JPH0740673Y2 - Air-fuel ratio learning controller for internal combustion engine - Google Patents

Description

[Detailed description of the device]

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a learning control device for an air-fuel ratio feedback control system in an internal combustion engine having an electronically controlled fuel injection device.

[0002]

2. Description of the Related Art A fuel injection valve used in an electronically controlled fuel injection device is opened by a drive pulse signal given in synchronism with the rotation of an engine, and a fuel of a predetermined pressure is injected during the valve opening period. Has become. Therefore, the fuel injection amount is controlled by the pulse width of the drive pulse signal, and this pulse width T
If i is a control signal corresponding to the fuel injection amount, Ti is determined by the following equation in order to obtain the theoretical air-fuel ratio which is the target air-fuel ratio.

T _i = T _p · COEF · α + T _s However, T _p is a basic pulse width corresponding to the basic fuel injection amount and is called the basic fuel injection amount for convenience. When T _p = K · Q / N, K
Is a constant, Q is an engine intake air flow rate, and N is an engine speed. COEF is various correction factors such as water temperature correction. α is a feedback correction coefficient for air-fuel ratio feedback control (λ control) described later. T _s is a voltage correction amount, and is for correcting the change in the injection flow rate of the fuel injection valve due to the fluctuation of the battery voltage.

For the λ control, the exhaust system is supplied with O ₂
A sensor is provided to detect the actual air-fuel ratio, and the slice level controls whether the air-fuel ratio is richer or thinner than the theoretical air-fuel ratio.Therefore, the feedback correction coefficient α is defined and Is maintained at the stoichiometric air-fuel ratio. Here, the value of the feedback correction coefficient α is changed by proportional-plus-integral (PI) control for stable control.

That is, the output voltage of the O ₂ sensor is compared with the slice level voltage. When the output voltage is higher than the slice level and is lower than the slice level, the air-fuel ratio becomes rich without suddenly increasing or decreasing. In the case of (light), the air-fuel ratio is controlled to be thin (thick) by first lowering (raising) P minutes and then gradually lowering (raising) I minutes (see FIG. 6).

However, under the condition that λ control is not performed, α is clamped and various correction coefficients COEF are set to obtain a desired air-fuel ratio. By the way, if the base air-fuel ratio under the λ control condition, that is, the air-fuel ratio when α = 1 can be set to the theoretical air-fuel ratio (λ = 1), the feedback control is not necessary, but in reality, the component parts ( For example, variations in the air flow meter, fuel injection valve, pressure regulator, control unit) and changes over time, non-linearity of the pulse width-flow rate characteristics of the fuel injection valve, changes in operating conditions and the environment, etc. Since deviation from = 1 occurs, feedback control is performed.

However, if the base air-fuel ratio deviates from λ = 1, it takes time to stabilize the step of the base air-fuel ratio to λ = 1 by feedback control when the operating region changes greatly. For this reason, since the proportional and integral constants (P / I) are increased, overshoot and undershoot occur and controllability deteriorates. That is, when the base air-fuel ratio deviates from λ = 1, the air-fuel ratio control is performed within a range that is considerably different from the theoretical air-fuel ratio.

As a result, the operation is performed in a place where the conversion efficiency of the three-way catalyst is poor, and the cost is increased due to an increase in the amount of precious metal in the catalyst, and the catalyst is replaced due to the deterioration of the conversion efficiency due to the deterioration of the catalyst. To be forced. Therefore, by setting the base air-fuel ratio to λ = 1 by learning, it is possible to eliminate the deviation from λ = 1 caused by the step of the base air-fuel ratio in the transition period, and to reduce the P / I component so that the controllability is improved. An air-fuel ratio learning control device for improving the fuel efficiency is disclosed by the present applicant in Japanese Patent Application No. 58-76221.
-203828) or Japanese Patent Application No. 58-197499.
Filed as an issue.

This is because when the base air-fuel ratio deviates from the stoichiometric air-fuel ratio during the feedback control of the air-fuel ratio, the feedback correction coefficient α becomes large in order to fill the gap, so that the related operating state at this time and α Is detected, a learning correction coefficient Kl based on the α is obtained, and this is stored,
When the same engine operating state occurs again, the stored learning correction coefficient Kl is used to correct the base air-fuel ratio to the stoichiometric air-fuel ratio so that the responsiveness is improved. Learning correction coefficient Kl here
Is stored for each area in a predetermined range which is grid-divided according to an appropriate parameter of the engine operating state such as engine speed and load on the RAM map.

Specifically, a map of the learning correction coefficient Kl in response to the engine operating conditions such as engine speed and load is provided on the RAM, and when calculating the fuel injection amount T _i , the basic fuel is calculated by the following equation. The injection amount T _P is corrected by the learning correction coefficient Kl. T _i = T _p · COEF · Kl · α + T _s Then, the learning of Kl proceeds in the following procedure.

1) In a steady state, a region of the engine operating state at that time is detected, and a deviation Δα (= α-α ₁ ) from a reference value α ₁ of α during that time is detected as an average value.
The reference value α ₁ is generally set to 1 as a value corresponding to λ = 1. 2) Search for Kl learned so far in response to the region of the engine operating state.

3) The value of Kl + MΔα is obtained from Kl and Δα, and the result (learning value) is updated as a new Kl _(NEW) and the memory is updated. M is a constant and 0 <M <1.

[0013]

By the way, in such an air-fuel ratio learning control device, learning of the learning correction coefficient is performed when the engine operating state is in the steady state, that is, the learning region, as described above. However, under actual operating conditions, there are few opportunities for the engine operating state to stay in the same learning region, so the learning progress speed is slow, and better air-fuel ratio control can be performed by learning. There was a problem that it took time to become.

If the number of grids dividing the region is reduced and each learning region is expanded, the chances that the engine operating state stays within the same learning region increases and the learning progress speed is increased. The deviation of the engine operating state in the same learning region becomes large, so that the deviation amount of the air-fuel ratio becomes large and the learning control accuracy cannot be improved. The relationships between these are shown in FIGS. 10 and 11.

The present invention has been made by paying attention to such a conventional problem, and an internal combustion engine which solves the above problems by changing the size of the learning region according to the learning progress of each region. An object of the present invention is to provide an air-fuel ratio learning control device for an engine.

[0016]

In order to achieve the above object, the present invention provides a learning control device for an air-fuel ratio of an internal combustion engine,
As shown in FIG. 1, it is configured by the following means (A) to (K), and is characterized in that the means (J) and (K) are provided in particular. (A) A first detecting means for detecting an engine intake air intake flow rate, a second detecting means for detecting an engine speed, and a third detecting means for detecting an engine exhaust gas component and thereby an air-fuel ratio of an engine intake air-fuel mixture. Engine operating state detection means including at least detection means (B) A basic fuel injection amount is calculated based on the engine intake air flow rate output by the first detection means and the engine speed output by the second detection means. Basic fuel injection amount calculation means (C) Lattice axis that divides the engine operating region state into a plurality of regions by its parameters, and learning correction for correcting the basic fuel injection amount for each region surrounded by these lattice axes Possible storage means for storing the coefficient and (D) Learning correction coefficient retrieval means for retrieving the learning correction coefficient of the corresponding region from the storage means based on the actual engine operating state (E) Output from the third detection means Feedback correction coefficient setting means for comparing the air-fuel ratio with the target air-fuel ratio and setting a feedback correction coefficient for correcting the basic fuel injection amount by increasing or decreasing a predetermined amount so as to bring the actual air-fuel ratio close to the target air-fuel ratio. (F) Fuel injection amount based on the basic fuel injection amount calculated by the basic fuel injection amount calculation means, the learning correction coefficient searched by the learning correction coefficient search means, and the feedback correction coefficient set by the feedback correction coefficient setting means (G) Fuel injection means for injecting fuel into the engine on / off according to a drive pulse signal corresponding to the fuel injection quantity calculated by the fuel injection quantity calculation means (H) Actual engine Steady-state detection means for detecting that the operating state is in a steady state (I) For each region corresponding to when the engine operating state is in a steady state Learning correction coefficient correction means (J) for correcting and rewriting the learning correction coefficient corresponding to the region of the engine operating state in the direction of learning the deviation of the feedback correction coefficient of the region from the reference value and reducing it, and Learning Progression Determining Means for Determining Each Area Divided by the Lattice Axis of the Storage Means (K) For the areas determined to have been learned by the learning progressing degree determining means, the areas are newly constructed as a new grid. Learning area switching means for subdividing into a plurality of small areas by an axis, and correcting and rewriting the learning correction coefficient by the learning correction coefficient correction means for each of the subdivided areas

[0017]

The basic fuel injection amount calculation means B calculates the basic fuel injection amount corresponding to the target air-fuel ratio from the engine intake air intake flow rate and the engine speed according to a predetermined calculation formula, and the learning correction coefficient retrieval means D stores it. The means C retrieves the learning correction coefficient in the region corresponding to the actual engine operating state, and the feedback correction coefficient setting means E compares the actual air-fuel ratio with the target air-fuel ratio and sets the actual air-fuel ratio to the target air-fuel ratio. The feedback correction coefficient is set to increase or decrease by a predetermined amount based on, for example, proportional-plus-integral control so as to approach. Then, the fuel injection amount calculation means F
Calculates the fuel injection amount by correcting the basic fuel injection amount with a learning correction coefficient (searched or corrected as described later after the search) and further with a feedback correction coefficient. Then, the fuel injection means G is operated by the drive pulse signal corresponding to this fuel injection amount.

On the other hand, when the steady state detecting means H detects the steady state, the learning correction coefficient correcting means I learns the deviation of the feedback correction coefficient from the reference value and decreases the deviation in the engine. The learning correction coefficient corresponding to the operating state region is corrected and the data in the storage unit C is rewritten.
Here, the learning progress correction unit J determines the learning progress for each of the regions partitioned by the lattice axis of the storage unit, and the learning region switching unit K operates for the region determined to have progressed the learning. The area is subdivided into a plurality of small areas by a new lattice axis, and the learning correction coefficient correcting unit I corrects and rewrites the learning correction coefficient for each of the subdivided areas.

In this way, in the region where learning is not progressing, learning is promoted by keeping the region that is relatively large initially divided, and the progress of learning is promoted, and the region where learning is progressing is Further, detailed learning is performed for each subdivided region, and the accuracy of air-fuel ratio control by learning can be improved. Therefore, in the stage where learning is not progressing in the entire region or around the region where the progress speed of learning is slow, it is possible to suppress the delay of local learning by uniformly learning in a relatively large divided region, After learning progresses to some extent and the average air-fuel ratio deviation in the region is reduced, learning can be performed for each region subdivided to eliminate variations in the region to improve the air-fuel ratio control accuracy. You can do it.

[0020]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. In FIG. 2, air is sucked into the engine 1 through an air cleaner 2, an intake duct 3, a throttle chamber 4 and an intake manifold 5. The intake duct 3 is provided with an air flow meter 6 as a means for detecting the intake air flow rate Q and outputs a voltage signal corresponding to the intake air flow rate Q signal. The throttle chamber 4 is provided with a primary-side throttle valve 7 and a secondary-side throttle valve 8 that interlock with an accelerator pedal (not shown), and controls the intake air flow rate Q. Further, an auxiliary air passage 9 for bypassing these throttle valves 7, 8 is provided, and an idle control valve 10 is interposed in this auxiliary air passage 9. The intake manifold 5 or the intake port of the engine 1 is provided with a fuel injection valve 11 as fuel injection means. This fuel injection valve
Reference numeral 11 denotes an electromagnetic fuel injection valve which is energized by a solenoid to open the valve and deenergized to close the valve.The solenoid is energized by a drive pulse signal to open the valve, and is fed under pressure from a fuel pump (not shown) to a predetermined pressure by a pressure regulator. The fuel whose pressure is controlled to is injected and supplied to the engine 1.

Exhaust gas is discharged from the engine 1 through an exhaust manifold 12, an exhaust duct 13, a three-way catalyst 14, and a muffler 15. The exhaust manifold 12 is provided with an O ₂ sensor 16. This O ₂ sensor 16 outputs a voltage signal according to the ratio between the oxygen concentration in the atmosphere (constant) and the oxygen concentration in the exhaust gas, and the electromotive force suddenly changes when the air-fuel mixture is burned at the stoichiometric air-fuel ratio. Sensor. Therefore, the O ₂ sensor 16 is a means for detecting the air-fuel ratio (rich / lean) of the air-fuel mixture. The three-way catalyst 14 is a catalyst device that efficiently oxidizes or reduces CO, HC, and NO _x in the exhaust gas components near the stoichiometric air-fuel ratio of the air-fuel mixture and converts them into other harmless substances.

Besides, a crank angle sensor 17 is provided. The crank angle sensor 17 is provided with a signal disk plate 19 on a crank pulley 18, and a tooth provided on the outer periphery of the plate 19 outputs a reference signal every 120 ° and a position signal every 1 °. Here, the engine speed N can be calculated by measuring the cycle of the reference signal. Therefore, the crank angle sensor 17 is a means for detecting not only the crank angle but also the engine speed N.

Output signals from the air flow meter 6, the crank angle sensor 17 and the O ₂ sensor 16 are all input to the control unit 30. Further, the voltage of the battery 20 is directly applied to the control unit 30 as its operating power source and for detecting the power source voltage via the engine key switch 21. Further, if necessary, the control unit 30 further includes a water temperature sensor 22 for detecting the engine cooling water temperature, a throttle sensor 23 including an idle switch for detecting the throttle opening of the primary throttle valve 7, a vehicle speed sensor 24 for detecting the vehicle speed, A signal from the neutral switch 25 or the like for detecting the neutral position of the transmission is input. Then, in this control unit 30, arithmetic processing is performed based on various input signals,
A drive pulse signal having an optimum pulse width is output to the fuel injection valve 11 to obtain the fuel injection amount for obtaining the optimum air-fuel ratio.

As shown in FIG. 3, the control unit 30 includes a CPU 31, a P-ROM 32, a CMOS-RAM 33,
It has an address decoder 34. Here, the RAM 33 is a rewritable storage means for learning control, and as an operating power source of the RAM 33, an appropriate power source for the operation of the RAM 33 without holding the battery 20 through the engine key switch 21 in order to retain the stored contents after the engine key switch 21 is turned off. Connect via a regulated power supply.

Among the input signals to the CPU 31, the voltage signals from the air flow meter 6, the O ₂ sensor 16, the battery 20, the water temperature sensor 22 and the throttle sensor 23 are analog signals, so the analog input interfaces 35 and A are used.
It is adapted to be inputted via the / D converter 36. A
The / D converter 36 is controlled by the CPU 31 via the address decoder 34 and the A / D conversion timing controller 37. The reference signal and the position signal from the crank angle sensor 17 are input via the one-shot multi circuit 38. The signal from the idle switch built in the throttle sensor 23 and the signal from the neutral switch 25 are input through the digital input interface 39, and the signal from the vehicle speed sensor 24 is a waveform shaping circuit 40.
It is designed to be input via.

An output signal from the CPU 31 (a drive pulse signal for the fuel injection valve 11) is sent to the fuel injection valve 11 via the current waveform control circuit 41. put it here,
The CPU 31 performs input / output operations and arithmetic processing according to a program (stored in the ROM 32) based on the flowcharts (fuel injection amount calculation routine, learning subroutine and lattice axis switching routine) shown in FIGS.
Control the fuel injection amount.

The basic fuel injection amount calculation means, learning correction coefficient retrieval means, feedback correction coefficient setting means, fuel injection amount calculation means, steady state detection means, learning correction coefficient correction means, learning progress determination means, learning area switching The function as means is achieved by the program. Next, the operation will be described with reference to the flowcharts of FIGS.

In the fuel injection amount calculation routine of FIG.
In step 1 (S1 in the figure), the basic fuel injection amount T _P (= K · Q /) is calculated from the intake air flow rate Q obtained from the signal from the air flow meter 6 and the engine speed N obtained from the signal from the crank angle sensor 17. N) is calculated. This portion corresponds to the basic fuel injection amount calculation means. Step two
Then, various correction coefficients COEF are set as necessary.

In step 3, the corresponding learning correction coefficient Kl is retrieved from the engine speed N representing the engine operating state and the basic fuel injection amount (load) T _P. This part corresponds to the learning correction coefficient search means. Here, the learning correction coefficient Kl is RA with the engine speed N as the horizontal axis and the basic fuel injection amount T _P as the vertical axis.
As will be described later, the map of M is divided into relatively large regions in the initial stage where learning has not progressed, and the progress of learning is determined for each region to determine that learning has progressed. On the other hand, the area is divided into a plurality of small areas, and the learning correction coefficient Kl is stored for each of the divided areas. When the learning is not started, the learning correction coefficient Kl is set to the initial value 1.

In step 4, the voltage correction component T _S is set based on the voltage value of the battery 20. In step 5, it is determined whether or not the λ control condition is satisfied. Here, when the condition is not the λ control condition, for example, in the high rotation, high load region or the like, the feedback correction coefficient α is clamped to the previous value (or the reference value 1), and the process proceeds from step 5 to step 10 described later.

In the case of the λ control condition, step 6
At ~ 8, the output voltage V _O2 of the O ₂ sensor 16 is compared with the slice level voltage V _ref corresponding to the theoretical air-fuel ratio to determine the rich / lean of the air-fuel ratio, and the feedback correction coefficient α is set by integral control or proportional integral control. To do. This portion corresponds to the feedback correction coefficient setting means. Specifically, in the case of integral control, when it is determined by comparison in step 6 that air-fuel ratio = rich (V _O2 > V _ref ), the feedback correction coefficient α is integrated with the previous value by a predetermined integral (I) in step 7.
When the air-fuel ratio is lean (V ₀₂ <V _ref ), the feedback correction coefficient α is determined in step 8.
Is increased by a predetermined integral (I) from the previous value. In the case of proportional-plus-integral control, in addition to this, when the rich / lean inversion is performed, a predetermined proportional amount (P) larger than the integral (I) amount is increased / decreased.

In the next step 9, the learning subroutine of FIG. 5 is executed. This will be described later. Then, in step 10, the fuel injection amount T _i is calculated according to the following equation. This portion corresponds to the fuel injection amount calculation means. T _i = T _P · COEF · Kl · α + T _s However, as Kl, the one retrieved in step 3 or the one modified by the learning subroutine of FIG. 5 is used.

When the fuel injection amount T _i is calculated, the calculated T _i
A drive pulse signal having a pulse width of is output at a predetermined timing in synchronism with engine rotation, is given to the fuel injection valve 11 via the current waveform control circuit 41, and fuel injection is performed.
Next, the learning subroutine of FIG. 5 will be described. In step 11, it is determined whether the engine speed N indicating the engine operating state and the basic fuel injection amount T _P are in the same region as the previous time. If it is in the same region as the previous time, it is determined in step 12 whether or not the flag F is set. If it is not set, the output of the O ₂ sensor 16 is reversed in step 13, that is, the feedback correction coefficient α is increased or decreased. It is determined whether or not has been inverted, and this flow is repeated to repeat step 14
The count value indicating the number of inversions is incremented by 1, and when C = 2, the process proceeds from step 15 to step 16 and the flag F
Set. This flag F is used for the O ₂ sensor 16 in the same area.
When the output of is inverted twice, it is considered to have become a steady state and is set. After the flag F is set, if it is determined in step 11 that the region is the same as the previous region, the process proceeds to step 17 through step 12. The steps 11 to 16 correspond to the steady state detecting means, the engine operating state is in one of the divided regions, and the increasing / decreasing direction of the feedback correction coefficient α is reversed a predetermined number of times (twice) or more. Is detected as a steady state.

In the steady state, the output of the O ₂ sensor 16 is inverted in step 17, that is, the feedback correction coefficient α
It is determined whether or not the increasing / decreasing direction of is reversed, and when it is reversed by repeating this flow, it is the first time since the steady state is reversed in step 18, and thus it is judged whether or not it is the third reversal in the same region. In the case of the first time, in step 19, the deviation Δα (= α−α ₁ ) from the current reference value α ₁ of the feedback correction coefficient α is temporarily stored as Δα ₁ . After that, when the fourth inversion is detected, the process proceeds to steps 20 to 25, and learning is performed based on the data from the third inversion to the fourth inversion (see FIG. 6). Even when the fifth or more inversion is detected, the process similarly proceeds to steps 20 to 25, and learning is performed based on the data from the previous inversion to the current inversion.

At the time of the fourth or more inversion, in step 20, the deviation Δα from the current reference value α ₁ of the feedback correction coefficient α
(= Α−α ₁ ) is temporarily stored as Δα ₂ . Δα ₁ and Δα ₂ stored at this time are the upper and lower peak values of Δα from the previous (for example, the third) inversion to the current (for example, the fourth) inversion as shown in FIG. Based on these upper and lower peak values Δα ₁ and Δα ₂ , the average value Δ of the deviation Δα
Since α _M can be calculated, in step 21, the average value Δα _M of the deviation Δα is calculated based on the following equation.

Δα _M = (Δα ₁ + Δα ₂ ) / 2 Next, at step 22, the learning correction coefficient Kl stored corresponding to the current area is searched. However, step 3 is actually
You can use the one searched in. Next, in step 23, a new learning is performed by adding the average value Δα _M of the deviation Δα (= α−α ₁ ) of the feedback correction coefficient α from the reference value α ₁ to the current learning correction coefficient K1 according to the following equation by a predetermined ratio. The correction coefficient Kl (new) is calculated, and the learning correction coefficient data in the same area is corrected and rewritten.

[0037] _{Kl (new) ← Kl + Δα} M / M; (M is a constant, M> 1) After this, substitutes the value of [Delta] [alpha] ₂ for the next calculation in step 24 to [Delta] [alpha] _1. Next, at step 25, the value of the learning update counter RC for judging the learning progress of the area is incremented and stored in the backup RAM. If it is determined in step 11 that the engine operating state is not in the same region as the last time, the count value C is cleared and the flag F is reset in step 26.

Here, steps 17 to 24 correspond to learning correction coefficient correction means. Next, the lattice axis switching routine of FIG. 7 will be described. In step 31, the number of corrections RC of the learning correction coefficient stored in step 25 of the learning subroutine is compared with a predetermined value RCO, and when it is less than the predetermined value RCO, it is determined that the learning of the area is not currently performed. The size of the area is maintained, but if it is equal to or larger than the RCO, it is determined that the learning of the area is advanced, and the process proceeds to step 32.

In step 32, the area is subdivided into a plurality of small areas by the new lattice axis. For example, in the initial stage, as shown in FIG. 8, the operating state in which the λ control of the engine is performed is roughly divided into nine regions, and the progress of learning is determined for each region, and the region of high progress is As shown in FIG. 9, it is subdivided into a plurality of small regions by the new lattice axis (illustrated regions A → a _{1 to} a ₄ ).

In this way, since learning does not proceed in all areas at the beginning of learning, areas that are largely divided are learned on average. That is, since the area learned by one learning is large, the progress of learning can be uniformly promoted over the entire area. When the learning is advanced in this way, it is divided into an area where the learning progresses slowly and an area where the learning progresses fast, and in the area where it is determined that the learning has progressed sufficiently, average learning over the entire area is sufficiently performed. Therefore, this time, by subdividing the region as described above to eliminate the variation of each part in the region, and performing the learning in a finely divided manner for each subdivided region, learning that accurately matches the operating state can be performed. The learning control accuracy of the air-fuel ratio can be increased as much as possible.

Further, only the region where the learning has progressed is subdivided, and in the region where the learning has not progressed, the learning is advanced in that region until the average learning of the entire region is sufficiently performed. Areas where learning is delayed are not left behind.

[0042]

As described above, according to the present invention, in the initial stage when learning is not progressing, the area for correcting and storing the learning correction amount is enlarged to uniformly learn all areas, and the learning is advanced. Since the region is subdivided sequentially from the determined region and learning is performed for each small region,
It is possible to improve the air-fuel ratio control accuracy as much as possible by accelerating the learning progress evenly over the entire region and then performing detailed air-fuel ratio learning that corresponds well to each operating state.

[Brief description of drawings]

FIG. 1 is a block diagram showing the configuration of the present invention.

FIG. 2 is a block diagram showing an embodiment of the present invention.

FIG. 3 is a block circuit diagram of a control unit in FIG.

FIG. 4 is a flowchart showing a fuel injection amount calculation routine of the above embodiment.

FIG. 5 is a flowchart showing a learning subroutine.

FIG. 6 is a control characteristic diagram of the same.

FIG. 7 is a flowchart showing a learning area switching routine.

FIG. 8 is a learning area division diagram in the same initial state.

FIG. 9 is a learning region classification diagram when learning similarly progresses.

FIG. 10 is a graph showing the relationship between the elapsed time and the number of times of learning depending on the size of the area.

FIG. 11 is a graph showing the amount of deviation of the air-fuel ratio between the same regions depending on the size of the regions.

[Explanation of symbols]

1 Engine 6 Air flow meter 11 Fuel injection valve 16 O ₂ sensor 17 Crank angle sensor 30 Control unit

Claims (1)

[Scope of utility model registration request] 1. A first detecting means for detecting an engine intake air flow rate, a second detecting means for detecting an engine speed, and an engine exhaust gas component, thereby detecting an air-fuel ratio of an engine intake air-fuel mixture. The basic fuel injection amount is determined based on the engine operating state detection means including at least a third detection means, the engine intake air flow rate output by the first detection means, and the engine speed output by the second detection means. A basic fuel injection amount calculation means for calculating, a lattice axis that divides the engine operating state into a plurality of regions by the parameters, and a learning correction coefficient for correcting the basic fuel injection amount for each region surrounded by these lattice axes. And a rewritable storage means for storing, and a learning correction coefficient retrieval means for retrieving the learning correction coefficient in the corresponding area from the storage means based on the actual engine operating state, and the third detection means. The feedback correction coefficient setting is performed by increasing or decreasing a predetermined amount of a feedback correction coefficient for correcting the basic fuel injection amount so as to bring the actual air-fuel ratio closer to the target air-fuel ratio by comparing the air-fuel ratio with the target air-fuel ratio. Means, a basic fuel injection amount calculated by the basic fuel injection amount calculation means, a learning correction coefficient searched by the learning correction coefficient search means, and a feedback correction coefficient set by the feedback correction coefficient setting means. A fuel injection amount calculation means for calculating the fuel injection amount, a fuel injection means for injecting fuel on and off to the engine in response to a drive pulse signal corresponding to the fuel injection amount calculated by the fuel injection amount calculation means, and an actual engine operating state. Steady-state detection means for detecting that the engine is in a steady state, and for each region corresponding to when the engine operating state is in a steady state, A learning correction coefficient correction means for learning the deviation from the reference value of the feedback correction coefficient and correcting and rewriting the learning correction coefficient corresponding to the region of the engine operating state in the direction of decreasing the deviation; For the learning progress determination unit that determines each region divided by the lattice axis, and for the region that the learning progress determination unit determines that learning has progressed, the region is divided into a plurality of small regions by a new lattice axis. A learning control device for an air-fuel ratio of an internal combustion engine, comprising: learning region switching means for subdividing into regions and correcting and rewriting the learning correction factor by the learning correction factor correction device for each of the subdivided regions.