KR102656131B1 - Device and method for detecting load of a truck - Google Patents

Abstract

The present invention relates to an apparatus and method for detecting the load of a truck, and includes a plurality of sensors that detect the inclination angle of a plurality of leaf springs installed in a truck, each detecting the period of a pulse that is an output of the sensors, and a spring coefficient of the leaf spring. It may include a control unit that converts the inclination angle detection results of each sensor into a load value and then detects the load by calculating the total of the load values, and a display unit that displays the detection result of the control unit.

Description

Device and method for detecting load of a truck}

The present invention relates to a load detection device and method for a cargo vehicle, and more specifically, to a load detection device and method that can check the total load and uneven loading of cargo.

In general, when a truck is loaded with cargo exceeding the load weight, there are problems such as damaging the road, causing traffic accidents, and increasing the emission of pollutants.

To prevent these problems, the loading weight of trucks is checked and regulated.

When a truck is running, the total weight of the truck can be estimated from the dynamic correlation between the vehicle's weight and engine output, and the loaded weight of the cargo can be estimated by considering the truck's own weight.

The technology related to detecting the loaded weight of a running vehicle is described in Patent Publication No. 10-2014-0103492 (Apparatus and method for measuring the loaded weight of a vehicle, published on August 27, 2014).

In the above published patent, the cargo loading weight is estimated using information from the vehicle's ECU.

However, since this algorithm cannot be used when the truck is stopped, various load weight detection devices or methods have been proposed.

For example, Patent No. 10-1531792 (Device for measuring the weight of a cargo vehicle, registered on June 19, 2015) describes a device that measures the weight of a cargo using tire air pressure.

This method of measuring weight using the air pressure of the tire had a problem in that errors could occur depending on the surrounding temperature or the condition of the tire.

As described above, various devices and methods for detecting the loading weight of a truck are known, but it has been difficult to determine whether the loading is uneven.

Unbalanced loading of cargo can cause accidents while driving a truck. Accidents at this time may include accidents involving falling cargo and rollover accidents due to shifting of the center of gravity of the truck due to unbalanced loading.

In this way, unbalanced loading causes various accidents, and there is a need to develop a device or method that can check whether or not the load is unevenly loaded.

The problem to be solved by the present invention in consideration of the above problems is to provide a device and method that can detect the load amount and quantify and display the degree of uneven loading of the load while using the inclination angle sensor applied to the existing leaf spring. there is.

A cargo vehicle load detection device according to one aspect of the present invention for solving the above technical problem includes a plurality of sensors that detect the inclination angles of a plurality of leaf springs installed in a truck, and a pulse period that is the output of the sensors. A control unit that detects each, estimates the spring coefficient of the leaf spring using Equation 1 below, converts the inclination angle detection result of each sensor into a load value, and then calculates the total of the load values to detect the load, and the control unit It may include a display unit that displays the detection result.

Equation 1

k' is the estimated spring constant

In an embodiment of the present invention, the control unit obtains the moment center, which is the center of gravity, through Equation 2 below using the load values detected by each of the sensors, and confirms the distance between the geometric center of the truck loading box and the moment center. This allows you to check whether the load is unevenly loaded.

Equation 2

X, Side load, F4 is load on the right rear wheel

In an embodiment of the present invention, the control unit determines the estimated spring constant (k') rather than the actual spring constant using Equation 3 derived using a function of the period (τ) of the pulse signal that is the output of the sensors. The load (F) can be calculated using

Equation 3

In addition, a method for detecting the load of a truck according to another aspect of the present invention includes the steps of a) receiving output pulse signals from sensors installed on each leaf spring of the truck from the control unit, and b) estimating the spring defined by Equation 1 below: It may include calculating the load acting on each sensor using a constant, and c) detecting the load by calculating the sum of the load values of each sensor.

Equation 1

In an embodiment of the present invention, after performing step c), d) obtain the moment center, which is the center of gravity, through Equation 2 below, and check the distance between the geometric center of the truck loading box and the moment center to determine the load bias. A step of checking whether or not it is loaded may be further included.

Equation 2

X, Side load, F4 is load on the right rear wheel

In an embodiment of the present invention, the control unit determines the estimated spring constant (k') rather than the actual spring constant using Equation 3 derived using a function of the period (τ) of the pulse signal that is the output of the sensors. The load (F) can be calculated using

Equation 3

The present invention detects the weight of the load using the inclination angle of the leaf spring detected using the inclination angle sensor, and also confirms the center position of the load to quantify the degree of uneven loading of the cargo, thereby preventing accidents due to poor cargo loading. There is a preventable effect.

1 is a block diagram of a load detection device for a truck according to a preferred embodiment of the present invention.
Figure 2 is an explanatory diagram for measuring load using the inclination angle of the leaf spring.
Figure 3 is a graph showing the relationship between pulse wave output and inclination angle of the first to fourth sensors.
Figure 4 is a graph showing the relationship between the average value of the sensor pulse period of the first to fourth sensors (FLS, FRS, RLS, and RRS) with respect to the total weight loaded on the vehicle.
Figure 5 is a graph interpreting the mathematical equation.
Figure 6 is a graph showing the relationship between the load value detected by the first to fourth sensors (FLS, FRS, RLS, and RRS) and the actual weight of the loaded object.
FIG. 7 is a graph comparing the sum of load values detected by each of the first to fourth sensors (FLS, FRS, RLS, and RRS) shown in FIG. 6 and the actual load.
Figures 8 and 9 are graphs of the error weight and error rate of the estimated load relative to the applied load, respectively.

In order to fully understand the configuration and effects of the present invention, preferred embodiments of the present invention will be described with reference to the attached drawings. However, the present invention is not limited to the embodiments disclosed below, and may be implemented in various forms and various changes may be made. However, the description of this embodiment is provided to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the present invention of the scope of the invention. In the attached drawings, components are shown enlarged in size for convenience of explanation, and the proportions of each component may be exaggerated or reduced.

Terms such as 'first' and 'second' may be used to describe various components, but the components should not be limited by the above terms. The above terms may be used only for the purpose of distinguishing one component from another. For example, the 'first component' may be named 'the second component' without departing from the scope of the present invention, and similarly, the 'second component' may also be named 'the first component'. You can. Additionally, singular expressions include plural expressions, unless the context clearly dictates otherwise. Unless otherwise defined, terms used in embodiments of the present invention may be interpreted as meanings commonly known to those skilled in the art.

Figure 1 is a configuration diagram of a load detection device for a truck according to a preferred embodiment of the present invention.

Referring to Figure 1, the present invention is a first to fourth sensor (FLS, FRS, RLS, RRS) that periodically detects the inclination angle of each leaf spring applied to the truck from the beginning of loading the cargo on the truck until the cargo loading is completed. ) and the detection data of the first to fourth sensors (FLS, FRS, RLS, RRS) are processed to determine the similar spring constants of each leaf spring, and the first to fourth sensors (FLS, FRS, RLS, RRS) are processed. ), a control unit 10 that obtains the load for each position, determines the change in the weight of the load, and quantifies the degree of bias of the load by finding the relationship between the geometric center of the cargo box and the load of the load, and the total load detected by the control unit 10 It is configured to include a display unit 20 that displays information and degree of bias.

Hereinafter, the configuration and operation of the truck load detection device of the preferred embodiment of the present invention configured as described above will be described in more detail.

First, the first to fourth sensors (FLS, FRS, RLS, RRS) refer to the right front wheel sensor, left front wheel sensor, right rear wheel sensor, and left rear wheel sensor, respectively, and detect the inclination angle of the leaf spring applied to the corresponding wheel, respectively. Do it by doing it.

The first to fourth sensors (FLS, FRS, RLS, and RRS) are each used to monitor the leaf spring that bends depending on the weight (load) of the load during the loading process from the initial state before loading the load on the truck. Detect the angle.

Detection at this time may be performed at a set time period.

The angle information detected from the first to fourth sensors (FLS, FRS, RLS, RRS) is provided to the control unit 10, and the control unit 10 detects the weight of the load by converting the change in angle into a change in load. can do.

The control unit 10 may be a processor that executes a given program, and may include a memory that stores data from the first to fourth sensors (FLS, FRS, RLS, RRS), data being processed, and processing result data. .

The first to fourth sensors (FLS, FRS, RLS, RRS) are preferably installed on the edge of the leaf spring. This is because the most significant angle change occurs with respect to the bending of the leaf spring.

Figure 2 is an explanatory diagram for measuring load using the inclination angle of the leaf spring.

Referring to Figure 2, the displacement height (h) is determined by the distance (L) and the inclination angle (θ) between the center and the end of the leaf spring (1).

In other words, Equation 1 below is established.

In Equation 1 above, when the inclination angle (θ) is a sufficiently small value, the change in height (h) can be expressed as the product of the inclination angle (θ) and the distance (L).

In order to detect the load using the angle detected by each of the first to fourth sensors (FLS, FRS, RLS, and RRS), it is necessary to check the spring constant of the leaf spring.

The control unit 10 assumes the constant k of the leaf spring. In an actual vehicle, the spring constants of the leaf springs where the first to fourth sensors (FLS, FRS, RLS, and RRS) are located may differ.

In the present invention, assuming that the spring constants of the leaf springs are the same, the load (F) detected by the first to fourth sensors (FLS, FRS, RLS, RRS) can be expressed by Equation 2 below.

In Equation 2 above, k is the assumed spring constant, and θ ₀ is the inclination angle of the leaf spring measured when there is no load.

In order to obtain the load (F), the change in inclination angle (θ) must be detected, and the pulse wave period detected in each of the first to fourth sensors (FLS, FRS, RLS, and RRS) is analyzed by the control unit 10 to determine the first Obtain the inclination angles of the leaf springs where each of the to fourth sensors (FLS, FRS, RLS, and RRS) are located.

Figure 3 is a graph showing the relationship between pulse wave output and inclination angle of the first to fourth sensors.

In Figure 3, the y-axis represents the pulse period, and the pulse period is measured in the form of a frequency that is its reciprocal.

In this way, the control unit 10 can obtain the inclination angle of each leaf spring using the outputs of the first to fourth sensors (FLS, FRS, RLS, and RRS). However, since the exact value of the spring constant of the leaf spring is not known, it is not easy to detect the exact load (loaded weight).

In order to solve this problem, the present invention establishes a functional relationship between the pulse period and inclination angle, which are the outputs of the first to fourth sensors (FLS, FRS, RLS, and RRS), and proposes a method of predicting an accurate spring constant using this. do.

Equation 3 is an equation expressing the inclination angle (θ) as a function (g) of the period (τ) of the pulse signal that is the output of the first to fourth sensors (FLS, FRS, RLS, and RRS).

By substituting Equation 3 above into Equation 2 above, Equation 4 below can be obtained.

Since the output graphs of the first to fourth sensors (FLS, FRS, RLS, and RRS) confirmed in FIG. 3 show a relatively proportional correlation with positive angles, Equation 4 can be replaced with a linear relationship equation such as Equation 5 below. It can be organized as:

In Equation 5 above, k' is the estimated spring coefficient of the leaf spring.

Figure 4 is a graph showing the relationship between the average value of the sensor pulse period of the first to fourth sensors (FLS, FRS, RLS, and RRS) with respect to the total weight loaded on the vehicle.

Referring to FIG. 4, the average of the detection values of the first to fourth sensors (FLS, FRS, RLS, and RRS) is compared with the average of the detection values while loading a vehicle with a known weight, and a linear proportional relationship is shown.

In order to increase the accuracy of data, Equation 5 can be converted into a mathematical expression that reflects the experimental results of FIG. 4, which can be defined as Equation 6 below.

Ftest is the total weight of the load, which reflects the experimental value, and each constant is a correction value obtained from the experiment.

The result of Equation 6 above is expressed graphically as shown in Figure 5.

The results of FIG. 5 are very similar to the results of FIG. 4, which are actual experimental values. Using Equation 6 above, the leaf spring constant k' at the positions of the first to fourth sensors (FLS, FRS, RLS, RRS) is as follows. It can be expressed as Equation 7.

Using the spring constant of the leaf spring obtained in this way and Equation 5 above, if you only know the positions of the first to fourth sensors (FLS, FRS, RLS, RRS), you can obtain the load F at that position.

Figure 5 is a diagram showing the positions of the first to fourth sensors geometrically.

In Figure 5, F1 is the load at the first sensor (FLS) location, F2 is the load at the second sensor (FRS) location, F3 is the load at the third sensor (RLS) location, and F4 is the fourth sensor (RRS). Indicates the load at the location.

Additionally, the geometric center (C) can be known.

Figure 6 is a graph showing the relationship between the load value detected by the first to fourth sensors (FLS, FRS, RLS, and RRS) and the actual weight of the loaded object.

As shown, during initial loading, the 3rd sensor (RLS) and 4th sensor (RRS) installed at the rear of the vehicle compared to the 1st sensor (FLS) and 2nd sensor (FRS) installed at the front of the truck. It is confirmed that the change in load (actually the inclination angle of the leaf spring) is larger.

This is because the first sensor (FLS) and the second sensor (FRS) are already under load due to the weight of the engine, etc., and the leaf spring inclination angle on the rear wheel side changes significantly depending on the weight of the loaded load.

FIG. 7 is a graph comparing the sum of load values detected by each of the first to fourth sensors (FLS, FRS, RLS, and RRS) shown in FIG. 6 and the actual load.

Referring to FIG. 7, the sum of the detected load values of the first to fourth sensors is similar to the actual load without much difference, and therefore, it can be confirmed that the method of detecting the load using the previously estimated equations is accurate.

Figures 8 and 9 show the error weight and error rate of the estimated load with respect to the applied load, respectively.

In this way, the present invention can estimate the spring constant of an unknown leaf spring and detect an accurate load using the first to fourth sensors (FLS, FRS, RLS, RRS) using the estimated constant.

Taking this into account, the final equation is obtained as the force balance equation in Equation 8 and the moment balance equation in Equation 9.

In the above equation, W is the weight of the load, i is the sensor number, and r represents the distance of each sensor from the center (C).

Referring again to FIG. 5, the geometric center (C) indicated by (X0,Y0) and the moment center (M) indicated by (Xn, Yn) can be considered.

a is the length of axle, and b represents the distance between axles (wheel base). a and b are constant values that can be known from vehicle specifications.

The solution that satisfies the hydrostatic equilibrium conditions of Equations 8 and 9 above is as shown in Equation 10 below.

Considering Equation 10 above, the distance from the geometric center (C) to the moment center (M), which is the center of gravity of the load, can be obtained using the detection values of the first to fourth sensors (FLS, FRS, RLS, RRS). You can.

Y represents the geometric center (C) of the loading box in the vehicle's straight direction, Indicates the distance from the center (C).

Therefore, the degree of bias of the load can be detected using the difference between the geometric center (C) and the moment center (M).

That is, the control unit 10 can check not only the weight of the load but also whether the load is unevenly loaded, and display the confirmed result on the display unit 20.

Figure 8 is an example graph of the difference between the geometric center (C) and the moment center (M) in the straight direction of the vehicle when loading a load.

Referring to Figure 8, it can be seen that at the beginning of loading, the center of moment (M) is biased toward the rear wheel, and as loading continues, the center of moment (M) gets closer to the geometric center (C).

At this time, if the difference between the geometric center (C) and the moment center (M) is greater than a set value even after final loading, the control unit 10 may display a warning message on the display unit 20.

Figure 9 is an example graph of the difference between the geometric center (C) and the moment center (M) with respect to the rotation direction (X).

Referring to FIG. 9, at the beginning of loading, the loading state is biased to the right, and as loading continues, the center of moment (M) becomes closer to the geometric center (C), indicating an unbiased loading state.

If the difference between the geometric center (C) and the moment center (M) is greater than a set value even after final loading, the control unit 10 may display a warning message on the display unit 20.

The display unit 20 may be a display device installed in the vehicle or a separate display device, and may include an audio output unit for visual display and auditory display.

In this way, the present invention has the effect of preventing accidents due to unbalanced loading by checking the distance and direction between the geometric center of the loading box of the truck and the center of moment detected through sensors to ensure that the load is not unbalanced. .

Although embodiments according to the present invention have been described above, they are merely illustrative, and those skilled in the art will understand that various modifications and equivalent scope of embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the following claims.

10: control unit 20: display unit

Claims (6)

A plurality of sensors that detect the inclination angle of a plurality of leaf springs installed in the truck;
The cycle of the pulse that is the output of the sensors is detected, the spring coefficient of the leaf spring is estimated using Equation 1 below, the inclination angle detection result of each sensor is converted into a load value, and the total of the load values is calculated to determine the load amount. A control unit that detects; and
It includes a display unit that displays the detection result of the control unit,
The control unit,
The load (F) is calculated using the estimated spring constant (k') rather than the actual spring constant using Equation 3, which is derived using a function of the period (τ) of the pulse signal that is the output of the sensors. A load detection device for cargo trucks.

Equation 1

k' is the estimated spring constant
Equation 3
According to paragraph 1,
The control unit,
The moment center of gravity, which is the center of gravity, is obtained through Equation 2 below using the load values detected from each of the sensors, and the distance between the geometric center of the truck loading box and the moment center is checked to check whether the load is unevenly loaded. Load detection device.
Equation 2

X, Side load, F4 is load on the right rear wheel delete a) receiving output pulse signals from sensors installed on each leaf spring of the truck from the control unit;
b) calculating the load acting on each sensor using the estimated spring constant defined by Equation 1 below; and
c) including the step of detecting the load by calculating the sum of the load values of each sensor,
The control unit,
The load (F) is calculated using the estimated spring constant (k') rather than the actual spring constant using Equation 3, which is derived using a function of the period (τ) of the pulse signal that is the output of the sensors. A method of detecting the load of a cargo vehicle.
Equation 1

Equation 3
According to paragraph 4,
After performing step c) above,
d) A method of detecting the load of a truck further comprising the step of determining whether the load is unevenly loaded by determining the moment center, which is the center of gravity, through Equation 2 below, and checking the distance between the geometric center of the truck loading box and the moment center.
Equation 2

X, Side load, F4 is load on the right rear wheel delete

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