KR101734370B1 - Apparatus and method for estimating road slope - Google Patents

Apparatus and method for estimating road slope Download PDF

Info

Publication number
KR101734370B1
KR101734370B1 KR1020150051947A KR20150051947A KR101734370B1 KR 101734370 B1 KR101734370 B1 KR 101734370B1 KR 1020150051947 A KR1020150051947 A KR 1020150051947A KR 20150051947 A KR20150051947 A KR 20150051947A KR 101734370 B1 KR101734370 B1 KR 101734370B1
Authority
KR
South Korea
Prior art keywords
vehicle
acceleration
driving
wheel
vehicle speed
Prior art date
Application number
KR1020150051947A
Other languages
Korean (ko)
Other versions
KR20160121990A (en
Inventor
이동진
Original Assignee
콘티넨탈 오토모티브 시스템 주식회사
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 콘티넨탈 오토모티브 시스템 주식회사 filed Critical 콘티넨탈 오토모티브 시스템 주식회사
Priority to KR1020150051947A priority Critical patent/KR101734370B1/en
Publication of KR20160121990A publication Critical patent/KR20160121990A/en
Application granted granted Critical
Publication of KR101734370B1 publication Critical patent/KR101734370B1/en

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/076—Slope angle of the road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105—Speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/107—Longitudinal acceleration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00—Testing of vehicles
    • G01M17/007—Wheeled or endless-tracked vehicles
    • B60W2550/142—

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The present invention discloses an apparatus and a method for estimating a road surface gradient. The inclination estimating apparatus includes a mode determining unit for confirming an operation mode of the vehicle and an inclination estimating unit for estimating the road surface inclination using the vehicle speed of the non-driving wheel determined according to the driving system of the vehicle based on the result of checking the operation mode.

Description

[0001] APPARATUS AND METHOD FOR ESTIMATING ROAD SLOPE [0002]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and method for estimating road surface gradient, and more particularly, to an apparatus and method for estimating road surface gradient in consideration of a vehicle test environment.

Recently, as the number of vehicles equipped with Electronic Stability Program (ESP) increases, a road surface gradient estimation method using a longitudinal acceleration sensor (g-sensor) applied to ESP has appeared.

That is, the road surface gradient estimating method using the longitudinal acceleration sensor can calculate the difference between the longitudinal acceleration value measured by the longitudinal acceleration sensor and the actual acceleration value of the vehicle calculated by the vehicle speed sensor (transmission output speed sensor) To determine whether the vehicle is located at an inclination.

Such a road surface gradient estimating technique can easily estimate an inclination in the case of running on an actual road.

However, in a vehicle test environment such as a dyno which is different from an actual road condition, the actual acceleration value is recognized as an uphill or downhill motion because the driving wheel is put on the roller and the running is performed in a state where the vehicle is stopped. However, There is a problem that accurate testing can not be performed since it is calculated as a value indicating that there is no load.

In order to solve such a problem, there is a demand for a technique for estimating the road surface inclination in consideration of the vehicle test environment.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an apparatus and a method for estimating road surface inclination in consideration of a vehicle test environment.

According to a first aspect of the present invention, there is provided an apparatus for estimating an inclination of a vehicle, comprising: a mode checking unit for checking an operation mode of the vehicle; And an inclination estimator for estimating the road surface inclination using the vehicle speed of the non-driving wheel determined according to the driving method of the vehicle based on the result of checking the operation mode.

Wherein the mode checking unit determines the operation mode as a test mode or a normal operation mode based on a result of sensing whether at least one of the wheels of the vehicle is confined to a dyno which is a vehicle test environment .

Wherein the inclination estimator determines the at least one wheel of the vehicle as the non-driving wheel according to a driving mode of the vehicle, when the operation mode is the test mode. An acceleration calculating unit for calculating the acceleration of the non-driving wheel by updating the vehicle speed at each sampling time; And an inclination calculating unit for calculating the road surface inclination using the acceleration of the longitudinal acceleration sensor (g-sensor) provided in the vehicle and the acceleration of the non-driving wheel.

Wherein the determination unit determines at least one rear wheel among the wheels of the vehicle as the non-driving wheel if the vehicle driving system is the all-wheel drive system, and if the vehicle driving system is the rear wheel drive system, Is determined as the non-driving wheel.

Wherein the acceleration calculating unit calculates the first acceleration of the non-driving wheel using the average vehicle speed of the at least one rear wheel updated during the sampling interval if the vehicle driving system is the all-wheel drive system, And a second acceleration of the non-driving wheel is calculated using the average vehicle speed of the at least one front wheel updated during the sampling period if the vehicle is a rear-wheel-drive system.

Wherein the average vehicle speed is calculated by applying a weight to a sampling vehicle speed calculated at a current sampling time during the sampling interval and a sampling vehicle speed calculated at at least one previous sampling time.

Wherein the inclination calculating unit calculates the road surface gradient based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the first acceleration if the vehicle driving system is the all-wheel drive system, And the road surface inclination is calculated based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the acceleration of the second acceleration.

According to a second aspect of the present invention, there is provided a method for estimating an inclination, comprising: confirming an operation mode of a vehicle; And estimating the road surface inclination using the vehicle speed of the non-driving wheel determined according to the driving method of the vehicle based on the result of checking the operation mode.

Wherein the verifying step includes determining that the operation mode is a test mode or a normal operation mode based on a result of sensing whether at least one of the wheels of the vehicle is constrained to a dyno which is a vehicle test environment .

Determining the at least one wheel of the vehicle as the non-driving wheel according to a driving mode of the vehicle if the operation mode is the test mode; Calculating the acceleration of the non-driving wheel by updating the vehicle speed at each sampling time; And calculating the road surface gradient using the acceleration of the longitudinal acceleration sensor (g-sensor) provided in the vehicle and the acceleration of the non-driving wheel.

Determining the non-driving wheel includes determining at least one rear wheel among the wheels of the vehicle as the non-driving wheel if the vehicle driving system is the all-wheel drive system; And determining the at least one front wheel of the vehicle as the non-driving wheel if the vehicle driving system is a rear wheel drive system.

The step of calculating the acceleration of the non-driving wheel may include calculating the first acceleration of the non-driving wheel using the average vehicle speed of the at least one rear wheel updated during the sampling interval if the vehicle driving system is the all-wheel drive system ; And calculating a second acceleration of the non-driving wheel using the average vehicle speed of the at least one front wheel updated during the sampling interval if the vehicle driving system is the rear wheel drive system.

Wherein the average vehicle speed is calculated by applying a weight to a sampling vehicle speed calculated at a current sampling time during the sampling interval and a sampling vehicle speed calculated at at least one previous sampling time.

The step of calculating the road surface gradient includes calculating the road surface gradient based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the first acceleration if the vehicle drive system is the all-wheel drive system ; And calculating the road surface gradient based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the acceleration of the second acceleration if the vehicle driving system is the rear wheel drive system.

According to the apparatus and method for estimating the road surface gradient of the present invention, the road surface gradient is estimated using the vehicle speed of the non-driving wheel after determining the front wheel or the rear wheel as the non-driving wheel in accordance with the vehicle driving system in the vehicle test environment, Since the actual acceleration and the acceleration of the non-driving wheel are matched with each other, it is possible to recognize the road surface inclination similar to that of the longitudinal acceleration sensor. If the acceleration of the longitudinal acceleration sensor and the acceleration of the driving wheel are different in the conventional vehicle test environment, The problem can be solved and the reliability of the vehicle test can be improved.

According to the present invention, the acceleration of the non-driving wheel is calculated based on the average vehicle speed obtained by applying the weights to the sampling vehicle speed calculated at the current sampling time and the sampling vehicle speed calculated at the previous sampling time, It is possible to freely select the viewpoint on the algorithm and to control not to reflect the sampling point at which the error occurs so that more accurate test results can be provided.

1 is a view for explaining a general road surface gradient estimating method.
2 is a diagram showing an example of a general vehicle test environment.
3 is a view schematically showing an apparatus for estimating an inclination according to an embodiment of the present invention.
FIG. 4 is a diagram specifically showing a functional portion of the tilt estimator shown in FIG. 3. FIG.
5 is a diagram illustrating an example of determining a non-driving wheel according to an embodiment of the present invention.
6 is a diagram showing an example of an algorithm for calculating the acceleration of a non-driving wheel of a vehicle according to an embodiment of the present invention.
7 is a flowchart illustrating an operation for estimating a road surface gradient according to an embodiment of the present invention.

It is noted that the technical terms used herein are used only to describe specific embodiments and are not intended to limit the invention. It is also to be understood that the technical terms used herein are to be interpreted in a sense generally understood by a person skilled in the art to which the present invention belongs, Should not be construed to mean, or be interpreted in an excessively reduced sense. Further, when a technical term used herein is an erroneous technical term that does not accurately express the spirit of the present invention, it should be understood that technical terms that can be understood by a person skilled in the art are replaced. In addition, the general terms used in the present invention should be interpreted according to a predefined or prior context, and should not be construed as being excessively reduced.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to like or similar elements throughout the several views, and redundant description thereof will be omitted. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

1 is a view for explaining a general road surface gradient estimating method. 2 is a diagram showing an example of a general vehicle test environment.

Referring to FIG. 1, a general road surface gradient can be measured by a longitudinal acceleration sensor (g-sensor) of an electronic stability program (ESP) mounted on a vehicle, X, y, and x axes, respectively.

More specifically, the longitudinal acceleration value is calculated by the longitudinal acceleration sensor. Then, the actual acceleration value of the vehicle is calculated by the vehicle speed sensor (transmission output speed sensor) connected to the vehicle gear.

Then, the inclination degree is determined by using the difference between the vertical acceleration value and the actual acceleration value of the vehicle as shown in Equation (1).

[Equation 1]

Slope (%) = 100 * tan (sin -1 (value-a / g))

Such a road surface gradient estimation method can easily estimate an inclination in a situation where the vehicle is traveling on an actual road.

However, in the vehicle test environment such as the dyno, which is different from the actual road condition as shown in Fig. 2, the drive wheel 21 is raised on the roller 22 in the stopped state and the vehicle is tested Or fuel economy.

In this case, since the longitudinal acceleration sensor has no inclination of the vehicle, it always calculates a value close to "0 ".

On the other hand, since the actual acceleration value calculated by the drive wheel 21 varies as the vehicle speed increases or decreases, when the vehicle accelerates, the road surface slope is recognized as a downward slope. When the vehicle decelerates, There is a problem that accurate testing becomes impossible.

Hereinafter, an apparatus and method for estimating the road surface inclination in consideration of the vehicle test environment will be described in detail with reference to FIGS. 3 to 6, in order to solve the problem that the road surface slope is not correctly recognized in the vehicle test environment .

3 is a view schematically showing an apparatus for estimating an inclination according to an embodiment of the present invention. FIG. 4 is a diagram specifically showing a functional portion of the tilt estimator shown in FIG. 3. FIG. 5 is a diagram illustrating an example of determining a non-driving wheel according to an embodiment of the present invention. 6 is a diagram showing an example of an algorithm for calculating the acceleration of a non-driving wheel of a vehicle according to an embodiment of the present invention.

3, the tilt estimation apparatus 100 according to the embodiment of the present invention estimates the road surface gradient using the vehicle speed of the non-driving wheels determined according to the driving system of the vehicle based on the result of checking the operation mode of the vehicle .

More specifically, the tilt estimation apparatus 100 may include a mode check unit 110, a tilt estimation unit 120, and a longitudinal acceleration sensor unit 130, which may be included in a transmission control unit do.

The mode checking unit 110 determines whether the vehicle is operating in a vehicle test environment such as a dyno, which is different from an actual road condition, and confirms the operation mode of the vehicle.

That is, the mode check unit 110 determines the operation mode of the vehicle as a test mode or a normal operation mode based on a result of sensing whether at least one of the wheels of the vehicle is constrained to the dyno.

Here, the test mode means that at least one of wheels of the vehicle is simulated for testing in a state where at least one of the wheels of the vehicle is confined to a dyno in an actual road but not in a real road, Which means that the vehicle is running (running).

If it is determined that at least one of the wheels of the vehicle is constrained to the dyno, the mode verifying unit 110 determines that the operation mode of the vehicle is the test mode and the wheels of the vehicle are not constrained to the dyno It can be confirmed that the operation mode of the vehicle is the normal operation mode.

Thereafter, the mode checking unit 110 transmits the result of checking the operation mode of the vehicle to the tilt estimating unit 120.

The tilt estimator 120 estimates the road surface gradient using the vehicle speed of the non-driving wheel determined according to the driving method of the vehicle when the operation mode of the vehicle transmitted from the mode checker 110 is the test mode.

That is, since the driving wheel of the vehicle is driven by the dynamo, the actual acceleration of the vehicle may be different from the actual acceleration of the vehicle. Therefore, the slope estimating unit 120 may calculate the non- To estimate the road surface gradient.

More specifically, the inclination estimating unit 120 includes a determining unit 121, an acceleration calculating unit 122, and an inclination calculating unit 123. [

The determining unit 121 determines at least one of the wheels of the vehicle as a non-driving wheel in accordance with the driving system of the vehicle.

Here, the driving system of the vehicle is divided into an all-wheel drive system and a rear-wheel drive system. The all-wheel drive system is a vehicle system in which a central force is applied to a front wheel (hereinafter, referred to as front wheel) of a vehicle, and a rear-wheel drive system is a vehicle system in which a central force is applied to a rear wheel (hereinafter referred to as a rear wheel).

That is, when the vehicle driving system is the all-wheel drive system, the determination unit 121 determines at least one rear wheel of the vehicle as a non-driving wheel. On the other hand, when the vehicle driving system is the rear wheel drive system, the determination unit 121 determines at least one front wheel among the wheels of the vehicle as the non-driving wheels.

For example, assuming that the vehicle driving system is the all-wheel drive system, the determining unit 121 determines the front wheel 510 of the vehicle 500 as the driving wheel and the rear wheel 520 as the non- . At this time, the front wheel 510 is raised on the roller 530, and the rear wheel 520 is restrained to the dyno.

If the vehicle driving system is the rear wheel drive system, the front wheel 510 of the vehicle 500 is determined as a non-driving wheel and the rear wheel 520 is determined as the driving wheel, as opposed to Fig.

Thereafter, the determination unit 121 notifies the acceleration calculation unit 122 that the determination of the non-driving wheel has been completed.

The acceleration calculating unit 122 updates the vehicle speed of the non-driving wheel of the vehicle at each sampling point to calculate the acceleration of the non-driving wheel. At this time, the sampling point may be an update point for calculating the average vehicle speed by updating the vehicle speed of the non-driving wheels during the entire sampling period.

That is, if the vehicle driving system is the all-wheel drive system, the acceleration calculating unit 122 calculates the first acceleration of the non-driving wheel using the average vehicle speed of at least one rear wheel updated during the sampling period. On the other hand, if the vehicle driving system is the rear wheel drive system, the acceleration calculating unit 122 calculates the second acceleration of the non-driving wheel using the average vehicle speed of at least one front wheel updated during the sampling period.

Here, the average vehicle speed is calculated by applying weights to the sampling vehicle speed calculated at the current sampling time during the sampling interval and the sampling vehicle speed calculated at the at least one previous sampling time, respectively. At this time, the weight is set by the user to freely select the sampling point required during the sampling interval in the algorithm when calculating the average vehicle speed.

More specifically, the acceleration calculator 122 divides the entire sampling period into sampling points for acceleration calculation of the non-driving wheels.

That is, the acceleration calculating unit 122 calculates the sampling vehicle speed at the present sampling time during the sampling period. The acceleration calculating unit 122 calculates the current vehicle speed by applying a weight to the sampling vehicle speed at the present sampling time.

Thereafter, the acceleration calculating unit 122 selects a sampling vehicle speed at at least one previous sampling time performed before the current sampling time. The acceleration calculator 122 calculates a previous vehicle speed by applying weights to sampling vehicle speeds at at least one previous sampling time.

The acceleration calculating unit 122 calculates the acceleration of the non-driving wheel by dividing the difference between the current vehicle speed and the previous vehicle speed, that is, the average vehicle speed, by the time.

For example, assuming that the sampling of the sampling interval is performed four times and the sampling time is updated every 0.01 second, when the vehicle driving system is the all-wheel drive system, the acceleration calculating unit 122 calculates A), a sampling vehicle speed vs_source_grd (k) at the current sampling time k during the sampling period is calculated. The acceleration calculating unit 122 calculates the present vehicle speed 600 by multiplying the sampling vehicle speed at the calculated present sampling point k by the weighting value id_fac_vs_grd [0].

Then, the acceleration calculator 122 selects the sampling vehicle speed at the previous sampling points (k-1, k-2, k-3) performed before the current sampling point. The acceleration calculator 122 calculates the previous vehicle speed 610 by applying weights to the sampling vehicle speeds at the previous sampling points (k-1, k-2, k-3).

That is, the acceleration calculating unit 122 multiplies the sampling vehicle speed vs_source_grd (k-1) at the first previous sampling time (k-1) by the weight id_fac_vs_grd [1]. The acceleration calculation section 122 multiplies the sampling vehicle speed vs_source_grd (k-2) at the second previous sampling time point (k-2) by the weighting value id_fac_vs_grd [2]. Similarly, the acceleration calculating section 122 multiplies the sampling vehicle speed vs_source_grd (k-3) at the third previous sampling time point (k-3) by the weighting value id_fac_vs_grd [3]. Thereafter, the acceleration calculator 122 calculates the previous vehicle speed 610 by adding the results obtained by multiplying the sampling vehicle speeds at the first to third previous sampling points (k-1, k-2, k-3) do.

When the calculation of the current vehicle speed 600 and the previous vehicle speed 610 is completed in the foregoing manner, the acceleration calculating unit 122 divides the difference between the current vehicle speed 600 and the previous vehicle speed 610 by the time, Gt; vs_grd. ≪ / RTI >

On the other hand, when the driving system of the vehicle is the rear wheel drive system, the acceleration calculation unit 122 calculates vs_grd, which is the acceleration of the non-driving wheel in the same manner as described above, and the result is shown in FIG.

Therefore, in the method of calculating the acceleration of the non-driving wheel, a weighting value is applied as shown in Equation (2) differently from a general acceleration calculation formula, so that a sampling point required during the sampling period can be freely selected on the algorithm.

&Quot; (2) "

Acceleration of the non-driving wheel (vs_grd) = (sampling vehicle speed at first sampling point * first weight) + (sampling vehicle speed at second sampling point * second weight) + (Sampled vehicle speed at the sampling time point (k-2) * third weight value) + (sampled vehicle speed at the third previous sampling time point * fourth weight value)} /

For example, if the first weight is 1, the second weight is -1, the third weight and the fourth weight are 0, the acceleration calculator 122 calculates {(sampling vehicle speed at the current sampling time k) (Sampling vehicle speed at the first previous sampling time k-1 * (-1)) + (sampling vehicle speed at the second previous sampling time k-2 * (0)) + (0) of the sampling time k-3) / time, that is, the vehicle speed of the current sampling time k and the vehicle speed of the first previous sampling time k-1, .

As another example, if the first weight is 0.5, the second weight is 0, the third weight is (-0.5), and the fourth weight is 0, the acceleration calculator 122 calculates { (Sampling vehicle speed * (0.5)) + (sampling vehicle speed at the first previous sampling time (k-1) * (0)) + (sampling vehicle speed at the second previous sampling time (k- (K) of the current sampling point - (the vehicle speed of the second sampling point (k-2)) / 2 at the sampling time point (k-3) The acceleration of the non-driving wheel is calculated.

Thereafter, the calculation unit 122 notifies the slope calculation unit 123 that the acceleration calculation of the non-driving wheel is completed.

Referring back to FIG. 4, the slope calculating unit 123 receives the acceleration of the non-driving wheel from the slope calculating unit 123. That is, if the vehicle drive system is a all-wheel drive system, the first acceleration of the non-drive wheel is transmitted. If the vehicle drive system is the rear-wheel drive system, the second acceleration of the non-

In addition, the slope calculating unit 123 receives the sensed acceleration (hereinafter, longitudinal acceleration) from the longitudinal acceleration sensor unit 130 provided in the vehicle.

Thus, the slope calculating unit 123 calculates the road surface slope using the longitudinal acceleration and the acceleration of the non-driving wheel.

That is, the slope calculating unit 123 calculates the slope of the road surface based on the difference between the longitudinal acceleration and the first acceleration when the vehicle drive system is the all-wheel drive system. On the other hand, if the vehicle driving system is the rear-wheel drive system, the slope calculating unit 123 calculates the road surface slope based on the difference between the longitudinal acceleration and the second acceleration.

Referring back to Fig. 3, the longitudinal acceleration sensor unit 130 includes a longitudinal acceleration sensor (g-sensor), and calculates the longitudinal acceleration as the vehicle tilts. The longitudinal acceleration sensor unit 130 transmits the longitudinal acceleration to the gradient estimator 120.

Hereinafter, an operation flow for estimating the road surface gradient performed by the tilt estimation apparatus according to the embodiment of the present invention will be described in detail with reference to FIG. Hereinafter, for convenience of description, reference will be made to the reference numerals mentioned in FIGS. 1 to 6 described above.

7, the mode check unit 110 of the tilt estimation apparatus 100 according to the embodiment of the present invention determines whether the vehicle is operating in a vehicle test environment such as a dyno that is different from an actual road condition And confirms the operation mode of the vehicle (S100).

That is, the mode identifying unit 110 distinguishes the test mode or the normal operation mode based on a result of sensing whether at least one of the wheels of the vehicle is constrained to the dyno.

Thereafter, the mode checking unit 110 transmits the result of checking the operation mode of the vehicle to the tilt estimating unit 120.

The tilt estimator 120 estimates the road surface gradient using the vehicle speed of the non-driving wheel determined according to the driving method of the vehicle when the operation mode of the vehicle transmitted from the mode checker 110 is the test mode.

That is, since the driving wheel of the vehicle is driven by the dynamo, the actual acceleration of the vehicle may be different from the actual acceleration of the vehicle. Therefore, the slope estimating unit 120 may calculate the non- To estimate the road surface gradient.

More specifically, the slope estimating unit 120 determines at least one of the wheels of the vehicle as a non-driving wheel according to the driving method of the vehicle (S110).

Here, the driving system of the vehicle is divided into an all-wheel drive system and a rear-wheel drive system. The all-wheel drive system is a vehicle system in which a central force is applied to a front wheel (hereinafter, referred to as front wheel) of a vehicle, and a rear-wheel drive system is a vehicle system in which a central force is applied to a rear wheel (hereinafter referred to as a rear wheel).

That is, the inclination estimating unit 120 determines at least one rear wheel of the vehicle as a non-driving wheel when the vehicle driving system is the all-wheel drive system. On the other hand, when the vehicle driving system is the rear wheel drive system, the determination unit 121 determines at least one front wheel among the wheels of the vehicle as the non-driving wheels.

Thereafter, the gradient estimating unit 120 updates the vehicle speed of the non-driving wheel of the vehicle at each sampling time to calculate the acceleration of the non-driving wheel (S120).

That is, if the vehicle driving system is the all-wheel drive system, the tilt estimator 120 calculates the first acceleration of the non-driving wheel using the average vehicle speed of at least one rear wheel updated during the sampling period. On the other hand, if the vehicle driving system is a rear wheel drive system, the tilt estimator 120 calculates the second acceleration of the non-driving wheel using the average vehicle speed of at least one front wheel updated during the sampling period.

Here, the average vehicle speed is calculated by applying weights to the sampling vehicle speed calculated at the current sampling time during the sampling interval and the sampling vehicle speed calculated at the at least one previous sampling time, respectively. At this time, the weight is set by the user to freely select the sampling point required during the sampling interval in the algorithm when calculating the average vehicle speed.

More specifically, the gradient estimator 120 divides the entire sampling interval into sampling points for acceleration calculation of the non-driving wheels.

That is, the inclination estimating unit 120 calculates the sampling vehicle speed at the present sampling time during the sampling period. The inclination estimating unit 120 calculates a current vehicle speed by applying a weight to a sampling vehicle speed at a sampling time.

Thereafter, the gradient estimator 120 selects a sampling vehicle velocity at at least one previous sampling point performed before the current sampling point. The inclination estimator 120 calculates a previous vehicle speed by applying weights to sampling vehicle speeds at at least one previous sampling time.

The gradient estimator 120 calculates the acceleration of the non-driving wheel by dividing the difference between the current vehicle speed and the previous vehicle speed, that is, the average vehicle speed, by the time.

The inclination estimating unit 120 receives the sensed acceleration (hereinafter, longitudinal acceleration) from the longitudinal acceleration sensor unit 130 provided in the vehicle (S130).

The slope estimating unit 120 calculates the road surface slope using the longitudinal acceleration and the acceleration of the non-driving wheel (S140).

That is, the tilt estimation unit 120 calculates the road surface gradient based on the difference between the longitudinal acceleration and the first acceleration when the vehicle drive system is the all-wheel drive system. On the other hand, if the vehicle driving system is a rear-wheel-drive system, the tilt estimation unit 120 calculates the road surface gradient based on the difference between the longitudinal acceleration and the second acceleration.

As described above, according to the present invention, since the front wheel or the rear wheel is determined as the non-driving wheel according to the vehicle driving system and the road surface gradient of the non-driving wheel is used, the actual acceleration of the vehicle and the acceleration of the non- It is possible to recognize the slope of the road surface in the same manner as in the longitudinal acceleration sensor, and if the acceleration of the longitudinal acceleration sensor and the acceleration of the drive wheel are different in the conventional vehicle test environment, the problem that the slope can not be accurately recognized can be solved, have.

According to the present invention, the acceleration of the non-driving wheel is calculated based on the average vehicle speed obtained by applying the weights to the sampling vehicle speed calculated at the current sampling time and the sampling vehicle speed calculated at the previous sampling time, It is possible to freely select the viewpoint on the algorithm and to control not to reflect the sampling point at which the error occurs so that more accurate test results can be provided.

As noted above, the functional operations and subject matter implementations described herein may be implemented in digital electronic circuitry, or may be implemented in computer software, firmware, or hardware, including the structures disclosed herein and structural equivalents thereof, And combinations of one or more of these. Implementations of the subject matter described herein may be implemented as one or more computer program products, i. E. One or more modules relating to computer program instructions encoded on a type of program storage medium for execution by, or control of, the operation of the processing system Can be implemented.

The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter that affects the machine readable propagation type signal, or a combination of one or more of the foregoing.

As used herein, the term " system "or" device "encompasses any apparatus, apparatus, and machine for processing data, including, for example, a programmable processor, a computer or a multiprocessor or computer. The processing system may, in addition to the hardware, comprise code that forms an execution environment for a computer program upon request, such as, for example, code comprising a processor firmware, a protocol stack, a database management system, an operating system, .

A computer program (also known as a program, software, software application, script or code) may be written in any form of programming language, including compiled or interpreted language, a priori or procedural language, Components, subroutines, or other units suitable for use in a computer environment. A computer program does not necessarily correspond to a file in the file system. The program may be stored in a single file provided to the requested program, or in multiple interactive files (e.g., a file storing one or more modules, subprograms, or portions of code) (E.g., one or more scripts stored in a markup language document). A computer program may be deployed to run on multiple computers or on one computer, located on a single site or distributed across multiple sites and interconnected by a communications network.

On the other hand, computer readable media suitable for storing computer program instructions and data include semiconductor memory devices such as, for example, EPROM, EEPROM and flash memory devices, for example magnetic disks such as internal hard disks or external disks, Non-volatile memory, media and memory devices, including ROM and DVD-ROM disks. The processor and memory may be supplemented by, or incorporated in, special purpose logic circuits.

Implementations of the subject matter described herein may include, for example, a back-end component such as a data server, or may include a middleware component, such as an application server, or may be a web browser or a graphical user, for example a user, who may interact with an implementation of the subject- Front-end components such as client computers with interfaces, or any combination of one or more of such back-end, middleware, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication, such as, for example, a communications network.

While the specification contains a number of specific implementation details, it should be understood that they are not to be construed as limitations on the scope of any invention or claim, but rather on the description of features that may be specific to a particular embodiment of a particular invention Should be understood. Likewise, the specific features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

It is also to be understood that although the present invention is described herein with particular sequence of operations in the drawings, it is to be understood that it is to be understood that it is to be understood that all such illustrated acts have to be performed or that such acts must be performed in their particular order or sequential order, Can not be done. In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various system components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and systems will generally be integrated together into a single software product or packaged into multiple software products It should be understood that

As such, the present specification is not intended to limit the invention to the specific terminology presented. Thus, while the present invention has been described in detail with reference to the above examples, those skilled in the art will be able to make adaptations, modifications, and variations on these examples without departing from the scope of the present invention. The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

100: an inclination estimator 110: a mode checker
120: inclination estimating unit 121:
122: acceleration calculating unit 123: gradient calculating unit
130: longitudinal acceleration sensor unit

Claims (15)

A mode checking unit for checking whether the operation mode of the vehicle is a test mode or a normal operation mode; And
Wherein when the operation mode is the test mode, an inclination degree estimating unit that estimates the road surface inclination using the vehicle speed of the non-driving wheel determined according to the driving method of the vehicle,
And an estimated value of the gradient. The method according to claim 1,
The mode verifying unit,
Wherein the controller determines the operation mode as a test mode or a normal operation mode based on a result of sensing whether at least one of the wheels of the vehicle is restrained by a dyno which is a vehicle test environment. 3. The method of claim 2,
The slope-
A determining unit determining at least one of the wheels of the vehicle as the non-driving wheel according to a driving mode of the vehicle, when the operation mode is the test mode;
An acceleration calculating unit for calculating the acceleration of the non-driving wheel by updating the vehicle speed at each sampling time; And
And an inclination calculating unit for calculating the road surface inclination using the acceleration of the longitudinal acceleration sensor (g-sensor) provided in the vehicle and the acceleration of the non-driving wheel. The method of claim 3,
Wherein,
Wherein at least one of the wheels of the vehicle is determined as the non-driving wheel if the vehicle driving system is the all-wheel drive system,
Wherein at least one front wheel of the vehicle is determined as the non-driving wheel if the vehicle driving system is a rear wheel drive system. 5. The method of claim 4,
The acceleration calculating unit may calculate,
And calculates a first acceleration of the non-driving wheel using the average vehicle speed of the at least one rear wheel updated during the sampling period if the vehicle driving system is the all-wheel drive system,
Wherein the second acceleration calculating unit calculates the second acceleration of the non-driving wheel using the average vehicle speed of the at least one front wheel updated during the sampling period if the vehicle driving system is the rear wheel drive system. 6. The method of claim 5,
The average vehicle speed
Wherein the weighting is calculated by applying a weight to a sampling vehicle speed calculated at a current sampling time and a sampling vehicle speed calculated at at least one previous sampling time during the sampling interval. The method according to claim 6,
The slope-
And calculates the road surface gradient based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the first acceleration if the vehicle driving system is the all-wheel drive system,
Wherein if the vehicle driving system is the rear-wheel-drive system, the road surface gradient calculating unit calculates the road surface gradient based on a difference between an acceleration of the longitudinal acceleration sensor (g-sensor) and the second acceleration. Confirming whether the operation mode of the vehicle is a test mode or a normal operation mode; And
Estimating the road surface gradient using the vehicle speed of the non-driving wheel determined according to the driving system of the vehicle when the operation mode is the test mode,
And estimating an inclination of the vehicle. 9. The method of claim 8,
Wherein the verifying step comprises:
And determining that the operation mode is a test mode or a normal operation mode based on a result of sensing whether at least one of wheels of the vehicle is restrained by a dyno which is a vehicle test environment. Estimation method. 10. The method of claim 9,
The step of estimating the road surface gradient includes:
Determining, if the operation mode is the test mode, at least one of the wheels of the vehicle as the non-driving wheel according to the driving mode of the vehicle;
Calculating the acceleration of the non-driving wheel by updating the vehicle speed at each sampling time; And
And calculating the road surface gradient using the acceleration of the longitudinal acceleration sensor (g-sensor) provided in the vehicle and the acceleration of the non-driving wheel. 11. The method of claim 10,
Wherein the step of determining as the non-
Determining at least one rear wheel of the vehicle as the non-driving wheel if the vehicle driving system is an all-wheel drive system; And
And determining the at least one front wheel among the wheels of the vehicle as the non-driving wheel if the vehicle driving system is a rear wheel drive system. 12. The method of claim 11,
Wherein the step of calculating the acceleration of the non-
Calculating a first acceleration of the non-driving wheel using the average vehicle speed of the at least one rear wheel updated during the sampling period if the vehicle driving system is the all-wheel drive system; And
And calculating the second acceleration of the non-driving wheel using the average vehicle speed of the at least one front wheel updated during the sampling period if the vehicle driving system is the rear wheel drive system. 13. The method of claim 12,
The average vehicle speed
Wherein the weighting is calculated by applying a weight to a sampling vehicle speed calculated at a current sampling time during the sampling interval and a sampling vehicle speed calculated at a previous sampling time. 14. The method of claim 13,
The step of calculating the road surface gradient includes:
Calculating the road surface gradient based on a difference between an acceleration of the longitudinal acceleration sensor (g-sensor) and the first acceleration if the vehicle driving system is the all-wheel drive system; And
And calculating the road surface gradient based on the difference between the acceleration of the longitudinal acceleration sensor (g-sensor) and the second acceleration if the vehicle drive system is the rear wheel drive system. Way. 15. A computer program stored on a medium for executing each step of the method of any one of claims 8 to 14.
KR1020150051947A 2015-04-13 2015-04-13 Apparatus and method for estimating road slope KR101734370B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
KR1020150051947A KR101734370B1 (en) 2015-04-13 2015-04-13 Apparatus and method for estimating road slope

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
KR1020150051947A KR101734370B1 (en) 2015-04-13 2015-04-13 Apparatus and method for estimating road slope

Publications (2)

Publication Number Publication Date
KR20160121990A KR20160121990A (en) 2016-10-21
KR101734370B1 true KR101734370B1 (en) 2017-05-24

Family

ID=57257110

Family Applications (1)

Application Number Title Priority Date Filing Date
KR1020150051947A KR101734370B1 (en) 2015-04-13 2015-04-13 Apparatus and method for estimating road slope

Country Status (1)

Country Link
KR (1) KR101734370B1 (en)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012067836A (en) * 2010-09-22 2012-04-05 Nissin Kogyo Co Ltd Vehicle control device

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012067836A (en) * 2010-09-22 2012-04-05 Nissin Kogyo Co Ltd Vehicle control device

Also Published As

Publication number Publication date
KR20160121990A (en) 2016-10-21

Similar Documents

Publication Publication Date Title
CN107628036B (en) Detection and reconstruction of sensor faults
JP5080767B2 (en) Method and system for recognizing sign of vehicle speed and evaluating road slope
CN106053879B (en) Pass through the vehicle speed estimation of the expiration operation of data fusion
EP2694344B1 (en) Estimation of road inclination
CN105209309B (en) For determining the method and apparatus of vehicle weight and the vehicle with this device
CN108688667B (en) System and method for detecting faults in lateral velocity estimation
CN105339227B (en) Use the integrated gradient and inclination estimation of three axis inertial measuring units
CN103661393A (en) Kinematic road gradient estimation
CN103661395A (en) Dynamic road gradient estimation
CN109388483A (en) Method and apparatus for supporting mission critical applications by calculating cloud unloading
CN103661394A (en) Road gradient estimation arbitration
CN103661352A (en) Static road gradient estimation
KR20140060349A (en) Method for estimating tire parameters for a vehicle
CN105339226B (en) Estimated using the integrated gradient of three axis inertial measuring units and pitching
US20210101416A1 (en) Tire wear measurement device using acceleration peak value of tire and tire wear measurement method using same
CN103781687B (en) The fusion of chassis sensing data and vehicle dynamics data
CN108058709A (en) For running the method and apparatus of driver assistance system, driver assistance system
CN112298189A (en) Method for training a neural network, method and device for estimating a friction coefficient, and machine-readable storage medium
CN112572460A (en) Method and apparatus for estimating yaw rate with high accuracy, and storage medium
KR102237230B1 (en) System and Method for estimating a state of road for a vehicle
KR101734370B1 (en) Apparatus and method for estimating road slope
CN115991187A (en) Vehicle control method, controller and storage medium based on non-offset model prediction
CN109307782A (en) Automobile speedestimate device, automobile speedestimate method and computer-readable medium
CN113335294A (en) Method and device for estimating longitudinal gradient of road surface, electronic device and storage medium
KR102200521B1 (en) Estimation device of lateral slip for vehicle

Legal Events

Date Code Title Description
A201 Request for examination
E902 Notification of reason for refusal
E701 Decision to grant or registration of patent right
GRNT Written decision to grant