Vehicle torque control method and device based on vehicle driving road surface

Abstract

The present disclosure provides a vehicle torque control method and device based on the vehicle driving road surface. The method includes: obtaining a target image of the target vehicle driving road surface at the current moment; determining the target category of the target vehicle driving road surface at the current moment based on the target image, and determining the torque change amplitude and torque distribution ratio corresponding to the target category; obtaining the control torque sequence of the target vehicle at multiple moments before the current moment and the vehicle feedback information corresponding to the control torque sequence; judging the torque change trend of the target vehicle based on the control torque sequence and the vehicle feedback information; predicting the target control torque of the target vehicle at the current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, and controlling the target vehicle at the current moment based on the target control torque and the torque distribution ratio. The above technical means are adopted to solve the problems of insufficient power, vehicle shaking and slipping caused by the vehicle torque control in the prior art not taking into account the vehicle driving road surface.

Description

Technical Field

[0001] The present disclosure relates to the field of automobile technology, and in particular to a vehicle torque control method and device based on a vehicle driving road surface. Background Art

[0002] The existing vehicle torque control algorithm is mainly based on engine speed and vehicle speed for control, and the torque distribution ratio can only be set in advance. This control method only considers some state parameters of the vehicle and does not consider the road surface on which the vehicle is driving. The vehicle torque control and torque distribution ratio are different under different driving surfaces. Because the existing vehicle torque control algorithm does not consider the vehicle's driving surface, the vehicle is prone to problems such as insufficient power, vehicle shaking and slipping, which affects the stability and safety of driving. Summary of the invention

[0003] In view of this, the embodiments of the present disclosure provide a vehicle torque control method, device, electronic device and storage medium based on the vehicle's driving surface, so as to solve the problems in the prior art that the vehicle torque control does not take the vehicle's driving surface into consideration, resulting in the vehicle being prone to insufficient power, vehicle shaking and slipping.

[0004] In a first aspect of an embodiment of the present disclosure, a vehicle torque control method based on a vehicle driving surface is provided, comprising: obtaining a target image of the target vehicle driving surface at a current moment; determining a target category of the target vehicle driving surface at a current moment based on the target image, and determining a torque change amplitude and a torque distribution ratio corresponding to the target category, wherein the torque change amplitude represents a minimum amplitude by which the target vehicle increases or decreases the control torque on a road surface of the target category; obtaining a control torque sequence of the target vehicle at multiple moments before a current moment and vehicle feedback information corresponding to the control torque sequence; judging a torque change trend of the target vehicle based on the control torque sequence and the vehicle feedback information, wherein the torque change trend represents an increase or decrease in the control torque of the target vehicle; predicting a target control torque of the target vehicle at a current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, and controlling the target vehicle at the current moment based on the target control torque and the torque distribution ratio.

[0005] According to a second aspect of an embodiment of the present disclosure, a vehicle torque control device based on a vehicle driving surface is provided, comprising: a first acquisition module, configured to acquire a target image of a target vehicle driving surface at a current moment; a determination module, configured to determine a target category of a target vehicle driving surface at a current moment based on the target image, and determine a torque change amplitude and a torque distribution ratio corresponding to the target category, wherein the torque change amplitude represents a minimum amplitude by which the target vehicle increases or decreases the control torque in a road of the target category; a second acquisition module, configured to acquire a control torque sequence of the target vehicle at multiple moments before a current moment and vehicle feedback information corresponding to the control torque sequence; a judgment module, configured to judge a torque change trend of the target vehicle based on the control torque sequence and the vehicle feedback information, wherein the torque change trend represents an increase or decrease in the control torque of the target vehicle; and a prediction module, configured to predict a target control torque of the target vehicle at a current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, and control the target vehicle at the current moment based on the target control torque and the torque distribution ratio.

[0006] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0007] According to a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any one of the methods described above are implemented.

[0008] Compared with the prior art, the beneficial effects of the disclosed embodiment include at least: determining the target category of the target vehicle's driving road at the current moment based on the target image of the target vehicle's driving road at the current moment, and determining the torque change amplitude and torque distribution ratio corresponding to the target category; judging the torque change trend of the target vehicle based on the control torque sequence and vehicle feedback information; predicting the target control torque of the target vehicle at the current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence; and controlling the target vehicle at the current moment based on the target control torque and the torque distribution ratio. Therefore, the above-mentioned technical means can be used to solve the problem that the vehicle torque control in the prior art does not take into account the vehicle's driving road surface, which leads to the problem of insufficient power, vehicle shaking and slipping of the vehicle, thereby reducing the number of vehicle power shortages, vehicle shaking and slipping, and ensuring the safety of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0010] Figure 1 is a flow chart of a vehicle torque control method based on a vehicle driving road surface provided by an embodiment of the present disclosure;

[0011] Figure 2 is a flow chart of a vehicle torque control method provided by an embodiment of the present disclosure;

[0012] Figure 3 is a structural schematic diagram of a vehicle torque control device based on a vehicle driving road surface provided by an embodiment of the present disclosure;

[0013] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0014] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0015] Figure 1 It is a flow chart of a vehicle torque control method based on the vehicle driving road surface provided by an embodiment of the present disclosure. Figure 1 The vehicle torque control method based on the vehicle driving road surface can be executed by a computer or a server, or a processor provided on the computer or the server, or software on a computer or a common server. The vehicle torque control method based on the vehicle driving road surface includes:

[0016] S101, obtaining a target image of the road surface on which the target vehicle is traveling at the current moment;

[0017] S102, determining the target category of the road surface on which the target vehicle is traveling at the current moment based on the target image, and determining the torque change amplitude and torque distribution ratio corresponding to the target category, wherein the torque change amplitude represents the minimum amplitude of increasing or decreasing the control torque of the target vehicle on the road surface of the target category;

[0018] S103, obtaining a control torque sequence of the target vehicle at multiple moments before the current moment and vehicle feedback information corresponding to the control torque sequence;

[0019] S104, judging a torque change trend of the target vehicle according to the control torque sequence and the vehicle feedback information, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque;

[0020] S105, predicting the target control torque of the target vehicle at the current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, and controlling the target vehicle at the current moment according to the target control torque and the torque distribution ratio.

[0021] The target categories of road surfaces include: dry road surface, slippery road surface, snowy road surface, gravel road surface, and muddy road surface. Dry road surface is the most common road surface, which is a road surface without rain; slippery road surface is often a road surface after rain, snowy road surface is a road surface after snow; gravel road surface is a road surface covered with gravel; muddy road surface is a road surface full of mud, which is often a dirt road surface after rain or melting ice and snow.

[0022] Based on the target image of the target vehicle driving road at the current moment, the target category of the target vehicle driving road at the current moment is determined, and each target category corresponds to a torque change amplitude and torque distribution ratio, and then the torque change amplitude and torque distribution ratio corresponding to the target category are determined. The control torque sequence is a plurality of control torques of the target vehicle at multiple moments before the current moment, and each control torque corresponds to a piece of feedback information in the vehicle feedback information (after each control torque controls the target vehicle, the feedback information of the control torque will be received), and each piece of feedback information includes: the number of vehicle jitters and the duration of jitters, the number of vehicle slips and the distance of slips, the vehicle acceleration performance change information, the vehicle speed change information, and the vehicle driving engine temperature change information. According to the control torque sequence and the vehicle feedback information, the torque change trend of the target vehicle to increase or decrease the control torque is judged. Based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, the target control torque of the target vehicle at the current moment is predicted. If the torque change trend indicates that the control torque should be increased, the control torque of the target vehicle can be increased according to the torque change amplitude, and if the torque change trend indicates that the control torque should be reduced, the control torque of the target vehicle can be reduced according to the torque change amplitude. The target control torque is the total control torque of the front and rear axles of the target vehicle. The control torque distributed on the front and rear axles of the target vehicle can be calculated based on the target control torque and the torque distribution ratio.

[0023] According to the technical solution provided by the embodiment of the present disclosure, a target image of the road surface on which the target vehicle is traveling at the current moment is obtained; based on the target image, the target category of the road surface on which the target vehicle is traveling at the current moment is determined, and the torque change amplitude and torque distribution ratio corresponding to the target category are determined, wherein the torque change amplitude indicates the minimum amplitude of the target vehicle increasing or decreasing the control torque in the road surface of the target category; the control torque sequence of the target vehicle at multiple moments before the current moment and the vehicle feedback information corresponding to the control torque sequence are obtained; based on the control torque sequence and the vehicle feedback information, the torque change trend of the target vehicle is judged, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque; based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, the target control torque of the target vehicle at the current moment is predicted, and the target vehicle is controlled at the current moment according to the target control torque and the torque distribution ratio. The above technical means can be used to solve the problems of insufficient power, vehicle shaking and slipping caused by the vehicle torque control in the prior art not considering the road surface on which the vehicle is traveling, thereby reducing the number of vehicle insufficient power, vehicle shaking and slipping, and ensuring the safety of users.

[0024] Furthermore, a target category of the road surface on which the target vehicle is traveling at the current moment is determined based on the target image, including: obtaining road surface features corresponding to various road surfaces such as dry highway road surfaces, wet highway road surfaces, snowy road surfaces, gravel road surfaces and muddy road surfaces; extracting target road surface features of the target image; calculating the Euclidean distance between the target road surface features and the road surface features of various road surfaces; and determining the road surface with the smallest corresponding Euclidean distance as the target category of the road surface on which the target vehicle is traveling at the current moment.

[0025] Furthermore, pavement features corresponding to various road surfaces such as dry road surfaces, wet and slippery road surfaces, snowy road surfaces, gravel road surfaces and muddy road surfaces are obtained, including: obtaining multiple pavement images of various road surfaces such as dry road surfaces, wet and slippery road surfaces, snowy road surfaces, gravel road surfaces and muddy road surfaces; extracting pavement features of each pavement image using a hash algorithm; calculating the average of pavement features of multiple pavement images of each pavement type, so as to fuse the pavement features corresponding to each pavement type.

[0026] Multiple road images of various road surfaces are pre-set, and the road features of the road images can be any commonly used image features of the road images. For example, if the road features are hash features, the road features of each road image are extracted using a hash algorithm, and the road features of various road surfaces are obtained by fusing the road features of multiple road images of various road surfaces. The hash features of the target image are extracted using the hash algorithm as the target road features.

[0027] Extracting the target road surface feature of the target image is to extract the image feature of the target image. The Euclidean distance between the target road surface feature and each road surface feature is calculated. The smaller the Euclidean distance between the target road surface feature and a road surface feature, the closer the target road surface feature and the road surface feature are, and the more similar the target categories of the target image and the road surface image corresponding to the road surface feature are. Therefore, the road surface with the smallest corresponding Euclidean distance can be determined as the target category of the road surface on which the target vehicle is traveling at the current moment.

[0028] Further, the torque variation amplitude and torque distribution ratio corresponding to the target category are determined, including: when the target category is a snowy road surface, the torque variation amplitude is determined to be a first variation amplitude, and the torque distribution ratio is determined to be a first distribution ratio; when the target category is a slippery road surface, the torque variation amplitude is determined to be a second variation amplitude, and the torque distribution ratio is determined to be a second distribution ratio; when the target category is a dry road surface, the torque variation amplitude is determined to be a third variation amplitude, and the torque distribution ratio is determined to be a third distribution ratio; when the target category is a gravel road surface, the torque variation amplitude is determined to be a fourth variation amplitude, and the torque distribution ratio is determined to be a fourth distribution ratio; when the target category is a muddy road surface, the torque variation amplitude is determined to be a fifth variation amplitude, and the torque distribution ratio is determined to be a fifth distribution ratio.

[0029] The adhesion coefficient and friction resistance between the vehicle and the road surface are different for different road surfaces, so the embodiment of the present application sets corresponding torque variation amplitudes and torque distribution ratios for various road surfaces, so that the vehicle can better adapt to the road conditions of various road surfaces.

[0030] In some embodiments, the various change amplitudes are, from small to large, the first change amplitude, the second change amplitude, the third change amplitude, the fourth change amplitude, and the fifth change amplitude. For example, because the adhesion coefficient between the vehicle and the road surface is the smallest on a snowy road surface, in order to reduce the side slip of the vehicle, the first change amplitude corresponding to the snowy road surface is the smallest, that is, the vehicle control torque should be adjusted slowly with the smallest amplitude. Because the adhesion coefficient between the vehicle and the road surface is the largest on a muddy road surface, the possibility of the vehicle side slipping is relatively small, and the fifth change amplitude corresponding to the muddy road surface is the largest, and the vehicle control torque can be adjusted quickly with the largest amplitude at this time.

[0031] In some embodiments, the distribution ratio can be recorded as the ratio of the torque distributed on the front axle and the rear axle of the vehicle, and the various distribution ratios are the first distribution ratio, the second distribution ratio, the third distribution ratio, the fourth distribution ratio and the fifth distribution ratio from large to small. For example, on a snowy road, because the adhesion coefficient between the vehicle and the road is the smallest, the vehicle is prone to side slip, the vehicle friction resistance is also the smallest, and the vehicle is easy to accelerate, so the torque distributed on the front axle of the vehicle should be larger, while the torque distributed on the rear axle of the vehicle should be smaller, and the first distribution ratio corresponding to the snowy road is the largest (relatively speaking, a larger torque distributed on the rear axle of the vehicle is conducive to vehicle acceleration, and a larger torque distributed on the front axle of the vehicle is conducive to vehicle direction control). On a muddy road, because the adhesion coefficient between the vehicle and the road is the largest, the vehicle is not prone to side slip, the vehicle friction resistance is also the largest, and the vehicle is not easy to accelerate, so the torque distributed on the front axle of the vehicle should be smaller, while the torque distributed on the rear axle of the vehicle should be larger, and the fifth distribution ratio corresponding to the muddy road is the smallest.

[0032] Furthermore, judging the torque change trend of the target vehicle based on the control torque sequence and the vehicle feedback information includes: the control torque sequence includes a plurality of control torques, each control torque corresponds to a piece of feedback information in the vehicle feedback information; determining a total score corresponding to each piece of feedback information; taking the control torque as an independent variable and the score corresponding to the control torque as a dependent variable, performing fitting processing on the plurality of control torques and the score corresponding to each control torque to obtain a fitting result; and determining the torque change trend of the target vehicle based on the fitting result.

[0033] Further, the total score corresponding to each piece of feedback information is determined, including: each piece of feedback information, including: the number of vehicle shakes and the duration of shakes, the number of vehicle slips and the distance of slips, the vehicle acceleration performance change information, the vehicle speed change information and the vehicle drive engine temperature change information; each piece of feedback information is scored from the following dimensions; the number of vehicle shakes and the duration of shakes, the number of vehicle slips and the distance of slips, the vehicle acceleration performance change information, the vehicle speed change information and the vehicle drive engine temperature change information; the multiple scores obtained by scoring each piece of feedback information are weightedly summed to obtain the total score corresponding to each feedback information.

[0034] The greater the value of the number of vehicle jitters and jitter duration, the number of vehicle skids and the skidding distance, the lower the corresponding score. The vehicle acceleration performance change information is a description of the acceleration performance of the target vehicle, which can be information such as the acceleration size of the target vehicle. The greater the vehicle acceleration, the higher the corresponding score; the vehicle speed change information is a description of the target vehicle speed change performance, which can be information such as the target vehicle speed change time and the speed increase size. The shorter the vehicle speed change time and the greater the speed increase, the higher the corresponding score; the vehicle drive engine temperature change information is a description of the target vehicle drive engine temperature change, which can be information such as the target vehicle drive engine temperature size. The lower the vehicle temperature, the higher the corresponding score. According to the above scoring criteria, the seven dimensions of the vehicle jitter number and jitter duration, the vehicle skid number and skidding distance, the vehicle acceleration performance change information, the vehicle speed change information, and the vehicle drive engine temperature change information of each feedback information are scored to obtain the scores of the seven dimensions of each feedback information. The weight corresponding to each dimension is set, and according to the weight corresponding to each dimension, the multiple scores of each feedback information are summed to obtain the total score corresponding to each feedback information.

[0035] The control torque is taken as the independent variable, and the score corresponding to the control torque is taken as the dependent variable. The fitting result obtained by fitting can be regarded as a linear expression. When the coefficient in front of the independent variable in the fitting result is greater than zero, it is considered that the torque change trend of the target vehicle is to reduce the control torque. When the coefficient in front of the independent variable in the fitting result is less than zero, it is considered that the torque change trend of the target vehicle is to increase the control torque.

[0036] Figure 2 is a flow chart of a vehicle torque control method provided by an embodiment of the present disclosure, such as Figure 2 As shown, including:

[0037] S201, according to the torque change trend, the last control torque in the control torque sequence is increased or decreased by the value of the torque change amplitude to obtain a target control torque, wherein the last control torque in the control torque sequence is the control torque of the target vehicle at the previous moment before the current moment;

[0038] S202, calculating the control torque of the front axle and the rear axle of the target vehicle at the current moment according to the target control torque and the torque distribution ratio;

[0039] S203, controlling the target vehicle according to the control torque of the front axle and the rear axle of the target vehicle at the current moment.

[0040] For example, the distribution ratio is the ratio of the torque distributed on the front axle and the rear axle of the vehicle, and the control torque distributed on the front axle and the rear axle of the target vehicle is calculated based on the target control torque and the torque distribution ratio.

[0041] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present disclosure, and will not be described in detail here.

[0042] The following are embodiments of the device disclosed herein, which can be used to execute the method embodiments disclosed herein. For details not disclosed in the device embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0043] Figure 3 Schematic diagram of a vehicle torque control device based on a vehicle driving road surface provided by an embodiment of the present disclosure. Figure 3 As shown, the vehicle torque control device based on the vehicle driving road surface includes:

[0044] The first acquisition module 301 is configured to acquire a target image of the road surface on which the target vehicle is traveling at the current moment;

[0045] The determination module 302 is configured to determine the target category of the road surface on which the target vehicle is traveling at the current moment based on the target image, and determine the torque change amplitude and torque distribution ratio corresponding to the target category, wherein the torque change amplitude represents the minimum amplitude of increasing or decreasing the control torque of the target vehicle on the road surface of the target category;

[0046] The second acquisition module 303 is configured to acquire the control torque sequence of the target vehicle at multiple moments before the current moment and the vehicle feedback information corresponding to the control torque sequence;

[0047] The judgment module 304 is configured to judge the torque change trend of the target vehicle according to the control torque sequence and the vehicle feedback information, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque;

[0048] The prediction module 305 is configured to predict the target control torque of the target vehicle at the current moment based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, and control the target vehicle at the current moment according to the target control torque and the torque distribution ratio.

[0049] According to the technical solution provided by the embodiment of the present disclosure, a target image of the road surface on which the target vehicle is traveling at the current moment is obtained; based on the target image, the target category of the road surface on which the target vehicle is traveling at the current moment is determined, and the torque change amplitude and torque distribution ratio corresponding to the target category are determined, wherein the torque change amplitude indicates the minimum amplitude of the target vehicle increasing or decreasing the control torque in the road surface of the target category; the control torque sequence of the target vehicle at multiple moments before the current moment and the vehicle feedback information corresponding to the control torque sequence are obtained; based on the control torque sequence and the vehicle feedback information, the torque change trend of the target vehicle is judged, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque; based on the torque change amplitude, the torque change trend and the last control torque in the control torque sequence, the target control torque of the target vehicle at the current moment is predicted, and the target vehicle is controlled at the current moment according to the target control torque and the torque distribution ratio. The above technical means can be used to solve the problems of insufficient power, vehicle shaking and slipping caused by the vehicle torque control in the prior art not considering the road surface on which the vehicle is traveling, thereby reducing the number of vehicle insufficient power, vehicle shaking and slipping, and ensuring the safety of users.

[0050] In some embodiments, the determination module 302 is also configured to obtain road surface features corresponding to various road surfaces such as dry highway road surfaces, wet highway road surfaces, snowy road surfaces, gravel road surfaces, and muddy road surfaces; extract target road surface features of the target image; calculate the Euclidean distance between the target road surface features and the road surface features of various road surfaces; and determine the road surface with the smallest corresponding Euclidean distance as the target category of the target vehicle driving road surface at the current moment.

[0051] In some embodiments, the determination module 302 is further configured to obtain multiple road surface images of various road surfaces, such as dry road surfaces, wet road surfaces, snowy road surfaces, gravel road surfaces, and muddy road surfaces; extract road surface features of each road surface image using a hash algorithm; and calculate the average value of the road surface features of multiple road surface images of each road surface to fuse and obtain the road surface features corresponding to each road surface.

[0052] In some embodiments, the determination module 302 is also configured to, when the target category is a snowy road surface, determine the torque variation amplitude to be a first variation amplitude, and determine the torque distribution ratio to be a first distribution ratio; when the target category is a slippery road surface, determine the torque variation amplitude to be a second variation amplitude, and determine the torque distribution ratio to be a second distribution ratio; when the target category is a dry road surface, determine the torque variation amplitude to be a third variation amplitude, and determine the torque distribution ratio to be a third distribution ratio; when the target category is a gravel road surface, determine the torque variation amplitude to be a fourth variation amplitude, and determine the torque distribution ratio to be a fourth distribution ratio; when the target category is a muddy road surface, determine the torque variation amplitude to be a fifth variation amplitude, and determine the torque distribution ratio to be a fifth distribution ratio.

[0053] In some embodiments, the determination module 302 is further configured such that the various change amplitudes are, from small to large, the first change amplitude, the second change amplitude, the third change amplitude, the fourth change amplitude, and the fifth change amplitude. For example, because the adhesion coefficient between the vehicle and the road surface is the smallest on a snowy road surface, in order to reduce the side slip of the vehicle, the first change amplitude corresponding to the snowy road surface is the smallest, that is, the vehicle control torque should be adjusted slowly with the smallest amplitude. Because the adhesion coefficient between the vehicle and the road surface is the largest on a muddy road surface, the possibility of the vehicle side slipping is relatively small, and the fifth change amplitude corresponding to the muddy road surface is the largest, and at this time, the vehicle control torque can be quickly adjusted with the largest amplitude.

[0054] In some embodiments, the determination module 302 is further configured such that the distribution ratio can be recorded as the ratio of the torque distributed on the front axle and the rear axle of the vehicle, and the various distribution ratios are the first distribution ratio, the second distribution ratio, the third distribution ratio, the fourth distribution ratio and the fifth distribution ratio from large to small. For example, on a snowy road, because the adhesion coefficient between the vehicle and the road is the smallest, the vehicle is prone to side slip, the friction resistance of the vehicle is also the smallest, and the vehicle is easy to accelerate, so the torque distributed on the front axle of the vehicle should be larger, while the torque distributed on the rear axle of the vehicle should be smaller, and the first distribution ratio corresponding to the snowy road is the largest (relatively speaking, a larger torque distributed on the rear axle of the vehicle is conducive to vehicle acceleration, and a larger torque distributed on the front axle of the vehicle is conducive to vehicle direction control). On a muddy road, because the adhesion coefficient between the vehicle and the road is the largest, the vehicle is not prone to side slip, the friction resistance of the vehicle is also the largest, and the vehicle is not easy to accelerate, so the torque distributed on the front axle of the vehicle should be smaller, while the torque distributed on the rear axle of the vehicle should be larger, and the fifth distribution ratio corresponding to the muddy road is the smallest.

[0055] In some embodiments, the judgment module 304 is further configured to control the torque sequence to include multiple control torques, each control torque corresponding to a piece of feedback information in the vehicle feedback information; determine the total score corresponding to each piece of feedback information; use the control torque as an independent variable, and the score corresponding to the control torque as a dependent variable, perform fitting processing on the multiple control torques and the score corresponding to each control torque to obtain a fitting result; and determine the torque change trend of the target vehicle based on the fitting result.

[0056] In some embodiments, the judgment module 304 is also configured to score each piece of feedback information from the following dimensions: the number of vehicle shakes and the duration of the shakes, the number of vehicle slips and the distance of the slips, the vehicle acceleration performance change information, the vehicle speed change information, and the vehicle drive engine temperature change information for each piece of feedback information; and perform weighted summation on the multiple scores obtained by scoring each piece of feedback information to obtain a total score corresponding to each piece of feedback information.

[0057] In some embodiments, the judgment module 304 is also configured to increase or decrease the torque change amplitude of the last control torque in the control torque sequence according to the torque change trend to obtain the target control torque, wherein the last control torque in the control torque sequence is the control torque of the target vehicle at the previous moment before the current moment; calculate the control torque of the front axle and the rear axle of the target vehicle at the current moment based on the target control torque and the torque distribution ratio; and control the target vehicle at the current moment based on the control torque of the front axle and the rear axle of the target vehicle.

[0058] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0059] Figure 4 Schematic diagram of an electronic device 4 provided in an embodiment of the present disclosure. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 401 executes the computer program 403, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0060] The electronic device 4 may include but is not limited to a processor 401 and a memory 402. Those skilled in the art will appreciate that Figure 4 The electronic device 4 is merely an example and does not limit the electronic device 4 , and may include more or less components than those shown in the figure, or different components.

[0061] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0062] The memory 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. The memory 402 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0063] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0064] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present disclosure implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0065] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be included in the protection scope of the present disclosure.

Claims

1. A vehicle torque control method based on a vehicle driving road surface, characterized in that: include: Acquire a target image of the road surface on which the target vehicle is traveling at the current moment; Determine the target category of the road surface on which the target vehicle is traveling at the current moment based on the target image, and determine the torque change amplitude and torque distribution ratio corresponding to the target category, wherein the torque change amplitude represents the minimum amplitude of increasing or decreasing the control torque of the target vehicle on the road surface of the target category; Acquire a control torque sequence of the target vehicle at multiple moments before the current moment and vehicle feedback information corresponding to the control torque sequence; Determining a torque change trend of the target vehicle according to the control torque sequence and the vehicle feedback information, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque; Based on the torque variation amplitude, the torque variation trend and the last control torque in the control torque sequence, predict the target control torque of the target vehicle at the current moment, and control the target vehicle at the current moment according to the target control torque and the torque distribution ratio; The step of determining the torque change trend of the target vehicle according to the control torque sequence and the vehicle feedback information includes: The control torque sequence includes a plurality of control torques, each control torque corresponding to a piece of feedback information in the vehicle feedback information; Determine the total score corresponding to each piece of feedback information; Taking the control torque as the independent variable and the score corresponding to the control torque as the dependent variable, a plurality of control torques and the score corresponding to each control torque are fitted to obtain a fitting result; The torque variation trend of the target vehicle is determined based on the fitting result.

2. The method according to claim 1, characterized in that Determining the target category of the road surface on which the target vehicle is traveling at the current moment based on the target image includes: The target categories include: dry road surface, wet road surface, snowy road surface, gravel road surface and muddy road surface; Obtain road surface characteristics corresponding to dry roads, slippery roads, snowy roads, gravel roads and muddy roads; Extracting target road surface features of the target image; Calculating the Euclidean distance between the target road surface feature and road surface features of various road surfaces; The road surface corresponding to the smallest Euclidean distance is determined as the target category of the road surface on which the target vehicle is traveling at the current moment.

3. The method according to claim 2, characterized in that Obtain the road surface characteristics corresponding to dry roads, slippery roads, snowy roads, gravel roads and muddy roads, including: Acquire multiple road images of dry roads, wet roads, snowy roads, gravel roads, and muddy roads; The road surface features of each road surface image are extracted using a hash algorithm; The average value of the road surface features of multiple road surface images of each road surface is calculated to fuse the road surface features corresponding to each road surface.

4. The method according to claim 1, characterized in that: Determining the torque variation range and torque distribution ratio corresponding to the target category includes: When the target category is a snowy road, determining the torque variation range to be a first variation range, and determining the torque distribution ratio to be a first distribution ratio; When the target category is a slippery road surface, determining the torque variation range to be a second variation range, and determining the torque distribution ratio to be a second distribution ratio; When the target category is a dry road surface, determining the torque variation range to be a third variation range, and determining the torque distribution ratio to be a third distribution ratio; When the target category is a gravel road, determining the torque variation range to be a fourth variation range, and determining the torque distribution ratio to be a fourth distribution ratio; When the target category is a muddy road, the torque variation range is determined to be a fifth variation range, and the torque distribution ratio is determined to be a fifth distribution ratio.

5. The method according to claim 1, characterized in that Determine the total score for each piece of feedback, including: Each piece of feedback information includes: the number and duration of vehicle shaking, the number and distance of vehicle skidding, vehicle acceleration performance change information, vehicle speed change information, and vehicle drive engine temperature change information; Each piece of feedback information is scored based on the following dimensions: the number and duration of vehicle vibrations, the number and distance of vehicle skidding, vehicle acceleration performance change information, vehicle speed change information, and vehicle drive engine temperature change information; The multiple scores obtained by scoring each piece of feedback information are weighted and summed to obtain the total score corresponding to each piece of feedback information.

6. The method according to claim 1, characterized in that Based on the torque variation amplitude, the torque variation trend and the last control torque in the control torque sequence, predicting the target control torque of the target vehicle at the current moment, and controlling the target vehicle at the current moment according to the target control torque and the torque distribution ratio, including: According to the torque variation trend, the last control torque in the control torque sequence is increased or decreased by the value of the torque variation amplitude to obtain the target control torque, wherein the last control torque in the control torque sequence is the control torque of the target vehicle at the previous moment before the current moment; Calculating the control torque of the front axle and the rear axle of the target vehicle at the current moment according to the target control torque and the torque distribution ratio; The target vehicle is controlled according to the control torque of the front axle and the rear axle of the target vehicle at the current moment.

7. A vehicle torque control device based on a vehicle driving road surface, characterized in that: include: A first acquisition module is configured to acquire a target image of a road surface on which a target vehicle is traveling at a current moment; a determination module configured to determine a target category of the road surface on which the target vehicle is traveling at a current moment based on the target image, and determine a torque variation amplitude and a torque distribution ratio corresponding to the target category, wherein the torque variation amplitude represents a minimum amplitude of increasing or decreasing a control torque of the target vehicle on the road surface of the target category; A second acquisition module is configured to acquire a control torque sequence of the target vehicle at multiple moments before a current moment and vehicle feedback information corresponding to the control torque sequence; A judgment module is configured to judge a torque change trend of the target vehicle according to the control torque sequence and the vehicle feedback information, wherein the torque change trend indicates that the target vehicle increases or decreases the control torque; a prediction module configured to predict a target control torque of the target vehicle at a current moment based on the torque variation amplitude, the torque variation trend and the last control torque in the control torque sequence, and control the target vehicle at a current moment according to the target control torque and the torque distribution ratio; The judgment module is specifically configured as follows: the control torque sequence includes multiple control torques, each control torque corresponds to a piece of feedback information in the vehicle feedback information; the total score corresponding to each piece of feedback information is determined; the control torque is used as an independent variable, the score corresponding to the control torque is used as a dependent variable, and the multiple control torques and the score corresponding to each control torque are fitted to obtain a fitting result; and the torque change trend of the target vehicle is determined based on the fitting result.

8. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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