JPH0656126B2 - 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 based on a data map, that is, a data map grid section is set according to an engine operating state, and a learning map in each learning area is set. This is a method in which the feedback control deviation amount is updated by repeated learning experience, so if the learning area divisions are set finely in order to improve learning correction accuracy, there is a drawback that 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 K as shown in FIG.

(A) Basic control amount setting means for setting the basic control amount corresponding to the control target value of the controlled object 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 multiple learning values for each factor (D) Area for each area of engine operating state Rewritable area-by-area learning value storage means for storing learning values (E) Area-by-area learning value search means (F) for searching for corresponding area-by-area learning values from the area-by-area learning value storage means based on engine operating conditions A control amount calculation for calculating a control amount by correcting the basic control amount with the feedback correction value, and further correcting the control amount with an arithmetic expression respectively set based on the factor-based learning value and the area-based learning value. Means ( G) Control means that operates according to the control amount to control the controlled object of the internal combustion engine (H) Deviation detection means that detects a deviation of the feedback correction value from a reference value (I) When the deviation is detected as a factor of the deviation Factor analysis means (J) for analyzing the deviation based on at least one of the information on the engine operating state and the information on the deviation and separating the deviation into a plurality of parameters for each factor at a rate determined by the information (J) Factor-based learning value updating means for modifying and rewriting the factor-based learning value in the storage means based on (K) A corresponding engine operating state of the area-based learning value storage means based on a parameter that cannot be factor analyzed in the deviation Area-specific learning value updating means for modifying and rewriting the area-specific learning value for each area <Operation> The basic control amount setting means A is a control target of the internal combustion engine (for example, air-fuel ratio, ignition timing, eye A basic control amount corresponding to a control target value such as dollar rotation speed) is set, and the feedback correction value setting means B compares the control target value with the actual value to perform feedback correction in a direction to bring the actual value closer to the control target value. The value is set by increasing or decreasing by a predetermined amount based on, for example, proportional / integral control, and the area-by-area learning value search means E learns from the area-by-area learning value storage means D by area-by-area learning corresponding to the area of the actual engine operating state. Search for a value. The control amount calculation means F
Is an optimum value which is set in accordance with a plurality of factor-based learning values stored in the factor-based learning value storage means C and an area-based learning value, respectively, by correcting the basic control amount with a feedback correction value. The control amount is calculated by correcting with a simple calculation formula. Then, the control means G operates according to this control amount, and controls the control measures of the internal combustion engine.

On the other hand, the deviation detecting means H detects the deviation of the feedback correction value from the reference value. Then, the factor analysis means I
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.). An inferential analysis is performed according to the analysis rule, and the deviation is separated into a plurality of parameters for each factor based on the analysis result. Then, the learning value updating means J for each factor is
The factor-based learning value in the factor-based learning value storage unit C is corrected and rewritten based on each of the separated plurality of parameters.

Further, the remaining part of the deviation, which cannot be factor-analyzed by the factor analysis means I, is treated as a parameter of the factor-analysis not possible portion, and the area-by-area learning value updating means K stores the area-by-area learning value storage means D on the basis of this parameter. Correct the learning value for each area of the corresponding engine operating state and rewrite.

In this way, the deviation (error amount) of the feedback control is detected, this is inferred using various information and the database, factor analysis is performed, the parameters are separated into a plurality of parameters, and an arithmetic expression suitable for each factor is used. Correct with high accuracy. Then, only the parameters for which the factor analysis cannot be completed are learned for each area of the engine operating state and corrected for each area. As a result, even if the learning by area is delayed, the learning correction accuracy and the learning speed can be made compatible by the uniform learning by factor.

<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.

In addition, the crank angle sensor 14 is provided, and in the case of four cylinders, it outputs a reference signal for each 180 ° crank angle and a unit signal for each 1 ° or 2 ° crank angle. 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 of the basic control amount setting means, the feedback correction value setting means, the area-based learning value searching means, the control amount computing means, the deviation detecting means, the factor analyzing means, the factor-based learning value updating means, and the area-based learning value updating means. Is achieved by the above program. Further, RAM is used as the learning value storage means for each factor and the learning value storage means for each area, 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, various correction coefficients including the water temperature correction coefficient K _TW according to the water temperature Tw, the air-fuel ratio correction coefficient K _MR according to the engine speed N and the basic fuel injection amount Tp, etc. COEF = 1 + K _TW +
Set 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. still,
When learning is not started, the initial value is X ₁
= 0 and X ₂ = 1 are stored.

In step 7, R as an area-by-area learning value storage means that stores the area-by-area learning value X ₃ corresponding to the engine speed N and the basic fuel injection amount (load) Tp representing the engine operating state.
X corresponding to actual N and Tp by referring to the map on AM
Search for and load ₃ . The part of step 7 corresponds to the learning value search means for each area. In the map of the learning value X ₃ for each area, the engine operating speed N is used as the horizontal axis and the basic fuel injection amount Tp is used as the vertical axis, and the engine operating state area is divided by a grid of about 8 × 8. The different learning value X ₃ is stored, and when the learning is not started, X ₃ = 0 is stored as the initial value.

In step 8, the fuel injection amount Ti is calculated according to the following equation. The part of step 8 corresponds to the control amount calculation means.

Ti = X ₂ · Tp · COEF · (α + X ₃ ) + (Ts + X ₁ ) In step 9, the calculated Ti is set in the output register. As a result, a predetermined engine rotation synchronization (for example, 1
At every fuel injection timing (every rotation), a 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 speed 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 to prevent seizure or three This is to prevent the original catalyst 10 from burning.

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

In step 12, the output voltage V ₀₂ of the O ₂ sensor 16 is read,
In the next step 13, the rich / lean air-fuel ratio is judged by comparing with the slice level voltage _Vref corresponding to the theoretical air-fuel ratio.

When the air-fuel ratio is lean (V ₀₂ <V _ref ), step 13
To step 14 to determine whether it is during the reversal from rich to lean (immediately after reversal), and when reversing, proceed to step 15 to perform the previous air-fuel ratio feedback correction for the optimum learning routine of FIG. 5 described later. After the deviation of the coefficient α from the reference value 1 is stored as a = α−1, the routine proceeds to step 16, where the air-fuel ratio feedback correction coefficient α is increased by a predetermined proportional constant P with respect to the previous value. Step 17 except when reversing
Then, 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. still,
P >> I.

If the air-fuel ratio is rich (V ₀₂ > V _ref ), step 13
To step 18 to determine whether or not the lean-to-rich reversal is being performed (immediately after the reversal), and when reversing, the process proceeds to step 19 to perform the previous air-fuel ratio feedback correction for the optimum learning routine shown in FIG. After the deviation of the coefficient α from the reference value 1 is stored as b = α−1, the routine proceeds to step 20, where the air-fuel ratio feedback correction coefficient α is decreased by a predetermined proportional constant P with respect to the previous value. Step 21 except when reversing
Then, the air-fuel ratio feedback correction coefficient α is decreased from the previous value by a predetermined integration constant I, and thus the air-fuel ratio feedback correction coefficient α is decreased at a constant slope.

FIG. 5 shows an optimal learning routine, which is executed at predetermined time intervals.
As a result, the learning values X ₁ and X _{2 for} each factor and the learning value X for each area
₃ is set and 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. Engine speed N and basic fuel injection amount T as data
Sample p and.

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 reference value 1 of the air-fuel ratio feedback correction coefficient α is obtained by obtaining the average value of these.
The average deviation Δα from is detected.

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

Next, the routine proceeds to step 35, where the changes in the engine speed N and the basic fuel injection amount Tp (N ₁ , N ₂ ..., Tp ₁ , Tp ₂ ...) are read while the output voltage V ₀₂ of the O ₂ sensor 16 is reversed. , The engine operating state (N, Tp) is specified as the average value thereof.

Next, the routine proceeds to step 36, in which the learning weighting parameters K ₁ , K ₂ , K ₃ assigned to each area are searched from the area of the engine operating state (N, Tp) with reference to the factor analysis map.
However, K ₁ + K ₂ + K ₃ = 1.

Here, the factors leading to the deviation Δα are 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 AF / M factor). , And other uncertain factors, and their respective proportions are represented by K ₁ , K ₂ , and K ₃ .

Then, it is estimated from experience that the F / I factor is large in the low rotation and low load region and the AF / M factor is large in the high rotation and high load, and the values K ₁ and K ₂ are assigned to each area. _Three
= _1-K 1 -K ₂ advance assigned as, by referring to this factor analysis map is perform factor analysis based on the engine operating condition.

As a result, the deviation Δα is set to the parameter K ₁ of the F / I factor.
- and [Delta] [alpha], and the parameter _{K 2} · [Delta] [alpha] of the AF / M factor, delta
It becomes possible to separate into α ₃ = parameter K ₃ · Δα of other undetermined factors, and in the next step 37, Δα ₁
= K ₁ · Δα, Δα ₂ = K ₂ · Δα, K ₃ · Δα, and the parameters are separated.

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
One F / I factor deviation [Delta] [alpha] ₁ to the learning value _{X 1} is updated by adding _{M 1} minute, the deviation [Delta] [alpha] ₂ is updated by adding _{M 2} minutes to the learning value _{X 2} of the other AF / M factors. 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, advance to step 39 and write these learning values X ₁ and X ₂ for each factor into 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 AF / M factor F / I factor is not is determined, these correction on groups, as shown in step 8 of FIG. 3 , It is performed in an optimal form for each factor based on the following arithmetic expression.

Ti = X ₂ · Tp · COEF · (α + X ₃ ) + (Ts + X ₁ ) That is, the learning value X ₁ of the F / I factor is caused by the fuel injection valve 6 itself, and thus is the same as the voltage correction component Ts. As an addition term to the basic fuel injection amount Tp,
Regarding the learning value X ₂ of the AF / M factor, the basic fuel injection amount T
Since it is due to the intake air flow rate Q in p (= K · Q / N) and is a proportional factor, an arithmetic expression is set as a multiplication term for the basic fuel injection amount Tp, and the optimum correction is made by these. Done.

Next, the routine proceeds to step 40, where the area learning value X ₃ in the area of the current engine operating state (N, Tp) is read by referring to the map on the RAM. Then, the deviation [Delta] [alpha] ₃ of the factor analysis impossible min in this area learning value X ₃ and M ₃ added in step 41, updates the area learning value X ₃ (see the following equation). M
₃ is a learning weighting coefficient.

X ₃ = X ₃ + M ₃ · Δα ₃ Next, advance to step 42, and write the updated learning value X ₃ by area in the area of the corresponding engine operating state of the map on the RAM to rewrite the data. .

Therefore, steps 40 to 42 correspond to the learning value updating means for each area.

In this way, as in the conventional case, the method of learning and correcting the non-factor analysis is performed for each engine operating area.

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 this 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.

<Effects of the Invention> As described above, according to the present invention, the factor that causes the deviation in the feedback control is analyzed and learned for each factor, and only the non-factor analysis is learned for each area. The learning speed can be significantly improved by uniform factor-based learning without lowering the correction accuracy. Further, by such learning control, it is possible to reduce matching man-hours, simplify component management, and maintain free.

BRIEF DESCRIPTION OF THE 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, FIG. 6 is a diagram showing how the air-fuel ratio feedback 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 area-specific learning for each engine operating area Rewritable area-by-area learning value storage means for storing a value; area-by-area learning value searching means for searching for the corresponding area-by-area learning value from the area-by-area learning value storage means based on the engine operating state; Is corrected with the feedback correction value,
Further, based on the learning value for each factor and the learning value for each area, a control amount calculation means for correcting the control amount by correcting with an arithmetic expression respectively set therein, and an internal combustion engine that operates according to the control amount Control means for controlling a controlled object of the engine, deviation detection means for detecting a deviation of the feedback correction value from a reference value, and at least one of information on the engine operating state and information on the deviation at the time of detecting the deviation factor Factor analysis means for analyzing the deviation on the basis of one and separating the deviation into a plurality of parameters for each factor at a rate determined by the information; and a learning value for each factor of the factor-based learning value storage means based on each of the plurality of parameters. Factor-based learning value updating means for modifying and rewriting the above, and corresponding engine operation of the area-based learning value storage means based on a parameter of the deviation that cannot be factor analyzed. Learning control apparatus for an internal combustion engine characterized in that it is configured to include an area learning value correction means to rewrite and correct the area learning value of the status area, the.