Vehicle lateral stability control method, device, equipment and storage medium

Abstract

The application provides a vehicle driving lateral stability control method, device, equipment and storage medium, in upper layer control, a slip controller is used to calculate an additional yaw moment of the whole vehicle based on a mass center side slip angle and a yaw angular velocity; in lower layer control, the additional yaw moment obtained through the upper layer control is used to distribute the tire torque based on tire adhesion utilization, and a minimum tire adhesion utilization is used as an optimization target; wherein in the upper layer control, the weight coefficient value is determined by using a fuzzy rule based on the deviation of the mass center side slip angle and the yaw angular velocity, the weight coefficient value is adaptively adjusted according to the motion state of the vehicle, and the lateral stability of the distributed electric drive vehicle during driving is effectively improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of vehicle control, and particularly relates to a vehicle driving lateral stability control method, device, equipment and storage medium. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute the prior art.

[0003] In recent years, with the development of the automobile industry, the research and application of electric vehicles have become an effective means to solve environmental pollution and energy crisis. The torque of each wheel of a distributed drive electric vehicle can be controlled by a wheel hub motor, which shows good maneuverability and control flexibility, and also provides more possibilities for improving the driving stability and safety of the vehicle.

[0004] In the design of the driving stability control algorithm of a vehicle (for example, a distributed drive electric vehicle), most studies take the centroid side slip angle and yaw rate as the joint control target, without considering the coupling relationship between the two. In the controller design, the weight coefficient of the control variable is a fixed value, which cannot be adaptively adjusted with the change of the driving condition and the motion state of the vehicle, thereby affecting the lateral stability of the distributed electric drive vehicle during driving. SUMMARY

[0005] To overcome the shortcomings of the prior art, the present application provides a vehicle driving lateral stability control method, device, equipment and storage medium, which can improve the lateral stability of a distributed electric drive vehicle during driving.

[0006] The technical solution is as follows:

[0007] On the one hand, a vehicle driving lateral stability control method is provided, which comprises:

[0008] obtaining the current centroid side slip angle and yaw rate of the vehicle;

[0009] taking the deviation of the centroid side slip angle and the deviation of the yaw rate as the input of a fuzzy controller, and determining the weight coefficient of the centroid side slip angle and the yaw rate by using fuzzy control rules;

[0010] based on the obtained weight coefficient, taking the centroid side slip angle and the yaw rate as the control target, and determining the additional yaw moment based on a sliding mode controller;

[0011] combining the calculated additional yaw moment, taking the minimum utilization rate of tire adhesion as the optimization target, determining the target wheel torque of each drive wheel of the vehicle, and controlling the driving of the vehicle according to the target wheel torque.

[0012] In another aspect, a vehicle driving lateral stability control system is provided, comprising:

[0013] an acquisition module configured to acquire a current vehicle mass center side slip angle and a yaw rate of the vehicle;

[0014] a first determination module configured to determine a weight coefficient of the mass center side slip angle and the yaw rate by using a fuzzy control rule with a deviation of the mass center side slip angle and a deviation of the yaw rate as inputs of a fuzzy controller;

[0015] a second determination module configured to determine an additional yaw moment based on a sliding mode controller with the mass center side slip angle and the yaw rate as control targets based on the weight coefficient;

[0016] a control module configured to determine target wheel torques of each driving wheel of the vehicle with a minimum tire adhesion utilization as an optimization target in combination with the calculated additional yaw moment, and to control driving of the vehicle according to the target wheel torques.

[0017] In another aspect, a computer device is provided, comprising a processor and a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor to enable the computer device to implement any of the above-mentioned vehicle driving lateral stability control methods.

[0018] In another aspect, a computer readable storage medium is also provided, the computer readable storage medium storing at least one computer program, the at least one computer program being loaded and executed by a processor to enable a computer to implement any of the above-mentioned vehicle driving lateral stability control methods.

[0019] In another aspect, a computer program product or computer program is also provided, the computer program product or computer program comprising computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to implement any of the above-mentioned vehicle driving lateral stability control methods.

[0020] The above one or more technical solutions have the following beneficial effects:

[0021] In the application, the calculation of the whole vehicle additional yaw moment is realized based on the sliding mode controller taking the centroid side slip angle and yaw rate as the control target, as the upper control; the tire force moment is distributed based on the additional yaw moment obtained by the upper control, taking the minimum tire adhesion utilization rate as the optimization target, as the lower control; wherein in the upper control, the weight coefficient value is determined by the deviation of the centroid side slip angle and the yaw rate using fuzzy rules, realizing the adaptive adjustment of the weight coefficient with the motion state of the vehicle, which can effectively improve the lateral stability of the distributed electric drive vehicle during driving.

[0022] Advantages of the additional aspects of the application will be partially given in the following description, partially will become obvious from the following description, or will be understood by the practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0023] The accompanying drawings, which form a part of the specification, are included to provide a further understanding of the application and are incorporated herein by reference. The illustrations are shown for the purpose of enabling those skilled in the art to implement the application and not intended to limit the scope of the application.

[0024] Figure 1 A vehicle driving lateral stability control method flowchart provided by the embodiment of the application;

[0025] Figure 2(a) is a centroid side slip angle deviation membership function schematic diagram provided by the embodiment of the application;

[0026] Figure 2(b) is a yaw rate deviation membership function schematic diagram provided by the embodiment of the application;

[0027] Figure 3 A fuzzy control rule output variable membership function schematic diagram provided by the embodiment of the application;

[0028] Figure 4 A server structure schematic diagram provided by the embodiment of the application;

[0029] Figure 5 A terminal structure schematic diagram provided by the embodiment of the application. DETAILED DESCRIPTION

[0030] It should be noted that the following detailed description is exemplary, and is intended to provide further explanation of the application. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the application belongs.

[0031] It should be noted that the terms used herein are only for the purpose of describing the specific embodiments, and are not intended to limit the exemplary embodiments according to the application.

[0032] In the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0033] One embodiment of the present application provides a vehicle control system. The vehicle control system comprises a data acquisition component, a vehicle controller, a sliding mode controller, a fuzzy controller, a longitudinal speed controller and a drive motor.

[0034] The data acquisition component is a collection of sensor components for acquiring various driving state data of the vehicle during driving. For example, a yaw rate sensor for acquiring the yaw rate of the vehicle, a center of mass side slip angle estimator for acquiring the center of mass side slip angle of the vehicle, and a wheel speed sensor for acquiring the wheel speed.

[0035] The fuzzy controller is a controller using fuzzy rule control mode, which can output corresponding weight coefficients according to the obtained current driving state data (vehicle yaw rate and center of mass side slip angle).

[0036] The sliding mode controller is a controller using fuzzy sliding mode control mode, which can output the additional yaw moment of the vehicle according to the obtained current driving state data (vehicle yaw rate and center of mass side slip angle).

[0037] The longitudinal speed controller is a controller using PID control mode, which can output the total driving force of the vehicle according to the obtained current driving state data (vehicle speed).

[0038] It should be noted that in the present embodiment, the fuzzy controller, the sliding mode controller and the longitudinal speed controller can also be embodied in the form of control strategies, and do not need to be separately provided outside the vehicle controller.

[0039] The vehicle controller has different names according to different electric drive vehicles. When the electric drive vehicle is a pure electric vehicle, the vehicle controller can be a vehicle control unit (VCU). In addition, the vehicle controller can also be a chip, device or vehicle computer loaded with a vehicle monitoring and management system (VMS). In the present embodiment, the vehicle controller can obtain the output results of the fuzzy controller, the sliding mode controller and the longitudinal speed controller. In the present embodiment, the vehicle controller further comprises a control decision execution module for determining the output target torque.

[0040] The vehicle controller can be connected to the drive motor through a communication cable.

[0041] The drive motor is a component for receiving the control signal sent by the vehicle controller and providing power to the wheels according to the control signal. According to the position where it is arranged, the drive motor can be divided into a front drive motor and a rear drive motor.

[0042] It should be noted that in the embodiments of the present application, the communication cable can be an automotive bus. The automotive bus can be at least one of a Controller Area Network (CAN) bus, a Local Interconnect Network (LIN) bus, or a Vehicle Area Network (VAN) bus.

[0043] As shown in Figure 1 The embodiments provide a vehicle lateral stability control method, which comprises the following steps:

[0044] Step 101: acquiring the current vehicle mass center side slip angle and yaw rate.

[0045] In one possible implementation, a sensor is arranged on the vehicle to collect the mass center side slip angle and the yaw rate, such as a yaw rate sensor to collect the vehicle yaw rate and a mass center side slip angle estimator to collect the vehicle mass center side slip angle.

[0046] Step 102: taking the deviation of the mass center side slip angle and the deviation of the yaw rate as the input of the fuzzy controller, and determining the weight coefficient of the mass center side slip angle and the yaw rate by using the fuzzy control rule.

[0047] In order to make the vehicle more stable in lateral driving, the coupling relationship between the mass center side slip angle and the yaw rate is considered, the weight coefficient is actively and adaptively modified by using the fuzzy control rule, and the lateral stability of the distributed electric drive vehicle in driving is improved.

[0048] Step 103: based on the obtained weight coefficient, taking the mass center side slip angle and the yaw rate as the control target, and determining the additional yaw moment based on the sliding mode controller;

[0049] Step 104: combining the calculated additional yaw moment, taking the minimum tire adhesion utilization rate as the optimization target, determining the target wheel torque of each drive wheel of the vehicle, and controlling the driving of the vehicle according to the target wheel torque.

[0050] The vehicle driving lateral stability control method disclosed by the embodiments of the present application comprises: in the upper layer control, the slip center side deflection angle and the yaw rate are taken as the control targets, and a whole vehicle additional yaw moment is calculated based on a slip controller; in the lower layer control, the additional yaw moment obtained by the upper layer control is taken as the optimization target, and the vehicle tire force moment is distributed based on the tire adhesion utilization rate; wherein, in the upper layer control, the weight coefficient value is determined by the deviation of the slip center side deflection angle and the yaw rate, and the weight coefficient is adaptively adjusted according to the motion state of the vehicle, so that the lateral stability of the distributed electric drive vehicle during driving is effectively improved.

[0051] Optionally, the deviation of the slip center side deflection angle and the deviation of the yaw rate are determined as follows:

[0052] A linear two-degree-of-freedom vehicle reference model is constructed based on the two degrees of freedom of the lateral motion and the yaw motion of the vehicle.

[0053] According to the constructed linear two-degree-of-freedom vehicle reference model, the ideal value of the slip center side deflection angle and the ideal value of the yaw rate are obtained.

[0054] Based on the current obtained slip center side deflection angle and yaw rate, and the corresponding ideal values, the deviation of the slip center side deflection angle and the deviation of the yaw rate are determined.

[0055] Optionally, the fuzzy rule is specifically as follows:

[0056] The fuzzy subsets of the input variables are set as "negative large, negative medium, negative small, zero, positive small, positive medium, and positive large";

[0057] The fuzzy domain of the input variables is set as [-0.1, 0.1], and the fuzzy domain of the output variables is set as [0, 1].

[0058] In one possible embodiment, the deviation of the slip center side deflection angle and the deviation of the yaw rate are taken as the input of the fuzzy controller, and the weight coefficient of the slip center side deflection angle and the yaw rate is determined by using the fuzzy control rule, which is specifically as follows:

[0059] When the deviation of the slip center side deflection angle and the deviation of the yaw rate are the same, the weight coefficient value is a first set value;

[0060] When the deviation of the slip center side deflection angle and the deviation of the yaw rate are both zero, the weight coefficient value is a second set value;

[0061] When the deviation of the slip center side deflection angle is not zero and the deviation of the yaw rate is zero, the weight coefficient value is a third set value;

[0062] When the deviation of the centroid side slip angle is zero and the deviation of the yaw rate is not zero, the weight coefficient takes a second set value; wherein the second set value is less than the first set value, and the first set value is less than the third set value.

[0063] Optionally, in the determination of the additional yaw moment based on the sliding mode controller, a saturation function is used to replace a sign function to weaken chattering.

[0064] Optionally, in combination with the calculated additional yaw moment, a target wheel torque of each drive wheel of the vehicle is determined by taking the minimum utilization rate of tire adhesion as an optimization target, specifically:

[0065] A constraint condition of the optimization target is constructed; the constraint condition includes tire longitudinal force constraints subjected to friction ellipses and road adhesion coefficients, motor torque constraints, vehicle drive force constraints, and yaw moment constraints;

[0066] Based on the constraint condition, the optimization target is converted into a quadratic programming problem for solving to determine the target wheel torque of each drive wheel of the vehicle.

[0067] Optionally, the vehicle drive force is determined by: acquiring a current driving speed of the vehicle, taking the current driving speed of the vehicle and a target speed as inputs of a PID controller, and obtaining a total drive force of the vehicle.

[0068] One embodiment of the present application provides a determination method of a deviation of a centroid side slip angle and a deviation of a yaw rate, specifically:

[0069] A front wheel rotation angle is taken as a control input, and two degrees of freedom of vehicle lateral motion and yaw motion are considered. The ideal centroid side slip angle and the yaw rate of the vehicle are calculated to provide ideal reference values for the design of a subsequent controller.

[0070] The motion differential equation of the two-degree-of-freedom vehicle model is:

[0071]

[0072] In the formula, k f ,k r are total side stiffness of front and rear tires of the vehicle; a and b are distances from the centroid of the vehicle to front and rear axles; v x is a longitudinal speed of the vehicle, and m is a total mass of the vehicle.

[0073] When the vehicle travels at a constant speed to reach a steady state, then the ideal centroid side slip angle and the yaw rate of the vehicle are:

[0074]

[0075] In the formula, L is a wheelbase of the vehicle, and K is a stability factor.

[0076]

[0077] In order to better maintain the consistency of the driving direction of the vehicle, the ideal mass center side slip angle is defined as:

[0078] β d = 0 (4)

[0079] Considering the limitation of the road adhesion coefficient on the vehicle yaw rate, the maximum value of the yaw rate is:

[0080]

[0081] In the formula, μ is the road adhesion coefficient; g is the acceleration of gravity.

[0082] Therefore, the ideal mass center side slip angle and the yaw rate reference value of the vehicle are:

[0083]

[0084] One embodiment of the application provides a wheel motor model, specifically:

[0085] The motor is simplified as a second-order transfer function to provide driving and braking for the vehicle:

[0086]

[0087] In the formula: T m is the actual output driving or braking torque of the wheel motor; is the expected driving or braking torque of the wheel motor; ξ is a physical constant of the motor, which is determined by the material and structure of the motor itself, and in this embodiment, 0.001 is taken.

[0088] One embodiment of the application provides a vehicle total driving force determination method, specifically:

[0089] In order to enable the vehicle to track the target vehicle speed, a longitudinal speed controller is designed based on a PID controller to control the driving or braking torque. The control input of the PID controller is the difference between the target vehicle speed and the actual vehicle speed, and the control output is the total driving force of the vehicle, which can be specifically written as:

[0090]

[0091] In the formula: e(t) = v xref -v x , which represents the difference between the target vehicle speed and the actual vehicle speed; F is the total driving force; K p , K i , K d respectively represent the proportional coefficient, integral coefficient and differential coefficient of the PID controller.

[0092] One embodiment of the present application provides an adaptive fuzzy sliding mode controller design, specifically:

[0093] The motion differential equation of the two-degree-of-freedom vehicle model after applying the additional yaw moment is:

[0094]

[0095] The sliding mode controller takes the deviation e β of the actual vehicle center of mass side slip angle from the ideal value and the deviation e ω of the actual vehicle yaw rate from the ideal value as the control target, and is defined as:

[0096] e = λe β + (1 - λ)e ω

[0097] = λ(β - β ref ) + (1 - λ)(ω - ω ref ) (10)

[0098] wherein λ is a weight coefficient, and 0 < λ < 1; β is the actual vehicle center of mass side slip angle; and ω is the actual vehicle yaw rate.

[0099] The sliding surface function s is defined as:

[0100]

[0101] wherein k is a sliding surface coefficient, and k > 0; and t is the simulation time.

[0102] The derivative of the sliding surface function s is:

[0103]

[0104] From equation (9), we have:

[0105]

[0106] Substituting equation (13) into equation (12), we have:

[0107]

[0108] The controller approaching rate is selected as the constant approaching rate:

[0109]

[0110] wherein η is a controller parameter, and η > 0.

[0111] Let Together with equations (14) and (15), the required additional yaw moment is:

[0112]

[0113] where I is the vehicle moment of inertia, β is the ideal center of mass side slip angle, ω is the ideal yaw rate, and ω is the actual yaw rate. z ref ref

[0114] In order to further weaken the chattering, the saturation function sat(s / Δ) is used to replace the sign function sgn(s), and the saturation function is defined as:

[0115]

[0116] where Δ is the thickness of the sliding mode boundary layer, and Δ>0.

[0117] Therefore, the final vehicle additional yaw moment is:

[0118]

[0119] The Lyapunov method is used to determine the stability of the vehicle control system, and the Lyapunov function is defined as:

[0120]

[0121] Taking the first derivative of equation (19) gives:

[0122]

[0123] Substituting equation (14) into equation (20) gives:

[0124]

[0125] Substituting equation (18) into equation (21) gives:

[0126]

[0127] Since the parameter η>0, then Therefore, the vehicle control system is stable.

[0128] The embodiment provides a design of a fuzzy controller, specifically:

[0129] The designed fuzzy controller takes the vehicle center of mass side slip angle deviation e β and the yaw rate deviation e ω as the control input, and takes the weight coefficient λ as the control output. The fuzzification of the input and output variables is determined by 7 language fuzzy subsets, namely "negative large" (NB), "negative medium" (NM), "negative small" (NS), "zero" (ZO), "positive small" (PS), "positive medium" (PM), and "positive large" (PB). The input variables e β and e ω ​​​The fuzzy domain of the input variable is [-0.1, 0.1], and the fuzzy domain of the output variable λ is [0, 1]. The membership functions of the input and output variables are shown in FIG. 2(a), FIG. 2(b) and Figure 3

[0130] The fuzzy control rules are formulated according to the changes of the side slip angle deviation e β and the yaw rate deviation e ω , and the formulation of the fuzzy control rules is summarized as follows:

[0131] (1) When e β and e ω are the same, the weight coefficient λ is 0.5;

[0132] (2) When e β and e ω are both zero, the weight coefficient λ is 0;

[0133] (3) When e β is not zero and e ω is zero, the weight coefficient λ is 1;

[0134] (4) When e β is zero and e ω is not zero, the weight coefficient λ is 0;

[0135] (5) When e β is larger and e ω is smaller, the weight coefficient λ is greater than 0.5 and less than 1;

[0136] (6) When e β is smaller and e ω is larger, the weight coefficient λ is greater than 0 and less than 0.5;

[0137] The fuzzy control rules formulated based on the above analysis are shown in Table 1.

[0138] Table 1: Fuzzy control rules

[0139]

[0140] The embodiment provides a torque distribution control method, in particular:

[0141] The tire adhesion utilization rate is minimized as an optimization target, the torque is distributed, and the vehicle driving stability can be effectively improved. Therefore, the optimization target function is designed as:

[0142]

[0143] In the formula, F xi , F yi , F zi ​respectively, represent the longitudinal force, lateral force and vertical load of the tire; μ represents the road adhesion coefficient, i = fl, fr, rl, rr represent the left rear wheel of the tractor, the right rear wheel of the tractor, the left wheel of the trailer and the right wheel of the trailer, respectively.

[0144] Since the lateral force has little effect on the yaw moment, the effect of the lateral force is ignored when designing the optimization objective function, and the simplified optimization objective function is:

[0145]

[0146] Since the longitudinal force of the tire is limited by the friction ellipse and the road adhesion coefficient, the constraint condition can be written as:

[0147]

[0148] In addition, it should also be limited by the motor torque, and the constraint condition is:

[0149]

[0150] When distributing the torque, the constraint expression of the vehicle driving force and the yaw moment equation should also be satisfied:

[0151]

[0152] Where, F xd represents the vehicle driving force, which is equal to the total driving force of the vehicle calculated by formula (8).

[0153] When the current wheel rotation angle is very small, cosδ f = 1, formula (27) is converted into a matrix form constraint expression:

[0154] B eq = A eq U (28)

[0155] In the formula: the output matrix B eq = [F xd M z ] T ; the coefficient matrix The input matrix U = [F xfl F xfr F xrl F xrr ] T .

[0156] The above problem is arranged into a standard quadratic programming form:

[0157]

[0158]

[0159] Solving the above quadratic programming problem, torque distribution of each drive wheel is realized.

[0160] The application provides a vehicle driving lateral stability control system, comprising:

[0161] An acquisition module is configured to acquire a current vehicle center-of-gravity side slip angle and a yaw rate;

[0162] A first determination module is configured to take a deviation of the center-of-gravity side slip angle and a deviation of the yaw rate as fuzzy controller inputs, and determine a weight coefficient of the center-of-gravity side slip angle and the yaw rate by using fuzzy control rules;

[0163] A second determination module is configured to determine an additional yaw moment based on a sliding mode controller, taking the center-of-gravity side slip angle and the yaw rate as control targets based on the obtained weight coefficient;

[0164] A control module is configured to determine target wheel torques of each drive wheel of the vehicle by taking the calculated additional yaw moment and taking minimum tire adhesion utilization as an optimization target, and control driving of the vehicle according to the target wheel torques.

[0165] Optionally, the first determination module comprises:

[0166] A first sub-determination module is configured to construct a linear two-degree-of-freedom vehicle reference model based on two degrees of freedom of lateral motion and yaw motion of the vehicle;

[0167] A second sub-determination module is configured to obtain ideal values of the center-of-gravity side slip angle and the yaw rate according to the constructed linear two-degree-of-freedom vehicle reference model;

[0168] A third sub-determination module is configured to determine the deviation of the center-of-gravity side slip angle and the deviation of the yaw rate based on the currently acquired center-of-gravity side slip angle and the yaw rate and the respective ideal values.

[0169] Optionally, the first determination module further comprises:

[0170] A fourth sub-determination module is configured to set fuzzy subsets of input variables as “negative large, negative medium, negative small, zero, positive small, positive medium, and positive large”;

[0171] A fifth sub-determination module is configured to set a fuzzy domain of output variables as [0, 1];

[0172] Optionally, the first determination module further comprises:

[0173] A seventh sub-determination module is configured to take the weight coefficient as a first set value when the deviation of the center-of-gravity side slip angle and the deviation of the yaw rate are the same.

[0174] The eighth sub-determination module is configured to take the weight coefficient as a second set value when the deviation of the centroid side slip angle and the deviation of the yaw rate are both zero;

[0175] The ninth sub-determination module is configured to take the weight coefficient as a third set value when the deviation of the centroid side slip angle is not zero and the deviation of the yaw rate is zero.

[0176] The tenth sub-determination module is configured to take the weight coefficient as the second set value when the deviation of the centroid side slip angle is zero and the deviation of the yaw rate is not zero; wherein the second set value is less than the first set value, and the first set value is less than the third set value.

[0177] Optionally, the second determination module comprises: replacing a sign function with a saturation function in the determination of the additional yaw moment based on the sliding mode controller, so as to weaken chattering.

[0178] Optionally, the control module comprises:

[0179] The construction sub-module is configured to construct a constraint condition of the optimization target; the constraint condition comprises a tire longitudinal force constraint subjected to a friction ellipse and a road adhesion coefficient constraint, a motor torque constraint, a vehicle driving force constraint, and a yaw moment constraint.

[0180] The solution sub-module is configured to convert the optimization target into a solution of a quadratic programming problem based on the constraint condition, and determine a target wheel torque of each drive wheel of the vehicle.

[0181] Optionally, the construction sub-module comprises:

[0182] The driving sub-module is configured to obtain a current driving speed of the vehicle, and take the current driving speed of the vehicle and a target vehicle speed as inputs of a PID controller to obtain a total driving force of the vehicle.

[0183] It should be noted that the apparatus provided in the above embodiments is only used as an example to divide the above functional modules, and in actual functions, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is described in detail in the method embodiments, which will not be described here.

[0184] Figure 4is a structural schematic diagram of a server provided by an embodiment of the present application. The server can have great differences due to different configurations or performances, and can include one or more processors 1101 and one or more memories 1102, wherein the one or more memories 1102 store at least one computer program, the at least one computer program is loaded and executed by the one or more processors 1101, so that the server implements the vehicle driving lateral stability control method provided by each method embodiment. Of course, the server can also have a wired or wireless network interface, a keyboard, and an input and output interface and other components for realizing the functions of the device, so as to input and output. The server can also include other components for realizing the functions of the device, which will not be described here.

[0185] Figure 5 is a structural schematic diagram of a terminal provided by an embodiment of the present application. The terminal can be, for example, a vehicle terminal, a smart phone, a tablet computer, a player, a notebook computer or a desktop computer. The terminal can also be referred to as user equipment, a portable terminal, a laptop terminal, a desktop terminal, and other names.

[0186] Generally, the terminal includes a processor 1501 and a memory 1502.

[0187] The processor 1501 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 1501 can be implemented in at least one of the hardware forms of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), and a PLA (Programmable Logic Array). The processor 1501 can also include a main processor and a coprocessor. The main processor is a processor for processing data in an awake state, also known as a CPU (Central Processing Unit). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 1501 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content required to be displayed by the display screen. In some embodiments, the processor 1501 can also include an AI (Artificial Intelligence) processor for processing machine learning-related computing operations.

[0188] The memory 1502 can include one or more computer-readable storage media. The computer-readable storage media can be non-transitory. The memory 1502 can also include high-speed random access memory and can include nonvolatile memory, such as one or more magnetic disk storage devices, optical storage devices, flash memory devices, or other nonvolatile solid-state storage devices. In some embodiments, the non-transitory computer-readable storage medium of the memory 1502 is used to store at least one instruction for execution by the processor 1501 to cause the terminal to implement the vehicle lateral stability control method provided by the method embodiments of the present application.

[0189] In some embodiments, the terminal can further include a peripheral device interface 1503 and at least one peripheral device. The processor 1501, the memory 1502, and the peripheral device interface 1503 can be connected by a bus or a signal line. Each peripheral device can be connected to the peripheral device interface 1503 through a bus, a signal line, or a circuit board. Specifically, the peripheral device includes at least one of a radio frequency circuit 1504, a display screen 1505, a camera assembly 1506, an audio circuit 1507, and a power supply 1508.

[0190] The peripheral device interface 1503 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 1501 and the memory 1502. In some embodiments, the processor 1501, the memory 1502, and the peripheral device interface 1503 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 1501, the memory 1502, and the peripheral device interface 1503 can be implemented on a separate chip or circuit board, and the present embodiment is not limited in this regard.

[0191] The radio frequency circuit 1504 is configured to receive and send RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 1504 communicates with communication networks and other communication devices through electromagnetic signals. The radio frequency circuit 1504 converts electrical signals into electromagnetic signals for transmission, or converts electromagnetic signals received into electrical signals. Optionally, the radio frequency circuit 1504 includes an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a subscriber identity module card, and the like. The radio frequency circuit 1504 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to, a metropolitan area network, various generations of mobile communication networks (2G, 3G, 4G, and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 1504 can also include NFC (Near Field Communication) related circuitry, which is not limited in the present application.

[0192] The display screen 1505 is configured to display a UI (User Interface). The UI can include graphics, text, icons, video, and any combination thereof. When the display screen 1505 is a touch display screen, the display screen 1505 also has the ability to collect touch signals on or above the surface of the display screen 1505. The touch signals can be input as control signals to the processor 1501 for processing. At this time, the display screen 1505 can also be used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the display screen 1505 can be one, arranged on the front panel of the terminal; in other embodiments, the display screen 1505 can be at least two, arranged on different surfaces of the terminal or in a folding design; in other embodiments, the display screen 1505 can be a flexible display screen, arranged on a curved surface or a folding surface of the terminal. Even, the display screen 1505 can also be arranged in an irregular shape, that is, a special-shaped screen. The display screen 1505 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0193] The camera component 1506 is configured to capture images or videos. Optionally, the camera component 1506 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is disposed on the front panel of the terminal, and the rear-facing camera is disposed on the back of the terminal. In some embodiments, the rear-facing camera is at least two, which are any one of a main camera, a depth-of-field camera, a wide-angle camera, and a telephoto camera, to realize the background blur function by fusing the main camera and the depth-of-field camera, the panorama shooting and VR (Virtual Reality) shooting function by fusing the main camera and the wide-angle camera, or other fusion shooting functions. In some embodiments, the camera component 1506 can further include a flash. The flash can be a single-color-temperature flash or a dual-color-temperature flash. The dual-color-temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0194] The audio circuit 1507 can include a microphone and a speaker. The microphone is configured to capture sound waves of a user and an environment, and convert the sound waves into an electrical signal input to the processor 1501 for processing or to the radio frequency circuit 1504 to realize voice communication. For the purpose of stereo sound collection or noise reduction, the microphone can be multiple, which are respectively disposed at different parts of the terminal. The microphone can also be an array microphone or an omnidirectional collection microphone. The speaker is configured to convert an electrical signal from the processor 1501 or the radio frequency circuit 1504 into sound waves. The speaker can be a traditional diaphragm speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert an electrical signal into a sound wave audible to humans, but also convert an electrical signal into an inaudible sound wave to humans for ranging purposes, etc. In some embodiments, the audio circuit 1507 can further include a headphone jack.

[0195] The power supply 1508 is configured to supply power to each component in the terminal. The power supply 1508 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 1508 includes a rechargeable battery, the rechargeable battery can support wired charging or wireless charging. The rechargeable battery can also be used to support fast charging technology.

[0196] In some embodiments, the terminal further includes one or more sensors 1509. The one or more sensors 1509 include, but are not limited to, an acceleration sensor 1510, a gyroscope sensor 1511, a pressure sensor 1512, an optical sensor 1513, and a proximity sensor 1514.

[0197] The acceleration sensor 1510 can detect the acceleration magnitude in three coordinate axes of a coordinate system established by the terminal. For example, the acceleration sensor 1510 can be used to detect the components of the gravitational acceleration in three coordinate axes. The processor 1501 can control the display screen 1505 to display the user interface in a landscape view or a portrait view according to the gravitational acceleration signals collected by the acceleration sensor 1510. The acceleration sensor 1510 can also be used for game or user motion data collection.

[0198] The gyroscope sensor 1511 can detect the body orientation and rotation angle of the terminal. The gyroscope sensor 1511 can work with the acceleration sensor 1510 to collect the 3D motion of the user to the terminal. The processor 1501 can implement the following functions according to the data collected by the gyroscope sensor 1511: motion sensing (e.g., changing the UI according to the user's tilt operation), image stabilization when shooting, game control, and inertial navigation.

[0199] The pressure sensor 1512 can be arranged on the side frame of the terminal and / or the lower layer of the display screen 1505. When the pressure sensor 1512 is arranged on the side frame of the terminal, the user's holding signal to the terminal can be detected, and the left-hand or right-hand recognition or shortcut operation can be performed by the processor 1501 according to the holding signal collected by the pressure sensor 1512. When the pressure sensor 1512 is arranged on the lower layer of the display screen 1505, the controllable control on the UI interface can be controlled by the processor 1501 according to the user's pressure operation on the display screen 1505. The controllable control includes at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0200] The optical sensor 1513 is used to collect the ambient light intensity. In one embodiment, the processor 1501 can control the display brightness of the display screen 1505 according to the ambient light intensity collected by the optical sensor 1513. Specifically, when the ambient light intensity is high, the display brightness of the display screen 1505 is increased; when the ambient light intensity is low, the display brightness of the display screen 1505 is decreased. In another embodiment, the processor 1501 can also dynamically adjust the shooting parameters of the camera assembly 1506 according to the ambient light intensity collected by the optical sensor 1513.

[0201] The proximity sensor 1514, also known as a distance sensor, is usually arranged on the front panel of the terminal. The proximity sensor 1514 is used to collect the distance between the user and the front of the terminal. In one embodiment, when the proximity sensor 1514 detects that the distance between the user and the front of the terminal gradually decreases, the display screen 1505 is switched from the bright screen state to the screen-off state by the processor 1501; when the proximity sensor 1514 detects that the distance between the user and the front of the terminal gradually increases, the display screen 1505 is switched from the screen-off state to the bright screen state by the processor 1501.

[0202] Those skilled in the art can understand that, Figure 5 The structure shown in the figures does not constitute a limitation on the terminal, and can include more or fewer components than shown, or combine certain components, or adopt a different component arrangement.

[0203] In an example embodiment, a computer device is also provided, which includes a processor and a memory having at least one computer program stored therein. The at least one computer program is loaded and executed by one or more processors to enable the computer device to implement any of the vehicle lateral stability control methods of the vehicle described above.

[0204] In an example embodiment, a computer readable storage medium is also provided, which stores at least one computer program, which is loaded and executed by a processor of a computer device to enable the computer to implement any of the vehicle lateral stability control methods of the vehicle described above.

[0205] In a possible implementation manner, the computer readable storage medium described above can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0206] In an example embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to enable the computer device to perform any of the vehicle lateral stability control methods of the vehicle described above.

[0207] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.), and signals involved in the present application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data need to comply with relevant laws, regulations, and standards of relevant countries and regions. For example, the relevant information of the vehicle involved in the present application is obtained under full authorization.

[0208] The above only describes example embodiments of the present application and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

[0209] The above description of the preferred embodiments of the application has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the application to the precise form described, and many modifications and variations are possible in light of the teaching above. The described embodiments were chosen and described in order to best explain the principles of the application and its best mode practical application. It is intended that the scope of the application be defined by the claims appended hereto and their equivalents.

Claims

1. A vehicle lateral stability control method, characterized by, The method comprises the following steps: acquiring a current vehicle center of mass side slip angle and a yaw rate; using a fuzzy control rule to determine a weight coefficient of the center of mass side slip angle and the yaw rate, taking a deviation of the center of mass side slip angle and a deviation of the yaw rate as fuzzy controller inputs; based on the obtained weight coefficient, taking the center of mass side slip angle and the yaw rate as control targets, determining an additional yaw moment based on a sliding mode controller; combining the calculated additional yaw moment, determining target wheel torques of each drive wheel of the vehicle by taking minimum tire adhesion utilization as an optimization target, and controlling driving of the vehicle according to the target wheel torques. The determination of the deviation of the center of mass side slip angle and the deviation of the yaw rate specifically comprises: constructing a linear two-degree-of-freedom vehicle reference model based on two degrees of freedom of lateral motion and yaw motion of the vehicle; obtaining ideal values of the center of mass side slip angle and the yaw rate according to the constructed linear two-degree-of-freedom vehicle reference model; and determining the deviation of the center of mass side slip angle and the deviation of the yaw rate based on the currently acquired center of mass side slip angle and yaw rate and the ideal values corresponding thereto respectively.

2. The vehicle travel lateral stability control method according to claim 1, characterized by, The fuzzy control rule specifically comprises: setting fuzzy subsets of input variables as "negative large, negative medium, negative small, zero, positive small, positive medium, and positive large"; setting a fuzzy domain of the input variables as [-0.1, 0.1], and a fuzzy domain of output variables as [0, 1].

3. The vehicle travel lateral stability control method according to claim 1 or 2, characterized by, The determination of the weight coefficient of the center of mass side slip angle and the yaw rate by taking the deviation of the center of mass side slip angle and the deviation of the yaw rate as fuzzy controller inputs and using a fuzzy control rule specifically comprises: when the deviation of the center of mass side slip angle and the deviation of the yaw rate are the same, the weight coefficient takes a first set value; when the deviation of the center of mass side slip angle and the deviation of the yaw rate are both zero, the weight coefficient takes a second set value; when the deviation of the center of mass side slip angle is not zero and the deviation of the yaw rate is zero, the weight coefficient takes a third set value; and when the deviation of the center of mass side slip angle is zero and the deviation of the yaw rate is not zero, the weight coefficient takes the second set value; wherein the second set value is smaller than the first set value, and the first set value is smaller than the third set value.

4. The vehicle travel lateral stability control method according to claim 1, characterized by, In the determination of the additional yaw moment based on the sliding mode controller, a saturation function is used to replace a sign function to weaken chattering.

5. The vehicle travel lateral stability control method according to claim 1, characterized by, The determination of the target wheel torques of each drive wheel of the vehicle by taking the calculated additional yaw moment and minimum tire adhesion utilization as an optimization target specifically comprises: constructing a constraint condition of the optimization target; the constraint condition comprises tire longitudinal force constraints subjected to a friction ellipse and a road adhesion coefficient, motor torque constraints, vehicle drive force constraints, and yaw moment constraints; based on the constraint condition, the optimization target is converted into a quadratic programming problem for solving to determine the target wheel torques of each drive wheel of the vehicle.

6. The vehicle travel lateral stability control method according to claim 5, characterized by, The determination of the vehicle drive force comprises: acquiring a current driving speed of the vehicle, taking the current driving speed of the vehicle and a target speed as inputs of a PID controller, and obtaining a total drive force of the vehicle.

7. A vehicle lateral stability control device characterized by comprising: The method comprises the following steps: An acquisition module is configured to acquire a current vehicle center-of-gravity side slip angle and a yaw rate; A first determination module is configured to take a deviation of the center-of-gravity side slip angle and a deviation of the yaw rate as fuzzy controller inputs, and determine weight coefficients of the center-of-gravity side slip angle and the yaw rate by using fuzzy control rules; A second determination module is configured to determine an additional yaw moment based on a sliding mode controller, taking the center-of-gravity side slip angle and the yaw rate as control targets based on the obtained weight coefficients; and a control module is configured to determine target wheel torques of each drive wheel of the vehicle by taking tire adhesion utilization as an optimization target in combination with the calculated additional yaw moment, and control driving of the vehicle according to the target wheel torques.

8. A computer device, comprising: The computer device comprises a processor and a memory, and the memory stores at least one computer program, which is loaded and executed by the processor, so that the computer device implements the vehicle driving lateral stability control method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one computer program, which is loaded and executed by the processor, so that the computer implements the vehicle driving lateral stability control method according to any one of claims 1 to 6.

Images