JPH0228700B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION <Field of Industrial Application> The present invention relates to a device for self-diagnosing abnormalities in an air-fuel ratio control device with a learning function applied to an electronically controlled fuel injection type internal combustion engine.

<Conventional technology> In an electronically controlled fuel injection internal combustion engine, the injection amount
Ti is determined by the following formula.

Ti=Tp×COEF×α+Ts Here, Tp is the basic injection amount Tp=K×Q/N It is.

K is a constant, Q is the intake air flow rate, and N is the engine speed. COEF is various correction coefficients. α is an air-fuel ratio feedback correction coefficient for air-fuel ratio feedback control (λ control) to be described later. Ts is a voltage correction amount, which is used to correct changes in the injection amount of the electromagnetic fuel injector due to changes in battery voltage.

Regarding λ control, an O ₂ sensor is installed in the exhaust system to detect the actual air-fuel ratio, and the slice level determines whether the air-fuel ratio is richer or leaner than the stoichiometric air-fuel ratio, and fuel is injected to achieve the stoichiometric air-fuel ratio. For this purpose, the air-fuel ratio feedback correction coefficient α is determined, and by varying this α, the stoichiometric air-fuel ratio is maintained.

Here, the value of the air-fuel ratio feedback correction coefficient α is changed by integral control to ensure stable control.

In other words, by comparing the O ₂ sensor output and the slice level, if the air-fuel ratio is higher or lower than the slice level, the air-fuel ratio will not be suddenly richer or leaner, and if the air-fuel ratio is richer (leaner), The air-fuel ratio is controlled to be leaner (richer) by gradually increasing the integral.

However, in the region where λ control is not performed, α=
1 and set various correction coefficients COEF to obtain the desired air-fuel ratio.

By the way, if the base air-fuel ratio when α = 1 in the λ control region could be set to the stoichiometric air-fuel ratio (λ = 1), feedback control would not be necessary. The base air-fuel ratio may vary from λ = 1 due to factors such as variations in the valve, pressure regulator, control unit) and changes over time, non-linearity of the pulse width-flow rate characteristic of the fuel injector, and changes in operating conditions and environment. Feedback control is used to prevent this from occurring.

However, if the base air-fuel ratio deviates from λ=1, it takes time to set the step in the base air-fuel ratio to λ=1 by feedback control when the operating range changes significantly. For this purpose, the proportional and integral constant (P/I) is increased, causing overshoot and undershoot.
Controllability deteriorates. In other words, the base air-fuel ratio is λ=
If it deviates from 1, the air-fuel ratio will be controlled within a range that deviates considerably from the stoichiometric air-fuel ratio.

As a result, the operation is performed at a location where the conversion efficiency of the three-way medium is poor, resulting in increased costs due to an increase in the amount of precious metal in the catalyst, and problems such as the need to replace the catalyst due to deterioration in conversion efficiency due to deterioration of the catalyst. It was hot.

Therefore, by setting the base air-fuel ratio to λ = 1 through learning, the deviation from λ = 1 caused by the step in the base air-fuel ratio during transient times can be eliminated, and the P/I
A learning control device for the base air-fuel ratio has been devised, which aims to improve controllability by making it possible to reduce the amount of air-fuel ratio, thereby reducing the cost of the catalyst.

In other words, a map of learning correction coefficient α ₀ corresponding to engine operating conditions such as engine speed and load is provided in RAM, and when calculating the injection amount Ti, the basic injection amount Tp is corrected by α ₀ as shown in the following formula. do.

Ti=Tp×COEF×α×α ₀ +Ts Then, the learning of α ₀ proceeds as follows.

(i) Detect the engine operating conditions and the control center value αc of α in a steady state.

(ii) Search for α ₀ that has been learned up to now corresponding to the engine operating conditions.

(iii) Find the value of α ₀ +Δα/M from αc and α ₀ and update the memory with the result (learning value) as new α ₀ .

Note that Δα indicates the amount of deviation from the reference value α ₁ , and Δα
=αc− _α1 , and the reference value _α1 is generally 1.0.
Further, M is a constant.

By the way, in this type of air-fuel ratio control device,
Some devices are equipped with a so-called self-diagnosis device that detects when an abnormality occurs.

As a conventional self-diagnosis device for an air-fuel ratio control device, for example, as shown in FIG. input to the self-diagnosis circuit 33 composed of a microcomputer,
The solenoid 31 and power transistor 3 measure the number of ON/OFF inversions of the input signal per unit time.
2, or as shown in FIG. 6, the output voltage from a hot wire flow meter 41 that outputs a voltage proportional to the intake air flow rate is transmitted to an amplifier 42 and an A/D converter 43. There is a system that detects that the hot wire flowmeter 41 is abnormal when a voltage lower than the voltage corresponding to the minimum intake air flow rate when the engine is rotating is detected.

As described above, conventional self-diagnosis devices determine whether an actuator or sensor is abnormal based on the characteristics of the actuator itself (output voltage, etc.) and the characteristics of other parts related thereto. Therefore, even if it is possible to determine a definitive failure, it is often not possible to determine changes in characteristics due to deterioration of durability, and there is a problem in that changes over time that may cause problems in engine characteristics cannot be detected.

<Problems to be Solved by the Invention> The present invention has been made in view of the above conventional problems, and is an air-fuel ratio control device equipped with a learning function for an electronically controlled fuel injection internal combustion engine. It is an object of the present invention to provide a self-diagnosis device that solves the above-mentioned problems by making an abnormality determination including changes over time in a control system.

<Means for Solving the Problem> Therefore, the first invention provides basic injection amount calculation means for calculating the basic injection amount from the intake air flow rate and engine speed, and an exhaust system as shown in FIG. established in
an air-fuel ratio feedback correction coefficient means that compares the actual air-fuel ratio detected based on the signal from the _O2 sensor with the stoichiometric air-fuel ratio and sets an air-fuel ratio feedback correction coefficient through integral control; A learning correction coefficient search means for searching the learning correction coefficient stored in the map of the RAM, and setting a new learning correction coefficient from the air-fuel ratio feedback correction coefficient and the learning correction coefficient, and using the learning correction coefficient.
learning correction coefficient updating means for updating data of the same engine operating condition in the RAM; injection quantity calculation means for calculating the injection quantity by multiplying the basic injection quantity by the air-fuel ratio feedback correction coefficient and the learning correction coefficient; drive pulse signal output means for outputting a drive pulse signal corresponding to the calculated injection amount to the fuel injection valve; a learning state determining means for determining a direction of deviation, and the determining means determines that a predetermined percentage or more of data of a plurality of learning correction coefficients deviate from a reference value by a predetermined value or more in the same deviation direction; In this case, the intake air flow rate detection means or a means for warning that the control system is abnormal is provided.

Further, a second invention is a learning method in which, in the same configuration as the first invention, the learning state determining means determines the value of the learning correction coefficient in a plurality of operating regions having the same fuel injection amount and the deviation direction from the reference value. a state determining means; and when the determining means determines that a predetermined percentage or more of the data of the plurality of learning correction coefficients is a value that deviates from the reference value by a predetermined value or more in the same deviation direction, the fuel injection amount is determined. The system is configured to include a means for warning that there is an abnormality in the detection or control system.

<Operation> As a result, in the first invention, an abnormality can be identified in the detection or control system of the intake air flow rate and an alarm can be issued, and in the second invention, the detection or control system of the fuel injection amount It is possible to identify the abnormality and issue an alarm.

<Example> Examples will be described below.

Figure 2 shows the hardware configuration.

1 is CPU, 2 is P-ROM, 3 is for learning control
CMOS-RAM, 4 is an address decoder.
Note that a backup power supply circuit is used for the RAM 3 to retain the memory contents even after the key switch is turned off.

Analog signals to the CPU 1 for controlling the fuel injection amount include an intake air flow rate signal from the hot wire air flow meter 5, a throttle opening signal from the throttle sensor 6, a water temperature signal from the water temperature sensor 7, and an O ₂ sensor. There are an exhaust oxygen concentration signal from 8, a battery voltage from a battery 9, etc., and these are inputted via an analog input interface 10 and an A/D converter 11.
12 is an A/D conversion timing controller.

Digital input signals include ON/OFF signals from an idle switch 13, a start switch 14, and a neutral switch 15, and these are inputted via a digital input interface 16.

In addition, for example, from the crank angle sensor 17
A reference signal every 180 degrees and a position signal every 1 degree are inputted via a one-shot multi-circuit 18. In addition, the vehicle speed sensor 19
The vehicle speed signal is inputted via the waveform shaping circuit 20.

A drive pulse signal from the CPU 1 to the fuel injection valve 22 is sent to the fuel injection valve 22 via a current waveform control circuit 21.

Here, the CPU 1 performs input/output operations, arithmetic processing, etc. according to a program (stored in the ROM 2) based on the flowchart shown in FIG. 3, and controls the fuel injection amount.

Further, an alarm device 23 such as a lamp or a buzzer is provided and is activated by the output from the CPU 1.

In this case, the CPU 1 diagnoses an abnormality in the control device according to a program based on the flowchart (self-diagnosis routine) shown in FIG. 4, and outputs an activation signal to the alarm 23 when an abnormality occurs.

Next, the fuel injection amount calculation routine and the learning control routine will be explained according to the flowchart of FIG.

SI calculates the basic injection amount Tp (=K×Q/N) from the intake air flow rate Q obtained from the signal from the air flow meter 5 and the engine rotation N obtained from the signal from the crank angle sensor 17. .

Set various correction coefficients COEF in S2.

In S3, the output voltage of the O ₂ sensor 8 is compared with the slice level voltage, and an air-fuel ratio feedback correction coefficient α is set by integral control. However, in a region where λ control is not performed, α is clamped to 1.
In addition, the data α ₀ already learned from the learning MAP on RAM 3 is used as the operating state (N, Tp) at that time.
Refer to corresponding.

In S4, a voltage correction amount Ts is set based on the battery voltage from the battery 9.

In S5, as a parameter indicating the engine operating state, for example, the operating region is divided into a plurality of areas based on the engine speed N and the basic injection amount (load) Tp,
The current ( _N ,
Tp) is located, and data indicating the area is set at a predetermined location A in the RAM 3.

In S6, the current (N,
The data in the area where Tp) exists is also stored in RAM3.
Last searched, (N,
Tp) is compared with the data of the area where it exists to determine whether they are the same. If the answer is YES, that is, if it is determined that the operating conditions are substantially the same, the process advances to S7.

In S7, the output voltage of O ₂ sensor 8 is determined by S6.
After YES, it is determined whether or not it has been reversed n rotations, and if YES, the process advances to S8.

That is, S6 and S7 are provided to determine whether the operating state is a steady state.
If the determination is YES, it is determined that the state is in a steady state. Such a steady state determination method can be performed easily and with high accuracy, but there are other methods, such as determining whether a predetermined time has elapsed with the vehicle speed constant, the gear position non-neutral, and the throttle opening constant. may be adopted. And S6 or
If any of the determinations in S7 is NO, it is determined that the state is unsteady, and in this case, the process proceeds to S11 without performing the learning in S8 to S10, which will be described later.

In S8, the control center value αc of the air-fuel ratio feedback correction coefficient α in the steady operating state is calculated.
This is, for example, the air-fuel ratio feedback correction coefficient α
It is also possible to find the average value from the time when the value of increases or decreases until the time of reversal, or to find the average value of only the value of the air-fuel ratio feedback correction coefficient α at the time of reversal.In this way, the steady state It can be determined more accurately from the control value αc in .

In S9, from engine speed N and basic injection amount Tp
The learning correction coefficient α ₀ corresponding to (N, Tp) stored in the area of the RAM 3 where (N, Tp) exists is searched. Note that α ₀ stored in the map
The values of are all α ₀ at the time when learning has not started
= 1.

In S10, the learning correction coefficient α ₀ found in S9
and the control center value αc calculated in S8 according to the following equation, and use the calculated value to update the value in the corresponding area of the new learning correction coefficient α ₀ map.

α ₀ ←α ₀ +Δα/M Note that Δα represents the amount of deviation between αc and the reference value, Δα=αc−α ₁ , and the reference value α ₁ is generally 1.0. Also M
is a constant.

The value of M, which determines the rate at which the learning deviation amount Δα of the learning correction coefficient α ₀ is added, may be constant, but if it is set to a value proportional to the engine speed, the integral of α will decrease as the injection cycle increases. Because it is possible to
More advanced injection amount control is possible.

In S11, the data of the previous area (N, Tp) set at address LA of RAM 3 is updated by transferring the data of the current area (N, Tp) set at address A. .

In S12, the injection amount Ti is calculated using the following equation.

Ti=Tp×COEF×α×α ₀ +Ts Here, in the case of a steady state, the learning correction coefficient α ₀ that is updated in S10 is used, and in the case of a transient state, the one that is updated in S10 is used. is used.

The injection amount Ti is calculated above, and this injection amount is calculated in S13.
A drive pulse signal corresponding to Ti is applied to the fuel injection valve 22 at a predetermined timing via the current waveform shaping circuit 21.

On the other hand, in the region where λ control is not performed, the air-fuel ratio feedback correction coefficient α is clamped to 1 as described above, and steps S5 to S11 are omitted.

Therefore, the injection amount is given by the following equation.

Ti=Tp×COEF×α ₀ +Ts However, Tp=K×Q/N In this way, in the feedback control region where λ control is performed, learning is performed to reduce the deviation amount between the control center value of the feedback correction coefficient and the reference value. As a result, overshoot and undershoot of the air-fuel ratio feedback correction coefficient α during transient operation can be suppressed, and the settling to λ=1 is accelerated, thereby improving controllability.

Next, a self-diagnosis routine of the air-fuel ratio control device equipped with such a learning function will be explained according to the flowchart shown in FIG. The hardware configuration is almost the same as that shown in Figure 2.
Since the only difference is the microcomputer program and the structure of the alarm, the same reference numerals as in FIG. 2 will be used for explanation.

In S31, the learning correction coefficient α ₀ in RAM map 3
In the area (N, Tp) where the data of is stored is divided by a large number of equal-Q lines with equal intake air flow rate Q, the parameter signal n of the equal-Q line is set to n corresponding to the minimum intake air flow rate. =0.

In S32, the map is searched for a plurality of α ₀ data on the iso-Q line of parameter n.

In S33, it is determined whether or not a predetermined percentage or more of these data deviates in either the positive or negative direction by a predetermined value or more.

Immediately after starting this routine, the determination is made from the data of the equal Q line of n=0 set in S31.

If the determination in S33 is YES, proceed to S34,
It is determined in S33 whether the data on all iso-Q lines have been determined, and the process proceeds to S35.

In S35, the value of n is counted by +1, and the process returns to S32.

Then, in S32, the same determination as described above is made regarding the data on the iso-Q line set in S31.

In this way, if the determination of S33 is YES for all the data on the iso-Q line, the determination of S34 is
If the answer is YES, the process advances to S36, where it is determined that the air flow meter 5 is abnormal, and this determination signal is output to the alarm 23. As a result, the alarm 23 is activated to warn of an abnormality in the air flow meter 5, and the process then proceeds to S37.

Also, the data on at least one iso-Q line
If the determination in S33 is NO, it is determined that the air flow meter 5 is normal and the process proceeds to S37.

In S37, the area (N, Tp) where the data of the learning correction coefficient α ₀ is stored is divided by a large number of iso-Tp lines with the same basic injection amount Tp.
Set the parameter m of the Tp line to m corresponding to the minimum value Tp
=0.

In S38, the map is searched for a plurality of pieces of α ₀ data on the iso-Q line of the parameter m.

In S39, it is determined whether a predetermined percentage or more of these data deviates by a predetermined value or more in one direction, either positive or negative. Initially, the determination is made from the data of the iso-Tp line with m=0 set in S37.

If the judgment in S39 is YES, proceed to S40, and judge whether or not the data on all iso-Tp lines have been judged in S39.If NO, proceed to S42, count the value of m by +1, and then proceed to S38. return.

In this way, when the determination in S39 for all the data on the iso-Tp line becomes YES, the process proceeds to S41, where it is determined that an abnormality such as clogging has occurred in the fuel injection valve 22, and this determination signal is sent to the alarm 22. Output to. As a result, the alarm 23 is activated and an abnormality of the fuel injection valve 22 is warned.

Further, if the determination in S39 based on the data on at least one iso-Tp line is NO, it is determined that there is no abnormality in the fuel injection valve 22, and this routine ends without activating the alarm 23.

Here, a case where a predetermined percentage or more of data among all the data on the iso-Tp line deviates in the same direction by a predetermined value or more means that the measured value of the intake air flow rate and the actual value or the fuel calculated by the microcomputer, respectively. Since there is a clear discrepancy between the injection amount and the actual fuel injection amount that exceeds the error range, this indicates an abnormality in the air flow meter 5 or fuel injection valve 22, including deterioration due to aging. is clear. Based on this point, the present embodiment can determine whether the air flow meter 5 or the fuel injection valve 22 is abnormal using the learning results.

<Effects of the Invention> As explained above, according to the present invention, in the air-fuel ratio control device, the control device is controlled based on the learning result of the learning performed to reduce the deviation amount of the air-fuel ratio feedback correction coefficient from the reference value. Determine abnormality,
In addition, since the system is configured to determine learning trends, abnormalities such as deterioration due to changes over time that adversely affect exhaust characteristics and engine performance can be diagnosed by pinpointing the occurrence location.

Note that although this embodiment has been shown to include both the first and second inventions, the embodiment of the first invention only detects the intake air flow rate or issues an alarm for abnormality determination in the control system, and the second invention does not. Of course, as an embodiment, only the detection of the fuel injection amount or the abnormality determination alarm of the control system may be performed.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing the configuration of the present invention, FIG. 2 is a hardware configuration diagram of an embodiment of the present invention including the first and second inventions, and FIG. 3 is a fuel block diagram of the same embodiment. FIG. 4 is a flowchart showing the injection amount calculation and learning control routine, and FIGS. 5 and 6 are flowcharts showing the self-diagnosis routine of the same embodiment.
The figures are schematic configuration diagrams showing different examples of conventional self-diagnosis devices. 1...CPU, 3...CMOS for learning control
RAM, 5... Air flow meter, 8... O ₂ sensor, 17... Crank angle sensor, 22... Fuel injection valve, 23... Alarm.

Claims (1)

[Scope of Claims] 1. Basic injection amount calculation means that calculates the basic injection amount from the intake air flow rate and engine speed, and the actual air-fuel ratio detected based on the signal from the O ₂ sensor installed in the exhaust system. an air-fuel ratio feedback correction coefficient setting means for setting an air-fuel ratio feedback correction coefficient by integral control by comparing the air-fuel ratio with the stoichiometric air-fuel ratio, and a learning correction coefficient for searching a learning correction coefficient stored in a map of RAM according to engine operating conditions. a coefficient search means; a learning correction coefficient updating means for setting a new learning correction coefficient from the air-fuel ratio feedback correction coefficient and the learning correction coefficient and updating data for the same engine operating condition in the RAM with the learning correction coefficient; injection amount calculation means for calculating the injection amount by multiplying the basic injection amount by an air-fuel ratio feedback correction coefficient and a learning correction coefficient;
drive pulse signal output means for outputting a drive pulse signal corresponding to the calculated injection amount to the fuel injection valve; learning state determining means for determining the direction of deviation of the learning correction coefficient; 1. A self-diagnosis device for an air-fuel ratio control device with a learning function in an electronically controlled fuel injection type internal combustion engine, characterized in that the device includes means for detecting the intake air flow rate or warning that the control system is abnormal when the intake air flow rate is abnormal. 2 Basic injection amount calculation means that calculates the basic injection amount from the intake air flow rate and engine speed, and the actual air-fuel ratio and stoichiometric air-fuel ratio detected based on the signal from the O ₂ sensor installed in the exhaust system. an air-fuel ratio feedback correction coefficient setting means for comparing and setting an air-fuel ratio feedback correction coefficient by integral control; a learning correction coefficient retrieval means for searching a learning correction coefficient stored in a map of RAM according to engine operating conditions; learning correction coefficient updating means for setting a new learning correction coefficient from the fuel ratio feedback correction coefficient and the learning correction coefficient and updating data for the same engine operating condition in the RAM with the learning correction coefficient; injection amount calculation means for calculating the injection amount by multiplying the feedback correction coefficient and the learning correction coefficient;
drive pulse signal output means for outputting a drive pulse signal corresponding to the calculated injection amount to the fuel injection valve; learning state determining means for determining the direction of deviation of the learning correction coefficient; 1. A self-diagnosis device for an air-fuel ratio control device with a learning function in an electronically controlled fuel injection type internal combustion engine, characterized in that the device includes means for detecting the fuel injection amount or warning that the control system is abnormal when the fuel injection amount is detected.