Method and device for estimating gradient based on weight distribution change of vehicle, electronic equipment, computer readable medium and vehicle

Abstract

The invention discloses a method and device for estimating gradient based on weight distribution change of a vehicle, electronic equipment, the vehicle and a computer readable medium. The method comprises the following steps: acquiring reference weight distribution of a vehicle with reference weight on a flat road; calculating the difference between the weight distribution of the vehicle on the ramps with different slope angles and the reference weight distribution as a theoretical weight distribution change; establishing a correction table according to the trend of the theoretical weight distribution change under different slope angles; real-time weight distribution of the vehicle on the ramp with the real-time slope angle is obtained; calculating a difference between the real-time weight distribution and the reference weight distribution as a real-time weight distribution change; and acquiring a real-time slope angle in the correction table according to the trend of the real-time weight distribution change. The method can simply and widely estimate the gradient.

Description

Method, device, electronic device, computer-readable medium, and vehicle for estimating slope based on weight distribution change of vehicle Technical Field

[0001] The present invention relates to the field of vehicle control, and in particular to a method, an apparatus, an electronic device, a computer-readable medium, and a vehicle for estimating a slope based on a change in weight distribution of a vehicle. Background Art

[0002] In vehicles, especially trucks, multiple load cells are typically installed between the vehicle chassis longitudinal beams and the cargo container to measure the container weight and vehicle payload. When measuring the container weight, the load cell reflects the force perpendicular to its measuring surface.

[0003] When a vehicle is on an inclined surface (slope) with a certain slope angle, the container weight is calculated by combining the component perpendicular to the sensor's measuring plane with the component parallel to the sensor's measuring plane. Because the component parallel to the sensor's measuring plane cannot affect the load cell's signal output, the weight measured by the load cell deviates from the actual container weight. To correct the weight measured by the load cell, the slope of the vehicle's location is required.

[0004] Prior art methods for estimating road slope based on vehicle longitudinal dynamics models are known. However, these methods are not suitable for stationary vehicles. In particular, when a vehicle is parked at a loading or unloading point, it is necessary to determine the slope at that point and, in turn, the weight correction factor for the load cell at that slope. This allows for real-time determination of the actual load weight during loading to prevent overloading.

[0005] Therefore, there is a need for a method of estimating slope that is also applicable to stationary vehicles.

[0006] Summary of the Invention

[0007] In view of this, embodiments of the present invention provide a method and apparatus for estimating a slope based on a change in weight distribution of a vehicle, which can estimate the slope in a simple and widely applicable manner.

[0008] To achieve the above object, according to one aspect of the present invention, a method for estimating slope based on changes in vehicle weight distribution is provided, wherein the weight distribution is obtained by a weighing sensor, and the method is characterized by comprising the following steps:

[0009] obtaining a reference weight distribution of a vehicle having a reference weight on a flat road;

[0010] calculating a difference between the weight distribution of the vehicle on slopes with different slope angles and the reference weight distribution as a theoretical weight distribution change;

[0011] Establishing a correction table based on the trend of the theoretical weight distribution change at different slope angles; obtaining the real-time weight distribution of the vehicle on the slope with the real-time slope angle;

[0012] calculating a difference between the real-time weight distribution and the reference weight distribution as a real-time weight distribution change;

[0013] The real-time slope angle is obtained from the correction table according to the trend of the real-time weight distribution change.

[0014] The concept of the present invention is that when a vehicle is traveling uphill, the weight of the container carried by the vehicle is placed more heavily on the rear end of the vehicle. Consequently, the weight distribution changes, with a decrease at the front end and an increase at the rear end. In other words, the weight distribution changes in a "downhill" pattern from the rear end to the front end, with this "downhill" pattern becoming steeper as the slope angle increases. Conversely, when the vehicle is traveling downhill, the weight distribution changes in an "uphill" pattern from the rear end to the front end. Therefore, by comparing the real-time weight distribution change with the theoretical weight distribution change at a known slope angle, the real-time slope angle can be determined.

[0015] The technical advantage of the method according to the present invention is that, in vehicles equipped with a measuring mechanism for determining weight distribution, the current grade can be easily estimated using the known container weight, even when the vehicle is parked. Furthermore, even during loading or unloading, the vehicle load can be determined in real time using the grade estimated while the vehicle is parked at the loading or unloading point.

[0016] According to the invention, the "reference weight of the vehicle" corresponds to the weight of the container carried by the vehicle, which is either derived from the sum of the weight distribution on a flat road or from an estimate of the container weight at a known gradient. The "weight distribution" corresponds to a plurality of weights detected by the vehicle's load cells, which only have components perpendicular to the measuring plane of the load cells, and no components parallel to this plane.

[0017] In a preferred embodiment, it is provided that

[0018] Establishing a first correction table based on a linear fitting gradient of a theoretical weight distribution change map, and establishing a second correction table based on the theoretical weight distribution change map, wherein the theoretical weight distribution change map reflects a corresponding relationship between a slope angle and the theoretical weight distribution change;

[0019] The real-time slope angle is obtained in the first correction table either based on the linear fitting gradient of the real-time weight distribution change, or in the second correction table based on the real-time weight distribution change.

[0020] According to the present invention, "linear fitting of the theoretical weight distribution change map" corresponds to performing a linear fit using the position of the weight distribution along the ramp as the abscissa and the magnitude of the weight distribution change as the ordinate. The direction of the weight distribution change is reflected either by the weight distribution change map itself or by the gradient of the linear fit of the weight distribution change map. This provides a specific calculation scheme for reflecting the direction of weight distribution change.

[0021] In a preferred embodiment, the vehicle's reference weight is calculated by obtaining a reference weight distribution of the vehicle, or the vehicle's reference weight distribution is calculated by obtaining a reference weight of the vehicle. This allows for more flexible application of the estimation method according to the present invention. Specifically, when the container weight is unknown, the vehicle's reference weight distribution is obtained on a flat road and the vehicle's reference weight is obtained by summing the weights. When the container weight is known, the reference weight distribution can be obtained based on the relative spatial positions of the weighing points and the vehicle's center of gravity. The former acquisition method is particularly suitable for obtaining the vehicle's reference weight distribution and calculating the vehicle's reference weight when the vehicle is unloaded and traveling on a flat road. The actual unloaded weight of the vehicle is determined before it is put into use in order to estimate the slope at the vehicle loading and unloading point and thereby determine the weight correction factor for that slope. Thus, the actual loaded weight is known in real time during loading to prevent overloading.

[0022] In a preferred embodiment, the weight distribution at different slope angles is calculated based on the relative spatial positions of multiple load cells used to determine weight distribution and the vehicle's center of gravity, as well as the reference weight. Based on vehicle structural dimensions, such as the load cell installation positions and the vehicle's center of gravity, the theoretical weight percentage supported by each load cell can be determined, thereby determining the weight supported by each load cell at different slope angles.

[0023] In the aforementioned preferred embodiment, weight distribution is calculated at different slope angles by grouping the multiple load cells in the direction of the ramp. Grouping according to the present invention equates the large number of load cells distributed across the measuring surface of the load cells to a smaller number of sensors arranged sequentially along a straight line in the direction of the ramp. This simplifies the planar weight distribution into a linear weight distribution, thereby reducing computational complexity.

[0024] In a preferred embodiment, the slope angles in the first correction table and the second correction table range from -45° to 45°. The slopes used for correction range from -45° to 45°, thereby covering most actual road slopes and leaving a margin.

[0025] In a preferred embodiment, if the fit quality of the linear gradient of the real-time weight distribution change exceeds a predetermined value, the first correction table is used to determine the current slope angle; otherwise, the second correction table is used to determine the current slope angle. The fit quality corresponds to the degree to which the distribution of the real-time weight distribution change approximates a straight line. For example, the mean square error or the sum of squared errors can be used to assess the fit quality. When the fit quality is high, the first correction table is used to reduce computational complexity; when the fit quality is low, the second correction table is used to ensure the accuracy of the slope estimation.

[0026] In a preferred embodiment, the current slope angle is determined by interpolation in the first correction table and / or the second correction table. Alternatively, the current slope angle is determined by single-parameter interpolation in the first correction table, and by multi-parameter interpolation in the second correction table. This allows for an estimate of the slope angle even when the slope angle step size in the first correction table and / or the second correction table is not precise enough.

[0027] According to another aspect of the present invention, there is provided an apparatus for estimating a slope based on a change in weight distribution of a vehicle, wherein the weight distribution is acquired by a weighing sensor, and the apparatus is characterized by comprising:

[0028] an acquisition module, the acquisition module being configured to acquire a reference weight distribution of a vehicle having a reference weight on a flat road, and the acquisition module being further configured to acquire a real-time weight distribution of the vehicle on a slope having a real-time slope angle;

[0029] a calculation module, the calculation module being configured to calculate a difference between a weight distribution of the vehicle on slopes having different slope angles and the reference weight distribution as a theoretical weight distribution change, and the calculation module being configured to calculate a difference between the real-time weight distribution and the reference weight distribution as a real-time weight distribution change;

[0030] An estimation module is used to establish a correction table based on the trend of theoretical weight distribution changes at different slope angles, and the estimation module is also used to obtain the real-time slope angle from the correction table based on the trend of the real-time weight distribution changes.

[0031] In a preferred embodiment, it is provided that the acquisition module comprises a plurality of weighing sensors for acquiring weight distribution.

[0032] According to another aspect of the present invention, there is provided an electronic device for estimating a slope based on a change in weight distribution of a vehicle, wherein the weight distribution is acquired by a weighing sensor, and the electronic device is characterized by comprising:

[0033] one or more processors;

[0034] a storage device for storing one or more programs,

[0035] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for estimating a slope based on a change in weight distribution of a vehicle according to the present invention.

[0036] According to another aspect of the present invention, a computer-readable medium is provided, on which a computer program is stored, wherein when the program is executed by a processor, the method for estimating a slope based on a change in weight distribution of a vehicle according to the present invention is implemented.

[0037] According to another aspect of the present invention, there is provided a vehicle having a plurality of load cells for acquiring weight distribution, wherein the vehicle has a device or electronic device for estimating a slope based on a change in weight distribution of the vehicle.

[0038] The advantages or beneficial effects described in terms of the method for estimating a slope based on a change in weight distribution of a vehicle according to the present invention also apply to the apparatus and electronic device for estimating a slope based on a change in weight distribution of a vehicle according to the present invention, as well as the computer-readable medium and vehicle according to the present invention.

[0039] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are provided for a better understanding of the present invention and are not intended to limit the present invention.

[0041] FIG1 is an exemplary application scenario of the method for estimating slope based on changes in vehicle weight distribution according to the present invention;

[0042] 2 is a schematic diagram of the main process of the method for estimating slope based on changes in vehicle weight distribution according to the present invention;

[0043] FIG3 is a schematic diagram of main modules of an apparatus for estimating a slope based on a change in weight distribution of a vehicle;

[0044] FIG4 is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following description of exemplary embodiments of the present invention is made in conjunction with the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding. These details should be considered as merely exemplary. Therefore, it should be appreciated by those skilled in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0046] Figure 1 illustrates an exemplary application scenario for the method for estimating slope based on changes in vehicle weight distribution according to the present invention. Vehicle 10, for example, is a loaded vehicle that is unloaded before being put into service and is about to be parked on an uphill slope with a slope of gradient α′ for loading. To obtain the vehicle load in real time, the slope needs to be estimated.

[0047] A sensor system consisting of six load cells is installed between the cargo container and the chassis longitudinal beams of vehicle 10. On the left side of the vehicle (m), load cells LC1, LC2, and LC3 are arranged from front to back. On the right side of the vehicle (n), load cells LC6, LC5, and LC4 are arranged from front to back. Load cells LC1 and LC6 are positioned opposite each other, LC2 and LC5 are positioned opposite each other, and LC3 and LC4 are positioned opposite each other. Each load cell can independently perform weighing, and the container weight G is obtained by summing the weighing results of all load cells.

[0048] In order to simplify the calculation, the six weighing sensors are divided into three groups in the direction of the ramp extension: the weighing sensors LC3 and LC4 are the first group, and the sum of the weights F3 and F4 they output constitutes the first weight F 34 , which is the weight of the rear of the container; weighing sensors LC2 and LC5 are the second group, and the sum of the weights F2 and F5 they output constitutes the second weight F 25 , which is the weight of the middle part of the container; weighing sensors LC1 and LC6 are the third group, and the sum of the weights F1 and F6 they output constitutes the third weight F 16 , which is the weight of the front of the container.

[0049] During the preparation for grade estimation, both the "unladen" and "flat road" conditions are checked. Specifically, if vehicle 10 is unladen before being put into use, only the "flat road" condition needs to be checked. When vehicle 10 is on a flat road before stopping at the uphill loading / unloading point shown in FIG1 , both conditions are met, and grade estimation is activated.

[0050] After activating the slope estimation, get the three weights F 34 、F 25 、F 16 , and sum to get the empty container weight G.

[0051] The theoretical weight F under no-load and on a slope with different slope angles α is calculated using formulas 1 to 3 based on the vehicle structure-related dimensional parameters a, b, c, and h. mn (m=3, 2, 1; n=4, 5, 6), that is, F 34 、F 25 and F 16 :

[0052]

[0053]

[0054]

[0055] Specifically, three theoretical weights, i.e., reference weights, are calculated using formulas 4 to 6 when the vehicle is unloaded and on a flat road. Right now

[0056]

[0057]

[0058]

[0059] Parameters a, b, and c represent the distances between each sensor group and the container's center of gravity along the ramp's extension direction, respectively. Parameter h represents the distance between the container's center of gravity and the load cell's measuring surface. The calculated slope angle α ranges from -45° to +45°, which sufficiently covers the range of slopes likely to occur in real-world conditions. The calculated slope angle α is incremented by 0.1°.

[0060] Next, at each slope angle α, calculate the theoretical weight F mn With reference weight The difference is the theoretical weight distribution change ΔF mn ,Right now and This gives the theoretical weight distribution change map ΔF mn (α), which reflects the slope angle α and the theoretical weight distribution change ΔF mn The corresponding relationship.

[0061] At each slope angle α, the theoretical weight distribution change ΔF is mapped 34 (α), ΔF 25 (α) and ΔF 16 (α) is used for linear fitting, wherein in the xy coordinate system used for linear fitting, the position of the weight distribution along the extension direction of the ramp is used as the abscissa and the value of the weight distribution change is used as the ordinate. The coordinates of the points to be fitted are (0, ΔF 34 (α))、(b,ΔF 25 (α))、(a+b,ΔF 16 (α)). Thus, the relationship between the slope angle α and the linear fitting gradient K of the theoretical weight distribution change map is obtained, and the relationship is stored as the first correction table (see Table 1). At the same time, the slope angle α and the theoretical weight distribution change map ΔF 34(α), ΔF 25 (α) and ΔF 16 The relationship of (α) is stored as the second correction table (see Table 2).

[0062] Slope angle α linear fitting gradient K-45°K1-44.9°K2…………44.9°Kp-1

[0063] 45°Kp

[0064] Table 1 First revised table

[0065]

[0066] Table 2 First Correction Table

[0067] When the vehicle 10 is parked at the uphill loading and unloading point in FIG1 and before being loaded, the real-time slope angle α′ is estimated using the first correction table or the second correction table in the following manner:

[0068] Get the real-time weight F' under no-load mn , that is, F′ 34 , F′ 25 , F′ 16 , and calculate the real-time weight F′ mn With reference weight The difference between the two is obtained, and the real-time weight distribution change ΔF′ is obtained. mn ,Right now

[0069] Real-time weight distribution change ΔF′ 34 , ΔF′ 25 and ΔF′ 16 A linear fitting is performed, wherein a linear fitting gradient K' and a fitting error e are obtained. The fitting error e is, for example, a mean square error or a sum of squared errors, etc., which are known metrics for reflecting the quality of the fitting.

[0070] If the fitting error e is less than or equal to the error threshold, the real-time slope angle α′ is obtained by looking up the linear fitting gradient K′ in the first correction table. Alternatively, when the linear fitting gradient K′ is between two K values ​​in the first correction table, the real-time slope angle α′ can be obtained by interpolation.

[0071] If the fitting error e is greater than or equal to the error threshold, the real-time weight distribution change ΔF′ is used in the second correction table. 34 , ΔF′ 25 and ΔF′ 16 The table is consulted to obtain the respective real-time slope angles α′. Optionally, when the three real-time weight distributions change ΔF′ 34 , ΔF′ 25 and ΔF′ 16When the values ​​are not in the same row in the second correction table of Table 2, the offset interpolation method can be used, that is, the three real-time weight distribution changes ΔF′ are comprehensively considered. 34 , ΔF′ 25 and ΔF′ 16 Interpolation is performed to obtain the real-time slope angle α′.

[0072] Thus, before the vehicle 10 is loaded, the slope angle α′ of the uphill slope at the loading and unloading point is known, and the weight correction coefficient cos(α′) at this slope is obtained.

[0073] During loading, the formula F C =(F′ 34 +F′ 25 +F′ 16 ) / cos(α′) to obtain the container weight F in real time C , to prevent overloading.

[0074] When loading is complete, the loaded container weight is known. The above method is then used to generate new first and second correction tables based on the loaded container weight. When vehicle 10 is at another location, the new correction tables can be used to estimate the real-time slope angle at that location. This is particularly advantageous for the next loading or unloading of vehicle 10, as it is necessary to estimate the slope at the new loading or unloading point in order to obtain the container weight in real time during loading or unloading.

[0075] Optionally, but not shown, when vehicle 10 is on a sloping road, to simplify the planar weight distribution into a linear weight distribution and reduce computational complexity, the three load cells LC1, LC2, and LC3 on the left side m can be grouped together, and the three load cells LC4, LC5, and LC6 on the right side n can be grouped together. Furthermore, when vehicle 10 is on a road that slopes both left and right and front and back, the front and back slope angle can be estimated using the embodiment shown in FIG1 , while the left and right slope angles can be estimated simultaneously using the aforementioned optional grouping method.

[0076] It is understood that the number of load cells is not limited to six and can be more or less, for example, nine, where an additional load cell is respectively installed between load cells LC1 and LC6, between load cells LC2 and LC5, and between load cells LC3 and LC4 of vehicle 10, or three, where only the aforementioned three additional load cells are arranged. The aforementioned preferred arrangements of nine and three load cells can still utilize the aforementioned method of estimating slope based on weight distribution changes determined by three groups of load cells.

[0077] According to the present invention, a method for estimating slope based on changes in vehicle weight distribution is proposed, wherein the weight distribution is obtained by a weighing sensor. FIG2 shows a schematic diagram of the main process of the method, which includes the following steps:

[0078] Step S201: Obtaining a reference weight distribution of a vehicle with a reference weight G on a flat road

[0079] Optionally, obtain a reference weight distribution of the vehicle And calculate the reference weight G of the vehicle or obtain the reference weight G of the vehicle and calculate the reference weight distribution of the vehicle

[0080] Step S202: Calculate the weight distribution F of the vehicle on the slope with different slope angles α mn With the reference weight distribution The difference is the theoretical weight distribution change ΔF mn .

[0081] Optionally, the weight distribution at different slope angles α is calculated based on the relative spatial positions between a plurality of load cells used to determine the weight distribution and the center of gravity of the vehicle, as well as the reference weight G. In particular, the weight distribution at different slope angles α is calculated by grouping the plurality of load cells in the direction in which the slope extends.

[0082] Step S203: The theoretical weight distribution changes ΔF mn A correction table is established for the strike direction at different slope angles α.

[0083] Alternatively, ΔF is mapped from the theoretical weight distribution change mn The linear fitting gradient K of (α) establishes the first correction table K(α), and the theoretical weight distribution change map ΔF mn (α) Establishing a second correction table, wherein the theoretical weight distribution change map ΔF mn (α) reflects the slope angle α and the theoretical weight distribution change ΔF mn The corresponding relationship.

[0084] Optionally, the slope angle range in the first correction table and the second correction table is from -45° to 45°.

[0085] Step S204: Obtain the real-time weight distribution F′ of the vehicle on the slope with the real-time slope angle α′ mn .

[0086] Step S205: Calculate the real-time weight distribution F′ mn With the reference weight distribution The difference is taken as the real-time weight distribution change ΔF′mn .

[0087] Step S206: According to the real-time weight distribution change ΔF′ mn The real-time slope angle α′ is obtained from the correction table.

[0088] Alternatively, either according to the real-time weight distribution change ΔF′ mn The linear fitting gradient K′ of the first correction table K(α) is used to obtain the real-time slope angle α′, or the real-time weight distribution change ΔF′ mn The real-time slope angle α′ is obtained from the second correction table.

[0089] Alternatively, if the real-time weight distribution changes ΔF′ mn If the fitting quality of the linear fitting gradient K′ is higher than a predetermined value, the first correction table is used to obtain the current slope angle; otherwise, the second correction table is used to obtain the current slope angle.

[0090] Optionally, the current slope angle is obtained by interpolation in the first correction table and / or the second correction table.

[0091] According to the present invention, a device 300 for estimating slope based on a change in weight distribution of a vehicle is also proposed, wherein the weight distribution is obtained by a weighing sensor. FIG3 shows a schematic diagram of the main modules of the device 300, which includes:

[0092] The acquisition module 301 is used to obtain the reference weight distribution of the vehicle with the reference weight G. The acquisition module is also used to acquire the real-time weight distribution F′ of the vehicle on a slope with a real-time slope angle α′. mn ;

[0093] Optionally, the acquisition module 301 includes a plurality of weighing sensors for obtaining weight distribution.

[0094] A calculation module is used to calculate the weight distribution F of the vehicle on a slope with different slope angles α. mn With the reference weight distribution The difference is the theoretical weight distribution change ΔF mn , and the calculation module is used to calculate the real-time weight distribution F′ mn With the reference weight distribution The difference is taken as the real-time weight distribution change ΔF′ mn ;

[0095] Estimation module 303, the estimation module 303 is used to estimate the theoretical weight distribution change ΔF mnA correction table is established for the direction under different slope angles α, and the estimation module is also used to change the weight distribution ΔF′ according to the real-time weight distribution mn The real-time slope angle α′ is obtained from the correction table.

[0096] 4, which shows a schematic diagram of a computer system 400 suitable for implementing a terminal device according to an embodiment of the present invention. The terminal device shown in FIG4 is merely an example and should not limit the functionality and scope of use of the embodiment of the present invention.

[0097] As shown in FIG4 , a computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage unit 408 into a random access memory (RAM) 403. Various programs and data required for the operation of the system 400 are also stored in the RAM 403. The CPU 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0098] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 408 including a hard disk; and a communication section 409 including a network interface card such as a LAN card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read therefrom can be installed into the storage section 408 as needed.

[0099] In particular, according to the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above-mentioned functions defined in the system of the present invention are performed.

[0100] It should be noted that the computer-readable medium described in the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0101] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0102] The modules described in the embodiments of the present invention may be implemented in software or hardware. The modules described may also be provided in a processor. For example, a processor may be described as including an acquisition module, a calculation module, and an estimation module. The names of these modules do not, in some cases, limit the modules themselves. For example, an acquisition module may also be described as an "acquisition module."

[0103] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiment, or may exist independently and not be incorporated into the device. The computer-readable medium carries one or more programs, and when executed by the device, causes the device to: obtain a reference weight distribution of a vehicle having a reference weight on a flat road; calculate the difference between the weight distribution of the vehicle on slopes with different slope angles and the reference weight distribution as a theoretical weight distribution change; establish a correction table based on the direction of the theoretical weight distribution change at different slope angles; obtain a real-time weight distribution of the vehicle on a slope with a real-time slope angle; calculate the difference between the real-time weight distribution and the reference weight distribution as a real-time weight distribution change; and obtain the real-time slope angle from the correction table based on the direction of the real-time weight distribution change.

[0104] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for estimating a slope based on a change in weight distribution of a vehicle, wherein: The weight distribution is obtained by a weighing sensor, which is characterized by comprising the following steps: Get the reference weight distribution of a vehicle with a reference weight (G) on a flat road Calculate the weight distribution (F) of the vehicle on a slope with different slope angles (α) mn ) and the reference weight distribution The difference between the theoretical weight distribution change (ΔF mn ); The theoretical weight distribution change (ΔF mn ) establishes a correction table for the strike direction at different slope angles (α); Obtain the real-time weight distribution (F′) of the vehicle on a slope with a real-time slope angle (α′) mn ); Calculate the real-time weight distribution (F′ mn ) and the reference weight distribution The difference between the two is taken as the real-time weight distribution change (ΔF′ mn ); According to the real-time weight distribution change (ΔF′ mn ) is used to obtain the real-time slope angle (α′) in the correction table.

2. The method according to claim 1, characterized in that Mapped by theoretical weight distribution change (ΔF mn (α)) to establish the first correction table (K(α)), and the theoretical weight distribution change map (ΔF mn (α)) establishes a second correction table, wherein the theoretical weight distribution change map (ΔF mn (α) reflects the slope angle (α) and the theoretical weight distribution change (ΔF mn )’s corresponding relationship; Either according to the real-time weight distribution change (ΔF′ mn ) is linearly fitted with the gradient (K′) to obtain the real-time slope angle (α′) in the first correction table (K(α)), or according to the real-time weight distribution change (ΔF′ mn ) The real-time slope angle (α′) is obtained in the second correction table.

3. The method according to claim 1, characterized in that The reference weight (G) of the vehicle is obtained by Calculated, or reference weight distribution of the vehicle It is calculated by obtaining the reference weight (G) of the vehicle.

4. The method according to claim 1, characterized in that: The weight distribution under different slope angles (α) is calculated depending on the relative spatial positions between a plurality of weighing sensors used to obtain the weight distribution and the center of gravity of the vehicle and the reference weight (G).

5. The method according to claim 3, characterized in that: The weight distribution is calculated at different slope angles (α) in a manner that the plurality of load cells are grouped in a slope extension direction.

6. The method according to any one of claims 2 to 5, characterized in that The slope angle range in the first correction table and the second correction table is from -45° to 45°.

7. The method according to any one of claims 2 to 5, characterized in that If the real-time weight distribution changes (ΔF′ mn ) is higher than a predetermined value, the first correction table is used to obtain the current slope angle, otherwise the second correction table is used to obtain the current slope angle.

8. The method according to any one of claims 2 to 5, characterized in that The current slope angle is obtained by interpolation in the first correction table and / or the second correction table.

9. A device for estimating a slope based on a change in weight distribution of a vehicle, wherein: The weight distribution is obtained by a weighing sensor, which is characterized by including: An acquisition module, the acquisition module is used to acquire a reference weight distribution of a vehicle with a reference weight (G) on a flat road The acquisition module is also used to acquire the real-time weight distribution (F′) of the vehicle on a slope with a real-time slope angle (α′). mn ); A calculation module, the calculation module is used to calculate the weight distribution (F) of the vehicle on a slope with different slope angles (α) mn ) and the reference weight distribution The difference between the theoretical weight distribution change (ΔF mn ), and the calculation module is used to calculate the real-time weight distribution (F′ mn ) and the reference weight distribution The difference between the two is taken as the real-time weight distribution change (ΔF′ mn ); An estimation module is used to estimate the theoretical weight distribution change (ΔF mn ) establishes a correction table at different slope angles (α), and the estimation module is also used to establish a correction table according to the real-time weight distribution change (ΔF′ mn ) is used to obtain the real-time slope angle (α′) in the correction table.

10. The device according to claim 9, characterized in that The acquisition module includes a plurality of weighing sensors for acquiring weight distribution.

11. An electronic device for estimating a slope based on a change in weight distribution of a vehicle, wherein: The weight distribution is obtained by a weighing sensor, which is characterized by including: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 8.

12. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

13. A vehicle having a plurality of weighing sensors for obtaining weight distribution, characterized in that: The vehicle has the device according to claim 9 or the electronic device according to claim 11 .

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