JPH0656118B2 - Internal combustion engine learning control device - Google Patents

Description

TECHNICAL FIELD The present invention relates to a learning control device for a feedback control system such as an air-fuel ratio (fuel injection amount) of an internal combustion engine, an ignition timing, an idle speed and the like.

<Prior Art> A conventional learning control device for an internal combustion engine is disclosed in Japanese Patent Laid-Open No. 59-
No. 203828, No. 59-21138, No. 60-90944, No. 61-19.
There is one disclosed in Japanese Patent No. 0141.

These are feedback correction values set by proportional / integral control, etc. while comparing the control target value and the actual value with the basic control amount set corresponding to the control target value such as the air-fuel ratio based on the operating state of the engine. In a system in which the control amount is calculated by performing a feedback control of the air-fuel ratio and the like by performing feedback control of the air-fuel ratio to the control target value, the deviation of the feedback correction value during feedback control from the reference value of the engine operating state Learning values for each area are used to determine the learning value for each area, and when calculating the control amount, the basic control amount is corrected by the learning value for each area, and the control value obtained by the control amount calculated without correction by the feedback correction value is controlled. The control amount is made to match the target value, and this is further corrected by the feedback correction value during the feedback control to calculate the control amount.

According to this, the follow-up delay of the feedback control during the transient operation can be eliminated during the feedback control, and the desired control output can be accurately obtained when the feedback control is stopped.

Therefore, variations in components such as the electronically controlled fuel injection device are absorbed, and secular changes in the charging efficiency of the engine and atmospheric pressure,
It is used to maintain maximum engine performance over a long period of time by compensating for changes in operating environment conditions such as temperature and humidity.

<Problems to be Solved by the Invention> However, such a conventional learning control device is a so-called iterative learning method using a data map, that is, a data map grid section is set according to an engine operating state, and feedback control in each learning area is performed. Since the deviation amount is updated by the repeated learning experience, if each learning area segment is set finely in order to improve the learning correction accuracy, the learning update speed becomes slow. In other words, the learning correction accuracy and the learning speed are conditions that conflict with each other.

In view of such conventional problems, an object of the present invention is to provide a learning control device for an internal combustion engine that can improve learning correction accuracy and significantly improve learning speed.

<Means for Solving Problems> In order to achieve the above object, the present invention configures a learning control device for an internal combustion engine including the following means A to H as shown in FIG.

(A) Basic control amount setting means for setting a basic control amount corresponding to the control target value of the control target of the internal combustion engine (B) Comparing the control target value and the actual value, in the direction of approaching the actual value to the control target value Feedback correction value setting means for increasing or decreasing the feedback correction value by a predetermined amount (C) Rewritable learning value storage means for storing a plurality of learning values for each factor (D) The basic control amount for the feedback correction value Control amount calculating means for calculating the control amount by further correcting the learning values for each of the plurality of factors into an addition term and a multiplication term with respect to the basic control amount, and correcting each according to these. Control means that operates according to the amount and controls the controlled object of the internal combustion engine (F) Deviation detection means that detects the deviation of the feedback correction value from the reference value (G) Engine operating state when the deviation is detected Information and deviations Factor analysis means for analyzing based on at least one of the related information and separating the deviation into a plurality of parameters for each factor at a rate determined by the information (H) For each factor of the storage means based on each of the plurality of parameters Factor-based learning value updating means for modifying and rewriting the learning value <Operation> The basic control amount setting means A corresponds to a control target value of a control target (for example, air-fuel ratio, ignition timing, idle speed, etc.) of the internal combustion engine. The basic control amount is set, and the feedback correction value setting means B compares the control target value with the actual value and sets the feedback correction value in a direction to bring the actual value closer to the control target value, for example, based on proportional / integral control. Increase or decrease the amount to set. Then, the control amount calculation means D corrects the basic control amount with the feedback correction value, and further, the plurality of factor-based learning values stored in the factor-based learning value storage means C are added to the basic control amount and the multiplication term. The control amount is calculated by dividing into and and optimally correcting according to these.
Then, the control means E operates according to the control amount to control the control target of the internal combustion engine.

On the other hand, the deviation detecting means F detects the deviation of the feedback correction value from the reference value. And the factor analysis means G
Is a predetermined factor based on at least one of information about the engine operating state at the time of deviation detection and information about deviation (information about deviation amount, deviation direction, deviation speed, deviation change direction, etc.). It is analyzed speculatively according to the analysis rule, and the deviation is separated into a plurality of parameters for each factor at a rate determined by the information. Then, the factor-based learning value updating means H corrects and rewrites the factor-based learning value in the storage means C based on each of the plurality of separated parameters.

In this way, the deviation (error amount) of the feedback control is detected, this is inferred using various information and the database, the factor analysis is performed, the parameter is separated into a plurality of parameters, and the optimum arithmetic expression for each factor is used. That is, the learning correction accuracy and the learning speed are made compatible by dividing the addition term and the multiplication term with respect to the basic control amount and correcting them with high accuracy.

<Example> An example in which the learning control device according to the present invention is applied to a feedback control system of an air-fuel ratio of an internal combustion engine having an electronically controlled fuel injection device will be described below.

In FIG. 2, air is sucked into the engine 1 from an air cleaner 2 through an intake duct 3, a throttle valve 4 and an intake manifold 5. At the branch portion of the intake manifold 5, a fuel injection valve 6 as a control means is provided for each cylinder. The fuel injection valve 6 is an electromagnetic fuel injection valve that is energized by a solenoid to open and stop energized to be closed. The fuel injection valve 6 is energized and opened by a drive pulse signal from a control unit 12 described later, and a fuel not shown is shown. Fuel that is pumped and adjusted to a predetermined pressure by a pressure regulator is injected and supplied. Although this example is a multi-point injection system, it may be a single-point injection system in which a single fuel injection valve is provided in common to all cylinders upstream of the throttle valve.

A spark plug 7 is provided in the combustion chamber of the engine 1 to ignite sparks to ignite and burn the air-fuel mixture.

Exhaust gas is discharged from the engine 1 through the exhaust manifold 8, the exhaust duct 9, the three-way catalyst 10, and the muffler 11. The three-way catalyst 10 is an exhaust purification device that oxidizes CO and HC in the exhaust components and reduces NO _x to convert them into other harmless substances, and burns the air-fuel mixture at the stoichiometric air-fuel ratio. Sometimes both conversion efficiencies are the best.

The control unit 12 includes a CPU, ROM, RAM,
The microcomputer is provided with an A / D converter and an input / output interface, receives input signals from various sensors, performs arithmetic processing as described later, and controls the operation of the fuel injection valve 6.

As the various sensors, a hot-wire type or flap type air flow meter 13 is provided in the intake duct 3 and outputs a voltage signal according to the intake air flow rate Q.

Further, the crank angle sensor 14 is provided, and in the case of four cylinders, it outputs a reference signal for each crank angle of 180 ° and a unit signal for each crank angle of 1 ° or 2 °. Here, the engine speed N can be calculated by measuring the cycle of the reference signal or the number of generated unit signals within a predetermined time.

A water temperature sensor 15 for detecting the cooling water temperature Tw of the water jacket of the engine 1 is also provided.

Further, an O ₂ sensor 16 is provided at the collecting portion of the exhaust manifold 8 to detect the air-fuel ratio of the air-fuel mixture sucked into the engine 1 via the O ₂ concentration in the exhaust. If the O ₂ sensor 16 with the NO _x reduction catalyst layer proposed in Japanese Patent Application No. 62-65844 is used, more accurate detection becomes possible.

Here, the CPU of the microcomputer built in the control unit 12 is a program (a fuel injection amount calculation routine, an air-fuel ratio feedback control routine, a program on a ROM shown as a flowchart in FIGS. 3 to 5).
The fuel injection is controlled by performing arithmetic processing according to the optimum learning routine).

The functions as the basic control amount setting means, the feedback correction value setting means, the control amount calculating means, the deviation detecting means, the factor analyzing means and the factor-based learning value updating means are achieved by the program. A RAM is used as the factor-based learning value storage means, and the stored contents are retained by the backup power source even after the engine key switch is turned off.

Next, with reference to the flow charts of FIGS. 3 to 5, the state of the arithmetic processing of the microcomputer in the control unit 12 will be described.

FIG. 3 is a fuel injection amount calculation routine, which is executed every predetermined time.

In step 1 (denoted as S1 in the drawing; the same applies hereinafter), the intake air flow rate Q detected based on the signal from the air flow meter 13 and the engine speed N calculated based on the signal from the crank angle sensor 14 , The water temperature Tw or the like detected based on the signal from the water temperature sensor 15 is input.

In step 2, the basic fuel injection amount Tp corresponding to the intake air amount per unit rotation is calculated from the intake air flow rate Q and the engine speed N.
= K · Q / N (K is a constant) is calculated. This step 2
The part of corresponds to the basic control amount setting means.

In step 3, the water temperature correction coefficient K _TW corresponding to the water temperature Tw,
Various correction factors including the air-fuel ratio correction factor K _MR according to the engine speed N and the basic fuel injection amount Tp COEF = 1 + K
Set _TW + K _MR + ...

In step 4, the latest air-fuel ratio feedback correction coefficient α (reference value 1) set by the air-fuel ratio feedback control routine of FIG. 4 described later is read.

In step 5, the voltage correction amount Ts is calculated based on the battery voltage.
To set. This is to correct the change in the injection flow rate of the fuel injection valve 6 due to the change in the battery voltage.

In step 6, the factor-based learning values X ₁ and X ₂ are read from a predetermined address of the RAM serving as the factor-based learning value storage means.
At the time when learning is not started, as an initial value,
X ₁ = 0 and X ₂ = 1 are stored.

In step 7, the fuel injection amount Ti is calculated according to the following equation. Here, one of the factor-based learning values X ₁ is defined as an addition term for the basic fuel injection amount Tp, and the other factor-based learning value X ₂ is defined as a multiplication term for the basic fuel injection amount Tp. . The part of this step 7 corresponds to the control amount calculation means.

Ti = X ₂ · Tp · COEF · α + (Ts + X ₁ ) In step 8, the calculated Ti is set in the output register. As a result, a predetermined engine rotation synchronization (for example, 1
At each fuel injection timing (every rotation), the drive pulse signal having the pulse width of Ti which is set latest is given to the fuel injection valve 6 to perform fuel injection.

FIG. 4 is an air-fuel ratio feedback control routine, which is executed in rotation synchronization or time synchronization, whereby the air-fuel ratio feedback correction coefficient α is set. Therefore, this routine corresponds to the feedback correction value setting means.

In step 11, it is determined whether or not a predetermined air-fuel ratio feedback control condition is satisfied. Here, the predetermined air-fuel ratio feedback control condition is a condition that the engine speed N is a predetermined value or less and the basic fuel injection amount Tp representing the load is a predetermined value or less. If this condition is not satisfied, this routine ends. In this case, the air-fuel ratio feedback correction coefficient α is clamped to the previous value (or the reference value 1), and the air-fuel ratio feedback control is stopped. This is because the air-fuel ratio feedback control is stopped in the high rotation or high load region, a rich output air-fuel ratio is obtained by the air-fuel ratio correction coefficient K _MR , and an increase in exhaust temperature is suppressed.
This is to prevent seizure of the engine 1 and burnout of the three-way catalyst 10.

If the air-fuel ratio feedback control condition is satisfied, step 12
Proceed to the following.

At step 12, the output voltage V ₀₂ of the O ₂ sensor 16 is read, and at next step 13, it is compared with the slice level voltage V _ref corresponding to the stoichiometric air-fuel ratio to determine the rich / lean of the air-fuel ratio.

When the air-fuel ratio is lean (V ₀₂ <V _ref ), the _routine proceeds from step 13 to step 14, and it is judged whether or not it is during the reversal from rich to lean (immediately after the reversal), and at the time of reversal, the routine proceeds to step 15. For the optimum learning routine shown in FIG. 5, which will be described later, the deviation of the previous air-fuel ratio feedback correction coefficient α from the reference value 1 is stored as a = α−1, and then the routine proceeds to step 16, where the air-fuel ratio feedback correction coefficient α is set to the previous time. The value is increased by a predetermined proportional constant P. Step except when flipping
Proceeding to 17, the air-fuel ratio feedback correction coefficient α is increased by a predetermined integration constant I with respect to the previous value, and thus the air-fuel ratio feedback correction coefficient α is increased at a constant slope.
Note that P >> I.

When the air-fuel ratio is rich (V ₀₂ > V _ref ), the _routine proceeds from step 13 to step 18, and it is determined whether or not the lean-to-rich reversal is occurring (immediately after the reversal). For the optimum learning routine shown in FIG. 5, which will be described later, after storing the deviation of the previous air-fuel ratio feedback correction coefficient α from the reference value 1 as b = α−1, the process proceeds to step 20 and the air-fuel ratio feedback correction coefficient α is set to the previous time. The value is decreased by a predetermined proportional constant P. Step except when flipping
The routine proceeds to step 21, where the air-fuel ratio feedback correction coefficient α is decreased by a predetermined integration constant I with respect to the previous value, and thus the air-fuel ratio feedback correction coefficient α is decreased with a constant inclination.

FIG. 5 shows an optimal learning routine, which is executed at predetermined time intervals.
As a result, the factor-specific learning values X ₁ and X ₂ are set / updated.

In step 31, it is determined whether or not a predetermined learning condition is satisfied. Here, the predetermined learning condition is that the air-fuel ratio feedback control is being performed, and the rich / lean signal of the O ₂ sensor 16 is inverted at an appropriate cycle. If this condition is not satisfied, this routine ends.

When the predetermined learning condition is satisfied, the routine proceeds to step 32, where it is judged whether or not the output voltage V ₀₂ of the O ₂ sensor 16 is reversed, and when it is not reversed, the routine proceeds to step 33 and the engine operating state at that time is judged. The engine speed N and the basic fuel injection amount Tp are sampled as the data.

When the output voltage V ₀₂ of the O ₂ sensor 16 is reversed, the process proceeds to step 34 to obtain the average value of the above-mentioned a and b for optimum learning. At this time, a and b are peak values above and below the deviation from the reference value 1 of the air-fuel ratio feedback correction coefficient α from the reverse of the increasing / decreasing direction of the air-fuel ratio feedback correction coefficient α to the inversion as shown in FIG. The average deviation Δα from the reference value 1 of the air-fuel ratio feedback correction coefficient α is detected by obtaining the average value of these.

Therefore, steps 15 and 19 in FIG. 4 and step 34 in FIG.
The part of corresponds to the deviation detecting means.

Next, in step 35, the output voltage V ₀₂ of the O ₂ sensor 16
Of the engine speed N and the basic fuel injection amount Tp (N ₁ , N ₂ ..., Tp ₁ , Tp ₂ , ...) During the reversal of
The engine operating state (N, Tp) is specified.

Next, the routine proceeds to step 36, where the learning weighting parameters K ₁ and K ₂ assigned to each area are searched by referring to the map from the area of the engine operating state (N, Tp). However, K ₁
+ K ₂ is 1 or less.

Here, the factors leading to the deviation Δα are mainly caused by the fuel injection valve 6 (hereinafter referred to as F / I factor) and those caused by the air flow meter 13 including the air density change (hereinafter referred to as Q factor). That is, each of them is represented by K ₁ and K ₂ .

Then, from the rule of thumb, it is estimated that the F / I factor is large in the low rotation and low load region and the Q factor is large in the high rotation and high load, and the values of K ₁ and K ₂ are assigned to each area, and this map is assigned. By referring to, the factor analysis is performed based on the engine operating state.

As a result, the deviation Δα is set to the parameter K ₁ of the F / I factor.
It becomes possible to separate Δα and the Q factor parameter K ₂ · Δα, and in the next step 37, Δα ₁ = K ₁ ·
Separation into each parameter with Δα and Δα ₂ = K ₂ · Δα.

Therefore, steps 35 to 37 correspond to factor analysis means.

Incidentally, the factor analysis is performed based on the information regarding the engine operating state as described above, and also based on the information regarding the deviation such as the deviation amount, the deviation direction, the deviation speed, and the deviation change direction, based on those databases. May be.

Next, in step 38, the factor-based learning values X ₁ and X ₂ stored in a predetermined address on the RAM are read out, and the deviation Δα ₁ is added to the learning value X ₁ of _one F / I factor as shown in the following equation. M ₁
The value is added and updated, and the deviation Δ is added to the learning value X ₂ of the other Q factor.
α ₂ is added by M ₂ and updated. M ₁ and M ₂ are learning weighting coefficients.

X ₁ = X ₁ + M ₁ · Δα ₁ X ₂ = X ₂ + M ₂ · Δα ₂ Next, the process proceeds to step 39, and these factor-based learning values X ₁ and X ₂ are written to a predetermined address on the RAM to write data. rewrite. This RAM is a backup memory, and the stored contents are stored and retained even after the engine key switch is turned off.

Therefore, the steps 38 and 39 correspond to the factor-based learning value updating means.

In this way, the learning value X ₂ of the learning values X ₁ and Q factor of the F / I factor is not is determined, these correction on groups, as shown by step 7 in Figure 3, the following It is performed in an optimal form for each factor based on the arithmetic expression of.

Ti = X ₂ · Tp · COEF · α + (Ts + X ₁ ) That is, since the learning value X ₁ of the F / I factor is due to the fuel injection valve 6 itself, the basic fuel injection amount is the same as the voltage correction amount Ts. As an addition term to Tp,
Regarding the learning value X ₂ of the Q factor, the basic fuel injection amount Tp (=
(K · Q / N) due to the intake air flow rate Q and correcting the constant K, the basic fuel injection amount Tp
An arithmetic expression is set as a multiplication term for, and optimal correction is performed by these.

Figure 7 shows that the effect of this learning control is + 16% of □.
The engine with a rich tendency of 4 approaches the engine with the central value of the variation of ● after learning about 4 times, and the engine of △ indicates-
The engine with a lean tendency of 16% approaches the engine with the median variation of the ● mark after learning about three times, and the learning speed improvement by this learning control is clearly shown.

In the present embodiment, the so-called L-Jetro system that has an air flow meter to detect the intake air flow rate is shown as the electronically controlled fuel injection device, but a so-called D-Jetro system that detects the intake manifold negative pressure is shown. , Or the so-called α depending on the throttle valve opening (α) and the engine speed (N)
-It can be applied to various systems such as N system.

Further, not only the feedback control of the air-fuel ratio, but also the ignition timing control by knocking detection and the feedback control of the idle speed via the auxiliary air valve can be applied.

<Advantages of the Invention> As described above, according to the present invention, the factor that causes the deviation is analyzed based on various information at that time and the factor is learned instead of the conventional method of learning by the area. As the method, and the learning value for each factor is divided into an addition term and a multiplication term for the basic control amount and is corrected by the optimal calculation formula for each factor, learning correction accuracy is improved and learning speed is significantly increased. Can be improved. Further, by such learning control, it is possible to reduce the matching man-hours, simplify component management, and maintain free. Also, the capacity of the backup memory can be reduced.

[Brief description of drawings]

FIG. 1 is a functional block diagram showing a configuration of the present invention, FIG. 2 is a system diagram showing an embodiment of the present invention, FIGS. 3 to 5 are flow charts showing control contents, and FIG. 6 is an air-fuel ratio feedback. FIG. 7 is a diagram showing how the correction coefficient changes, and FIG. 7 is a diagram showing the effect of learning control. 1 ...... engine, 6 ...... fuel injection valve, 12 ...... control unit, 13 ...... air flow meter, 14 ...... crank angle sensor, 16 ...... O ₂ sensor

Claims (1)

[Claims] 1. A basic control amount setting means for setting a basic control amount corresponding to a control target value of an object to be controlled of an internal combustion engine, and a direction in which a control target value and an actual value are compared to bring the actual value closer to the control target value. Feedback correction value setting means for increasing or decreasing the feedback correction value by a predetermined amount, rewritable learning value storage means for storing a plurality of learning values for each factor, and the basic control amount by the feedback correction value. Correct,
Further, the plurality of factor-based learning values are divided into an addition term and a multiplication term with respect to the basic control amount, respectively corrected and corrected, and a control amount calculation means for calculating the control amount, and an operation according to the control amount are performed. Control means for controlling the controlled object of the internal combustion engine, a deviation detection means for detecting a deviation of the feedback correction value from the reference value, and a factor of the deviation of information on the engine operating state and information on the deviation at the time of deviation detection Factor analysis means for analyzing at least one of the parameters and separating the deviation into a plurality of parameters for each factor at a rate determined by the information, and modifying the factor-based learning value of the storage means based on each of the plurality of parameters. A learning control device for an internal combustion engine, characterized in that: