Driving control method and vehicle on split slope

Abstract

The present invention provides a method and a vehicle for controlling driving on a split ramp, and belongs to the technical field of vehicle braking. The method comprises: obtaining an additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle; obtaining a feedforward angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data; obtaining a feedback angle of the vehicle based on the current vehicle data of the vehicle, the slope angle of the road surface and the ideal steady state of the vehicle; performing angle distribution according to the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle; and controlling the steering of each wheel of the vehicle according to each wheel angle. In this way, based on the relevant data of the vehicle on the split ramp and the ideal steady state of the vehicle, the feedforward angle and the feedback angle are obtained, and the feedback angle is used for angle compensation, and then the wheel angle distribution and control are performed accordingly, which can not only improve the climbing ability of the vehicle, but also ensure the lateral stability of the vehicle through steering control, and ensure the driving safety of the vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle braking, and in particular to a method for controlling driving on a ramp and a vehicle. Background Art

[0002] A split ramp is a specially designed sloped road surface, which usually contains two road surfaces with different adhesion coefficients, one half is a high adhesion coefficient road surface, and the other half is a low adhesion coefficient road surface. A four-wheel independent steering drive vehicle requires a lot of driving force when starting on a ramp. If the ramp on which the vehicle is located at the time of starting is a split ramp, the adhesion coefficients of the roads on both sides are inconsistent, and the adhesion of the low adhesion road surface will be greatly reduced, causing the driving wheel on this side to slip significantly and the driving force to drop significantly. However, a vehicle with independent steering drive on the high adhesion coefficient side requires a lot of starting torque to start on the ramp. Due to the difference in driving force on both sides, an additional yaw moment is generated, causing the vehicle to become lateral unstable and unable to drive in the direction expected by the driver, seriously affecting driving safety.

[0003] The passability of electric vehicles can be guaranteed by actively reducing the output torque to suppress slip. However, this method is not suitable for double-slope conditions. On double-slopes, the drive wheels on the high-adhesion coefficient road surface must provide a sufficiently high power output to ensure the passability of the vehicle on the double-slope. Once the driving force is limited, the vehicle will not be able to guarantee passability. The lateral instability problem caused by the unequal driving force on both sides of the vehicle on the double-slope can be solved by driving stability control technology. However, this method cannot guarantee the lateral stability of the vehicle and poses a great safety hazard to the vehicle. Summary of the invention

[0004] In view of this, an object of the present invention is to provide a method and vehicle for controlling driving on a double slope, which can realize active correction of the vehicle's turning angle to generate additional tire lateral force to suppress the vehicle's yaw motion, ensure the vehicle's lateral stability, and improve the vehicle's safety.

[0005] In a first aspect, the present invention provides a method for controlling driving on a ramp, the method comprising:

[0006] Obtaining an additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle;

[0007] Obtaining a feedforward steering angle of the vehicle based on the additional yaw torque, an ideal steady state of the vehicle and current vehicle data;

[0008] Based on the current vehicle data of the vehicle, the slope angle of the road on which the vehicle is located, and the ideal steady state of the vehicle, a feedback turning angle of the vehicle is obtained;

[0009] Performing angle distribution according to the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle;

[0010] According to the wheel turning angles, the steering of each wheel of the vehicle is controlled.

[0011] Optionally, the vehicle data includes the current speed and power parameters of the vehicle;

[0012] The step of obtaining the feedforward steering angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data comprises:

[0013] Based on the current vehicle speed and the power parameter of the vehicle, the whole vehicle slip data of the vehicle is obtained; wherein the whole vehicle slip data includes a rear slip moment difference, a front slip total moment, a front wheel slip moment and a rear wheel slip moment; the rear slip moment difference represents an additional moment generated by a difference between a rear wheel slip angle and a vehicle center of mass slip angle; the front slip total moment represents a total moment generated by the front wheel slip moment on the vehicle center of mass;

[0014] Obtaining a debiasing motion torque according to the rear yaw moment difference, the front yaw total moment, the additional yaw torque and an ideal steady state of the vehicle; wherein the ideal steady state of the vehicle includes no additional yaw torque;

[0015] A feedforward angle is obtained according to the debiasing motion torque, the front wheel cornering torque, the rear wheel cornering torque and ramp influence characteristics.

[0016] Optionally, the step of obtaining the vehicle side slip data based on the current vehicle speed and the power parameter of the vehicle comprises:

[0017] Obtaining wheel slip data of the vehicle according to the current vehicle speed and the power parameter; wherein the wheel slip data includes a front wheel slip angle, a rear wheel slip angle, a front wheel slip moment, and a rear wheel slip moment;

[0018] Subtract the vehicle center of mass slip angle from the rear wheel slip angle, and then multiply the result by the rear wheel slip moment to obtain a rear slip moment difference;

[0019] The front wheel slip angle is added to the vehicle center of mass slip angle, and then multiplied by the front wheel slip moment to obtain the total front slip moment.

[0020] Optionally, the step of obtaining a feedforward angle according to the debiasing motion torque, the front wheel cornering torque, the rear wheel cornering torque and ramp influence characteristics comprises:

[0021] According to the slope angle of the road surface on which the vehicle is currently located, the turning angle ratio table is queried to obtain a target ratio; wherein the target ratio represents the ratio of the turning angle of the front axle of the vehicle to the turning angle of the rear axle of the vehicle;

[0022] The ramp cornering moment is obtained by multiplying the rear wheel cornering moment by the target ratio, and the front-rear moment difference between the front wheel cornering moment and the ramp cornering moment is obtained;

[0023] According to the debiasing motion torque and the front-rear torque difference, a feedforward front wheel angle is obtained;

[0024] Obtaining a feedforward rear wheel steering angle according to the feedforward front wheel steering angle and the target ratio;

[0025] The feedforward front wheel steering angle and the feedforward rear wheel steering angle are combined to obtain a feedforward steering angle.

[0026] Optionally, the vehicle data includes the current speed and power parameters of the vehicle;

[0027] The step of obtaining the feedback turning angle of the vehicle based on the current vehicle data, the slope angle of the road surface and the ideal steady state of the vehicle comprises:

[0028] The dynamic rates of the yaw rate and the sideslip angle of the center of mass in the two-degree-of-freedom model of the vehicle are set to zero, and the ideal yaw rate and the ideal sideslip angle of the center of mass are obtained;

[0029] updating a state space equation of feedback control according to the vehicle speed, the power parameter, the ideal yaw rate and the ideal sideslip angle of the center of mass to obtain a current state space equation;

[0030] Based on the slope angle of the road surface on which the vehicle is currently located, a linear quadratic regulator is used to solve the current state space equation to obtain the feedback steering angle of the vehicle.

[0031] Optionally, the current state space equation includes a variable matrix consisting of an ideal yaw rate, an ideal center-of-mass sideslip angle, and a current center-of-mass sideslip angle and yaw rate of the vehicle;

[0032] The step of solving the current state space equation using a linear quadratic regulator based on the slope angle of the road surface currently located by the vehicle to obtain the feedback turning angle of the vehicle includes:

[0033] According to the slope angle of the road on which the vehicle is currently located, and the reference weights of the front axle angle and the rear axle angle, the current front axle angle weight and the rear axle angle weight are obtained;

[0034] Constructing an R weight matrix with the current front axle angle weight and the rear axle angle weight, and solving the current state space equation using a linear quadratic regulator, the R weight matrix and a default Q weight matrix to obtain a feedback control matrix;

[0035] A feedback angle is obtained according to the feedback control matrix and the variable matrix.

[0036] Optionally, the step of obtaining the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle comprises:

[0037] For each wheel, a longitudinal force of the wheel is obtained according to the driving torque of the wheel; the wheels include a front left wheel, a front right wheel, a rear left wheel and a rear right wheel;

[0038] According to the longitudinal forces of the front left wheel and the front right wheel, a front wheel force difference is obtained;

[0039] According to the longitudinal forces of the rear left wheel and the rear right wheel, a rear wheel force difference is obtained;

[0040] An additional yaw torque is obtained according to the front wheel force difference, the rear wheel force difference longitudinal and the vehicle track.

[0041] Optionally, the method further comprises:

[0042] According to the vehicle's whole vehicle motion information and wheel motion information, detect whether the vehicle is started on a ramp;

[0043] If so, the step of obtaining the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle is executed.

[0044] Optionally, the vehicle is provided with a slope force sensor, the whole vehicle motion information includes the vehicle's accelerator pedal signal, vehicle speed and speed in each direction, and the wheel motion information includes the driving torque and steering angle of each wheel;

[0045] The step of detecting whether the vehicle is started on a ramp according to the vehicle movement information and wheel movement information includes:

[0046] detecting whether the accelerator pedal signal and the vehicle speed meet a start condition;

[0047] If yes, then according to the vehicle's speed in each direction, as well as the driving torque and the turning angle of each wheel, the adhesion coefficient of the road surface on which each wheel is located is obtained;

[0048] When each of the adhesion coefficients meets the conditions of the split road working condition, the slope angle of the road on which the vehicle is located is obtained according to the vehicle speed and the unit mass ramp force measured by the ramp force sensor;

[0049] When the slope angle is greater than the angle threshold, it is determined that the vehicle is started on an oncoming ramp.

[0050] In a second aspect, the present invention provides a vehicle comprising a controller and a vehicle body, wherein the controller comprises a processor and a memory, wherein the memory stores a computer program that can be executed by the processor, and the processor can execute the computer program to implement the double-slope driving control method as described in the first aspect.

[0051] In a third aspect, the present invention provides a control device for driving on a split slope, comprising a yaw calculation module, a feedforward processing module, a feedback processing module and a steering control module;

[0052] The yaw calculation module is used to obtain the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle;

[0053] The feedforward processing module is used to obtain a feedforward steering angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and current vehicle data;

[0054] The feedback processing module is used to obtain a feedback turning angle of the vehicle based on the current vehicle data of the vehicle, the slope angle of the road on which the vehicle is located, and the ideal steady state of the vehicle;

[0055] The steering control module is used to: distribute the steering angle according to the feedforward steering angle and the feedback steering angle to obtain the wheel steering angle of each wheel of the vehicle; and control the steering of each wheel of the vehicle according to each wheel steering angle.

[0056] In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program that can be executed by the processor, and the processor can execute the computer program to implement the double-slope driving control method as described in the first aspect above.

[0057] In a fifth aspect, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for controlling driving on a double-slope as described in the first aspect above.

[0058] The present invention provides a method and vehicle for controlling driving on a ramp, the method comprising: obtaining an additional yaw torque of the vehicle based on the driving torque of each wheel of the vehicle; obtaining a feedforward angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and current vehicle data; obtaining a feedback angle of the vehicle based on the current vehicle data of the vehicle, the slope angle of the road surface and the ideal steady state of the vehicle; performing angle distribution based on the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle; and controlling the steering of each wheel of the vehicle based on the wheel angle.

[0059] In this way, based on the relevant data of the vehicle on the double-ended ramp and the ideal steady state of the vehicle, the feedforward angle and feedback angle are obtained, and the feedback angle is used for angle compensation, and then the wheel angle is distributed and controlled accordingly. This can not only improve the vehicle's climbing ability, but also ensure the vehicle's lateral stability through steering control, greatly improving the vehicle's driving safety on the double-ended ramp.

[0060] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0062] Figure 1 A schematic diagram of the system architecture of a ramp driving control system provided by an embodiment of the present invention is shown.

[0063] Figure 2 A schematic diagram of a module architecture of an electronic device provided by an embodiment of the present invention is shown.

[0064] Figure 3 One of the flow charts of the ramp driving control method provided by an embodiment of the present invention is shown.

[0065] Figure 4 Shows Figure 3 Schematic diagram of the process flow of some sub-steps of step 11.

[0066] Figure 5 Shows Figure 3 Schematic diagram of the process flow of some sub-steps of step 13.

[0067] Figure 6 Shows Figure 5 A flowchart of some sub-steps of step 131 in FIG.

[0068] Figure 7 Shows Figure 5 A flowchart of some sub-steps of step 135 in FIG.

[0069] Figure 8 Shows Figure 3 Schematic diagram of the process flow of some sub-steps of step 15.

[0070] Fig. 9 Shows Figure 8 A flowchart of some sub-steps of step 155.

[0071] Fig.10 The second flowchart of the ramp driving control method provided by the embodiment of the present invention is shown.

[0072] Fig.11 Shows Fig.10Schematic diagram of the process of some sub-steps of step 21.

[0073] Fig.12 A schematic diagram of the module architecture of a ramp driving control device provided by an embodiment of the present invention is shown.

[0074] Icons: 10-slope driving control system; 110-controller; 120-steering motor; 130-sensor; 20-electronic equipment; 210-memory; 220-processor; 230-communication module; 30-slope driving control device; 310-yaw calculation module; 320-feedforward processing module; 330-feedback processing module; 340-steering control module. DETAILED DESCRIPTION

[0075] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0076] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0077] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0078] The ramp driving control method provided by the embodiment of the present invention can be applied to Figure 1In the ramp driving control system 10 shown, the ramp driving control system 10 includes a vehicle controller 110, a steering motor 120 and various sensors 130 arranged on the vehicle. The controller 110 can be communicated with the steering motor 120 and the sensor 130 respectively through any data line (such as CAN bus, etc.).

[0079] Sensor 130 is used to measure the real-time vehicle data and unit mass ramp force of the vehicle. The vehicle data includes vehicle speed and power parameters. The power parameters include the lateral speed, longitudinal acceleration, lateral acceleration, yaw rate, vehicle center of mass side slip angle, vehicle mass, vehicle moment of inertia, distance between the vehicle center of mass and the front and rear axles, and any of the driving torque, steering angle, steering angle and lateral stiffness of the wheels.

[0080] The controller 110 is used to receive the measurement data of each sensor 130, and to implement the control method for driving on a ramp provided by an embodiment of the present invention. The control method for driving on a ramp includes: obtaining the additional yaw torque of the vehicle based on the driving torque of each wheel of the vehicle; obtaining the feedforward angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data; obtaining the feedback angle of the vehicle based on the current vehicle data of the vehicle, the slope angle of the road surface and the ideal steady state of the vehicle; performing angle distribution based on the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle; and controlling the steering of each wheel of the vehicle based on the wheel angle. For example, the controller 110 sends a steering instruction to the steering motor 120 based on the wheel angle.

[0081] The steering motor 120 is used for steering in response to a steering instruction.

[0082] The controller 110 may be a computer, a microprocessor 220, a single chip microcomputer, a programmable logic controller, a field programmable gate array or any programmable control processing device. The sensor 130 includes a slope force sensor, a speed sensor and an inertial measurement unit.

[0083] Please refer to Figure 2 , is a block diagram of an electronic device 20, which may be Figure 1 The controller 110 in the ramp driving control system 10 is shown. The electronic device 20 includes a memory 210, a processor 220 and a communication module 230. The memory 210, the processor 220 and the communication module 230 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0084] The memory 210 is used to store programs or data and can be, but not limited to, a random access memory, a read-only memory, a programmable read-only memory, an erasable read-only memory, an electrically erasable read-only memory, and the like.

[0085] The processor 220 is used to read / write data or programs stored in the memory 210 and execute corresponding functions. For example, Figure 1 In the illustrated control system 10 for driving on a slope, the processor 220 of the controller 110 reads the computer program stored in the memory 210 to implement the control method for driving on a slope provided in an embodiment of the present invention.

[0086] The communication module 230 is used to establish a communication connection between the electronic device 20 and other communication terminals (such as the sensor 130, the steering motor 120, etc.), and to send and receive data. For example, Figure 1 In the illustrated control system 10 for driving on a slope, the controller 110 transmits and receives data with the steering motor 120 and the controller 110 respectively through the communication module 230 .

[0087] It should be understood that Figure 2 The structure shown is only a schematic diagram of the structure of the electronic device 20. The electronic device 20 may also include Figure 2 More or fewer components as shown, or with Figure 2 Different configurations shown. Figure 2 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0088] In order to solve the problem that the related vehicle control technology can improve the power output but cannot ensure the lateral stability of the vehicle when driving on a ramp, resulting in a potential safety hazard of the vehicle, the embodiment of the present invention provides a ramp driving control method, referring to Figure 3 , including steps 11 to 19. And, Figure 2 In the control system 10 for driving on a slope, the controller 110 is Figure 2 The structure shown implements steps 11 to 19 when the processor 220 reads the computing program stored in the memory 210 .

[0089] Step 11, obtaining the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle.

[0090] Step 13, obtaining the feedforward steering angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data.

[0091] Step 15, obtaining the feedback turning angle of the vehicle based on the current vehicle data, the slope angle of the road surface and the ideal steady state of the vehicle.

[0092] Step 17, performing angle distribution according to the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle.

[0093] Step 19, controlling the steering of each wheel of the vehicle according to the steering angle of each wheel.

[0094] For example, in combination Figure 1 The ramp driving control system 10 shown, when the vehicle starts or drives on the ramp, collects the driving torque and other vehicle data of each vehicle through the sensor 130, and obtains the slope angle of the road surface on which the vehicle is located (i.e. the slope angle of the ramp).

[0095] Next, the controller 110 obtains the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle, that is, the additional yaw torque (also the additional yaw torque) generated due to the difference in driving force between the two sides of the vehicle on the ramp. Furthermore, the controller 110 obtains the feedforward angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle (the ideal steady state here refers to the lateral stable state of the vehicle without yaw) and the current vehicle data. The feedforward angle can be understood as the vehicle angle required when the vehicle is not expected to yaw.

[0096] At the same time, the controller 110 obtains the feedback angle of the vehicle based on the current vehicle data, the slope angle of the road surface and the ideal steady state of the vehicle. The feedback angle can be understood as the compensation angle required to improve the angle accuracy and make the yaw rate deviation zero.

[0097] After obtaining the feedforward angle and the compensation angle, the controller 110 distributes the angle according to the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle. According to the wheel angle, the controller 110 sends a steering command to the steering motor 120 to control the wheel to rotate the corresponding wheel angle through the steering motor 120. Thus, the vehicle is actively steered to ensure the lateral stability of the vehicle on the ramp.

[0098] In the above steps 11 to 19 of the ramp driving control method provided by an embodiment of the present invention, a feedforward angle and a feedback angle are obtained based on relevant data of the vehicle on the ramp and the ideal steady state of the vehicle, so that the feedback angle is used for angle compensation, and then the wheel angle is distributed and controlled accordingly, so that the vehicle actively steers to achieve a yaw angular velocity deviation of zero and no yaw motion of the vehicle, thereby improving the vehicle's climbing ability and ensuring the vehicle's lateral stability through steering control, greatly improving the vehicle's driving safety on the ramp.

[0099] In step 11, any feasible method can be used to obtain the additional yaw torque of the vehicle. For example, a model for calculating the additional yaw torque can be pre-trained and fitted, and the driving torque of each wheel of the vehicle is used as the input of the model, and the additional yaw torque of the vehicle is inferred using the model. Alternatively, the additional yaw torque of the vehicle can be calculated according to a preset rule.

[0100] In order to ensure the accuracy of the additional yaw torque, in the process of obtaining the additional yaw torque of the vehicle in step 11, the idea of ​​calculating according to the principle of the generation of the additional yaw torque is introduced. Figure 4 , step 11 obtains the additional yaw torque through steps 111 to 117.

[0101] Step 111 : for each wheel, obtain the longitudinal force of the wheel according to the driving torque of the wheel.

[0102] Among them, the wheels of the four-wheel independent steering drive vehicle include a front left wheel, a front right wheel, a rear left wheel and a rear right wheel.

[0103] Step 113, obtaining the front wheel force difference according to the longitudinal forces of the front left wheel and the front right wheel.

[0104] Step 115, obtaining the rear wheel force difference according to the longitudinal forces of the rear left wheel and the rear right wheel.

[0105] Step 117, obtaining an additional yaw torque according to the front wheel force difference, the rear wheel force difference longitudinal and the vehicle track.

[0106] The process from step 111 to step 117 can be expressed by the formula: .in, , , , .

[0107] Characterizes the additional yaw torque, Respectively represent the tire longitudinal forces corresponding to the front left wheel, front right wheel, rear left wheel and rear right wheel of the vehicle, Respectively represent the driving torque of the front left wheel, front right wheel, rear left wheel and rear right wheel, Respectively represent the moment of inertia of the front left wheel, front right wheel, rear left wheel and rear right wheel, B Characterizes the vehicle wheelbase, Characterizes the rolling radius of the wheel tire, Respectively represent the rotation speeds of the front left wheel, front right wheel, rear left wheel and rear right wheel.

[0108] The front wheel force difference is , the rear wheel force difference is .

[0109] Through the above method, according to the principle of generating additional yaw torque, the additional yaw torque is calculated according to the current wheel speed and driving torque of the vehicle, that is, the additional yaw torque generated by the difference in driving force of the wheels on both sides when the vehicle is driving on opposite slopes, thereby ensuring the accuracy of the additional yaw torque.

[0110] After the additional yaw torque is obtained in the above manner, any feasible manner may be used to process and obtain the feedforward angle of the vehicle in step 13. For example, the feedforward angle may be obtained according to a preset rule, or the feedforward angle may be inferred by a model, and both of these methods are examples, and the implementation methods are not limited.

[0111] When the vehicle is on a slope, the corresponding maximum tire force is different due to the difference in front and rear loads. In order to fully utilize the lateral force of the wheel tire, it is necessary to apply a larger tire turning angle on the side with a larger load to generate a yaw torque in the opposite direction of the additional yaw torque caused by the imbalance of driving force.

[0112] In order to make the feedforward angle play a role in preventing the vehicle from yaw on a slope, a two-degree-of-freedom model of the vehicle is introduced in step 13 to obtain the relationship between the feedforward angle and various vehicle parameters, and the feedforward angle is calculated accordingly.

[0113] The vehicle two-degree-of-freedom model is obtained by simplifying the vehicle model. The vehicle two-degree-of-freedom model can be expressed by the formula: .

[0114] in, Characterizes the quality of the vehicle, Represents the speed component of the vehicle speed on the x-axis of the vehicle's three-dimensional coordinate system, Characterizes the vehicle's moment of inertia around the z-axis, Characterizes the vehicle's center of mass sideslip angle, Characterizes the vehicle's yaw rate, Respectively represent the cornering stiffness of the front and rear tires of the vehicle, Represents the distance between the vehicle's center of mass and the vehicle's axis Represents the distance between the vehicle's center of mass and the vehicle's rear axle, Characterizes the vehicle's front axle angle, Characterizes the rear axle angle of the vehicle.

[0115] The ideal steady state of the vehicle includes no additional yaw torque (i.e., the vehicle does not yaw). When the vehicle is driving on a ramp, if you want the vehicle not to yaw, you need to generate additional tire lateral force to suppress the additional yaw torque of the vehicle, which can be expressed as: .

[0116] Simplifying the above formula, we can get the dynamic equation of the vehicle in the ideal steady state: .in, It can represent the front wheel cornering moment. Characterizes the rear wheel cornering moment, Characterizes the rear wheel slip angle, Characterizes the front wheel slip angle, Characterizes the difference in rearward moment, Characterizes the total forward moment. It can be expressed as the depolarizing motion torque.

[0117] Here, the rear cornering moment difference represents the additional moment generated due to the difference between the rear wheel slip angle and the vehicle center of mass slip angle, and the front cornering moment represents the total moment generated by the front wheel cornering moment on the vehicle center of mass.

[0118] Therefore, in order to make the feedforward angle play a role in preventing the vehicle from yaw motion on the slope, the concept of calculating the feedforward angle based on the principle of the vehicle two-degree-of-freedom model and considering the slope influence characteristics is introduced in the process of obtaining the vehicle's feedforward angle in step 13. Figure 5 In step 13, the feedforward angle is obtained through steps 131 to 135.

[0119] Step 131, based on the current vehicle speed and power parameters of the vehicle, obtain the vehicle side slip data.

[0120] Among them, the vehicle cornering data includes the rear cornering moment difference, the front cornering moment, the front wheel cornering moment and the rear wheel cornering moment.

[0121] Step 133, obtaining the anti-bias motion torque according to the rear yaw moment difference, the front yaw total moment, the additional yaw torque and the ideal steady state of the vehicle.

[0122] The ideal steady state of the vehicle includes no additional yaw torque.

[0123] Step 135, obtaining a feedforward angle according to the debiasing motion torque, the front wheel cornering torque, the rear wheel cornering torque and the slope influence characteristics.

[0124] Based on the above-mentioned dynamic equation of the ideal steady state of the vehicle, any feasible method can be used to obtain the vehicle side slip data in step 1311. For example, the calculation function of the rear side slip moment difference and the front side slip total moment can be constructed and deployed first, and the calculation function can be called and the vehicle speed and dynamic parameters can be assigned to the calculation function, and the rear side slip moment difference and the front side slip total moment can be calculated using the calculation function. It can also be calculated directly according to the principle in the dynamic equation.

[0125] For example, refer to Figure 6 The process of obtaining the vehicle side slip data of the vehicle in step 131 includes steps 1311 to 1315.

[0126] Step 1311, obtaining the wheel slip data of the vehicle according to the current vehicle speed and power parameters.

[0127] The wheel slip data includes the front wheel slip angle, the rear wheel slip angle, the front wheel slip moment and the rear wheel slip moment.

[0128] Step 1313, subtract the vehicle center of mass slip angle from the rear wheel slip angle, and multiply the result by the rear wheel slip moment to obtain a rear slip moment difference.

[0129] Step 1315, add the front wheel slip angle to the vehicle center of mass slip angle, and then multiply by the front wheel slip moment to obtain the total front slip moment.

[0130] Through the above steps 1311 to 1315, accurate rear bias moment difference and front bias total moment are obtained.

[0131] The above two methods of obtaining vehicle side slip data are examples, and the implementation methods are not limited.

[0132] After the vehicle side slip data is obtained, in step 133, according to the dynamic equation of the vehicle under the ideal state, the additional yaw torque is subtracted from the sum of the rear side slip moment difference and the front side slip total moment to obtain the anti-side slip motion moment.

[0133] After the debiasing motion torque is calculated according to the aforementioned dynamic equation of the ideal steady state of the vehicle in the above steps 131 to 133, the method of obtaining the feedforward angle in step 135 can be flexibly selected. For example, the slope angle of the ramp can be used as the ramp influence feature, and input into the pre-trained feedforward control model together with the debiasing motion torque, the front wheel side torque, and the rear wheel side torque, and the feedforward angle is inferred by the feedforward control model. It is also possible to calculate the feedforward angle according to preset rules combined with the aforementioned dynamic equation of the ideal steady state of the vehicle. The above two methods are examples, and their implementation methods are not limited.

[0134] Considering that different slope angles correspond to different balancing states, in order to make the feedforward angle more matched with the slope angle and to suppress the additional yaw torque more accurately, the concept of determining the ratio of the vehicle front axle angle to the vehicle rear axle angle based on the slope angle is introduced in step 135. Figure 7 , step 135 determines the feedforward angle by following steps 1351 to 1359.

[0135] Step 1351, according to the slope angle of the road surface on which the vehicle is currently located, query the turning angle ratio table to obtain the target ratio.

[0136] The target ratio represents the ratio of the front axle angle of the vehicle to the rear axle angle of the vehicle. The angle ratio table can be a table obtained by fitting multiple sets of calibration data obtained from calibration tests, or a table obtained by fitting historical driving data, and the acquisition method is not limited.

[0137] Step 1353, multiplying the rear wheel cornering moment by the target ratio to obtain the ramp cornering moment, and obtaining the front-to-rear moment difference between the front wheel cornering moment and the ramp cornering moment.

[0138] Step 1355, obtain the feedforward front wheel angle based on the debiasing motion torque and the front-rear torque difference.

[0139] Step 1357, obtaining the feedforward rear wheel steering angle according to the feedforward front wheel steering angle and the target ratio.

[0140] Step 1359, combining the feedforward front wheel angle and the feedforward rear wheel angle to obtain a feedforward angle.

[0141] The processing from step 1351 to step 1355 can be expressed by the formula: , Characterize the target ratio.

[0142] The feedforward rear wheel steering angle obtained in step 1357 can be expressed as: . Based on this, the feedforward angle can be expressed as: .

[0143] The feedforward angle obtained in the above manner takes into account both the ideal steady state of the vehicle and the influence of the slope angle, so that the feedforward angle is more matched with the additional yaw torque, that is, it can suppress the additional yaw torque causing yaw, thereby improving the yaw suppression effect and ensuring the lateral stability of the vehicle.

[0144] Since the feedforward angle obtained in the above-mentioned manner is obtained based on the principle of the vehicle's two-degree-of-freedom model, the control of the feedforward angle depends on the model accuracy. It is difficult to ensure the stability control effect by feedforward control alone. Feedback control is applied through step 15, that is, the feedback angle is obtained according to the vehicle state to correct the vehicle steering.

[0145] The method of obtaining the feedback angle in step 15 can be flexibly set. For example, the current vehicle data, the slope angle of the road surface and the ideal steady state of the vehicle can be input into the feedback control model, and the feedback angle can be inferred by the feedback control model. The feedback angle can also be estimated by using Kalman filtering. The implementation method is not limited.

[0146] In order to make the feedback angle more accurately compensate the feedforward angle, to ensure the accuracy of steering control to suppress the additional yaw torque and to avoid over- or under-steering, the ideal steady state and slope angle corresponding to the two-degree-of-freedom model of the vehicle are introduced in step 15, and the feedback angle is obtained by adopting the LQR control principle. Figure 8 , step 15 obtains the feedback angle by following steps 151 to 155.

[0147] Step 151, set the dynamic rates of the yaw rate and the sideslip angle of the center of mass in the two-degree-of-freedom model of the vehicle to zero, and obtain the ideal yaw rate and the ideal sideslip angle of the center of mass.

[0148] Step 153, based on the vehicle speed, power parameters, ideal yaw rate and ideal sideslip angle of the center of mass, update the state space equation of the feedback control to obtain the current state space equation.

[0149] Step 155 , based on the slope angle of the road surface on which the vehicle is currently located, a linear quadratic regulator is used to solve the current state space equation to obtain the feedback angle of the vehicle.

[0150] Let the dynamic rate of the yaw rate and the sideslip angle of the center of mass in the two-degree-of-freedom model of the vehicle be zero, that is, , , we can get the ideal yaw rate and ideal sideslip angle of the vehicle in steady state, expressed as and .

[0151] Combined with the vehicle two-degree-of-freedom model, based on the feedback control principle, the state space equation of the feedback control system corresponding to the vehicle two-degree-of-freedom model can be expressed as follows: .when When it tends to 0, that is, the yaw angular velocity deviation is zero, the feedback angle achieves the effect of compensating the feedforward angle.

[0152] Then, step 153 substitutes the current vehicle speed, power parameters, ideal yaw rate and ideal center of mass sideslip angle into the state space equation of the feedback control to obtain the updated current state space equation. That is, it is a variable matrix composed of the ideal yaw rate, the ideal center of mass sideslip angle, and the vehicle's current center of mass sideslip angle and yaw rate.

[0153] In step 15, to obtain The feedback angle when it tends to 0 can be obtained by solving the current state equation using a linear quadratic regulator (i.e., LQR control principle) to obtain the initial feedback angle, and then correcting it using the target ratio corresponding to the slope angle to obtain the final feedback angle. Alternatively, the influence value (such as weight) of the slope angle on the front and rear axle angles can be introduced in the process of solving the current state equation using a linear quadratic regulator (i.e., LQR control principle). The above methods are all examples, and their implementation methods are not limited.

[0154] Maximum tire force of the vehicle Vertical load corresponding to maximum tire force The relationship between can be expressed as , is a coefficient, that is, under the same road adhesion coefficient, the greater the vertical load, the greater the corresponding tire force.

[0155] Therefore, in order to make full use of the vertical load of the vehicle and improve the vehicle's passability, the accuracy of the feedback angle is made higher. In step 155, the design of the front axle angle weight is introduced. Positively correlated with the slope angle (i.e., the greater the slope, the smaller the front axle angle is expected to be), the rear axle angle weight The concept of constructing the R weight matrix of the linear quadratic regulator is negatively correlated with the slope angle (i.e., the greater the slope, the greater the rear axle angle is expected to be), and based on this, it can be illustrated by referring to Fig. 9 The process of obtaining the feedback angle in step 155 includes steps 1551 to 1555.

[0156] Step 1551, obtaining the current front axle angle weight and rear axle angle weight according to the slope angle of the road on which the vehicle is currently located and the reference weights of the front axle angle and the rear axle angle.

[0157] Step 1553, construct an R weight matrix with the current front axle angle weight and rear axle angle weight, use a linear quadratic regulator, the R weight matrix and the default Q weight matrix to solve the current state space equation and obtain a feedback control matrix.

[0158] Step 1555, obtain the feedback angle according to the feedback control matrix and the variable matrix.

[0159] Since the greater the slope, the smaller the front axle angle is desired, the front axle angle weight obtained in step 1551 is expressed as: The greater the slope, the greater the rear axle angle is expected to be, so the rear axle angle weight is expressed as: .in, Characterizes the slope angle, is the reference weight of the front axle angle, is the base weight of the rear axle angle.

[0160] The R weight matrix is ​​expressed as: , and the default Q weight matrix can be expressed as: .

[0161] Then, in step 1553, the current state control equation is As the A matrix, As the B matrix, As a variable matrix. is 0, and the linear quadratic regulator (i.e., LQR control principle) is used to solve the current state space equation to obtain the feedback control matrix .

[0162] Then, in step 1555, the variable matrix and the negative feedback control matrix are multiplied to obtain the feedback angle ,Right now .

[0163] The feedback angle includes the feedback amounts of the front axle angle and the rear axle angle and in this process, since the front axle angle weight is positively correlated with the slope angle, the rear axle angle weight is negatively correlated with the slope angle, and the front axle angle weight and the rear axle angle weight constitute a Q weight matrix, after solving the current state space equation by the LQR control principle (i.e., using a linear quadratic regulator, an R weight matrix and a default Q weight matrix for solving), if the slope angle is larger, the feedback amount of the front axle angle is smaller, and the feedback amount of the rear axle angle is larger; conversely, if the slope angle is smaller, the feedback amount of the front axle angle is larger, and the feedback amount of the rear axle angle is smaller.

[0164] Through the above method, the feedback angle and the feedforward angle are more matched, that is, the feedback angle is more accurate, thereby improving the accuracy of the active correction of the wheel angle and further ensuring the stability of the vehicle.

[0165] In step 17, the feedforward angle and the feedback angle are superimposed to obtain the target control angle of the front and rear axle angles. , which can be expressed as Then, the target control angle is allocated according to the Ackerman steering model to obtain the wheel angle of each wheel. The angle allocation of the Ackerman steering model is a common method and will not be elaborated on.

[0166] On the basis of the above, in the ramp driving control method provided by the embodiment of the present invention, the above steps 11 to 19 are applicable to the scenario where the vehicle is driving or starting on the ramp. The judgment of whether the vehicle is driving or starting on the ramp can be flexibly set. For example, each ramp can be evaluated and measured in advance to determine its attributes (i.e., whether it is a ramp or an ordinary ramp), and its slope angle can be obtained, and the above information can be displayed on the map. Thus, the vehicle can obtain the attributes and slope angle of the current ramp from the map. When the attribute is a ramp and the vehicle is driving or starting, the above steps 11 to 19 are used to perform stability control.

[0167] For example, refer to Fig.10 , step 21 may be further included before the above step 11.

[0168] Step 21, based on the vehicle's entire motion information and wheel motion information, detect whether the vehicle is started on a ramp.

[0169] If it is determined that the vehicle is started on a ramp, step 11 is executed. The starting here includes starting and driving.

[0170] The vehicle motion information includes the vehicle's accelerator pedal signal, vehicle speed, and speed in each direction, and the wheel motion information includes the driving torque and steering angle of each wheel. In step 21, the vehicle motion information and wheel motion information may be input into a pre-trained start discrimination model, and the start discrimination model may be used to infer whether the vehicle is driving on a ramp. It may also be determined according to a preset rule. The implementation method is not limited.

[0171] In order to more accurately determine whether the vehicle is started on a ramp, the concepts of vehicle start determination, ramp determination and adhesion coefficient calculation determination are introduced in step 21. Fig.11 In step 21, the following steps 211 to 217 can be performed to detect whether the vehicle is started on the opposite ramp.

[0172] Step 211, detect whether the accelerator pedal signal and the vehicle speed meet the start condition. If yes, execute step 213, if not, end.

[0173] Step 213, obtaining the adhesion coefficient of the road surface on which each wheel is located according to the speed of the vehicle in each direction, and the driving torque and the turning angle of each wheel.

[0174] Step 215, when each adhesion coefficient meets the conditions of the open road working condition, the slope angle of the road surface on which the vehicle is located is obtained according to the vehicle speed and the unit mass ramp force measured by the ramp force sensor.

[0175] Step 217: When the slope angle is greater than the angle threshold, it is determined that the vehicle is started on an oncoming ramp.

[0176] In step 211 , if the vehicle speed is not zero, or if the vehicle speed is zero but the accelerator pedal signal starts to increase from 0, it can be determined that the start condition is met; otherwise, the start condition is not met.

[0177] The method of obtaining the adhesion coefficient in step 213 can be flexibly set. For example, the speed of the vehicle in each direction, the driving torque and the turning angle of each wheel can be assigned to the adhesion coefficient function, and the adhesion coefficient is obtained by using the adhesion coefficient function, which is a pre-constructed function. Alternatively, the adhesion coefficient of the road surface on which each wheel is located can be calculated according to a preset rule. The implementation method is not limited.

[0178] To make the adhesion coefficient more accurate, in step 213, the longitudinal acceleration of the vehicle is collected. , lateral acceleration , yaw rate As well as the driving torque and steering angle of each wheel, the Kalman filter algorithm and Dugoff tire model are used to estimate the road adhesion coefficient of each wheel (i.e. the adhesion coefficient of the front left wheel, front right wheel, rear left wheel and rear right wheel) ), if the absolute difference between the total adhesion coefficient of the left wheel and the total adhesion coefficient of the right wheel is greater than the preset threshold, that is (N can be , or 0.3, or any other arbitrary value), the wheel is considered to be in the split road condition and meets the split road condition condition.

[0179] The process of estimating the road adhesion coefficient of each wheel is as follows.

[0180] The Dugoff tire model is used as the research object, and the formula for establishing the Dugoff tire model is as follows: , , .

[0181] in, .

[0182] is the longitudinal driving force of the wheel, is the wheel cornering force, is the tire vertical force, =fl, fr, rl, rr represent each tire. is the road adhesion coefficient, is the tire longitudinal stiffness, is the tire cornering stiffness, is the tire slip angle, is the tire slip rate, is the function definition for judging the tire status, is the current state coefficient value, is the longitudinal speed of the wheel, is the vehicle speed influencing factor.

[0183] The Dugoff tire model is normalized and deformed to obtain: in, represent the normalized tire longitudinal force and lateral force, respectively.

[0184] The calculation of tire force using the Dugoff tire model also requires the input of slip rate, tire side slip angle and tire vertical force. Other dynamic equations are also needed to calculate these input quantities. The formula is: , , .

[0185] in, is the front wheel turning angle of the vehicle, The lateral speed of the vehicle, is the vehicle yaw angular velocity, , are the distances from the vehicle center of mass to the front and rear axles, Vehicle center of mass height, is the vehicle longitudinal acceleration, The lateral acceleration of the vehicle, is the vehicle wheelbase, Rotation speed, is the tire rolling radius, is the longitudinal velocity of the wheel center in the wheel coordinate system.

[0186] Using the normalized Dugoff tire model, a road adhesion coefficient estimation algorithm based on extended Kalman filter is designed to estimate the adhesion coefficients of the roads on which the four tires are traveling.

[0187] The state, output and input of the extended Kalman filter algorithm are as follows: , , .

[0188] The state space equation is: , .

[0189] in, Characterize process noise, Characterize the observation noise.

[0190] .

[0191] .

[0192] .

[0193] .

[0194] Based on the above formula, the current speed of the vehicle in each direction, as well as the driving torque and steering angle of each wheel are substituted into the formula to estimate the road adhesion coefficient of each wheel. .

[0195] In the above step 215, the slope angle can be obtained according to the principle of the following slope angle formula, which can be expressed as: , is the unit mass ramp force measured by the ramp force sensor, is the differential of the longitudinal vehicle speed, is the vehicle longitudinal velocity.

[0196] When the slope angle is greater than the angle threshold, it can be determined that the vehicle is starting on the ramp. , or , its specific value is not limited.

[0197] Based on the same concept as the above-mentioned ramp driving control method, refer to Fig.12 The embodiment of the present invention further provides a ramp driving control device 30 , which includes a yaw calculation module 310 , a feedforward processing module 320 , a feedback processing module 330 and a steering control module 340 .

[0198] The yaw calculation module 310 is used to obtain the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle.

[0199] The feedforward processing module 320 is used to obtain a feedforward steering angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data.

[0200] The feedback processing module 330 is used to obtain the feedback angle of the vehicle based on the current vehicle data of the vehicle, the slope angle of the road surface and the ideal steady state of the vehicle.

[0201] The steering control module 340 is used to: distribute the steering angle according to the feedforward steering angle and the feedback steering angle to obtain the wheel steering angle of each wheel of the vehicle; and control the steering of each wheel of the vehicle according to each wheel steering angle.

[0202] Under the coordinated action of the yaw calculation module 310, the feedforward processing module 320, the feedback processing module 330 and the steering control module 340, the above-mentioned ramp driving control device 30 obtains the feedforward angle and the feedback angle based on the relevant data of the vehicle on the ramp and the ideal steady state of the vehicle, and uses the feedback angle to perform angle compensation, and then distributes and controls the wheel angle accordingly, so that the vehicle actively steers to achieve a yaw angular velocity deviation of zero and no yaw motion of the vehicle, thereby improving the vehicle's climbing ability and ensuring the vehicle's lateral stability through steering control, greatly improving the vehicle's driving safety on the ramp.

[0203] For the specific implementation and effect of the double-slope driving control device 30, please refer to the description of the implementation of the double-slope driving control method in the above text, such as, for the specific implementation and effect of the yaw calculation module 310, please refer to the description of the relevant content of step 11 in the above text, for the specific implementation and effect of the feedforward processing module 320, please refer to the description of the relevant content of step 13 in the above text, for the specific implementation and effect of the feedback processing module 330, please refer to the description of the relevant content of step 15 in the above text, for the specific implementation and effect of the steering control module 340, please refer to the description of the relevant content of steps 17 to step 17 in the above text, and will not be repeated here.

[0204] In addition, each module of the above-mentioned ramp driving control device 30 can be implemented in whole or in part by software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor 220 in the electronic device 20 in the form of hardware, or can be stored in the memory 210 of the electronic device 20 in the form of software, so that the processor 220 can call and execute the operations corresponding to the above-mentioned modules to implement the ramp driving control method provided above.

[0205] An embodiment of the present invention also provides a vehicle, including a controller 110 and a vehicle body, the controller 110 includes a processor 220 and a memory 210, the memory 210 stores a computer program that can be executed by the processor 220, and the processor 220 can execute the computer program to implement the double-slope driving control method mentioned above.

[0206] An embodiment of the present invention also provides an electronic device 20, including a processor 220 and a memory 210, wherein the memory 210 stores a computer program that can be executed by the processor 220, and the processor 220 can execute the computer program to implement the double-slope driving control method provided above.

[0207] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor 220, the method for controlling driving on a ramp as proposed in the embodiment of the present invention is implemented.

[0208] In summary, the ramp driving control method and vehicle provided by the embodiments of the present invention have at least the following beneficial effects:

[0209] (i) Through the combination of feedforward control and feedback control, the wheel angle is actively corrected to generate additional tire lateral force to suppress the vehicle's yaw motion and improve vehicle safety;

[0210] (ii) Without affecting the safety of the vehicle, improve the vehicle's climbing ability and steering compensation to ensure the safety and lateral stability of the vehicle.

[0211] In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes 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 and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0212] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0213] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.

[0214] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for controlling driving on a ramp, characterized in that: The method comprises: Obtaining an additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle; Obtaining a feedforward steering angle of the vehicle based on the additional yaw torque, an ideal steady state of the vehicle and current vehicle data; Based on the current vehicle data of the vehicle, the slope angle of the road on which the vehicle is located, and the ideal steady state of the vehicle, a feedback turning angle of the vehicle is obtained; Performing angle distribution according to the feedforward angle and the feedback angle to obtain the wheel angle of each wheel of the vehicle; Controlling the steering of each wheel of the vehicle according to each wheel steering angle; The vehicle data includes the current speed and power parameters of the vehicle; The step of obtaining the feedforward steering angle of the vehicle based on the additional yaw torque, the ideal steady state of the vehicle and the current vehicle data comprises: Based on the current vehicle speed and the power parameter of the vehicle, the whole vehicle slip data of the vehicle is obtained; wherein the whole vehicle slip data includes a rear slip moment difference, a front slip total moment, a front wheel slip moment and a rear wheel slip moment; the rear slip moment difference represents an additional moment generated by a difference between a rear wheel slip angle and a vehicle center of mass slip angle; the front slip total moment represents a total moment generated by the front wheel slip moment on the vehicle center of mass; Obtaining a debiasing motion torque according to the rear yaw moment difference, the front yaw total moment, the additional yaw torque and an ideal steady state of the vehicle; wherein the ideal steady state of the vehicle includes no additional yaw torque; A feedforward angle is obtained according to the debiasing motion torque, the front wheel cornering torque, the rear wheel cornering torque and ramp influence characteristics.

2. The method for controlling driving on a ramp according to claim 1, characterized in that: The step of obtaining the vehicle side slip data based on the current vehicle speed and the power parameter of the vehicle comprises: Obtaining wheel slip data of the vehicle according to the current vehicle speed and the power parameter; wherein the wheel slip data includes a front wheel slip angle, a rear wheel slip angle, a front wheel slip moment, and a rear wheel slip moment; Subtract the vehicle center of mass slip angle from the rear wheel slip angle, and then multiply the result by the rear wheel slip moment to obtain a rear slip moment difference; The front wheel slip angle is added to the vehicle center of mass slip angle, and then multiplied by the front wheel slip moment to obtain the total front slip moment.

3. The method for controlling driving on a ramp according to claim 1, characterized in that: The step of obtaining the feedforward angle according to the debiasing motion torque, the front wheel cornering torque, the rear wheel cornering torque and the slope influence characteristic comprises: According to the slope angle of the road surface on which the vehicle is currently located, the turning angle ratio table is queried to obtain a target ratio; wherein the target ratio represents the ratio of the turning angle of the front axle of the vehicle to the turning angle of the rear axle of the vehicle; The ramp cornering moment is obtained by multiplying the rear wheel cornering moment by the target ratio, and the front-rear moment difference between the front wheel cornering moment and the ramp cornering moment is obtained; According to the debiasing motion torque and the front-rear torque difference, a feedforward front wheel angle is obtained; Obtaining a feedforward rear wheel steering angle according to the feedforward front wheel steering angle and the target ratio; The feedforward front wheel steering angle and the feedforward rear wheel steering angle are combined to obtain a feedforward steering angle.

4. The method for controlling driving on a ramp according to any one of claims 1 to 3, characterized in that: The vehicle data includes the current speed and power parameters of the vehicle; The step of obtaining the feedback turning angle of the vehicle based on the current vehicle data, the slope angle of the road surface and the ideal steady state of the vehicle comprises: The dynamic rates of the yaw rate and the sideslip angle of the center of mass in the two-degree-of-freedom model of the vehicle are set to zero, and the ideal yaw rate and the ideal sideslip angle of the center of mass are obtained; updating a state space equation of feedback control according to the vehicle speed, the power parameter, the ideal yaw rate and the ideal sideslip angle of the center of mass to obtain a current state space equation; Based on the slope angle of the road surface on which the vehicle is currently located, a linear quadratic regulator is used to solve the current state space equation to obtain the feedback steering angle of the vehicle.

5. The method for controlling driving on a ramp according to claim 4, characterized in that: The current state space equation includes a variable matrix consisting of an ideal yaw rate, an ideal center-of-mass sideslip angle, and the vehicle's current center-of-mass sideslip angle and yaw rate; The step of solving the current state space equation using a linear quadratic regulator based on the slope angle of the road surface currently located by the vehicle to obtain the feedback turning angle of the vehicle comprises: According to the slope angle of the road on which the vehicle is currently located, and the reference weights of the front axle angle and the rear axle angle, the current front axle angle weight and the rear axle angle weight are obtained; Constructing an R weight matrix with the current front axle angle weight and the rear axle angle weight, and solving the current state space equation using a linear quadratic regulator, the R weight matrix and a default Q weight matrix to obtain a feedback control matrix; A feedback angle is obtained according to the feedback control matrix and the variable matrix.

6. The method for controlling driving on a ramp according to any one of claims 1 to 3, characterized in that: The step of obtaining the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle comprises: For each wheel, a longitudinal force of the wheel is obtained according to the driving torque of the wheel; the wheels include a front left wheel, a front right wheel, a rear left wheel and a rear right wheel; According to the longitudinal forces of the front left wheel and the front right wheel, a front wheel force difference is obtained; According to the longitudinal forces of the rear left wheel and the rear right wheel, a rear wheel force difference is obtained; An additional yaw torque is obtained according to the front wheel force difference, the rear wheel force difference longitudinal and the vehicle track.

7. The method for controlling driving on a ramp according to any one of claims 1 to 3, characterized in that: The method further comprises: According to the vehicle's whole vehicle motion information and wheel motion information, detect whether the vehicle is started on a ramp; If so, the step of obtaining the additional yaw torque of the vehicle according to the driving torque of each wheel of the vehicle is executed.

8. The method for controlling driving on a ramp according to claim 7, characterized in that: The vehicle is provided with a slope force sensor, the whole vehicle motion information includes the vehicle's accelerator pedal signal, vehicle speed and speed in each direction, and the wheel motion information includes the driving torque and rotation angle of each wheel; The step of detecting whether the vehicle is started on a ramp according to the vehicle movement information and wheel movement information includes: detecting whether the accelerator pedal signal and the vehicle speed meet a start condition; If yes, then according to the vehicle's speed in each direction, as well as the driving torque and the turning angle of each wheel, the adhesion coefficient of the road surface on which each wheel is located is obtained; When each of the adhesion coefficients meets the conditions of the split road working condition, the slope angle of the road on which the vehicle is located is obtained according to the vehicle speed and the unit mass ramp force measured by the ramp force sensor; When the slope angle is greater than the angle threshold, it is determined that the vehicle is started on an oncoming ramp.

9. A vehicle, characterized in that: It comprises a controller and a vehicle body, wherein the controller comprises a processor and a memory, wherein the memory stores a computer program that can be executed by the processor, and the processor can execute the computer program to implement the ramp driving control method as described in any one of claims 1 to 8.

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