KR20220072952A - Method for estimating a vehicle's center of gravity and wheel load, and system for vehicle's center of gravity and wheel load estimation by performing the same - Google Patents

Abstract

An embodiment of the present invention provides a technique for accurately estimating the load of each wheel in a driving situation of deceleration or turning of a vehicle. A method for estimating an axial weight of a vehicle according to an embodiment of the present invention includes: a first step of preparing a three-dimensional map that is a three-dimensional graph of a relationship between a load applied to a tire, a contact angle of the tire, and a pressure of the tire; A dynamic model for the vehicle is generated, and the contact angle and pressure values of the tire model according to the acceleration (longitudinal/lateral direction) of the vehicle model in the dynamic model are substituted into the 3D map to the tire model for each acceleration of the vehicle model. a second step of calculating an estimated load that is an applied load; By inputting the estimated load and the acceleration of the vehicle model into the vehicle dynamics governing equation, the three-dimensional (vertical, horizontal, and height) coordinates of the load of the vehicle model and the center of gravity of the vehicle model are calculated, thereby the acceleration of the vehicle model a third step of generating center of gravity coordinate data for each acceleration, which is three-dimensional coordinate data of the center of gravity of the vehicle model according to and a fourth step of calculating the load of each of a plurality of tires installed in the vehicle when the vehicle is driven by substituting the load of the vehicle model, the center of gravity coordinate data for each acceleration, and the vehicle acceleration into the vehicle dynamics governing equation; includes

Description

Method for estimating center of gravity coordinates and axial load of a vehicle, and a system for estimating center of gravity coordinates and axial load of a vehicle for the same PERFORMING THE SAME}

The present invention relates to a method for estimating center of gravity coordinates and axial load of a vehicle, and to a system for estimating center of gravity coordinates and axial load of a vehicle for performing the same, and more particularly, to a vehicle weight in a driving situation of deceleration or turning of the vehicle It relates to a technology for accurately estimating the center coordinates and the load of each wheel in real time.

As a vehicle load estimation method, there is a Longitudinal Dynamic-based total vehicle load estimation method using vehicle sensors (IMU, GPS). In addition, in a method of estimating the load of each wheel from the total weight of the vehicle, the estimation error for each wheel affects each other, and there is a limit in securing accuracy compared to the sensor method.

The load load estimation method using the tire sensor is more accurate than the vehicle sensor method that estimates the load of each wheel from the total load because it is possible to estimate the load on each wheel. It may take less time to estimate. For load estimation using these tire sensors, there are a method using a deformation sensor (strain gage, piezo film, etc.) and a technique using an optical sensor/acceleration sensor/pressure sensor, etc. In particular, acceleration-based load estimation has many advantages in terms of commercialization because it has superior durability compared to deformation sensors and can be implemented in a modular way. In this method, the method of estimating the grounding field by analyzing the signal of the accelerometer and analyzing it is common. US Registration No. 10,684,161 (Tire load estimation method and tire load estimation device) and US Patent Publication No. 10,684,161 The method is disclosed in 2020-0164703 No. (title of the invention: TIRE LOAD ESTIMATION SYSTEM AND METHOD).

However, the aforementioned method of estimating each axle load through the tire sensor has faster estimation and accuracy compared to vehicle sensor-based estimation, but has the following disadvantages. First, in the case of the sampling rate, one tire load is estimated per tire rotation, and about 5 data can be obtained at a speed of 65 kph. The reality is that the number of data is insufficient to be applied to vehicle control. In addition, it has low robustness to the extent that it is impossible to estimate the static load of each wheel for general driving conditions such as deceleration or turning.

US Registration No. 10,684,161 US Patent Publication No. 2020-0164703

An object of the present invention for solving the above problems is to accurately estimate the load of each wheel in a driving situation of deceleration or turning of a vehicle.

And, an object of the present invention is to enable real-time load estimation using a vehicle model with a minimum number of sensors based on vehicle factors.

The technical problems to be achieved by the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. There will be.

The configuration of the present invention for achieving the above object is a first step of preparing a three-dimensional map, which is a three-dimensional graph of the relationship between the load applied to the tire, the tread angle (or grounding field) of the tire, and the pressure of the tire ; A dynamic model for the vehicle is generated, and the contact angle and pressure values of the tire model according to the acceleration (longitudinal/lateral direction) of the vehicle model in the dynamics model are substituted into the 3D map to the tire model for each acceleration of the vehicle model. a second step of calculating an estimated load that is an applied load; By inputting the estimated load and the acceleration of the vehicle model into the vehicle dynamics governing equation, the three-dimensional (longitudinal, lateral, and height) coordinates of the load of the vehicle model and the center of gravity of the vehicle model are calculated, thereby the acceleration of the vehicle model a third step of generating center of gravity coordinate data for each acceleration, which is three-dimensional coordinate data of the center of gravity of the vehicle model according to and a fourth step of calculating the load of each of a plurality of tires installed in the vehicle when the vehicle is driven by substituting the load of the vehicle model, the center of gravity coordinate data for each acceleration, and the vehicle acceleration into the vehicle dynamics governing equation; includes

In an embodiment of the present invention, the fourth step may include a 4-1 step of calculating a static load that is a load of each of a plurality of tires installed in the vehicle when the vehicle is traveling at a constant speed.

In an embodiment of the present invention, the fourth step may include a step 4-2 of calculating a dynamic load that is a real-time load of each of a plurality of tires installed in the vehicle when the vehicle is driven under deceleration.

In an embodiment of the present invention, the vehicle dynamics governing equation may be generated by calculating a cost function after linear regression analysis on four tire models.

The configuration of the present invention for achieving the above object is a vehicle in which four tires are installed; an acceleration calculation unit installed in the vehicle to calculate an acceleration of the vehicle; and a real-time algorithm driving device for storing a load estimation algorithm including the vehicle dynamics governing equation and the center of gravity coordinate data for each acceleration; The real-time load of each of a plurality of tires installed in the vehicle may be calculated by substituting the three-dimensional coordinates of the center of gravity of the vehicle calculated using the coordinate data into the vehicle dynamics governing equation.

The effect of the present invention according to the above configuration is that it is possible to accurately estimate the load of each wheel in a driving situation in a deceleration turning by fusing tire sensing and vehicle dynamics, and utilize a vehicle model without a sensor signal based on the vehicle factor. This means that real-time load estimation is possible.

It should be understood that the effects of the present invention are not limited to the above-described effects, and include all effects that can be inferred from the configuration of the invention described in the detailed description or claims of the present invention.

1 is a graph showing the relationship between the tire pressure and the tire tread angle.
2 is a graph of a 3D map according to an embodiment of the present invention.
3 is an image of vehicle-related figures according to an embodiment of the present invention.
4 is a graph based on a vehicle dynamics governing equation according to an embodiment of the present invention.
5 is an image of a screen displaying a result value obtained by a method for estimating an axial weight of a vehicle according to an embodiment of the present invention.
6 is a table for calculating a dynamic load according to an embodiment of the present invention.
7 to 15 are tables and graphs showing the use of the method for estimating the axial weight of a vehicle according to an embodiment of the present invention under each condition.

Hereinafter, the present invention will be described with reference to the accompanying drawings. However, the present invention may be embodied in several different forms, and thus is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is said to be “connected (connected, contacted, coupled)” with another part, it is not only “directly connected” but also “indirectly connected” with another member interposed therebetween. "Including cases where In addition, when a part "includes" a certain component, this means that other components may be further provided without excluding other components unless otherwise stated.

The terms used herein are used only to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present specification, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

Estimation using the tire sensor of the prior art generates 1 data per rotation, and about 5 data can be obtained at a speed of 65 kph. However, after estimation of the vehicle model due to the tire load estimation method of the present invention, it may be possible to secure 100 data or more of the estimated load per second. In this process, based on the tire sensor signal, it is possible to estimate the CG Point (Center of Gravity Point) and CG Height (Center of Gravity Height) as the coordinates of the center of gravity of the vehicle that are difficult to obtain only with the vehicle on-board sensor, and furthermore, the tire sensor Accurate load estimation of each tire may be possible without a tire sensor through the vehicle model information obtained by The CG Point may represent the coordinates of the center of gravity in the longitudinal and lateral directions of the vehicle, and the CG Height may represent the coordinates of the center of gravity in the height direction of the vehicle. Here, the forward direction of the vehicle may be referred to as a longitudinal direction, the vehicle axle direction may be referred to as a transverse direction, and a direction perpendicular to the ground may be referred to as a height direction. In addition, the longitudinal direction may be the x-axis direction, the lateral direction may be the y-axis direction, and the z-axis may be the height direction. And, FL and Fl and fl may mean the front left side of the vehicle, FR, Fr and fr may mean the front right side of the vehicle, RL, Rl and rl may mean the rear left side of the vehicle, RR and Rr and rr may mean a rear right side of the vehicle. Hereinafter, it is the same.

1 is a graph showing a relationship between tire pressure and a tire tread angle, and FIG. 2 is a graph of a 3D map according to an embodiment of the present invention.

1 is a graph of the relationship between the load applied to the tire under various conditions - the contact angle of the tire - the pressure of the tire, and the horizontal axis is the reference load (435 kgf) converted into % when the reference load (435 kgf) is 100%. and the vertical axis represents the tread angle of the tire. Here, the pressure of the tire is the internal pressure of the tire. Hereinafter, it is the same.

Each of the graphs a, b, c, and d is a graph of the relationship between the tire load and the tire tread angle obtained while changing the tire pressure. It can be seen that the graph is spread to some extent for each pressure, which may be an effect of changing speed and wear.

That is, it may be a state in which a plurality of conditions (3 speed stages * 4 wear stages) are included for one pressure. Therefore, the smaller the spread of the graph for each pressure is, the more likely it is that the pressure and the contact angle dominate the load on the tire. Each of the graphs a, b, c, and d indicated by the thick solid line of the search may represent the average value of the load and the contact angle at each tire internal pressure. As can be seen in FIG. 1 , in the case of the tire load, it can be confirmed that the tire's contact angle and pressure are predominantly changed. However, it can be seen that when the speed or wear is changed, the change in the load is remarkably small.

Based on the above results, in order to perform the tire load estimation method of the present invention, first, in the first step, 3 is a three-dimensional graph of the relationship between the load applied to the tire, the tire tread angle, and the tire pressure. You can create a dimensional map. The first step may be performed using values measured after installing an intelligent tire sensor on a tire on an indoor experimental track (Flat trac III). In addition, a three-dimensional map can be generated by inputting the tire pressure and the tire tread angle to an algorithm used in the experimental track to derive an estimated tire load value. That is, the three-dimensional map as described above is derived theoretically and experimentally, and a detailed description thereof will be omitted as it is a prior art.

In the second step, a dynamic model for the vehicle is created, and the tire model for each acceleration of the vehicle model is substituted by the contact angle and pressure value of the tire model according to the acceleration (longitudinal/lateral) in the dynamic model in the 3D map. The estimated load, which is the load acting on the , can be calculated.

In order to estimate the load in the actual driving environment, it may be necessary to converge with vehicle dynamics to secure the performance of the load estimation method (algorithm) even under driving conditions such as deceleration and turning rather than in a constant-speed straight-line situation.

In conclusion, by combining the tire sensor and vehicle dynamics, the load estimation method of the present invention has the following three advantages. The first advantage is that it can secure a high sampling rate of 100 estimation/sec by combining it with the IMU sensor. The second advantage is that it can have high robustness in estimating dynamic and static loads even in deceleration driving situations or turning driving situations. The third advantage is that it is possible to estimate vehicle parameters such as the dynamic load static load of each tire of the vehicle, as well as the coordinates of the vehicle's center of gravity (CG point and CG height). In addition, the following steps 3 to 5 may be performed in order to realize such an advantage.

In the third step, by inputting the estimated load and the acceleration of the vehicle model into the vehicle dynamics governing equation, the three-dimensional (longitudinal, lateral, and height) coordinates of the load of the vehicle model and the center of gravity of the vehicle model are calculated. It is possible to generate the center of gravity coordinate data for each acceleration, which is the three-dimensional coordinate data of the center of gravity of the vehicle model according to .

Here, by estimating the coordinates of the center of gravity (CG point, CG height) of the vehicle, the coordinates of the center of gravity of the vehicle are calculated using the tire sensor and the in-vehicle acceleration sensor in the first and second steps. For example, the value used through the tire sensor is the real-time load value of each tire of the vehicle, and these values are implemented in the estimated load calculation using the 3D map by the first and second steps, _The estimated load as described above and the acceleration of the changing vehicle model can be substituted into the vehicle dynamics governing equation. ) is the direction acceleration value a _y .

As a result, by substituting a total of six values (the estimated loads of each of the four tires, a _x and a _y ) into the vehicle dynamics governing equation, four values (the total load (m) of the vehicle and the three-dimensional coordinates of the center of gravity) can be derived. That is, the vehicle dynamics model models the load movement with respect to the longitudinal/lateral acceleration of the vehicle after the vehicle is assumed to be a rigid body. In this study, in a MIMO (multi input multi output) linear system with 6 inputs and 4 outputs, it was calculated using the MIMO linear regression algorithm, and the total vehicle load (m), CG point, and CG height were estimated. can do.

3 is an image of vehicle-related numerical values according to an embodiment of the present invention, and FIG. 4 is a graph based on a vehicle dynamics governing equation according to an embodiment of the present invention. Specifically, FIG. 4 is a graph between the acceleration (horizontal axis) of the vehicle model and the load (vertical axis) of the vehicle model.

The vehicle dynamics governing equation may be generated by calculating a cost function after linear regression analysis for four tire models.

Linear regression analysis can be performed by [Equation 1]. In [Equation 1], X, Y, B ₀ , and B ₁ may be determinants.

[Formula 1]

The X matrix and the Y matrix may be formed as shown in [Equation 2] and [Equation 3] below.

[Equation 2]

[Equation 3]

In [Equation 2] and [Equation 3], a _x may be the longitudinal acceleration of the vehicle, and a _y may be the lateral acceleration of the vehicle. And, F _z,FR is the load on the front right tire of the vehicle, F _z,FL is the load on the front left tire of the vehicle, F _z,RR is the load on the rear right tire of the vehicle, F _{z, RL} may be a load on the tire on the rear left side of the vehicle.

The B ₀ matrix and the B ₁ matrix may be formed as shown in [Equation 4] and [Equation 5] below.

[Equation 4]

[Equation 5]

In [Equation 4] and [Equation 5], m is the vehicle load, D is the distance between both front tires of the vehicle, L is the distance between both tires on the side of the vehicle, and D _l is the vehicle's center of gravity and the vehicle It is the lateral distance between the front left tires, Lr is the longitudinal distance between the center of gravity of the vehicle and the rear right tire of the vehicle, and h is the height of the center of gravity of the vehicle.

By calculating the cost function, the vehicle dynamics governing equation may be formed as in [Equation 6] below.

[Equation 6]

And, [Equation 6] can be calculated as in [Equation 7] and [Equation 8] below.

[Equation 7]

[Equation 8]

By the calculations up to [Equation 8], the total load (m or M) of the vehicle, the z-axis coordinate of the center of gravity, the x-axis coordinate of the center of gravity, and the y-axis coordinate of the center of gravity can be sequentially derived.

In the fourth step, by substituting the center of gravity coordinate data for each load and acceleration of the vehicle model and the vehicle acceleration into the vehicle dynamics governing equation, the load of each of the plurality of tires installed in the vehicle may be calculated when the vehicle is driven. Here, the fourth step may include a step 4-1 of calculating a static load that is a load of each of a plurality of tires installed in the vehicle when the vehicle is traveling at a constant speed. In addition, the fourth step may include a 4-2 step of calculating a dynamic load, which is a real-time load of each of a plurality of tires installed in the vehicle, when the vehicle is driven under deceleration.

In step 4-1, the total load value of the vehicle model estimated in step 3 and the coordinate values (CG point, CG height) of the vehicle model are substituted into the vehicle dynamics governing equation to estimate the static load of each tire installed in the vehicle. can do. Considering that the vehicle is traveling at a constant speed, both the acceleration a _x in the x-axis direction and the acceleration a _y in the y-axis direction of the vehicle may be set to 0.

In step 4-2, the total load value of the vehicle model estimated in step 3, the coordinate values (CG point, CG height) of the vehicle model, and the vehicle acceleration are substituted into the vehicle dynamics governing equation for each tire installed in the vehicle. It is possible to estimate the dynamic load of Since acceleration or deceleration driving is considered, the vehicle's x-axis acceleration a _x and y-axis acceleration a _y can be substituted into the vehicle dynamics governing equation.

Hereinafter, actual vehicle test results will be described.

In order to verify the performance of the tire load estimation method of the present invention fused with vehicle dynamics, an actual vehicle test was conducted. It received the tire sensor signal of each wheel and the IMU sensor signal, which is an in-vehicle sensor, and estimated and analyzed the load in real time using a real-time algorithm drive equipment (Autobox 3.0) capable of a real time interface. The tire load estimation method of the present invention was implemented using a real-time program, and the result data was effectively analyzed by using a control desk program to produce a graphical user interface that shows the result values in graphs and tables in real time. .

5 is an image of a screen displaying a result value obtained by a method for estimating an axial weight of a vehicle according to an embodiment of the present invention. Specifically, FIG. 5 is a screen of the graph interface described above. In FIG. 5, vehicle speed (Velocity) and center of gravity coordinate values (CG point, CG height) are displayed in area a, and time (horizontal axis) in area b. The acceleration (vertical axis) of each vehicle is displayed as a graph, and the load (vertical axis) for each time (horizontal axis) measured by the tire sensor installed on each tire can be displayed in area c. In addition, in area d, whether the axial weight estimation method of the vehicle of the present invention is executed or not, in area e and g, the load distribution of the front side and rear side of the vehicle is displayed, respectively, and in area f, the total load of the vehicle is displayed. can be displayed In the T _fl area, the load information of the front left tire of the vehicle is displayed, in the T _fr area, the load information of the front right tire is displayed, in the T _fl area the load information of the rear left tire is displayed, and in the T _rr station, the load information of the front left tire is displayed. Load information of the rear right tire may be displayed. Here, the reference load, the estimated load, the dynamic load, and the error rate of the dynamic load compared to the reference load measured by the tire sensor may be displayed in each area. In this way, the actual vehicle test can be performed in real time by using the graph interface to compare the actual tire load measurement and the estimated load and dynamic load using the axial weight estimation method of the vehicle of the present invention.

6 is a table for calculating a dynamic load according to an embodiment of the present invention. And, FIGS. 7 to 15 are tables and graphs showing the use of the method for estimating the axial weight of a vehicle according to an embodiment of the present invention under each condition.

Line (a) of FIG. 6 is for data calculated during constant speed driving, line (b) of FIG. 6 is for data calculated during deceleration driving, and line (c) of FIG. 6 is for data calculated during normal driving It's about data.

FIG. 7(a) is an enlarged view of the graph Ax (acceleration of the vehicle in the X-axis direction) of FIG. 6(a), and FIG. acceleration) is an enlarged graph. Also, (a) of FIG. 8 is a graph of the load change of the front left (FL) tire of the vehicle, FIG. 8 (b) is a graph of the load change of the front right (FR) tire of the vehicle, and FIG. 8 (c) is a graph of the load change of the rear left (RL) tire of the vehicle, and (d) of FIG. 8 is a graph of the load change of the rear right (RR) tire of the vehicle. Here, the horizontal axis is time and the vertical axis is load.

In Figure 8 (a) to (d), the dotted line represents the change in the reference load (True static load), a straight line in the horizontal axis direction represents the change in the Estimated static load, and the line whose amplitude is variable in the vertical axis direction is the dynamic load ( Estimated dynamic load) changes. 9 shows the calculated values of the estimated total weight (Mass) of the vehicle and the x-coordinate (CG x-axis), y-coordinate (CG y-axis), and z-coordinate (CG z-axis) of the center of gravity, , by comparing each of these values and the three-dimensional coordinate values of the total weight of the vehicle and the center of gravity derived when substituting the load of each tire measured by the tire sensor into the vehicle dynamics governing equation, respectively, the error rate (Error) This is a table organized by deriving .

As shown in FIGS. 7 to 9 , in the constant speed driving situation of the vehicle, the speed of the vehicle is constantly maintained and the vehicle may be operated. It can be seen as cruise control during actual driving, and load transfer may not occur because there is no vehicle acceleration. It can be seen that the estimated dynamic load of the four wheels is maintained at a constant value, and the estimated static load of each wheel is estimated within the range of the actual load value and the maximum error rate of 3.9%. In addition, it can be confirmed that the x-coordinate (CG x-axis) and y-coordinate (CG y-axis) of the center of gravity are estimated within a maximum error rate of 1.01%, and the total load has an error rate of 2.26%. Since there is no dynamic situation such as load transfer, it can be confirmed that the estimation time is 5 seconds, which is relatively fast compared to other situations. This is the section where the accuracy of load estimation using the tire sensor can be secured when there is no vehicle signal.

10A is an enlarged view of the Ax (X-axis direction vehicle acceleration) graph of FIG. 6B , and FIG. 10B is an enlarged view Ay (y-axis direction vehicle acceleration) graph of FIG. acceleration) is an enlarged graph. In addition, FIG. 11 (a) is a graph of the load change of the front left (FL) tire of the vehicle, FIG. 11 (b) is a graph of the load change of the front right (FR) tire of the vehicle, and FIG. (c) is a graph of the load change of the rear left (RL) tire of the vehicle, and (d) of FIG. 11 is a graph of the load change of the rear right (RR) tire of the vehicle. Here, the horizontal axis is time and the vertical axis is load.

11 (a) to (d), the dotted line represents the change in the true static load, the straight line in the horizontal axis direction represents the change in the Estimated static load, and the line whose amplitude is variable in the vertical axis direction is the dynamic load ( Estimated dynamic load) changes. 12 shows the calculated values of the estimated total weight (Mass) of the vehicle and the x-coordinate (CG x-axis), y-coordinate (CG y-axis), and z-coordinate (CG z-axis) of the center of gravity, and , by comparing each of these values and the three-dimensional coordinate values of the total weight of the vehicle and the center of gravity derived when substituting the load of each tire measured by the tire sensor into the vehicle dynamics governing equation, respectively, the error rate (Error) This is a table organized by deriving .

10 to 12 , in the deceleration driving situation of the vehicle, the speed of the vehicle may be decelerated and the vehicle may be driven. Since it is a situation in which the vehicle's longitudinal (x-axis direction) acceleration exists, it is a situation in which load transfer is performed in the longitudinal direction. It can be seen that the estimated dynamic load of the four wheels well indicates that the load was transferred back and forth in the deceleration and acceleration section of 30 to 35 seconds. On the other hand, it can be seen that the estimated static load is maintained at a constant value. This may mean that the static load of each wheel of the vehicle is well estimated by the robustness of the tire load estimation method of the present invention even in a deceleration/deceleration situation.

It can be confirmed that the estimated static load value of each wheel was estimated within the range of the actual load value and the maximum error rate of 1.57%. In addition, it can be confirmed that the x-coordinate (CG x-axis) and the y-coordinate (CG y-axis) of the center of gravity are estimated within a maximum error rate of 0.87%, and the total load of the vehicle is estimated with an error rate of 0.54%. Considering the dynamic situation in which the load transfer is made, it can be confirmed that the load estimation time is 19 seconds, which is longer than the estimated time of 5 seconds in the constant speed driving situation scenario.

13A is an enlarged view of the Ax (X-axis direction vehicle acceleration) graph of FIG. 6C , and FIG. 13B is an enlarged view Ay (y-axis direction vehicle acceleration) graph of FIG. 6C . acceleration) is an enlarged graph. Also, FIG. 14 (a) is a graph of the load change of the front left (FL) tire of the vehicle, FIG. 14 (b) is a graph of the load change of the front right (FR) tire of the vehicle, and FIG. (c) is a graph of the load change of the rear left (RL) tire of the vehicle, and (d) of FIG. 14 is a graph of the load change of the rear right (RR) tire of the vehicle. Here, the horizontal axis is time and the vertical axis is load.

In Figure 14 (a) to (d), the dotted line represents the change in the reference load (True static load), the horizontal straight line represents the static load (Estimated static load) change, and the line whose amplitude is variable in the vertical axis direction is the dynamic load ( Estimated dynamic load) changes. 15 shows the calculated values of the estimated total weight (Mass) of the vehicle and the x-coordinate (CG x-axis), y-coordinate (CG y-axis) and z-coordinate (CG z-axis) of the center of gravity, and , by comparing each of these values and the three-dimensional coordinate values of the total weight of the vehicle and the center of gravity derived when substituting the load of each tire measured by the tire sensor into the vehicle dynamics governing equation, respectively, the error rate (Error) This is a table organized by deriving .

13 to 15 , in a general driving situation, the speed of the vehicle changes chaotically, and the vehicle can be driven while simultaneously acting in the longitudinal direction (x-axis direction) as well as the lateral direction (y-axis direction). Because the vehicle has lateral acceleration, it may be a situation in which lateral load transfer is made.

It can be seen that the estimated dynamic load of the four wheels well indicates that the load was transferred from side to side in 15 to 25 seconds, which is the turning section of the vehicle. On the other hand, it can be confirmed that the estimated static load is maintained at a constant value, which means that the static load of each wheel of the vehicle is well estimated even in a general driving situation, indicating that the robustness of the load estimation method of the present invention has been proven. can It can be confirmed that the estimated static load value of each wheel was estimated within the range of the actual load value and the maximum error rate of 4.44%. In addition, it can be confirmed that the x-coordinate (CG x-axis) and the y-coordinate (CG y-axis) of the center of gravity are estimated within the maximum error rate of 2.26%, and the total load has an error rate of 3.72%. Considering that the load transfer is a dynamic situation, the load estimation time is 25 seconds, which is relatively long compared to other situations.

The following points can be confirmed through the actual vehicle measurement over the three situations as described above. By fusion with vehicle dynamics, it can be confirmed that static load, dynamic load, and CG point CG height have been estimated with a high sampling rate of 100 estimation/sec. In addition, it was confirmed that the load estimation algorithm had high robustness in estimating static and dynamic loads in deceleration and general driving situations. At this time, all estimations are completed within 30 seconds of starting the vehicle operation, and in this verification test, it can be confirmed that the maximum error rate for estimating static load of each wheel is 4.44% and the maximum error rate for estimating CG point and CG height is 3.72%.

Hereinafter, a system for estimating the axial weight of a vehicle for performing the method for estimating the tire load of the present invention will be described.

An axial weight estimation system for a vehicle according to the present invention includes: a vehicle in which four tires are installed; an acceleration calculation unit installed in a vehicle to calculate an acceleration of the vehicle; and a real-time algorithm driving device for storing a load estimation algorithm including vehicle dynamics governing equations and acceleration-specific center of gravity coordinate data.

Then, by substituting the three-dimensional coordinates of the vehicle's center of gravity calculated using the vehicle's load and the vehicle's acceleration and center of gravity coordinate data for each acceleration into the vehicle dynamics governing equation, the real-time load of each of a plurality of tires installed in the vehicle is The dynamic load can be calculated.

The remaining details for each configuration are the same as those described in the method for estimating the tire load of the present invention.

The description of the present invention described above is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a dispersed form, and likewise components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included in the scope of the present invention.

Claims (9)

A first step of preparing a three-dimensional map, which is a three-dimensional graph of the relationship between the load applied to the tire, the tread angle of the tire, and the pressure of the tire;
A dynamic model for the vehicle is generated, and the contact angle and pressure values of the tire model according to the acceleration (longitudinal/lateral direction) of the vehicle model in the dynamic model are substituted into the 3D map to the tire model for each acceleration of the vehicle model. a second step of calculating an estimated load that is an applied load;
By inputting the estimated load and the acceleration of the vehicle model into the vehicle dynamics governing equation, the three-dimensional (vertical, horizontal, and height) coordinates of the load of the vehicle model and the center of gravity of the vehicle model are calculated, thereby the acceleration of the vehicle model A third step of generating the coordinate data (CG point, CG height) for each acceleration, which is the three-dimensional coordinate data of the center of gravity of the vehicle model according to ; and
A fourth step of calculating the load of each of the plurality of tires installed in the vehicle when the vehicle is driving by substituting the load of the vehicle model, the center of gravity coordinate data for each acceleration, and the vehicle acceleration into the vehicle dynamics governing equation; A method of estimating the center of gravity coordinates and axial load of a vehicle, comprising:
The method according to claim 1,
The fourth step is a method for estimating the center of gravity coordinates and axial load of a vehicle, characterized in that it includes a step 4-1 of calculating a static load, which is a load of each of a plurality of tires installed in the vehicle when the vehicle is traveling at a constant speed.
3. The method according to claim 2,
The fourth step includes a step 4-2 of calculating a dynamic load, which is a real-time load of each of a plurality of tires installed in the vehicle, during deceleration and deceleration of the vehicle. Way.
The method according to claim 1,
The vehicle dynamics governing equation is a method for estimating center of gravity coordinates and axial weight of a vehicle, characterized in that it is generated by calculating a cost function after linear regression analysis on four tire models.
5. The method according to claim 4,
The linear regression analysis is a method of estimating the center of gravity coordinates and axial load of a vehicle, characterized in that performed by the following equation.

Here, X, Y, B ₀ , and B ₁ are determinants.
6. The method of claim 5,
The X matrix and the Y matrix are the center of gravity coordinates of the vehicle and the axial weight estimation method, characterized in that formed as follows.

,

Here, a _x is the longitudinal acceleration of the vehicle, and a _y is the lateral acceleration of the vehicle. And, F _z,FR is the load on the front right tire of the vehicle, F _z,FL is the load on the front left tire of the vehicle, F _z,RR is the load on the rear right tire of the vehicle, F _{z, RL} is the load on the tire on the left rear side of the vehicle.
7. The method of claim 6,
The B ₀ matrix and the B ₁ matrix are the center of gravity coordinates and axial weight estimation method of the vehicle, characterized in that formed as follows.

,

where m is the load of the vehicle, D is the distance between both front tires of the vehicle, L is the distance between both tires on the side of the vehicle, and D _l is the lateral distance between the center of gravity of the vehicle and the front left tire of the vehicle, Lr is the longitudinal distance between the vehicle's center of gravity and the rear right tire of the vehicle, and h is the height of the vehicle's center of gravity.
8. The method of claim 7,
By the cost function calculation, the vehicle dynamics governing equation is formed as follows.

In the system for estimating the coordinates of the center of gravity of the vehicle and the axial load of the vehicle for performing the method of estimating the coordinates of the center of gravity of the vehicle of claim 8,
Vehicles with 4 tires;
an acceleration calculation unit installed in the vehicle to calculate an acceleration of the vehicle; and
and a real-time algorithm driving device for storing a load estimation algorithm including the vehicle dynamics governing equation and the acceleration-specific center of gravity coordinate data;
Each of the plurality of tires installed in the vehicle by substituting the three-dimensional coordinates of the vehicle's center of gravity calculated using the vehicle's load and the vehicle's acceleration and the center of gravity coordinate data for each acceleration into the vehicle dynamics governing equation Axial weight estimation system of a vehicle, characterized in that for calculating the real-time load of.

Images