self-learning is small;
the voltage of the storage battery is in a certain range, and the voltage fluctuation of the storage battery entering the phase closed-loop control self-learning mode is small;
the difference between the target load and the actual load of the engine is always greater than 0 and is within a certain range or the difference between the target load and the actual load of the engine is always less than 0 and is within a certain range, and the fluctuation of the difference between the target load and the actual load of the engine entering the phase closed-loop control self-learning is small;
the water temperature of the engine is in a certain range;
the VVT control enters a closed loop control activation phase.
3. The VVT phase closed-loop adaptive control method of claim 2, wherein at any stage of self-learning, when any one of the self-learning activation conditions is not satisfied, then exiting to a self-learning inactive state.
4. The VVT phase closed-loop adaptive control method of claim 1, wherein the condition that the self-learning activation condition is stable is:
the phase control self-learning non-updating time exceeds the preset time;
the self-learning activation conditions are all satisfied for exceeding the preset time;
at least one of the working condition conditions has a satisfied time exceeding a preset time;
the working condition comprises the following steps:
condition 1: the ratio of the engine requested gas circuit torque to the maximum gas circuit torque capacity exceeds a preset value;
condition 2: the ignition efficiency exceeds a preset value;
condition 3: the throttle is in a fully open mode;
condition 4: the throttle is in a non-wide open mode.
5. The VVT phase closed-loop adaptive control method of claim 4, wherein the updating the calculation result to the I-term control duty cycle storage value includes: and sequentially judging whether the working condition is met or not according to the priority of each condition in the working condition, and if so, updating the current average target VVT phase, the average engine oil temperature, the average engine oil pressure, the average engine target load and the average I item control duty ratio under the average engine actual load into an I item control duty ratio storage area under the corresponding condition.
6. The VVT phase closed-loop adaptive control method of claim 5, wherein the determining a final I term control duty cycle learned value includes: and sequentially judging whether the working condition conditions are met or not according to the priority of each condition in the working condition conditions, and if so, extracting the learning values of the corresponding storage area and the working condition as the final I-item control duty ratio learning value.
7. The VVT phase closed-loop adaptive control method of claim 6, wherein when a change in operating condition occurs, a rate of change of the I term control duty learning value is limited, and an absolute value maximum of the rate of change of the I term control duty learning value is determined according to the following formula:
wherein rho DsrdAvg As an average value of the target engine load, rho ActAvg As the average value of the actual engine load, phi DsrdAvg K1, k2, D are constants for the target VVT phase average.
8. The VVT phase closed-loop adaptive control method of claim 1, wherein repeating the self-learning process until a self-learning activation condition is no longer satisfied comprises: and after the self-learning storage stage is finished, if the self-learning times are plus 1 and the self-learning activation condition is still met, returning to the self-learning activation stage to start a new round of self-learning.
9. A VVT phase closed-loop adaptive control apparatus comprising a memory and a processor, the memory having stored thereon a control program that is loaded and executed by the processor to implement the VVT phase closed-loop adaptive control method according to any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a control program which when executed by a processor is configured to implement the VVT phase closed-loop adaptive control method of any one of claims 1 to 8.
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