KR20120133513A - Apparatus and method for correcting learn value of rold slop - Google Patents

Abstract

PURPOSE: A driving road gradient learning revision apparatus and method thereof are provided to improve the accuracy by respectively calculating and revising the gradient learning value of driving road. CONSTITUTION: A first gradient learning value generating part(10) generates a learning value of the first gradient by conducting the study of a driving road. A second gradient learning value generating part(30) generates a learning value of the second gradient by conducting a study of a driving road. A learning value revising condition judgment module determines whether a learning value revising condition of gradient is satisfied or not based on the gradient information. A calculation module calculates the difference between the first gradient learning value and the second gradient learning value. Gradient learning value revision part(50) revises error of the second gradient learning value based on the first gradient learning value and the second gradient learning value. [Reference numerals] (10) First inclination learning value generating unit; (30) Second inclination learning value generating unit; (50) Inclination learning value correcting unit; (AA) Vehicle speed; (BB) Gear number; (CC) Engine torque

Description

Apparatus and method for correcting vehicle road slope inclination learning {APPARATUS AND METHOD FOR CORRECTING LEARN VALUE OF ROLD SLOP}

The present invention relates to an apparatus and method for correcting and learning a driving road inclination of a vehicle, and more particularly, to an apparatus and a method for deriving an accurate slope learning value based on learning values of a driving road based on engine torque and acceleration information. will be.

The driving road inclination is predicted based on the engine torque received from the general automatic transmission, the target speed change stage is set according to the predicted driving road inclination, and the driving speed and the speed change are executed based on the set target speed change.

The inclination of the driving road is to learn the inclination of the driving road based on the calibration data reflecting the rolling resistance and the air resistance to the driving speed and the calibration data reflecting the inertia resistance according to the acceleration and deceleration of the vehicle speed.

That is, after classifying the vehicle speed into predetermined units and driving at constant speed, it calculates calibration data reflecting rolling resistance and air resistance for the traveling speed of each predetermined unit, and then runs with the same acceleration to inertial resistance according to acceleration and deceleration of the vehicle speed. Calculate the reflected calibration data.

That is, the inclination is derived from the sum of the friction torque of the engine and the engine inertia torque and the engine output torque.

That is, engine torque = engine friction torque + engine inertia torque + engine output torque, where the engine input torque is the engine output torque * torque converter amplification * torque converter efficiency, the engine output torque is the automatic transmission Input torque + gear ratio + transmission friction torque + transmission inertia torque. The driving road inclination is learned based on this engine torque.

That is, since the torque satisfies the output torque-vehicle drag torque-vehicle inertia torque of the transmission, the running road slope is learned from the torque, the final gear ratio, the wheel radius, and the weight.

However, a series of processes for learning the driving road inclination of the vehicle is very complicated, and as the load of the transmission increases, the response to the transmission is degraded.

Therefore, in order to facilitate the learning of the driving road, recently, from the inertia torque derived from the acceleration information and the resistance torque for rolling resistance and air resistance generated by the engine and the weight of the vehicle and the radius and slope information of the vehicle wheel We derived the calibration data for each resistance torque and inertia torque, and learned about the slope based on the derived calibration data for each torque.

However, the learning of the inclination of the road running using the acceleration information has a disadvantage in that it is not possible to distinguish the inclination of the vehicle body due to the change of the installation tolerance and the suspension.

Therefore, the present invention was created to solve the above problems, and an object of the present invention is to satisfy the learning value correction condition for the inclination based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period. The inclination learning value of the driving road is calculated based on the acceleration information and the engine torque, and the inclination learning value based on the acceleration information is corrected with the calculated correction values for the respective inclination learning values, thereby improving accuracy of the inclination learning value. An object of the present invention is to provide a method and apparatus for correcting a learning road slope of a vehicle that can be fundamentally improved.

Driving road slope learning correction apparatus of a vehicle according to the first aspect of the present invention for achieving the above object,

A first gradient learning value generator configured to generate and store a first gradient learning value by performing a learning on a driving road based on an engine torque value supplied from the outside;

A second slope learning value generation unit configured to generate and store a second slope learning value by performing a learning on the driving road based on the acceleration information supplied from the outside;

The apparatus comprises:

Error for the second gradient learning value based on the first gradient learning value and the second gradient learning value when the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period. It characterized in that it further comprises a slope learning value correction unit for correcting.

Preferably, the gradient learning value correction unit,

A learning value correction condition determination module for determining whether the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period;

A calculation module for calculating a difference between the first gradient learning value and the second gradient learning value when the learning correction condition determination module satisfies the learning correction condition;

And a second slope learning value correction module configured to correct the second slope learning value with a correction value corresponding to the calculation module, and then store the corrected second slope learning value as a learning value for a driving road.

Preferably the second slope learning value correction module,

When the difference between the first slope learning value and the second slope learning value is greater than or equal to a predetermined reference value, after correcting the second slope learning value with the predefined correction value, the corrected second slope learning value is a learning value for a driving road. Characterized in that it is provided to store as.

The correction value,

The difference between the first gradient learning value and the second gradient learning value may be set based on a theoretical proportionality equation.

The correction value,

And a lookup table value corresponding to the difference between the first gradient learning value and the second gradient learning value.

Driving road inclination learning method of a vehicle according to a second aspect of the present invention for achieving the above object,

A first gradient learning value generation step of performing learning on the driving road based on engine torque values supplied from the outside to generate and store a first gradient learning value;

A second slope learning value generation step of generating and storing a second slope learning value by performing a learning on the driving road based on the acceleration information supplied from the outside;

The method comprises:

Error for the second gradient learning value based on the first gradient learning value and the second gradient learning value when the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period. Characterized in that it further comprises the step of correcting the learning value gradient.

Preferably, the gradient learning value correction step,

It is determined whether the learning value correction condition for the gradient is satisfied based on the vehicle speed, the number of gears, the engine torque, and the gradient information input at a predetermined period.

Calculating a difference between the first gradient learning value and the second gradient learning value when the learning correction condition determination module satisfies the learning correction condition;

A correction for storing the corrected second slope learning value as a learning value for a driving road after correcting the second slope learning value with a predefined correction value corresponding to the difference between the first slope learning value and the second slope learning value. Characterized in that it comprises a step.

The correction step,

When the difference between the first slope learning value and the second slope learning value is greater than or equal to a predetermined reference value, after correcting the second slope learning value with the predefined correction value, the corrected second slope learning value is a learning value for a driving road. Characterized in that it is provided to store as.

The correction value,

The difference between the first gradient learning value and the second gradient learning value may be set based on a theoretical proportionality equation.

The correction value,

And a lookup table value corresponding to the difference between the first gradient learning value and the second gradient learning value.

As described above, according to the apparatus and method of the learning method for driving road inclination of a vehicle according to the present invention, the learning value correction condition for the slope is satisfied based on the vehicle speed, the gear stage, the engine torque, and the inclination information input at a predetermined period. In this case, the inclination learning value of the driving road is calculated based on the acceleration information of the vehicle and the engine torque, respectively, and the inclination learning value is corrected according to the calculated inclination learning value by the acceleration information. The effect is to fundamentally improve accuracy.

1 is a view showing the configuration of a learning road slope learning correction apparatus according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating the configuration of the learning value correction unit illustrated in FIG. 1 in detail.
3 is a waveform diagram illustrating a learning value corrected by the learning value correcting unit illustrated in FIG. 1.
4 is a flowchart illustrating a process of correcting a learning road slope in accordance with another embodiment of the present invention.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention. In addition, about the part same as a conventional structure, the same code | symbol and the same name are written together.

1 is a view showing the configuration of the learning value correction unit of the driving road inclination learning apparatus of the vehicle according to an embodiment of the present invention, Figure 2 is learning about the slope calculated by the driving road slope correction unit shown in FIG. The waveform diagrams show the values. Driving road inclination learning apparatus of a vehicle according to the present invention, as shown in Figures 1 and 2, satisfying the learning value correction condition for the slope based on the vehicle speed, gear number, engine torque and the inclination information input at a predetermined period In this case, the inclination learning values of the driving roads are calculated based on the acceleration information of the vehicle and the engine torque, respectively, and the inclination learning values of the acceleration information are corrected with the calculated correction values for the respective inclination learning values. The first gradient learning value generation unit 10, the second gradient learning value generation unit 30, and the gradient learning value correction unit 50 are included.

The first gradient learning value generation unit 10 is configured to generate and store a first gradient learning value by performing a learning on a driving road based on engine torque values supplied from the outside.

The second inclination learning value generation unit 30 is provided to generate and store a second inclination learning value by performing a learning on the driving road based on the acceleration information supplied from the outside.

Since a series of processes for generating the first gradient learning value are well known techniques, a detailed description thereof will be omitted.

The second gradient learning value is the inertia torque derived from the acceleration information, the resistance torque for the rolling resistance and the air resistance generated by the engine, and the respective resistance torque and the inertia torque from the vehicle weight and the radius and slope information of the vehicle wheel. It is calculated by deriving the calibration data for and performing the learning about the slope based on the derived calibration data for each torque.

Here, since the second gradient learning value has been filed by the present applicant as the same, a detailed description thereof will be omitted.

When the learning value correction condition for the inclination is satisfied based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period, the inclination learning value correction unit 50 may learn the first inclination learning value and the second inclination. It is provided to correct the error with respect to the second gradient learning value based on the learning value.

That is, as shown in FIG. 2, the gradient learning value correction unit 50 learns whether to satisfy the learning value correction condition for the gradient based on the speed, the gear stage, the engine torque, and the gradient information input at a predetermined period. A calculation module for calculating a difference between the first gradient learning value and the second gradient learning value when the value correction condition determination module 51 and the learning value correction condition determination module 51 satisfy the learning correction condition; 53), a comparison module 55 for comparing the difference between the first gradient learning value and the second gradient learning value by the calculation module with a predefined reference value, and the first gradient learning value and the second gradient learning value. And a second slope learning value correction module 55 for correcting the second slope learning value with a correction value corresponding to the difference and storing the corrected second slope learning value as a learning value for a driving road.

The correction value is set based on a theoretical proportional relationship with respect to the difference between the first slope learning value and the second slope learning value, and corresponds to the difference between the first slope learning value and the second slope learning value as a lookup table value. It is stored in advance in the gradient learning value correction unit.

According to this configuration, when the learning value correction condition for the inclination is satisfied based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period, the inclination learning value of the driving road is calculated based on the acceleration information of the vehicle and the engine torque, respectively. Then, the gradient learning value based on the acceleration information is corrected with the calculated correction values for the gradient learning values, respectively.

Thus, the accuracy with respect to the second gradient learning value is fundamentally improved.

Referring to Figure 3, as shown in a), a waveform diagram showing the gradient learning value calculated based on the output torque, the vehicle speed drag torque, and the vehicle speed inertia torque derived from the existing engine torque, b) is Learning value for slope using calibration data values for each torque derived from slope information (slope), acceleration information (a), vehicle wheel radius (R), vehicle speed (v), and deceleration ratio information This is a waveform diagram showing.

In addition, c) is a waveform diagram showing the corrected second slope learning value, wherein the corrected second slope learning value according to the embodiment of the present invention reduces the error between the first slope learning value and the second slope learning value. Able to know.

When the learning value correction condition for the inclination is satisfied based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period, the inclination learning value is corrected by the acceleration information as a correction value for the difference between the inclination learning values, which are calculated. The process of doing this will be described with reference to FIG.

FIG. 4 is a flowchart illustrating a gradient learning value correction process performed by the learning value correcting unit of FIG. 1, based on an error between the first gradient learning value and the second gradient learning value with reference to FIG. 4. It will be described in more detail the process of correction.

First, the gradient learning value corrector 50 is configured to generate the first gradient learning value of the first gradient learning value generator 10 based on the vehicle speed, the gear stage, the engine torque, and the gradient information input in a predetermined period. And the learning value correction condition for correcting the error of the second gradient learning value of the second gradient learning value generator 30 of the second gradient learning value generator 30 is satisfied (step 103). .

Here, the learning value correction condition is that the vehicle speed is a predetermined value or more, the gear stage is a predetermined value or more, and the engine torque is present within a predetermined range.

Here, the predetermined value, the constant value, and the predetermined range are the result values obtained through a plurality of experiments, and are preset and stored in order to learn the optimal gradient.

Subsequently, in step 105, when the learning value correction condition is satisfied through the step 103, the first gradient learning value and the second gradient learning value generator 30 of the first gradient learning value generator 10 are satisfied. An error of the second gradient learning value of the second gradient learning value generator 30 is calculated.

In addition, the gradient learning value correction unit 50 compares an error between the first gradient learning value and the second gradient learning value with a predetermined reference value through step 105. If the difference between the first gradient learning value and the second gradient learning value is greater than or equal to the reference value as a result of the comparison of step 105, a correction value for the error between the first gradient learning value and the second gradient learning value is output (step 109). .

In addition, the gradient learning value correction unit 50 corrects the second gradient learning value with the correction value in step 111, and the second gradient learning value correction process is performed at a predetermined cycle. Quit the program.

According to the present invention, when the learning value correction condition for the inclination is satisfied based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period, the inclination learning value of the driving road is calculated based on the acceleration information of the vehicle and the engine torque, respectively. Then, the gradient learning value based on the acceleration information is corrected with the calculated correction values for the gradient learning values, respectively.

Thus, the accuracy with respect to the second gradient learning value is fundamentally improved.

As such, those skilled in the art to which the present invention pertains will understand that the present invention may be embodied in other specific forms without changing to the technical spirit or essential features of the present invention. Therefore, the above-described embodiments are to be understood in all respects as illustrative and not restrictive. The scope of the present invention is defined by the appended claims rather than the foregoing detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be interpreted as being included in the scope of the present invention .

When the learning value correction condition for the inclination is satisfied based on the vehicle speed, the number of gears, the engine torque, and the inclination information input at a predetermined period, the inclination learning value of the driving road is calculated based on the acceleration information of the vehicle and the engine torque, respectively. As a correction value for the difference of the slope learning value, the accuracy of the second slope learning value can be fundamentally improved by correcting the slope learning value based on the acceleration information. It is an invention that has industrial applicability because it can bring great progress in terms of accuracy and reliability, and furthermore, in terms of performance efficiency, and is not only sufficiently commercially available or commercially applicable, but also practically evident.

Claims (10)

A first gradient learning value generator configured to generate and store a first gradient learning value by performing a learning on a driving road based on an engine torque value supplied from the outside;
A second slope learning value generation unit configured to generate and store a second slope learning value by performing a learning on the driving road based on the acceleration information supplied from the outside;
The apparatus comprises:
Error for the second gradient learning value based on the first gradient learning value and the second gradient learning value when the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period. And a slope learning value correction unit for correcting the driving road slope learning correction device for a vehicle. The method of claim 1, wherein the gradient learning value correction unit,
A learning value correction condition determination module for determining whether the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period;
A calculation module for calculating a difference between the first gradient learning value and the second gradient learning value when the learning correction condition determination module satisfies the learning correction condition;
And a second slope learning value correction module configured to correct the second slope learning value with a correction value corresponding to the calculation module and then store the corrected second slope learning value as a learning value for a driving road. Road slope learning correction device. The method of claim 2, wherein the second gradient learning value correction module,
When the difference between the first slope learning value and the second slope learning value is greater than or equal to a predetermined reference value, after correcting the second slope learning value with the predefined correction value, the corrected second slope learning value is a learning value for a driving road. Running road slope learning correction device of a vehicle, characterized in that it is provided to store as. The method according to claim 3, The correction value,
And a vehicle learning road tilt learning correction apparatus for the difference between the first learning slope value and the second learning slope value based on a theoretical proportional expression.
The method according to claim 4, wherein the correction value,
And a look-up table value corresponding to the difference between the first slope learning value and the second slope learning value and stored as a look-up table value. A first gradient learning value generation step of performing learning on the driving road based on engine torque values supplied from the outside to generate and store a first gradient learning value;
A second slope learning value generation step of generating and storing a second slope learning value by performing a learning on the driving road based on the acceleration information supplied from the outside;
The method comprises:
Error for the second gradient learning value based on the first gradient learning value and the second gradient learning value when the learning value correction condition for the gradient is satisfied based on the vehicle speed, the gear stage, the engine torque, and the gradient information input at a predetermined period. And a slope learning value correction step of correcting the driving road slope learning correction method for the vehicle. The method of claim 6, wherein the gradient learning value correction step,
A determination step of determining whether the learning value correction condition for the gradient is satisfied based on the vehicle speed, the number of gears, the engine torque, and the gradient information input at a predetermined period;
Calculating a difference between the first gradient learning value and the second gradient learning value when the learning correction condition determination module satisfies the learning correction condition;
A correction for storing the corrected second slope learning value as a learning value for a driving road after correcting the second slope learning value with a preset correction value corresponding to the difference between the first slope learning value and the second slope learning value. Running road slope learning correction method of a vehicle, characterized in that it comprises a step. The method of claim 7, wherein the correcting step,
When the difference between the first slope learning value and the second slope learning value is greater than or equal to a predetermined reference value, after correcting the second slope learning value with the predefined correction value, the corrected second slope learning value is a learning value for a driving road. Road learning slope learning correction method of a vehicle, characterized in that it is provided to store. The method according to claim 8, wherein the correction value,
The vehicle road slope learning correction method, characterized in that set based on the theoretical proportional relation to the difference between the learning value and the first slope learning value. The method according to claim 9, wherein the correction value,
And a look-up table value corresponding to the difference between the first slope learning value and the second slope learning value and stored as a look-up table value.

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