JPS6340933B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION Technical Field The present invention relates to a learning control device for various feedback controls performed during operation of an internal combustion engine.

<Background Art> As this type of learning control device, there is one used, for example, in air-fuel ratio feedback control of an electronically controlled fuel injection type internal combustion engine.

To explain this, in an electronically controlled fuel injection type internal combustion engine, the fuel injection amount Ti (valve opening pulse width for driving the fuel injection valve) is determined by the following equation.

Ti=Tp×COEF×α+Ts Here, Tp is the basic injection amount and is expressed as Tp=K×Q/N, where K is a constant, Q is the intake air flow rate, and N is the engine rotation speed. COEF is a correction coefficient determined from various operating conditions, and α is a feedback correction coefficient for air-fuel ratio feedback control (hereinafter referred to as λ control), which will be described later. Ts is a voltage correction amount, which is used to correct variations in battery voltage.

λ control installs an O ₂ sensor in the exhaust system to detect the actual air-fuel ratio, and uses the slice level to determine whether the air-fuel ratio is richer or leaner than the theoretical air-fuel ratio.
The fuel injection amount is controlled so that the air-fuel mixture supplied to the cylinder has the stoichiometric air-fuel ratio.For this purpose, the above-mentioned air-fuel ratio feedback correction coefficient α is determined and by varying this α. This is to ensure that the stoichiometric air-fuel ratio is achieved.

Here, the value of the air-fuel ratio feedback correction coefficient α is changed by proportional-integral control (PI control) to achieve stable control.

In other words, the output of the O ₂ sensor is compared with the slice level, and if the output of the O ₂ sensor is larger (smaller) than the slice level and the air-fuel ratio is richer (leaner), the air-fuel ratio is suddenly made leaner (richer). The air-fuel ratio is controlled to be gradually leaner (richer) by first lowering (raising) it by a proportional amount, then lowering (raising) it by an integral amount.

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

By the way, if the air-fuel ratio obtained when α = 1 in the λ control region, that is, the base air-fuel ratio, could be set to the stoichiometric air-fuel ratio (λ = 1), feedback control would be unnecessary. Due to factors such as variations in parts (for example, air flow meters, fuel injection valves, pressure regulators, control units), changes over time, non-linearity of the pulse width vs. flow rate characteristics of fuel injection valves, and changes in operating conditions and environment. Since the base air-fuel ratio deviates from λ=1, as described above, the value of α is changed by proportional-integral control to perform feedback control so that λ=1.

However, the deviation of the base air-fuel ratio from λ = 1 differs depending on the operating region. In other words, the value of α to obtain λ = 1 differs depending on the operating region, so if this difference is large, the operating region When the air-fuel ratio changes, it takes time to settle the air-fuel ratio to λ=1 through feedback control.

As a result, the three-way catalyst is operated at an air-fuel ratio with poor conversion efficiency, which increases costs due to an increase in the amount of precious metals in the catalyst, and further deteriorates the conversion efficiency due to deterioration of the catalyst, forcing the catalyst to be replaced. The problem arises that

Therefore, a learning correction coefficient α ₀ is introduced so that the air-fuel ratio when α = 1, that is, the base air-fuel ratio, becomes λ = 1, and this α ₀ is changed to λ = 1 when α = 1 in each operating state. Make it. As a result, we came up with a base air-fuel ratio learning control device that reduces the step in the base air-fuel ratio due to changes in operating conditions, shortens the period in which the air-fuel ratio deviates from λ = 1, and reduces the cost of the catalyst. It was done.

That is, as shown in Fig. 1, the horizontal axis represents the engine rotational speed N, and the vertical axis represents the engine load, the basic injection amount Tp.
, and a group of parallel lines dividing both axes into a predetermined number forms an operating area (hereinafter referred to as learning area) group, and the base air-fuel ratio in each learning area is λ = 1.
A map of learning correction coefficient α ₀ is provided such that
Specifically, this α ₀ map is provided on data storage means such as RAM of a microcomputer.

Then, with this learning correction coefficient α ₀ , the basic injection amount is
The injection amount Ti is determined by correcting Tp as shown in the following equation.

Ti=Tp×COEF×α×α ₀ +Ts Here, learning (updating) of the learning correction coefficient α ₀ proceeds in the following steps.

When N and Tp, which represent the engine operating state, remain within one learning area and the output of the oxygen sensor is reversed a predetermined number of times, it is determined that the engine and air-fuel ratio control are in a steady state, and the current Detect α.

α ₀ that has been learned and stored up to now in the learning area corresponding to the steady engine operating condition is searched.

Calculate the value of α ₀ +△α/M from this α and α ₀ , and use the result as a new α ₀ for α ₀ in the learning area.
Refresh your memory. Note that Δα indicates the amount of deviation from the reference value α ₁ , Δα=α−α ₁ , and the reference value α ₁ is generally 1.0. Furthermore, M is a constant for weighting updates.

However, N and Tp, which represent the engine operating state,
There is usually some variation in the value of N or
When the center value of the fluctuation of Tp is near the boundary of the learning area, the value of N or Tp may temporarily take a value outside the learning area due to this fluctuation.
Therefore, if we adopt the condition that the values of N and Tp continue to remain within one learning area as described in (as the standard for determining steady state), it is determined that the steady state is in the original state. It will be determined that what should be changed is not in a steady state, and an opportunity to update the learning correction coefficient will be lost. That is, when the operating region near the boundary of the learning area is in a steady state (although temporary fluctuations occur), no learning is performed, and the efficiency of learning is reduced.

In order to avoid this, it is possible to set the learning area so that the normal driving mode is located in the center of the learning area, but the above-mentioned disadvantage still occurs for different driving modes, so this is not a fundamental solution. No, no.

Further, such inconvenience occurs not only in feedback control in air-fuel ratio control, but also in general when the above-described learning control is performed in feedback control during internal combustion engine operation.

<Objective of the Invention> The present invention has been made with attention to such problems, and provides a learning control in which learning correction coefficients are reliably updated in all operating regions in learning control of an internal combustion engine as described above. The purpose is to provide a device.

<Summary of the Invention> To this end, the present invention, as shown in FIG. means for determining a value of a learning correction coefficient for correcting the value according to the progress of the control; and means for storing the value of the learning correction coefficient determined by the means in correspondence with a pre-divided driving region. A learning control device for an internal combustion engine, comprising: means for sampling a plurality of pieces of data representing an engine operating state; means for detecting a degree of dispersion of the plurality of pieces of data sampled by the means; means for updating the value of the learning correction coefficient stored in correspondence with the driving region in which the representative value of the plurality of data is included, if the degree of dispersion of the plurality of data is less than or equal to a predetermined value; The purpose of the present invention is to construct a learning control device that achieves the above objectives.

<Example> The present invention will be described below based on an example shown in FIG. In this case, the present invention is applied to the learning control in the air-fuel ratio feedback control of the electronically controlled fuel injection type internal combustion engine mentioned above.

That is, in the figure, 1 is CPU, 2 is P-
ROM, 3 is used as a learning correction coefficient storage means.
CMOS-RAM, 4 is an address decoder.
Note that a backup power supply circuit is used for the RAM 3 in order to retain the stored contents even after the key switch is turned off.

Analog input signals to the CPU 1 for fuel injection amount control include an intake air flow rate signal from the hot wire airflow 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. Exhaust oxygen concentration signal from 8,
There are battery voltages from battery 9, these are connected to analog input interface 10 and A/D
The signal is input via a 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.

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

Next, the operation of this device will be explained according to the flowchart shown in FIG.

In S1, various data such as intake air flow rate and crank angle are read. In other words, this process S1 corresponds to the engine operating state display data sampling means shown in FIG.

Next, in S2, the engine rotational speed N obtained from the intake air flow rate Q read in S1 and the signal from the crank angle sensor 17 also read in S1.
The basic injection amount Tp (=K×Q/N) is calculated from .

In S3, COEF is calculated based on the engine operating state read in S1.

In S4, the output from the O ₂ sensor 8 is compared with the slice level, and the air-fuel ratio feedback correction coefficient α is set by proportional-integral control. This process S4
corresponds to the feedback correction amount determining means in FIG.

In S5, a voltage correction amount Ts is set based on the battery voltage of the battery 9.

In S6, the absolute value of the difference between the engine rotation speed N and the engine rotation speed Nf read in the previous operation of this routine is compared with the set value ΔN. If the absolute value is less than or equal to ΔN, it is determined that the fluctuation in the engine rotational speed N is small, and the process proceeds to S7.

In S7, the basic injection amount Tp calculated in S2,
The absolute value of the difference from the basic injection amount Tpf calculated in the previous operation of this routine is compared with the set value ΔTp. If the absolute value is less than △Tp, it is determined that the engine load fluctuation is small, and the process proceeds to S8, where the value of the counter I indicating how many consecutive times the engine operating state remains in a predetermined small fluctuation range is calculated. Increase by 1.

On the other hand, if the conditions in the determinations in S6 and S7 are not satisfied, it is determined that the fluctuation in the engine operating state is large, and after clearing the value of the counter I to zero in S9, the process proceeds to S21.

In S10, it is determined whether the value of the counter I is 1 or not.
That is, it is determined whether or not the engine operating state has just entered a steady state. If I=1, the process proceeds to S11 and starts counting the number of times the output of the oxygen sensor 8 reverses, which has a meaning to be described later. On the other hand, if I is 2 or more, S11 is bypassed and the process directly proceeds to S12.

In S12, the value of the counter I is compared with a predetermined value Is, and if I is greater than or equal to Is, that is, if it remains within the predetermined fluctuation range from the previous operating state for Is or more times, the data is It is determined that the variation, that is, the degree of dispersion is small, and that the operating state has reached a steady state, and the process proceeds to S13, where the counting of the number of times the output of the O ₂ sensor 8 reverses, which was started in S11, is completed.
On the other hand, if I has not reached Is in S12, S
Proceed to 21. As is clear from the above, process S
6, S7, S8, S9 and S12 correspond to the data dispersion degree detection means shown in FIG.

In S14, the number of inversions of the output of the O ₂ sensor 8, which has been counted in S13, is compared with a predetermined value. Here, the output of the O ₂ sensor 8 does not cross the slice level and does not invert in an excessive state of control where the air-fuel ratio deviates from λ=1.
That is, if the output of the O ₂ sensor 8 is reversed a predetermined number of times in the comparison in S14, this indicates that the control is in a steady state, and in this case, the process advances to S15. On the other hand, if this condition is not satisfied, S1
After clearing the counter I to zero in step 6, the process advances to S21.

In S15, the average value of the feedback correction coefficient α while the operating state remains within a predetermined fluctuation range Is times is calculated. Then, in S17, the average value of the rotational speed N and the basic injection amount Tp within the same period,
Calculate.

In S18, the learning correction coefficient α ₀ calculated in S17 is retrieved from the map stored in the RAM 3, and in S19, a new learning correction coefficient α ₀ is calculated using the formula α ₀ ← α ₀ + (−α ₁ )/M. Determine.
Then, in S20, this α ₀ is stored in the area of the map corresponding to . Here, if the value of , is equal to the boundary value of the area of 2 or more, then
The value of α ₀ is stored in the two or more areas. That is, step S19 corresponds to the learning correction coefficient determining means in FIG. 2, and step S20 corresponds to the learning correction coefficient storage updating means in FIG.

According to this method of updating α ₀ , even if the value of , is near the boundary of the learning area, and α ₀ cannot be updated using conventional methods, it becomes possible to update α ₀ , and learning Efficiency will be improved.

In S21, a learning correction coefficient α ₀ is searched from the engine rotational speed N and basic injection amount Tp determined from the data read in S1, and using this α ₀ , S22
The fuel injection amount Ti is calculated using the formula: Ti=Tp×COEF×α×α ₀ +Ts. Then, a drive pulse signal corresponding to this Ti is given to the fuel injection valve 22 via the current waveform control circuit 21 at a predetermined timing.

It goes without saying that the degree of dispersion of the data representing the engine operating state may be detected by using the dispersion or standard deviation of the data, in addition to the method of this embodiment, if the microcomputer has sufficient storage capacity. . Furthermore, the representative value of the data for determining the storage area of the updated learning correction coefficient α ₀ is not limited to the average value, but a median value, mode value, etc. may be used.

Furthermore, the present invention is also applied to learning control in idle speed control, ignition timing control, injection timing control of diesel engines, etc., and produces similar effects.

<Effects of the Invention> As explained above, according to the present invention, a plurality of pieces of data representing engine operating conditions are sampled in time series, and when the degree of dispersion of the data is smaller than a predetermined value, the data is Since the stored learning correction coefficients are updated in accordance with the driving range that includes the representative value, the learning correction coefficients are reliably updated in all driving ranges, improving learning efficiency. It is something.

[Brief explanation of the drawing]

Fig. 1 is a diagram showing an example of the configuration of a learning area, Fig. 2 is a block diagram showing the configuration of the present invention, Fig. 3 is a hardware configuration diagram of an embodiment of the present invention, and Fig. 4 is the operation of the same. This is a flowchart showing the process. 1...CPU, 3...RAM, 5...Air flow meter, 6...Throttle sensor, 8... _O2 sensor, 1
7...Crank angle sensor.

Claims (1)

[Scope of Claims] 1. A means for determining a feedback correction amount for making a controlled variable follow a target value, and learning for correcting the feedback correction amount determined by the means in accordance with the progress of control. A learning control device for an internal combustion engine, comprising means for determining a value of a correction coefficient, and means for storing a value of a learning correction coefficient determined by the means in correspondence with a pre-divided operating region. means for sampling a plurality of pieces of data representing an operating state; means for detecting a degree of dispersion of said plurality of data sampled by said means; and a degree of dispersion of said plurality of data detected by said means is less than or equal to a predetermined value; In the case of , the learning control device for an internal combustion engine is characterized in that it is provided with means for updating the value of the learning correction coefficient stored in correspondence with the operating region in which the representative value of the plurality of data is included. . 2. The means for detecting the degree of dispersion of a plurality of pieces of sampled data is to detect the degree of dispersion as the number of consecutive times that sampled data is included within an interval of a predetermined width that includes the previously sampled data. A learning control device for an internal combustion engine according to claim 1.