Vehicle control method and related apparatus, device and medium

Abstract

This application discloses a vehicle control method and related devices, equipment, and media. The vehicle control method includes: determining vehicle stability parameters using first vehicle state data; selecting a control mode that matches the stability parameters from several preset control modes as a target control mode; wherein different preset control modes correspond to different steering and braking control strategies; and controlling the vehicle to drive according to the target control mode. In this method, adaptively selecting a suitable steering and braking control strategy based on the vehicle's stability parameters to control the vehicle can reduce the risk of vehicle loss of control and improve vehicle driving stability and safety.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a vehicle control method and related devices, equipment and media. Background Technology

[0002] In varying road conditions and complex driving environments, especially when road surface adhesion changes abruptly, vehicles are prone to instability, leading to traffic accidents. Therefore, improving vehicle stability and safety has become an urgent technical problem to be solved. Summary of the Invention

[0003] The main technical problem addressed by this application is to provide a vehicle control method and related devices, equipment, and media to improve vehicle driving stability and safety.

[0004] To solve the above-mentioned technical problems, one technical solution adopted in this application is: to provide a vehicle control method, the method comprising: determining the stability parameters of the vehicle using first vehicle state data; selecting a control mode that matches the stability parameters from a number of preset control modes as a target control mode; wherein the steering and braking control strategies corresponding to different preset control modes are different; and controlling the vehicle to drive according to the target control mode.

[0005] In one embodiment, several preset control modes include a first control mode, a second control mode, and a third control mode; wherein, the first control mode provides a first assist torque and an additional steering torque through the steering system and provides a first wheel braking force through the braking system, the second control mode provides a second assist torque and a steering wheel return torque through the steering system and provides a second wheel braking force through the braking system, and the third control mode provides a third assist torque through the steering system.

[0006] Selecting a control mode that matches the stability parameter from several preset control modes as the target control mode includes: determining the target range to which the stability parameter belongs; wherein the target range is one of the first range corresponding to the first control mode, the second range corresponding to the second control mode, and the third range corresponding to the third control mode, the lower limit of the first range is greater than or equal to the upper limit of the second range, and the lower limit of the second range is greater than or equal to the upper limit of the third range; and using the control mode corresponding to the target range as the target control mode.

[0007] In one embodiment, the step of determining the additional steering torque and the first wheel braking force in the first control mode includes: determining a target yaw moment using second vehicle state data; distributing the target yaw moment to obtain a target steering yaw moment and a target braking yaw moment; determining the additional steering torque using the target steering yaw moment; and determining the first wheel braking force using the target braking yaw moment.

[0008] In one embodiment, determining the target yaw moment using second vehicle state data includes: constructing a state tracking error term using the second vehicle state data; constructing a cost function using the state tracking error term and the yaw moment control term to perform model predictive control, thereby obtaining a first feedforward yaw moment; and determining the target yaw moment using the first feedforward yaw moment.

[0009] In one embodiment, determining the target yaw moment using a first feedforward yaw moment includes: using the first feedforward yaw moment as the target yaw moment; or, using the yaw rate error at the current moment and the historical accumulated yaw rate error to determine the feedback yaw moment; wherein the yaw rate error is the difference between the expected yaw rate and the actual yaw rate; and using the sum of the first feedforward yaw moment and the feedback yaw moment as the target yaw moment.

[0010] In one embodiment, torque distribution of the target yaw moment to obtain a target steering yaw moment and a target braking yaw moment includes: determining a first braking weight using at least one of a stability parameter, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment; using the first braking weight to distribute the target yaw moment to obtain a base steering yaw moment and a base braking yaw moment; determining the target steering yaw moment using the base steering yaw moment; and determining the target braking yaw moment using the base braking yaw moment.

[0011] In one embodiment, determining a first braking weight using at least one of a stability parameter, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment includes: weighting and summing at least one of the stability parameter, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment to obtain a second braking weight, wherein the steering wheel angle ratio at the current moment is the ratio of the absolute value of the steering wheel angle at the current moment to the maximum steering wheel angle; and adjusting the second braking weight based on the current driving condition, the maximum braking weight, and the minimum braking weight to obtain the first braking weight.

[0012] In one embodiment, adjusting a second braking weight based on the current driving condition, maximum braking weight, and minimum braking weight to obtain a first braking weight includes: in response to satisfying a first driving condition condition, determining a weight difference between the second braking weight and the first adjustment weight, and determining the larger of the weight difference and the minimum braking weight as the first braking weight; wherein the first driving condition condition includes: the absolute value of the steering wheel angle at the current moment is greater than a first steering wheel angle threshold, and the difference between the actual yaw rate at the current moment and the expected yaw rate at the current moment is greater than a yaw rate threshold; in response to satisfying the second driving condition condition, determining a first weight sum of the second braking weight and the second adjustment weight, and determining the smaller of the first weight sum and the maximum braking weight as the first braking weight. The weights are as follows: the second driving condition includes: the current steering wheel change direction is inconsistent with the system correction direction, and the absolute value of the steering wheel angle at the current moment is greater than the second steering wheel angle threshold; in response to satisfying the third driving condition, the second weight sum of the second braking weight and the third adjustment weight is determined, and the smaller value between the second weight sum and the maximum braking weight is determined as the first braking weight; the third driving condition includes: the road surface adhesion coefficient at the current moment is less than the road surface adhesion coefficient threshold; in response to not satisfying the first driving condition, the second driving condition, and the third driving condition, the smaller braking weight between the second braking weight and the maximum braking weight is determined, and the larger braking weight between the smaller braking weight and the minimum braking weight is determined as the first braking weight.

[0013] In one embodiment, determining the target steering yaw moment using the base steering yaw moment includes: using the sum of the base steering yaw moment and the intervention torque as the target steering yaw moment; wherein the intervention torque is obtained by corrective control using the difference between the actual yaw rate at the current moment and the desired yaw rate at the current moment; determining the target braking yaw moment using the base braking yaw moment includes: determining the torque difference between the base braking yaw moment and the braking adjustment torque; and determining the target braking yaw moment based on the torque difference.

[0014] In one embodiment, determining an additional steering torque using a target steering yaw moment includes: determining an additional front wheel steering angle increment using the target steering yaw moment; using the additional front wheel steering angle increment as a steering angle deviation and performing correction control to obtain the additional steering torque. And / or, determining a first wheel braking force using a target braking yaw moment includes: using the ratio of the target braking yaw moment to a preset distance as the braking force magnitude of the first wheel braking force; wherein the preset distance is half the vehicle's wheelbase; in the case of understeer, the first wheel braking force is the braking force of the inner rear wheel, and in the case of oversteer, the first wheel braking force is the braking force of the inner front wheel.

[0015] In one embodiment, a first assist curve is used to determine the first assist torque in the first control mode, a second assist curve is used to determine the second assist torque in the second control mode, and a third assist curve is used to determine the third assist torque in the third control mode. Each assist curve represents the relationship between the steering wheel torque and the assist torque provided by the steering system. The assist torque corresponding to the target steering wheel torque in the first assist curve is less than the assist torque corresponding to the target steering wheel torque in the second assist curve, and the assist torque corresponding to the target steering wheel torque in the second assist curve is less than the assist torque corresponding to the target steering wheel torque in the third assist curve.

[0016] In one embodiment, the first vehicle state data includes at least one of the yaw rate deviation rate, the lateral load transfer coefficient, and the steering wheel angle at the current moment; using the first vehicle state data, determining the vehicle's stability parameters includes: weighting each piece of the first vehicle state data to obtain the stability parameters.

[0017] To solve the above-mentioned technical problems, another technical solution adopted in this application is: to provide a vehicle control device, the device comprising: a determining module, used to determine the stability parameters of the vehicle using first vehicle state data; a selecting module, used to select a control mode that matches the stability parameters from a plurality of preset control modes as a target control mode; wherein the steering and braking control strategies corresponding to different preset control modes are different; and a control module, used to control the vehicle to drive according to the target control mode.

[0018] To solve the above-mentioned technical problems, another technical solution adopted in this application is: to provide an electronic device, including a memory and a processor coupled to each other, wherein the memory stores program instructions; and the processor is used to execute the program instructions stored in the memory to implement the above-mentioned vehicle control method.

[0019] To solve the above-mentioned technical problems, another technical solution adopted in this application is to provide a computer-readable storage medium for storing program instructions that can be executed by a processor to implement the above-mentioned vehicle control method.

[0020] The above scheme utilizes the first vehicle state data to determine the vehicle's stability parameters; it then selects a control mode that matches the stability parameters from several preset control modes as the target control mode. Different preset control modes correspond to different steering and braking control strategies. The vehicle is then controlled according to the target control mode. This method adaptively selects a suitable steering and braking control strategy based on the vehicle's stability parameters, reducing the risk of vehicle loss of control and improving vehicle stability and safety. Attached Figure Description

[0021] Figure 1This is a flowchart illustrating an embodiment of the vehicle control method provided in this application;

[0022] Figure 2 This is a flowchart illustrating an implementation method for determining the additional steering torque and the first wheel braking force in the first control mode, as provided in this application.

[0023] Figure 3 This is a schematic diagram of the structure of an embodiment of the vehicle control system provided in this application;

[0024] Figure 4 This is a schematic diagram of the framework of an embodiment of the vehicle control device provided in this application;

[0025] Figure 5 This is a schematic diagram of the framework of an embodiment of the electronic device provided in this application;

[0026] Figure 6 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium provided in this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0028] It should be noted that the term "and / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The terms "first" and "second" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, features defined as "first" or "second" may explicitly or implicitly include at least one of those features. The term "multiple" in this application means at least two, such as two, three, etc. The term "multiple" in this application means at least one. The term "several" in this application means at least two. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0029] Please see Figure 1 , Figure 1This is a schematic flowchart of an embodiment of the vehicle control method provided in this application. Figure 1 As shown, the method includes the following steps:

[0030] S11: Determine the vehicle's stability parameters using the first vehicle state data.

[0031] The stability parameter reflects the vehicle's stability. A smaller value indicates a more stable vehicle, while a larger value indicates a less stable vehicle. In step S11, the vehicle's stability parameter is determined using the first vehicle state data.

[0032] In one embodiment, the first vehicle state data includes at least one of the yaw rate deviation rate, the lateral load transfer coefficient, and the steering wheel angle at the current moment. For example, the first vehicle state data may only include the yaw rate deviation rate and the lateral load transfer coefficient at the current moment. Alternatively, the first vehicle state data may simultaneously include the yaw rate deviation rate, the lateral load transfer coefficient, and the steering wheel angle at the current moment.

[0033] The yaw rate deviation rate at the current moment measures the difference between the vehicle's actual yaw motion and its expected yaw motion at that moment. A smaller yaw rate deviation rate indicates that the vehicle is executing the driver's steering commands normally and is in a stable and controllable state; a larger yaw rate deviation rate indicates that the vehicle is closer to losing control. The yaw rate deviation rate at the current moment is further determined through the following steps:

[0034] Step 1: Determine the actual yaw rate at the current moment.

[0035] The actual yaw rate at the current moment can be obtained from the vehicle's inertial measurement unit (IMU).

[0036] Step 2: Determine the desired yaw rate at the current moment.

[0037] The desired yaw rate at the current moment can be determined by the following formula:

[0038]

[0039] Where v_x is the longitudinal vehicle speed at the current moment; L is the vehicle wheelbase, which is the distance from the center of the front axle to the center of the rear axle; K is the stability factor, used to describe the vehicle's steering characteristics; δ_sw is the steering wheel angle at the current moment; and i_sw is the steering system transmission ratio.

[0040] Step 3: Using the expected yaw rate at the current moment, the actual yaw rate at the current moment, and the maximum yaw rate, determine the yaw rate deviation rate at the current moment.

[0041] The yaw rate deviation at the current moment can be determined by the following formula:

[0042]

[0043] Where ω_err is the yaw rate deviation rate at the current moment, ω_act is the actual yaw rate at the current moment, ω_d is the expected yaw rate at the current moment, and ω_max is the maximum yaw rate, and ω_max is determined by the road surface adhesion coefficient μ.

[0044] Lateral load transfer refers to the process by which a vehicle tilts during cornering due to centrifugal force, causing some weight to shift from the inside wheels to the outside wheels. LTR (Lateral Load Transfer Ratio) is a dimensionless parameter used to quantify the degree of this transfer. LTR can be determined using the following formula:

[0045]

[0046] Where Fz_out represents the sum of the vertical loads on the outer wheels, and Fz_in represents the sum of the vertical loads on the inner wheels. For details on obtaining the sum of the vertical loads on the outer wheels, please refer to known related technologies; further explanation is not provided here.

[0047] The LTR value ranges from -1 to 1. When LTR=0, it means there is no load transfer, and the load on both wheels is equal (in static straight-line conditions or ideal cornering). When LTR=1, it means all the load has been transferred to the outer wheel, and the inner wheel is about to lift off the ground, which is an extremely dangerous point of loss of control. When LTR=-1, it means all the load has been transferred to the inner wheel, a situation that almost never occurs in normal cornering.

[0048] The steering wheel angle at any given moment is the driver's direct input to control the vehicle, reflecting the driver's strong desire to change the vehicle's direction. When the driver smoothly controls the steering wheel (i.e., the steering wheel angle changes slightly), the vehicle is usually in a stable and controllable state; when the driver sharply controls the steering wheel (i.e., the steering wheel angle changes significantly), it is easy to cause the vehicle to lose control.

[0049] In one embodiment, to ensure that the determined stability parameters more accurately reflect the stability of the vehicle and improve the reliability of subsequent vehicle control, the stability parameters can be determined by comprehensively analyzing the state data of each first vehicle. For example, the stability parameters can be obtained by weighting the state data of each first vehicle.

[0050] For example, the first vehicle state data includes the yaw rate deviation rate, the lateral load transfer coefficient, and the steering wheel angle at the current moment. In this example, the stability parameters can be determined using the following formula:

[0051]

[0052] Where k1, k2, and k3 are the yaw rate deviation rate, lateral load transfer coefficient, and steering wheel angle at the current moment, respectively. k1, k2, and k3 can be optimized and calibrated through extensive simulations and real-vehicle tests under various operating conditions. For example, the sum of k1, k2, and k3 is 1.

[0053] S12: Select the control mode that matches the stability parameters from several preset control modes as the target control mode.

[0054] Different preset control modes correspond to different steering and braking control strategies. The steering and braking control strategy corresponding to a preset control mode can be steering control only, braking control only, or a combination of steering and braking control.

[0055] In step S12, several preset control modes include a first control mode, a second control mode, and a third control mode.

[0056] The first control mode, also known as the emergency steering correction mode, is used when vehicle stability is low and there is a high risk of instability. It provides emergency steering correction by leveraging the steering system to deliver initial assist torque and additional steering torque, and the braking system to provide initial wheel braking force. The initial assist torque in this mode is a small amount of torque that the steering motor needs to output, determined based on the steering wheel torque operated by the driver. By designing a smaller initial assist torque, the driver feels a noticeable increase in steering wheel weight, essentially reminding them that "the vehicle is approaching its limits, please operate with caution." This also increases unintended steering wheel rotation, suppressing potential over-operation by the driver. In the first control mode, the steering system not only provides basic assist torque but also actively provides additional steering torque to assist the driver in turning the steering wheel to the correct position to restore stability. The braking system in the first control mode actively provides initial wheel braking force for forced braking, pulling the vehicle back to a stable state.

[0057] The second control mode, also known as the coordinated intervention mode, is used when vehicle stability decreases, such as when slight understeer or oversteer occurs. This mode provides a second assist torque and steering wheel return torque through the steering system, and a second wheel braking force through the braking system. The second assist torque in this mode is a smaller assist torque output by the steering motor, determined based on the driver's steering wheel torque input. This reduces steering motor assist, making the driver feel the steering wheel become heavier and suppressing potential over-operation. By increasing the steering wheel return torque in the second control mode, the driver experiences a stronger sense of center and responsiveness when turning or returning the steering wheel, as if the steering wheel is more inclined to remain centered. This significantly enhances vehicle stability and driver confidence, allowing for clearer perception of vehicle dynamics and smoother steering inputs. The braking system intervenes in the second control mode, with the second wheel braking force applied to the inner wheels (those closest to the apex of the curve). By applying a second wheel braking force to the inner wheel, a yaw moment is generated in the opposite direction of the turn, which helps the vehicle travel on the desired trajectory.

[0058] The third control mode, also known as the conventional power steering mode, can be used when the vehicle has high stability and there is no risk of instability. In this mode, the steering system provides a third power steering torque to reduce the driver's workload on the steering wheel, providing a comfortable and easy driving experience. Furthermore, the braking system does not intervene in the third control mode.

[0059] In one implementation, a first assist curve is used to determine the first assist torque in the first control mode, a second assist curve is used to determine the second assist torque in the second control mode, and a third assist curve is used to determine the third assist torque in the third control mode. Each assist curve represents the relationship between the steering wheel torque and the assist torque provided by the steering system.

[0060] The assist torque corresponding to the target steering wheel torque in the first assist curve is less than the assist torque corresponding to the target steering wheel torque in the second assist curve, and the assist torque corresponding to the target steering wheel torque in the second assist curve is less than the assist torque corresponding to the target steering wheel torque in the third assist curve. Here, the target steering wheel torque refers to the same steering wheel torque in the first, second, and third assist curves. That is, compared to the second assist curve, the assist torque provided by the steering system changes more smoothly with the steering wheel torque in the first assist curve; compared to the third assist curve, the assist torque provided by the steering system changes more smoothly with the steering wheel torque in the second assist curve.

[0061] In one embodiment, each preset control mode has a corresponding stability parameter range. Selecting a control mode that matches the stability parameter from several preset control modes as the target control mode includes: determining the target range to which the stability parameter belongs; and selecting the control mode corresponding to the target range as the target control mode. The target range is one of the stability parameter ranges corresponding to each preset control mode.

[0062] For example, a first control mode corresponds to a first range, a second control mode corresponds to a second range, and a third control mode corresponds to a third range, with the target range being one of the first, second, and third ranges. The lower limit of the first range is greater than or equal to the upper limit of the second range, and the lower limit of the second range is greater than or equal to the upper limit of the third range. The upper and lower limits of the first, second, and third ranges can be pre-calibrated according to actual needs.

[0063] For example, when the stability parameter is within a first range, the target control mode is determined to be the first control mode. When the stability parameter is within a third range, the target control mode is determined to be the third control mode.

[0064] For example, the first range is: 0.6≤S_index<≤1, the second range is: 0.3≤S_index<0.6, and the third range is: 0≤S_index<0.3.

[0065] S13: Control the vehicle's movement according to the target control mode.

[0066] After determining the target control mode, the vehicle's movement is further controlled according to the steering and braking control strategy corresponding to the target control mode.

[0067] In step S13, when the target control mode is the first control mode, the first assist torque, the additional steering torque, and the first wheel braking force in the first control mode are determined for vehicle control.

[0068] In the first control mode, the steering system and braking system work together to generate the required yaw moment, i.e., the target yaw moment. In this embodiment, the target yaw moment is first obtained. After obtaining the target yaw moment, the target moment is divided into the target steering yaw moment of the steering system and the target braking yaw moment of the braking system. Then, the target steering yaw moment is used to determine the additional steering moment, and the target braking yaw moment is used to determine the braking force of the first locomotive wheel.

[0069] Figure 2 This is a flowchart illustrating an implementation method for determining the additional steering torque and the first wheel braking force in the first control mode, as provided in this application. Figure 2 As shown, determining the additional steering torque and first wheel braking force in the first control mode includes the following steps:

[0070] S201: Determine the target yaw moment using the second vehicle status data.

[0071] In one embodiment, determining the target yaw moment using second vehicle state data further includes the following steps:

[0072] Step 1: Construct a state tracking error term using the second vehicle state data.

[0073] For example, the second vehicle state data includes the yaw rate at the current moment.

[0074] Step 2: Construct a cost function using the state tracking error term and the yaw moment control term to perform model predictive control and obtain the first feedforward yaw moment.

[0075] The basic idea of ​​Model Predictive Control (MPC) is to build a dynamic model of the system and use this model at each control time step to predict the system's future behavior. Based on these predictions, an optimal control sequence can be generated. The system state is then adjusted by executing the first control action in the optimal control sequence, and then recalculated and executed at the next time step. This process is repeated to enable the system to optimize a specific performance metric over a future period.

[0076] In this embodiment, the core task of model predictive control is to predict the dynamic behavior of the vehicle in a finite time domain (prediction time domain) in the future based on the current vehicle state, and to optimize and calculate the optimal braking force distribution scheme to generate the required yaw moment for correction, thereby preventing or suppressing vehicle instability.

[0077] The following is a brief introduction to the process of obtaining the first feedforward yaw moment using model predictive control optimization.

[0078] (1) Establishing a state-space model

[0079] The classic two-degree-of-freedom bicycle model is used as the prediction model, which can effectively capture the main characteristics of yaw and lateral dynamics, and has low computational cost, making it suitable for MPC.

[0080] The state variables are: Where β is the vehicle's sideslip angle and ω_act is the actual yaw rate.

[0081] Control input: u = M_z. Where M_z is the yaw moment.

[0082] Interference input: d = δ_f. Where δ_f is the front wheel steering angle, and .

[0083] State-space equations: .

[0084] The derivation of matrices A, B, and E is as follows:

[0085] Based on the dynamic equations of the two-degree-of-freedom model, the following lateral force balance equations are obtained:

[0086]

[0087] Assuming δ_f is small and cos(δ_f)≈1, then the following equation holds:

[0088]

[0089] Where m is the vehicle mass, β' is the rate of change of the sideslip angle, F_yf is the lateral force of the front wheel, and F_yr is the lateral force of the rear wheel.

[0090] The equilibrium equation for the yaw moment is as follows:

[0091]

[0092] Where I_z is the vehicle's moment of inertia about the z-axis, l_f is the distance from the vehicle's center of mass to the front axle, and l_r is the distance from the vehicle's center of mass to the rear axle.

[0093] If we use a linear model for the lateral forces of the tire, then we have the following equation:

[0094]

[0095]

[0096] Where C_αf and C_αr are the front wheel lateral stiffness and the rear wheel lateral stiffness, respectively, and α_f and α_r are the front wheel lateral slip angle and the rear wheel lateral slip angle, respectively.

[0097] Substituting the tire forces into the dynamic equations, the results are presented in the following matrix form:

[0098]

[0099] Then we have:

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] (2) Model discretization

[0108] Discretizing the continuous model using the Euler method, we have:

[0109]

[0110]

[0111] in, , , T_s is the control period.

[0112] (3) Prediction equation

[0113] Based on a discrete model, predict the state in the next N_p steps (prediction time domain):

[0114]

[0115] in: It is a predicted state sequence; is the control sequence to be optimized (N_c is the control time domain, N_c≤N_p); D is the known disturbance (front wheel steering angle) sequence; F, Φ and Γ are prediction matrices composed of A_d, B_d and E_d.

[0116] (4) Optimize problem construction

[0117] At each time k, solve the following optimization problem (i.e., construct the cost function):

[0118]

[0119] in, For the aforementioned state tracking error term, This refers to the yaw moment control item mentioned above. It is the predicted yaw rate. This represents the expected yaw rate for the next i steps, which can be assumed to be constant or slowly changing based on the current v_x and δ_f. Q and R are weight matrices. Q penalizes the tracking error; a larger Q indicates a stricter requirement to closely follow the expected value. R penalizes the control input; a larger R indicates a more conservative control. Q and R are the core parameters that need to be adjusted.

[0120] The constraints of model predictive control include:

[0121] u_min≤u(k+j|k)≤u_max

[0122] Δu_min≤Δu(k+j|k)≤Δu_max

[0123] The first constraint is an actuator saturation constraint, and the second constraint is a control increment constraint, ensuring ride smoothness. The maximum value of the yaw moment M_z is determined by the road adhesion coefficient μ.

[0124] (5) Solving and Output

[0125] Solving the constrained quadratic programming (QP) problem above yields the optimal control sequence. Take the first element in the sequence. This refers to the first feedforward yaw moment required for this cycle.

[0126] Step 3: Determine the target yaw moment using the first feedforward yaw moment.

[0127] In one example, the first feedforward yaw moment is directly used as the target yaw moment.

[0128] In another example, considering that feedforward control (based on model predictive control) relies on the accuracy of the model, but in reality, due to factors such as model mismatch (e.g., tire nonlinearity, parameter variations) and road disturbances (e.g., changes in road adhesion coefficient), feedforward control cannot completely track errors. Therefore, robust feedback control is used to further eliminate errors that feedforward control cannot compensate for. In this example, the target yaw moment is determined using the first feedforward yaw moment, further including the following sub-steps:

[0129] Sub-step one: By combining the current yaw rate error and the historical cumulative yaw rate error, the feedback yaw torque is determined.

[0130] The yaw rate error is the difference between the desired yaw rate and the actual yaw rate. Feedback control compensates for this difference through sliding mode variable structure control.

[0131] Define the sliding surface s with the yaw rate error as the core:

[0132]

[0133] Where (ω_d-ω_act) is the yaw rate error at the current moment; ∫(ω_d-ω_act)dt is the historical cumulative yaw rate error; λ is the weighting coefficient, which determines the dynamic characteristics of the system error convergence.

[0134] Furthermore, the feedback yaw moment is determined using the following formula:

[0135]

[0136] Where M_z_fb is the feedback yaw moment; K is the control gain; Φ is the boundary layer thickness; and sat() is the saturation function used to reduce chattering.

[0137] Sub-step two: The sum of the first feedforward yaw moment and the feedback yaw moment is taken as the target yaw moment.

[0138] The target yaw moment is expressed by the following formula:

[0139] M_z_des=M_z_ff+M_z_fb

[0140] Among them, M_z_des, M_z_ff, and M_z_fb are the target yaw moment, the first feedforward yaw moment, and the feedback yaw moment, respectively.

[0141] S202: Distribute the target yaw moment to obtain the target steering yaw moment and the target braking yaw moment.

[0142] In step S202, the target yaw moment is distributed to obtain the target steering yaw moment and the target braking yaw moment, including the following steps:

[0143] Step 1: Determine the first braking weight using at least one of the stability parameters, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment.

[0144] The stability parameters and the yaw rate deviation rate at the current moment can be referred to the relevant content in step S11 above, and will not be repeated here.

[0145] Step one further includes: determining a second braking weight by considering at least one of the comprehensive stability parameters, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment, wherein the steering wheel angle ratio at the current moment is the ratio of the absolute value of the steering wheel angle at the current moment to the maximum steering wheel angle; and determining a first braking weight using the second braking weight.

[0146] In one embodiment, determining the second braking weight by taking into account at least one of the stability parameters, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment includes: weighting and summing at least one of the stability parameters, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment to obtain the second braking weight.

[0147] For example, the second braking weight is obtained by weighting and summing the stability parameter, the current steering wheel angle ratio, and the current yaw rate deviation rate. The weighting coefficients for the stability parameter, the current steering wheel angle ratio, and the current yaw rate deviation rate can be set according to actual needs. The determined second braking weight can be expressed by the following formula:

[0148]

[0149] Where ks, kδ, and kω are the weighting coefficients of the stability parameter S_index, the steering wheel angle ratio at the current moment (|δ_sw| / δ_sw_max), and the yaw rate deviation rate at the current moment (|ω_act-ω_d| / ω_max), respectively.

[0150] In one embodiment, determining the first braking weight using the second braking weight includes: using the second braking weight as the first braking weight.

[0151] In another embodiment, to further improve the rationality and accuracy of the target yaw moment distribution, thereby further improving the stability and safety of vehicle driving, a first braking weight is determined using a second braking weight. This includes adjusting the second braking weight based on the current driving conditions, the maximum braking weight, and the minimum braking weight to obtain the first braking weight. The maximum and minimum braking weights are preset according to actual conditions.

[0152] In the first scenario, when the first driving condition is met, the weight difference between the second braking weight and the first adjustment weight is determined, and the larger of this weight difference and the minimum braking weight is determined as the first braking weight.

[0153] The first driving condition includes: the absolute value of the steering wheel angle at the current moment is greater than the first steering wheel angle threshold, and the difference between the actual yaw rate at the current moment and the expected yaw rate at the current moment is greater than the yaw rate threshold. The first driving condition can be expressed as: |δ_sw|>δ_emergency and |ω_act-ω_d|>ω_threshold. Where δ_emergency is the first steering wheel angle threshold, i.e., the set emergency threshold; ω_threshold is the yaw rate threshold.

[0154] In this scenario, the first braking weight can be determined using the following formula: α = max(α_min, α_base - Δα_steer). Where α_base is the second braking weight; Δα_steer is the first adjustment weight, i.e., the additional weight of the steering system, which is a value within the range of 0.3 to 0.5; and α_min is the minimum braking weight.

[0155] In this scenario, when the first driving condition is met, it is assumed that the vehicle is experiencing severe oversteering, meaning that the driver's sudden steering wheel turn could easily lead to loss of vehicle control. Direct intervention from the steering system is more effective than intervention from the braking system. Therefore, the first braking weight is determined by reducing the second braking weight, allowing the steering system to bear more torque. At the same time, the constraint of the minimum braking weight is used to prevent the determined first braking weight from being too low, which could lead to braking failure.

[0156] In the second scenario, when the second driving condition is met, the first weight sum of the second braking weight and the second adjustment weight is determined, and the smaller value between the first weight sum and the maximum braking weight is determined as the first braking weight.

[0157] The second driving condition includes: the current steering wheel change direction is inconsistent with the system correction direction, and the absolute value of the steering wheel angle at the current moment is greater than the second steering wheel angle threshold. The system correction direction can be determined using the additional front wheel angle increment Δδ_des determined at the previous moment, which will be described in detail later. The second driving condition can be expressed as: sign(δ_sw) ≠ sign(Δδ_des) and |δ_sw| > δ_resist_threshold. Here, δ_resist_threshold is the second steering wheel angle threshold, i.e., the set countermeasure threshold.

[0158] In this scenario, the first braking weight can be determined using the following formula: α = min(α_max, α_base + Δα_brake). Where α_base is the second braking weight; Δα_brake is the second adjustment weight, i.e., the braking system compensation weight, which is a value ranging from 0.2 to 0.4; and α_max is the maximum braking weight.

[0159] In this scenario, when the second driving condition is met, it is assumed that the driver is engaging in antagonistic intervention (i.e., hindering stabilization). The driver's antagonistic intervention will weaken the steering system's correction effect. Therefore, the first braking weight is determined by increasing the second braking weight, and the braking system generates torque to compensate, thereby ensuring the overall correction effect. At the same time, the constraint of the maximum braking weight avoids the determination of the first braking weight being too high, which would lead to over-braking.

[0160] In the third scenario, when the third driving condition is met, the second weight sum of the second braking weight and the third adjustment weight is determined, and the smaller value between the second weight sum and the maximum braking weight is determined as the first braking weight.

[0161] The third driving condition includes: the current road surface adhesion coefficient is less than the road surface adhesion coefficient threshold. This third driving condition can be expressed as: μ < μ_low, where μ_low is a set low road surface adhesion coefficient threshold.

[0162] In this scenario, the first braking weight can be determined using the following formula: α = min(α_max, α_base + Δα_μ). Where α_base is the second braking weight; Δα_μ is the third adjustment weight, a value ranging from 0.1 to 0.3; and α_max is the maximum braking weight.

[0163] In this scenario, when the third driving condition is met, it is assumed that the vehicle is traveling on a low-adhesion road surface. Because the friction between the vehicle tires and the ground is small on a low-adhesion road surface, the steering efficiency of the steering system is low. The yaw moment generated by the braking system through differential braking is relatively less affected by the road surface adhesion coefficient. Therefore, the first braking weight is determined by increasing the second braking weight, allowing the braking system to undertake more correction tasks. At the same time, the constraint of the maximum braking weight avoids the determined first braking weight from being too high.

[0164] In the fourth scenario, when the current driving condition does not meet the aforementioned first, second, and third driving condition conditions, the smaller of the second and maximum braking weights is determined, and the larger of the smaller and minimum braking weights is determined as the first braking weight. Thus, the first braking weight determined by the constraints falls within the range of the minimum and maximum braking weights.

[0165] In this case, the first braking weight can be determined by the following formula: α=max(α_min,min(α_max,α_base)).

[0166] Step 2: Using the first braking weight, the target yaw moment is distributed to obtain the basic steering yaw moment and the basic braking yaw moment.

[0167] In one embodiment, the step of determining the basic braking yaw moment includes: multiplying a first braking weight by a target yaw moment as the basic braking yaw moment. The basic braking yaw moment can be expressed by the following formula: .

[0168] The steps for determining the base steering yaw moment include: taking the difference between the target yaw moment and the base braking yaw moment as the base steering yaw moment. The base steering yaw moment can be expressed by the following formula: .

[0169] Step 3: Determine the target steering yaw moment using the basic steering yaw moment, and determine the target braking yaw moment using the basic braking yaw moment.

[0170] In one embodiment, the basic steering yaw moment is used as the target steering yaw moment, and the basic braking yaw moment is used as the target braking yaw moment.

[0171] In another implementation, the steering system not only bears the allocated basic steering yaw moment, but also needs to add an additional intervention moment to quickly respond to yaw rate deviations and achieve active stability control of the vehicle. At the same time, the braking system reduces its torque accordingly to avoid excessive total correction force.

[0172] In this embodiment, the step of determining the target steering yaw moment includes: taking the sum of the basic steering yaw moment and the intervention moment as the target steering yaw moment. The intervention moment is obtained by corrective control using the difference between the actual yaw rate at the current moment and the desired yaw rate at the current moment; for example, the corrective control can be proportional-derivative control.

[0173] The target steering yaw moment can be expressed by the following formula:

[0174] M_z_steer_active=M_z_steer+M_z_intervention

[0175] Where M_z_intervention is the defined intervention torque. The intervention torque can be expressed by the following formula: Where k_p and k_d are the proportional coefficient and differential coefficient, respectively.

[0176] In this embodiment, the step of determining the target braking yaw moment includes: determining the torque difference between the basic braking yaw moment and the braking adjustment torque, and determining the target braking yaw moment based on the torque difference.

[0177] In one example, the braking adjustment torque is the product of a preset adjustment factor and the basic braking yaw torque. For example, the preset adjustment factor is 0.3.

[0178] In one example, determining the target braking yaw moment based on the torque difference includes: determining the larger of the torque difference and a preset torque as the target braking yaw moment. For example, the preset torque is 0, to constrain the determined target braking yaw moment to be non-negative.

[0179] In this embodiment, the target braking yaw moment can be expressed by the following formula:

[0180]

[0181] S203: Determine the additional steering torque by utilizing the target steering yaw moment.

[0182] Understandably, in the first control mode (i.e., emergency steering mode), the steering system no longer simply provides assist torque, but actively intervenes in the steering to generate the required yaw moment. The steering system guides the steering wheel to turn by generating additional steering torque (which may be assist or resistance), thereby generating the allocated target steering yaw moment and assisting the driver in operation.

[0183] In one embodiment, determining the additional steering moment using the target steering yaw moment further includes the following steps:

[0184] Step 1: Use the target steering yaw moment to determine the additional front wheel steering angle increment.

[0185] Based on the vehicle model, the desired target steering yaw moment is converted into the required additional front wheel steering angle increment, which can be achieved using the following formula:

[0186] Δδ_des=M_z_steer_active / ( M_z / δ)

[0187] Where Δδ_des is the additional front wheel steering angle increment; M_z_steer_active is the target steering yaw moment; M_z / δ is the sensitivity coefficient of yaw moment to front wheel steering angle, which can be obtained by looking up a table or estimating online.

[0188] Understandably, when Δδ_des is positive, it means that the front wheel steering angle needs to be increased to increase the understeer tendency and suppress oversteer; when Δδ_des is negative, it means that the front wheel steering angle needs to be decreased to reduce the understeer tendency and correct understeer.

[0189] Step two: The additional front wheel steering angle increment is used as the steering angle deviation and corrective control is performed to obtain the additional steering torque.

[0190] Since the expected total front wheel steering angle δ_des is the steering wheel angle δ_driver corresponding to the current moment of the driver's current input plus the additional front wheel steering angle increment, we have: Δδ_des = δ_des - δ_driver.

[0191] Taking PID (Proportional-Integral-Derivative) control as an example, the additional steering torque can be calculated using the following formula:

[0192]

[0193] Where Kp, Ki, and Kd are the parameters of the PID controller.

[0194] In the first control mode, the final assist torque T_final of the steering system is the synthesis of the additional steering torque and the first assist torque (i.e., the basic assist).

[0195] The additional steering torque T_assist_follow has two effects: if the driver's direction of operation is the same as the direction of Δδ_des, it is an assist, helping the driver to reach the target steering wheel angle more quickly; if the driver's direction of operation is opposite to the direction of Δδ_des, it is a resistance, which strongly prompts and prevents the driver's incorrect operation through the tactile feedback of the reverse torque of the steering wheel, guiding the driver to turn in a stable direction.

[0196] S204: Determine the braking force of the first wheel by utilizing the target braking yaw moment.

[0197] In one embodiment, the ratio of the target braking yaw moment to a preset distance is used as the braking force of the first wheel. The first wheel braking force is applied to the inner wheel, and the preset distance is half the vehicle's track width.

[0198] When the vehicle is understeer (ω_act < ω_d), the braking force of the first wheel is the braking force of the inner rear wheel. That is, braking is applied to the inner rear wheel, generating a yaw moment pointing inwards from the vehicle.

[0199] In the case of vehicle oversteer (ω_act > ω_d), the braking force of the first wheel is the braking force of the inner front wheel. Applying braking to the inner front wheel generates a yaw moment pointing outwards from the vehicle.

[0200] It should be noted that this embodiment does not specifically limit the execution order of steps S203 and S204. Step S204 can be executed first and then step S203 can be executed, or steps S203 and S204 can be executed simultaneously.

[0201] In step S13, when the target control mode is the second control mode, the second assist torque, steering wheel return torque, and second wheel braking force in the second control mode are determined for vehicle control.

[0202] In this scenario, the step of determining the second assist torque of the second control mode includes: using the second assist curve to determine the assist torque corresponding to the steering wheel torque at the current moment, and using it as the second assist torque.

[0203] In this scenario, the steps for determining the steering wheel return torque in the second control mode include: determining the steering wheel return torque through a steering wheel return control algorithm. For example, increasing the return torque compensation coefficient allows the EPS motor to actively generate a larger steering wheel return torque at the same vehicle speed and lateral acceleration.

[0204] In this scenario, the steps for determining the second wheel braking force under the second control mode include: constructing a state tracking error term using third vehicle state data; constructing a cost function using the state tracking error term and the yaw moment control term to perform model predictive control and obtain the second feedforward yaw moment; and determining the second wheel braking force using the second feedforward yaw moment. The third vehicle state data may include the current yaw rate, lateral acceleration, etc. Determining the second feedforward yaw moment through model predictive control is similar to the previously discussed method for determining the first feedforward yaw moment, and will not be repeated here. Distributing braking force using the second feedforward yaw moment to determine the second wheel braking force is similar to the previously discussed method for distributing braking force using the target braking yaw moment to determine the first wheel braking force, and will not be repeated here.

[0205] In step S13, when the target control mode is the third control mode, the third assist torque in the third control mode is determined and used for vehicle control.

[0206] In this scenario, the steps for determining the third assist torque of the third control mode include: using the third assist curve to determine the assist torque corresponding to the steering wheel torque at the current moment, and using it as the third assist torque.

[0207] In this embodiment, the vehicle's stability parameters are determined using first vehicle state data; a control mode matching the stability parameters is selected from several preset control modes as the target control mode, wherein different preset control modes correspond to different steering and braking control strategies; the vehicle is controlled to drive according to the target control mode. In this method, the adaptive selection of a suitable steering and braking control strategy based on the vehicle's stability parameters can reduce the risk of vehicle loss of control and improve vehicle driving stability and safety.

[0208] Please see Figure 3 , Figure 3 This is a schematic diagram of an embodiment of the vehicle control system provided in this application. Figure 3The vehicle control system shown is actually the original braking system, with steering-related components added. Among these, the Torque and Steering Angle Sensor (TAS), the Motor Position Sensor (MPS) for the steering motor, the second interface, the steering motor drive, and the steering motor are added steering-related components. The remaining components (including the main controller, auxiliary controller, first communication interface, first communication module, second communication interface, second communication module, first power module, second power module, wheel speed sensor, first interface, brake motor drive, brake motor, solenoid valve drive, solenoid valve, first parking brake drive, first parking brake motor, second parking brake drive, and second parking brake motor) are all original components of the original braking system.

[0209] For example, the first interface is the AK interface; the second interface is the SENT (Single EdgeNibble Transmission) interface.

[0210] For example, both the main controller and the auxiliary controller use MCU (Microcontroller Unit).

[0211] For example, both the first communication module and the second communication module are CAN (Controller Area Network) modules; both the first communication interface and the second communication interface are CAN communication interfaces. Both the first and second communication interfaces are connected to the vehicle chassis CAN communication interface. Figure 3 (Not shown in the diagram) is used to acquire data such as longitudinal acceleration and yaw rate from the IMU (Inertial Measurement Unit), and to acquire commands from the upper-level Advanced Driver Assistance Systems (ADAS).

[0212] For example, both the first power module and the second power module are power chips, which are used to supply power to the corresponding devices.

[0213] In this embodiment, steering-related components in the steering system are integrated into the braking system, and the auxiliary controller in the braking system is used as the steering control unit. This enables the following: the integrated system can respond to changes in driving conditions more quickly because steering and braking operations can be coordinated more rapidly; in emergency situations, the integrated system can implement emergency braking and obstacle avoidance operations more quickly, reducing the risk of accidents; it facilitates the application of autonomous driving technology, providing support for future autonomous vehicles; through integrated control, the number of individual controllers and actuators required can be reduced, thereby simplifying the vehicle's electronic architecture and reducing hardware costs; the integrated system can provide more precise steering and braking control, improving the vehicle's handling and stability performance.

[0214] In this application, the main controller and the auxiliary controller can be connected via SPI (Serial Peripheral Interface) to achieve ultra-low latency interaction between the main and auxiliary controllers.

[0215] In this application, the division of labor between the main controller and the auxiliary controller in the original braking system is redefined. The main controller continues to implement the original braking control functions. The auxiliary controller expands upon these functions with steering control and combined steering and braking control. By expanding the steering control and combined steering and braking control functions into the auxiliary controller, its hardware resources can be fully utilized.

[0216] In this application, the input data of the main controller includes vehicle speed, wheel speed, longitudinal acceleration provided by the IMU, yaw rate and other data. In addition, the main controller can send data such as vehicle speed, wheel speed and ABS (Anti-lock Braking System) function activation status to the auxiliary controller via SPI.

[0217] The auxiliary controller can acquire steering wheel torque and angle signals through the torque and angle sensor, and acquire MPS signals through the motor position sensor of the steering motor. Furthermore, the auxiliary controller can send the acquired steering wheel torque, angle, and braking commands for specific wheels (such as the inner wheel) to the main controller via SPI. After receiving the braking command, the main controller will brake the specific wheel.

[0218] In one embodiment, the vehicle control method of this application can be provided by... Figure 3 The auxiliary controller in the middle is used to execute.

[0219] Please see Figure 4 , Figure 4 This is a schematic diagram of a framework of an embodiment of the vehicle control device provided in this application. In this embodiment, the vehicle control device 40 includes a determining module 41, a selecting module 42, and a controlling module 43.

[0220] The determination module 41 is used to determine the vehicle's stability parameters using the first vehicle state data. The selection module 42 is used to select a control mode that matches the stability parameters from several preset control modes as the target control mode; wherein, the steering and braking control strategies corresponding to different preset control modes are different. The control module 43 is used to control the vehicle's movement according to the target control mode.

[0221] In one embodiment, several preset control modes include a first control mode, a second control mode, and a third control mode; wherein, the first control mode provides a first assist torque and an additional steering torque through the steering system and provides a first wheel braking force through the braking system, the second control mode provides a second assist torque and a steering wheel return torque through the steering system and provides a second wheel braking force through the braking system, and the third control mode provides a third assist torque through the steering system.

[0222] The selection module 42 is used to determine the target range to which the stability parameter belongs; wherein, the target range is one of the first range corresponding to the first control mode, the second range corresponding to the second control mode, and the third range corresponding to the third control mode, the lower limit of the first range is greater than or equal to the upper limit of the second range, and the lower limit of the second range is greater than or equal to the upper limit of the third range; the control mode corresponding to the target range is taken as the target control mode.

[0223] In one embodiment, the control module 43 is used to determine a target yaw moment using second vehicle state data; to distribute the target yaw moment to obtain a target steering yaw moment and a target braking yaw moment; to determine an additional steering moment using the target steering yaw moment; and to determine the braking force of the first wheel using the target braking yaw moment.

[0224] In one embodiment, the control module 43 is used to construct a state tracking error term using the second vehicle state data; construct a cost function using the state tracking error term and the yaw moment control term to perform model predictive control, thereby obtaining a first feedforward yaw moment; and determine a target yaw moment using the first feedforward yaw moment.

[0225] In one embodiment, the control module 43 is used to take the first feedforward yaw moment as the target yaw moment. Alternatively, the control module 43 is used to determine the feedback yaw moment by comprehensively utilizing the current yaw rate error and the historical accumulated yaw rate error; wherein the yaw rate error is the difference between the desired yaw rate and the actual yaw rate; and the sum of the moments of the first feedforward yaw moment and the feedback yaw moment is taken as the target yaw moment.

[0226] In one embodiment, the control module 43 is configured to determine a first braking weight using at least one of a stability parameter, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment; to distribute the target yaw moment using the first braking weight to obtain a base steering yaw moment and a base braking yaw moment; to determine the target steering yaw moment using the base steering yaw moment; and to determine the target braking yaw moment using the base braking yaw moment.

[0227] In one embodiment, the control module 43 is used to perform a weighted summation of at least one of the stability parameter, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment to obtain a second braking weight, wherein the steering wheel angle ratio at the current moment is the ratio of the absolute value of the steering wheel angle at the current moment to the maximum steering wheel angle; based on the current driving conditions, the maximum braking weight, and the minimum braking weight, the second braking weight is adjusted to obtain a first braking weight.

[0228] In one embodiment, the control module 43 is configured to, in response to satisfying a first driving condition, determine the weight difference between a second braking weight and a first adjustment weight, and determine the larger of the weight difference and a minimum braking weight as the first braking weight; wherein, the first driving condition includes: the absolute value of the steering wheel angle at the current moment is greater than a first steering wheel angle threshold, and the difference between the actual yaw rate at the current moment and the expected yaw rate at the current moment is greater than a yaw rate threshold; in response to satisfying a second driving condition, determine a first weight sum of the second braking weight and the second adjustment weight, and determine the smaller of the first weight sum and a maximum braking weight as the first braking weight; wherein, the second driving condition includes: when The direction of the steering wheel change is inconsistent with the system correction direction, and the absolute value of the steering wheel angle at the current moment is greater than the second steering wheel angle threshold; in response to meeting the third driving condition, the second weight sum of the second braking weight and the third adjustment weight is determined, and the smaller value between the second weight sum and the maximum braking weight is determined as the first braking weight; wherein, the third driving condition includes: the road surface adhesion coefficient at the current moment is less than the road surface adhesion coefficient threshold; in response to not meeting the first driving condition, the second driving condition, and the third driving condition, the smaller braking weight between the second braking weight and the maximum braking weight is determined, and the larger braking weight between the smaller braking weight and the minimum braking weight is determined as the first braking weight.

[0229] In one embodiment, the control module 43 is used to take the sum of the basic steering yaw moment and the intervention moment as the target steering yaw moment; wherein, the intervention moment is obtained by corrective control using the difference between the actual yaw rate at the current moment and the desired yaw rate at the current moment; determining the target braking yaw moment using the basic braking yaw moment includes: determining the torque difference between the basic braking yaw moment and the braking adjustment moment; and determining the target braking yaw moment based on the torque difference.

[0230] In one embodiment, the control module 43 is used to determine the additional front wheel steering angle increment using the target steering yaw moment; the additional front wheel steering angle increment is used as the steering angle deviation and corrective control is performed to obtain the additional steering moment. And / or, the control module 43 is used to use the ratio of the target braking yaw moment to a preset distance as the braking force of the first wheel; wherein the preset distance is half of the vehicle's wheelbase; in the case of understeer, the braking force of the first wheel is the braking force of the inner rear wheel, and in the case of oversteer, the braking force of the first wheel is the braking force of the inner front wheel.

[0231] In one embodiment, a first assist curve is used to determine the first assist torque in the first control mode, a second assist curve is used to determine the second assist torque in the second control mode, and a third assist curve is used to determine the third assist torque in the third control mode. Each assist curve represents the relationship between the steering wheel torque and the assist torque provided by the steering system. The assist torque corresponding to the target steering wheel torque in the first assist curve is less than the assist torque corresponding to the target steering wheel torque in the second assist curve, and the assist torque corresponding to the target steering wheel torque in the second assist curve is less than the assist torque corresponding to the target steering wheel torque in the third assist curve.

[0232] In one embodiment, the first vehicle state data includes at least one of the yaw rate deviation rate, the lateral load transfer coefficient, and the steering wheel angle at the current moment. The determination module 41 is used to weight each of the first vehicle state data to obtain stability parameters.

[0233] It should be noted that the apparatus of this embodiment can perform the steps in the above method. For detailed descriptions of the relevant content, please refer to the method section above, which will not be repeated here.

[0234] Please see Figure 5 , Figure 5 This is a schematic diagram of a framework of an embodiment of the electronic device provided in this application. In this embodiment, the electronic device 50 includes a memory 51 and a processor 52.

[0235] Processor 52 can also be referred to as CPU (Central Processing Unit). Processor 52 may be an integrated circuit chip with signal processing capabilities. Processor 52 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. A general-purpose processor can be a microprocessor, or processor 52 can be any conventional processor 52, etc.

[0236] The memory 51 in the electronic device 50 is used to store the program instructions required for the processor 52 to run.

[0237] The processor 52 is used to execute program instructions to implement the vehicle control method of this application.

[0238] Please see Figure 6 , Figure 6 This is a schematic diagram of a framework of an embodiment of the computer-readable storage medium provided in this application. The computer-readable storage medium 60 of this embodiment stores program instructions 61, which, when executed, implement the vehicle control method provided in this application. The program instructions 61 can be formed into a program file and stored in the aforementioned computer-readable storage medium 60 in the form of a software product, so that a computer device (which may be a personal computer, server, or network device, etc.) can execute all or part of the steps of the methods of various embodiments of this application. The aforementioned computer-readable storage medium 60 includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, or terminal devices such as computers, servers, mobile phones, and tablets.

[0239] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0240] The description of the various embodiments above tends to emphasize the differences between the various embodiments. The similarities or similarities between them can be referred to, and for the sake of brevity, they will not be repeated here.

[0241] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus implementations described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or units may be electrical, mechanical, or other forms.

[0242] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0243] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0244] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0245] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A vehicle control method, characterized in that, The method includes: Using the first vehicle state data, determine the vehicle's stability parameters; The target range to which the stability parameter belongs is determined; wherein the target range is one of a first range corresponding to a first control mode, a second range corresponding to a second control mode, and a third range corresponding to a third control mode, wherein the lower limit of the first range is greater than or equal to the upper limit of the second range, and the lower limit of the second range is greater than or equal to the upper limit of the third range; the first control mode provides a first assist torque and an additional steering torque through the steering system and provides a first wheel braking force through the braking system; the second control mode provides a second assist torque and a steering wheel return torque through the steering system and provides a second wheel braking force through the braking system; and the third control mode provides a third assist torque through the steering system. The control mode corresponding to the target range shall be taken as the target control mode; The vehicle is controlled to drive according to the target control mode.

2. The method according to claim 1, characterized in that, The steps of determining the additional steering torque and the first wheel braking force in the first control mode include: The target yaw moment is determined using the second vehicle status data; The target yaw moment is distributed to obtain the target steering yaw moment and the target braking yaw moment; The additional steering torque is determined using the target steering yaw moment; and the braking force of the first wheel is determined using the target braking yaw moment.

3. The method according to claim 2, characterized in that, The step of determining the target yaw moment using the second vehicle state data includes: Using the second vehicle state data, a state tracking error term is constructed; A cost function is constructed using the state tracking error term and the yaw moment control term to perform model predictive control, thereby obtaining the first feedforward yaw moment. The target yaw moment is determined using the first feedforward yaw moment.

4. The method according to claim 3, characterized in that, The step of determining the target yaw moment using the first feedforward yaw moment includes: The first feedforward yaw moment is taken as the target yaw moment; Alternatively, the feedback yaw torque can be determined by combining the current yaw rate error and the historical cumulative yaw rate error; wherein, the yaw rate error is the difference between the expected yaw rate and the actual yaw rate. The sum of the first feedforward yaw moment and the feedback yaw moment is taken as the target yaw moment.

5. The method according to claim 2, characterized in that, The process of distributing the target yaw moment to obtain the target steering yaw moment and the target braking yaw moment includes: The first braking weight is determined using at least one of the stability parameter, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment. Using the first braking weight, the target yaw moment is distributed to obtain the basic steering yaw moment and the basic braking yaw moment; The target steering yaw moment is determined using the base steering yaw moment, and the target braking yaw moment is determined using the base braking yaw moment.

6. The method according to claim 5, characterized in that, Determining the first braking weight using at least one of the stability parameter, the steering wheel angle at the current moment, and the yaw rate deviation rate at the current moment includes: The second braking weight is obtained by weighted summation of at least one of the stability parameter, the steering wheel angle ratio at the current moment, and the yaw rate deviation rate at the current moment, wherein the steering wheel angle ratio at the current moment is the ratio of the absolute value of the steering wheel angle at the current moment to the maximum steering wheel angle. Based on the current driving conditions, maximum braking weight, and minimum braking weight, the second braking weight is adjusted to obtain the first braking weight.

7. The method according to claim 6, characterized in that, The step of adjusting the second braking weight based on the current driving conditions, maximum braking weight, and minimum braking weight to obtain the first braking weight includes: In response to meeting the first driving condition, the weight difference between the second braking weight and the first adjustment weight is determined, and the larger value between the weight difference and the minimum braking weight is determined as the first braking weight; wherein, the first driving condition includes: the absolute value of the steering wheel angle at the current moment is greater than the first steering wheel angle threshold, and the difference between the actual yaw rate at the current moment and the expected yaw rate at the current moment is greater than the yaw rate threshold; In response to meeting the second driving condition, the first weight sum of the second braking weight and the second adjustment weight is determined, and the smaller value between the first weight sum and the maximum braking weight is determined as the first braking weight; wherein, the second driving condition includes: the current steering wheel change direction is inconsistent with the system correction direction, and the absolute value of the steering wheel angle at the current moment is greater than the second steering wheel angle threshold. In response to meeting the third driving condition, the second weight sum of the second braking weight and the third adjustment weight is determined, and the smaller value between the second weight sum and the maximum braking weight is determined as the first braking weight; wherein, the third driving condition includes: the road surface adhesion coefficient at the current moment is less than the road surface adhesion coefficient threshold; In response to the fact that none of the first driving condition, the second driving condition, and the third driving condition are met, the smaller of the second braking weight and the maximum braking weight is determined, and the larger of the smaller braking weight and the minimum braking weight is determined as the first braking weight.

8. The method according to claim 5, characterized in that, Determining the target steering yaw moment using the basic steering yaw moment includes: The sum of the basic steering yaw moment and the intervention moment is taken as the target steering yaw moment; wherein, the intervention moment is obtained by corrective control using the difference between the actual yaw rate at the current moment and the expected yaw rate at the current moment. Determining the target braking yaw moment using the basic braking yaw moment includes: Determine the torque difference between the basic braking yaw torque and the braking adjustment torque; The target braking yaw moment is determined based on the torque difference.

9. The method according to claim 2, characterized in that, The step of determining the additional steering torque using the target steering yaw moment includes: Using the target steering yaw moment, determine the additional front wheel steering angle increment; The additional front wheel steering angle increment is used as the steering angle deviation and corrective control is performed to obtain the additional steering torque; And / or, determining the braking force of the first wheel using the target braking yaw moment includes: The ratio of the target braking yaw moment to the preset distance is used as the braking force of the first wheel. Wherein, the preset distance is half of the vehicle's wheelbase; in the case of understeer, the braking force of the first wheel is the braking force of the inner rear wheel, and in the case of oversteer, the braking force of the first wheel is the braking force of the inner front wheel.

10. The method according to claim 1, characterized in that, In the first control mode, the first assist curve is used to determine the first assist torque; in the second control mode, the second assist curve is used to determine the second assist torque; and in the third control mode, the third assist curve is used to determine the third assist torque. Each of the assist curves represents the relationship between the steering wheel torque and the assist torque provided by the steering system. The assist torque corresponding to the target steering wheel torque in the first assist curve is less than the assist torque corresponding to the target steering wheel torque in the second assist curve, and the assist torque corresponding to the target steering wheel torque in the second assist curve is less than the assist torque corresponding to the target steering wheel torque in the third assist curve.

11. The method according to claim 1, characterized in that, The first vehicle state data includes at least one of the following: the yaw rate deviation rate at the current moment, the lateral load transfer coefficient, and the steering wheel angle at the current moment; the step of determining the vehicle's stability parameters using the first vehicle state data includes: The stability parameters are obtained by weighting the state data of each of the first vehicles.

12. A vehicle control device, characterized in that, The device includes: The determination module is used to determine the stability parameters of the vehicle using the first vehicle state data; The selection module is used to determine the target range to which the stability parameter belongs; wherein, the target range is one of a first range corresponding to a first control mode, a second range corresponding to a second control mode, and a third range corresponding to a third control mode, wherein the lower limit of the first range is greater than or equal to the upper limit of the second range, and the lower limit of the second range is greater than or equal to the upper limit of the third range; the first control mode provides a first assist torque and an additional steering torque through the steering system and provides a first wheel braking force through the braking system; the second control mode provides a second assist torque and a steering wheel return torque through the steering system and provides a second wheel braking force through the braking system; the third control mode provides a third assist torque through the steering system; the control mode corresponding to the target range is taken as the target control mode; The control module is used to control the vehicle's movement according to the target control mode.

13. An electronic device, characterized in that, Including interconnected memory and processor, The memory stores program instructions; The processor is configured to execute program instructions stored in the memory to implement the method according to any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program instructions that can be executed by a processor to implement the method of any one of claims 1-11.

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