KR20020040334A - Method for re-learning clip-values learned in vehicle - Google Patents

Abstract

PURPOSE: A method for the re-learning of a learned clip value of a vehicle is provided to make normal control possible by correcting an error over a limit value and re-learning a predetermined clip value. CONSTITUTION: A method for the re-learning of a learned clip value of a vehicle comprises the steps of reading a learning value of an object to study of a vehicle(a1), progressing learning by deciding the satisfaction of a feedback condition with a read-out learning value(2a,3a), deciding if the learned value approaches a critical value of a specific clip(4a), and setting up the learning value approaching the critical value of a clip value as a learning value(7a).

Description

Method for re-learning clip-values learned in vehicle}

The present invention relates to a method of learning a vehicle, and more particularly, to a method for relearning a learned clip of a vehicle that is adapted to cope with various aids of a vehicle by relearning a learned object.

Currently, the closed-loop control method is adopted as a control method that plays an important role in the ECU of an engine mounted on the vehicle, and representative examples thereof include fuel amount control and air flow control. .

When the engine is started to drive the vehicle, the engine is first driven by an open-loop control method based on data stored in the engine control device, and then the control method is changed by the closed loop control. If the conditions are met, the control scheme is converted to the closed loop scheme. At this time, the conditions to be satisfied include the cooling water temperature, the signal of the oxygen sensor.

The closed loop method is basically to feed back the result of the input to find the optimum condition of the vehicle and maintain the value. At this time, the value corresponding to the optimal condition is called a learning value.

This learning value is an error compensation for change and is managed under a boundary value which is a predetermined value.

When the feedback control is performed based on the learning value, for example, the feedback result of the input of these components causing various errors such as the injector, the engine unit, the oxygen sensor, and the like is close to the above-described boundary value, which is a clip. It is called.

As described above, in the closed loop control method, learning is performed to find a learning value corresponding to an optimal condition according to the feedback of fuel or air amount, and when the learned value approaches a boundary value, that is, a clip state is reached, feedback control is performed. No further progress is made and progress is performed with an open loop.

In the open loop operation, since the learned value is used, the driving can be performed in an optimal state. However, since the vehicle state in the open loop is driven as determined, it may cause an abnormal state and various reliefs may occur. It is necessary to return to closed loop control, that is, feedback control.

However, in the current vehicle, for example, the learning value to which the vehicle variation is applied is reset to zero only in the case of a battery reset of the vehicle, so that the learning proceeds. As mentioned above, the above-mentioned problems remain.

The present invention has been made in view of the above circumstances, and, for example, a problem of failing to eliminate the occurrence of anomalous occurrences of various vehicles due to the operation of the closed loop learning in the battery reset and the open loop once the closed loop learning has been performed It is therefore to provide a method for relearning learned clip values of a vehicle.

1 is a flow chart for implementing a learned clip tooth re-learning method of a vehicle according to the present invention.

In order to solve the above problems, the present invention provides a re-learning method of the learned clip value of the vehicle, the method comprising the steps of: (a) reading the learning value of the learning target of the vehicle; (b) proceeding with learning by determining whether the read learning value satisfies a feedback condition; (c) determining whether the learned result has reached a threshold of a predetermined clip value; And (d) setting the learning value that has reached the threshold of the clip value as a new learning value and returning to (a).

According to the present invention, the fuel amount learning value and the air amount learning value already learned, if the fuel amount feedback condition and the air amount feedback condition do not correspond, the routine will be terminated. If each of the feedback conditions is true, re-learning is in progress, and accordingly, new learning values adapted to various aids are obtained.

According to the present invention, an error exceeding a predetermined threshold value among the fuel and air amount feedback can be corrected, and the engine state can be operated under normal control by relearning the predetermined clip value. Therefore, it is possible to prevent the rotation speed relief phenomenon that may occur during driving and idle driving.

Hereinafter, the learned clip tooth re-learning method of a vehicle according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 shows an exemplary flowchart for realizing a learned clip tooth relearning method of a vehicle according to the present invention.

For example, the fuel quantity learning and the airflow learning selected as the learning control object in the closed loop control of the vehicle, the fuel quantity learning is performed in all areas of driving and idle state, and the airflow learning is performed only in the idle region. It is common to be. When the vehicle is started, the vehicle is driven in the open loop mode. In this case, after reading each basic learning value, if it is determined that the learning condition is met, the fuel quantity learning and the air quantity learning are performed.

In FIG. 1, steps 1a and 1b show the steps of reading the basic fuel amount learning value and the basic air amount learning value, respectively. The process then goes to steps 2a and 2b. In steps 2a and 2b, it is determined whether the fuel amount feedback condition is satisfied and whether the air amount feedback condition is satisfied. If the result is determined to be NO in this determination step, the loop ends. If the result in this determination step is YES, i.e., it is determined that each feedback progress is necessary, the process proceeds to the next step.

The process proceeds to the next step, steps 3a and 3b, respectively, where the learning for the required fuel amount learning and the learning for the air amount learning are performed.

The learned result derives each learning value, and it is determined whether the derived learning value reaches 0.95 or 95% of the upper / lower limit clip value. Thus, the learning control object is determined by the threshold value of the clip value for each. If the result of the determination is NO, the process proceeds to steps 1a and 1b, respectively. If the determination result is yes, the process has reached the learning value, and then proceeds to the next steps 5a and 5b.

In steps 5a and 5b, the process reads each learning value obtained in the previous step, and in step 6a and 6b, the learning values are reset to learning values C and D to which these values and the values of steps 1a and 1b are added. Subsequently, the fuel quantity learning value and the air quantity learning value in steps 7a and 7b are converted into the learning value read in the reset state (ie, 1.0) into the learning value of the basic fuel amount and the air amount to use it. Note that the feedback is fed back to steps 1a and 1b in steps 7a and 7b.

By the feedbacked control, the processing proceeds again to the above-described steps. Therefore, for the fuel amount learning value and the air amount learning value that have already been learned, if the fuel amount feedback condition and the air amount feedback condition do not correspond, the routine is terminated, or even in the learned state, the respective feedback due to the occurrence of various reliefs and the like. If the condition is met, re-learning is in progress, and accordingly, a new learning value adapted to various aids is obtained.

As described above, according to the present invention, an error exceeding a predetermined threshold value among fuel and air amount feedbacks can be corrected, and the engine state can be operated under normal control by relearning the predetermined clip value.

Therefore, it is possible to prevent the rotation speed relief phenomenon that may occur during driving and idle driving.

Claims (3)

In the re-learning method of the learned clip value of the vehicle, (a) reading a learning value of a learning object of the vehicle; (b) proceeding with learning by determining whether the read learning value satisfies a feedback condition; (c) determining whether the learned result has reached a threshold of a predetermined clip value; And (d) setting the learning value that has reached the threshold value of the clip value as a new learning value and returning to (a). The method of claim 1, wherein the learning object is a fuel amount and an air amount. 2. The method of claim 1 wherein the threshold is 95% of the clip value.