Vehicle steering stability control method and device, vehicle and storage medium

Abstract

The invention relates to the technical field of vehicles, in particular to a vehicle steering stability control method and device, a vehicle and a storage medium. The method comprises the steps of obtaining current driving data of a vehicle, calculating a comprehensive instability index of the vehicle based on the current driving data, determining an actual state of the vehicle according to the comprehensive instability index, matching a stability control strategy of the vehicle according to the state of the vehicle, and performing stability control on the vehicle according to the stability control strategy. Therefore, the comprehensive instability index is calculated through the current driving data of the vehicle, the layered vehicle steering stability control method adopting cooperative control is adopted, and the problems that in a traditional electric vehicle chassis system, due to subsystem decentralized control, the collaboration is insufficient, the combination advantage is difficult to play, and the vehicle stability is affected are solved; and the driving safety and controllability of drivers and passengers are greatly improved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a vehicle steering stability control method, device, vehicle, and storage medium. Background Technology

[0002] With the upgrading of electric vehicles to be electrified and intelligent, the number of electronic control components in automobiles is increasing, and the traditional chassis system (steering, braking, drive) is independently controlled.

[0003] In related technologies, two methods are generally used for vehicle stability control. One method uses a single control parameter to reflect the vehicle's dynamic characteristics, such as relying on parameters like yaw rate or sideslip angle for control decisions. The other method mainly utilizes the individual functions of various vehicle subsystems, such as the braking system, steering system, and drive system, to achieve vehicle stability control.

[0004] However, these methods often lead to problems such as uneven torque distribution causing yaw instability in in-wheel motor driven vehicles, insufficient dynamic coupling between trajectory tracking and stability control in autonomous driving mode, and unclear control strategy hierarchy leading to response lag. These issues seriously affect the stability of vehicles with intelligent chassis and urgently need to be addressed. Summary of the Invention

[0005] This application provides a vehicle steering stability control method, device, vehicle, and storage medium to solve the problem of insufficient coordination and difficulty in leveraging combined advantages caused by the decentralized control of subsystems in traditional electric vehicle chassis systems, which affects vehicle stability and greatly improves the driving safety and handling of passengers.

[0006] To achieve the above objectives, the first aspect of this application proposes a vehicle steering stability control method, comprising the following steps:

[0007] Obtain the vehicle's current driving data;

[0008] Based on the current driving data, calculate the comprehensive instability index of the vehicle, and determine the actual state of the vehicle based on the comprehensive instability index;

[0009] The stability control strategy of the vehicle is matched according to the actual state of the vehicle, and the stability control of the vehicle is performed according to the stability control strategy.

[0010] Optionally, in some embodiments, the current driving data includes at least one of the following: current sensor dataset, current brake pedal opening, current gear, current accelerator pedal opening, current steering wheel signal, and control commands from the intelligent driving controller.

[0011] Optionally, in some embodiments, calculating the vehicle's comprehensive instability index based on the current driving data includes:

[0012] The yaw rate error coefficient, tire slip variance, and energy efficiency of the vehicle are calculated based on the sensor data in the current sensor dataset.

[0013] The comprehensive instability index is calculated based on the yaw rate error coefficient, the tire slip ratio variance, and the energy efficiency.

[0014] Optionally, in some embodiments, determining the actual state of the vehicle based on the comprehensive instability index includes:

[0015] Determine whether the comprehensive instability index is less than a first preset threshold;

[0016] If the overall instability index is less than the first preset threshold, then the actual state of the vehicle is determined to be a preset stable state; otherwise, the overall instability index is determined to be less than or equal to the second preset threshold.

[0017] If the comprehensive instability index is less than or equal to the second preset threshold, the actual state of the vehicle is determined to be a preset critical state; otherwise, the actual state of the vehicle is determined to be a preset instability state.

[0018] Optionally, in some embodiments, the actual state is the preset stable state, and the step of matching the vehicle's stability control strategy according to the vehicle's actual state and performing stability control on the vehicle according to the stability control strategy includes:

[0019] When the actual state is the preset stable state, the stability control strategy is determined to maintain the current control mode of the vehicle.

[0020] The vehicle is subjected to stability control based on the current control mode.

[0021] Optionally, in some embodiments, the actual state is the preset instability state, and the step of matching the vehicle's stability control strategy according to the vehicle's actual state and performing stability control on the vehicle according to the stability control strategy includes:

[0022] When the actual state is the preset unstable state, the stability control strategy is determined to be an emergency control strategy.

[0023] Based on the aforementioned emergency control strategy, the vehicle's stability is controlled according to a preset four-wheel independent braking strategy, a preset steering angle limiting strategy, and a preset drive torque cutoff strategy.

[0024] According to the vehicle steering stability control method proposed in the embodiments of this application, the comprehensive instability index is calculated by using the current driving data of the vehicle. The hierarchical vehicle steering stability control method with collaborative control solves the problem of insufficient coordination and difficulty in leveraging the combined advantages caused by the decentralized control of subsystems in traditional electric vehicle chassis systems, which affects vehicle stability. This greatly improves the driving safety and handling of the driver and passengers.

[0025] To achieve the above objectives, a second aspect of this application provides a vehicle steering stability control device, comprising:

[0026] The acquisition module is used to acquire the vehicle's current driving data;

[0027] The determination module is used to calculate the comprehensive instability index of the vehicle based on the current driving data, and determine the actual state of the vehicle based on the comprehensive instability index;

[0028] The matching module is used to match the stability control strategy of the vehicle according to the actual state of the vehicle, and to perform stability control on the vehicle according to the stability control strategy.

[0029] Optionally, in some embodiments, the current driving data includes at least one of the following: current sensor dataset, current brake pedal opening, current gear, current accelerator pedal opening, current steering wheel signal, and control commands from the intelligent driving controller.

[0030] Optionally, in some embodiments, the determining module is specifically used for:

[0031] The yaw rate error coefficient, tire slip variance, and energy efficiency of the vehicle are calculated based on the sensor data in the current sensor dataset.

[0032] The comprehensive instability index is calculated based on the yaw rate error coefficient, the tire slip ratio variance, and the energy efficiency.

[0033] Optionally, in some embodiments, the determining module is further configured to:

[0034] Determine whether the comprehensive instability index is less than a first preset threshold;

[0035] If the overall instability index is less than the first preset threshold, then the actual state of the vehicle is determined to be a preset stable state; otherwise, the overall instability index is determined to be less than or equal to the second preset threshold.

[0036] If the comprehensive instability index is less than or equal to the second preset threshold, the actual state of the vehicle is determined to be a preset critical state; otherwise, the actual state of the vehicle is determined to be a preset instability state.

[0037] Optionally, in some embodiments, the matching module is specifically used for:

[0038] When the actual state is the preset stable state, the stability control strategy is determined to maintain the current control mode of the vehicle.

[0039] The vehicle is subjected to stability control based on the current control mode.

[0040] Optionally, in some embodiments, the matching module is specifically used for:

[0041] When the actual state is the preset critical state, the stability control strategy is determined to be a coordinated control strategy.

[0042] Based on the aforementioned coordinated control strategy, the vehicle's stability is controlled according to a preset wheel hub motor torque dynamic distribution algorithm and a preset steer-by-wire angle compensation amount.

[0043] Optionally, in some embodiments, the matching module is specifically used for:

[0044] When the actual state is the preset unstable state, the stability control strategy is determined to be an emergency control strategy.

[0045] Based on the aforementioned emergency control strategy, the vehicle's stability is controlled according to a preset four-wheel independent braking strategy, a preset steering angle limiting strategy, and a preset drive torque cutoff strategy.

[0046] The vehicle steering stability control device proposed in this application calculates the comprehensive instability index using the vehicle's current driving data and adopts a hierarchical vehicle steering stability control method with collaborative control. This solves the problem of insufficient coordination and difficulty in leveraging combined advantages caused by the decentralized control of subsystems in traditional electric vehicle chassis systems, which affects vehicle stability and greatly improves the driving safety and handling of passengers.

[0047] To achieve the above objectives, a third aspect of this application provides a vehicle comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a vehicle steering stability control method as described in the above embodiments.

[0048] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a vehicle steering stability control method as described in the above embodiments.

[0049] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0050] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0051] Figure 1 This is a schematic diagram showing the relationship between the main system components of a power chassis according to an embodiment of this application;

[0052] Figure 2 This is a schematic diagram of a chassis system structure based on chassis domain control according to an embodiment of this application;

[0053] Figure 3 This is a schematic diagram of the structure of a modular wheel according to an embodiment of this application;

[0054] Figure 4 This is a flowchart of a vehicle steering stability control method according to an embodiment of this application;

[0055] Figure 5 This is a schematic diagram of a driving intent input module according to an embodiment of this application;

[0056] Figure 6 This is a flowchart illustrating the drive and steering coordination process according to one embodiment of this application.

[0057] Figure 7 An emergency avoidance flowchart is provided according to one embodiment of this application;

[0058] Figure 8 This is a flowchart of a wet and slippery road surface control according to an embodiment of this application;

[0059] Figure 9 for Figure 9 The present application provides an embodiment of an instability level classification theory and a collaborative control flowchart.

[0060] Figure 10 A control flowchart based on slip ratio under unstable conditions provided in one embodiment of this application;

[0061] Figure 11 A general flowchart of the main control program is provided according to one embodiment of this application;

[0062] Figure 12 Here is a detailed flowchart of the main control program provided according to an embodiment of this application;

[0063] Figure 13This is a block diagram of a vehicle steering stability control device according to an embodiment of this application;

[0064] Figure 14 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application. Detailed Implementation

[0065] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0066] The following describes a vehicle steering stability control method according to an embodiment of this application, with reference to the accompanying drawings.

[0067] Before introducing the vehicle steering stability control method of this application embodiment, let's briefly introduce the current power chassis system and the chassis system based on chassis domain control of this application embodiment.

[0068] like Figure 1 As shown, the power chassis system includes: a left front tire 101, a right front tire 101, a left rear tire 103, and a right rear tire 104. 105. Front left brake, 106. Front right brake, 107. Rear left brake, 108. Rear right brake, 109. Front left wheel speed sensor, 110. Rear left wheel speed sensor, 111. Rear right wheel speed sensor, 112. Rear left wheel EPB (Electronic Park Brake) caliper, 113. Rear right wheel EPB caliper, 114. ESP (Electronic Stability Program) control module / onebox control module, 115. EPB control module, 116. Drive motor, 117. MCU (Motor Control Unit) control module, 118. Driver demand calculation module, 119. Brake pedal, 120. Front left wheel speed sensor linear speed, 121. Front right wheel speed sensor linear speed, 122. Rear right wheel speed sensor linear speed, 123. Rear left wheel speed sensor linear speed, 124. Front left half-shaft, 125. Front right half-shaft, 126. CAN (Controller Area) Network (Controller Area Network) bus 127, brake oil line 128.

[0069] Specifically, the ESP control module 115 is connected to four wheel speed sensors via linear speed. The four wheel speed sensors collect wheel speed signals and input them into the ESP module / onebox module 115. The ESP control module 115 is connected to the brakes on the wheels via brake lines 128, delivering brake fluid to the wheel brakes in a timely manner. This drives the pistons on the brake calipers to move, thereby producing a braking effect. The force transmission medium is brake fluid, and the transmission path is through the brake lines 128. This is what we commonly refer to as a hydraulic braking system. The ESP control module 115 is connected to the MCU control module 118 and the EPB control module 116 via bus 127. The ESP control module 115 is also connected to the DBR (Dynamic Brake Regeneration) driver demand calculation module 119 via linear speed to collect the driver's actual braking intentions and needs. Based on the driver's braking intentions, the appropriate braking torque is calculated. The brake pedal 120 is connected to the DBR via a fixed link mechanism, feeding back the driver's needs to the DBR module 119; the EPB control module 116 is connected to the EPB caliper 113 via a linear speed link; the left front brake 105 is fixedly connected to the left front tire 101 with bolts, similarly, the right front tire 102 is fixedly connected to the right front brake 106, the left rear tire 103 is fixedly connected to the left rear brake 107, and the right rear tire 104 is fixedly connected to the right rear brake 108; the brakes and tires are all fixedly connected with bolts; the left front half-shaft... The left front half-shaft 125 is rigidly connected to the left front brake 105 via splines and locking bolts, enabling the motor to rotate and drive the wheel. The right front half-shaft 126 is rigidly connected to the right front brake 106 via splines, enabling the motor to rotate and drive the wheel. The MCU control module 118 drives the motor to rotate. The motor and gearbox are connected by bolts to form a powertrain unit. The powertrain unit is connected to the left front brake 105 and the right front brake 106 via the left front half-shaft 125 and the right front half-shaft 126, respectively. The EPS module 129 in the figure communicates with the EPS control module 115 and the MCU control module 118 via the CAN bus to transmit and implement the driver's steering intentions.

[0070] Furthermore, such as Figure 2 As shown, Figure 2 Mainly for Figure 1 The architecture and control coordination of the electric vehicle chassis control system have been improved. By introducing the main / auxiliary chassis domain control ECU as the central controller, the functions of the originally dispersed subsystems are integrated into the domain controller, realizing centralized decision-making and decentralized execution.

[0071] Figure 2The names of the components are as follows: left front wheel module assembly 201, right front wheel module assembly 202, right rear wheel module assembly 203, left rear wheel module assembly 204, main chassis domain control ECU 205, secondary chassis domain control ECU 206, driving intention input module 207, power supply 208, bus 209.

[0072] The connection relationships between the above components are as follows: The EMB (Electro-Mechanical Brake) caliper controller on the wheel is connected to the main chassis domain control ECU 205 and the auxiliary chassis domain control ECU 206 via CAN bus 209. The connection adopts two forms as shown in the figure, with double arrows in solid black lines and double arrows in dashed black lines. The main chassis domain control ECU 205 and the auxiliary chassis domain control ECU 206 are connected via CAN bus 209 with double arrows in thick black lines. The driving intention input module 207 is connected to the main chassis domain control ECU 205 and the auxiliary chassis domain control ECU 206 via CAN bus with double arrows in thick black dashed lines.

[0073] The EMB caliper controller on the wheel uses an electronic braking system EMB caliper wheel-side controller, such as... Figure 3 As shown, Figure 3 This is a schematic diagram of the structure of a modular wheel according to an embodiment of this application.

[0074] Figure 3 The system adopts an electronic braking mechanism (EMB) caliper wheel-side controller, replacing... Figure 1 The brake system utilizes a hydraulic caliper (with brake fluid as the force transmission medium). The EMB caliper is driven by a rotating motor that moves a piston within the caliper, clamping and releasing the brake disc. The EMB caliper wheel-side controller collects data from wheel speed sensors, calculates and processes the wheel speed signals, and executes commands from the upper control layer to clamp and release the brake disc, achieving the braking effect. It also integrates some MCU functions, enabling drive control of the hub motor and achieving preliminary coordinated control of both drive and braking. The figure shows the hub motor, brake disc, and EMB caliper. The brake is bolted to the wheel and is treated as a single module in this implementation.

[0075] In summary, existing chassis control systems have undergone development stages from distributed control to centralized domain control, and from hydraulic braking to brake-by-wire. The following section provides a detailed description of the specific content of the embodiments described in this application.

[0076] Figure 4 This is a flowchart of a vehicle steering stability control method according to an embodiment of this application.

[0077] like Figure 4 As shown, the vehicle steering stability control method includes the following steps:

[0078] In step S401, the current driving data of the vehicle is obtained.

[0079] Optionally, in some embodiments, the current driving data includes at least one of the following: current sensor dataset, current brake pedal opening, current gear, current accelerator pedal opening, current steering wheel signal, and control commands from the intelligent driving controller.

[0080] Among them, the current driving data is the real-time status information of the vehicle at this moment.

[0081] Specifically, the vehicle's current driving data can be obtained based on sensors in various subsystems. For example, the electric power steering system is equipped with corresponding sensors, and the EMB calipers and wheel-side sensors of the wheel module, as well as the wheel hub motor, are all equipped with various sensors to obtain current driving data.

[0082] It should be understood that the driving intent acquisition module is the key to current driving data collection, and the collection of driving intent data includes, for example,... Figure 5 As shown, Figure 5 This is a schematic diagram of a driving intent input module according to an embodiment of this application.

[0083] The driving intent input module primarily acquires the driver's intent and sends it as an input signal to the main chassis domain control ECU 205 and the auxiliary chassis domain control ECU 206. Based on the information from the driving intent input module, the main chassis domain control ECU 205 and the auxiliary chassis domain control ECU 206 calculate the braking clamping force required by the EMB calipers of each wheel and the driving torque of the wheel hub motor. This information is then input to the wheel's EMB caliper wheel-side controller via the CAN bus 209 in the form of electrical signals. The EMB caliper wheel-side controller drives the EMB motor to apply clamping force to the brake disc and controls the drive of the wheel hub motor, thus realizing the braking and driving functions at the wheel end. The driving intent input module includes brake pedal input 501, gear position signal input 502, accelerator pedal signal input 503, steering wheel input 504, and intelligent driving signal input 505, etc. In this invention, the driving intent input module 209 acts as a modular control unit, interpreting driving intents and also receiving control commands from the upper-level intelligent driving controller 506.

[0084] Therefore, by collecting current driving data and displaying the vehicle's operating condition information, and by focusing on capturing the driver's operation commands through the driver intent acquisition module, the problem of the disconnect between human and vehicle commands and the actual state of the vehicle is solved, providing a core foundation for intelligent chassis control and supporting the precise and safe regulation of the vehicle in various scenarios.

[0085] In step S402, the comprehensive instability index of the vehicle is calculated based on the current driving data, and the actual state of the vehicle is determined according to the comprehensive instability index.

[0086] The Comprehensive Instability Index (CII) is a quantitative indicator that measures whether a vehicle is at risk of losing control. The actual state of a vehicle is determined by a stability level label based on the CII, which clarifies the vehicle's current safety status.

[0087] Optionally, in some embodiments, the comprehensive instability index of the vehicle is calculated based on the current driving data, including: calculating the vehicle's yaw rate error coefficient, tire slip ratio variance, and energy efficiency based on the sensor data in the current sensor dataset, and calculating the comprehensive instability index based on the yaw rate error coefficient, tire slip ratio variance, and energy efficiency.

[0088] Among these, the yaw rate error coefficient is an indicator that measures the deviation between the actual yaw state of the vehicle and the theoretical expectation. The tire slip ratio variance reflects the difference in the degree of slippage between different wheels; the larger the variance, the more uneven the wheel slippage, and the more prone the vehicle is to instability phenomena such as veering and sideslipping. Energy efficiency is the efficiency with which the energy output by the vehicle's drive system is converted into effective driving kinetic energy. When the vehicle becomes unstable, energy is ineffectively consumed due to tire friction, leading to a decrease in efficiency; therefore, it can be used as an auxiliary indicator for judging instability.

[0089] Therefore, by embedding wheel speed sensors and steering angle sensors in each wheel module, basic data such as wheel speed, steering angle, and yaw rate are collected in real time to provide raw input for the calculation of the comprehensive instability index. Driving intention data such as steering wheel angle and pedal travel are collected to assist in judging the vehicle state. Then, the main chassis domain control ECU 205 integrates the data from the wheel modules and the driving intention module to calculate indicators such as the yaw rate error coefficient and tire slip ratio variance, and weights them to obtain the comprehensive instability index. The auxiliary chassis domain control ECU 306 and the main chassis domain control ECU 305 interact in real time via the CAN bus 308. Based on the comparison result of the comprehensive instability index with a preset threshold, the system determines whether the vehicle is in a stable, critical, or unstable state.

[0090] Optionally, in some embodiments, determining the actual state of the vehicle based on the comprehensive instability index includes: determining whether the comprehensive instability index is less than a first preset threshold; if the comprehensive instability index is less than the first preset threshold, then determining that the actual state of the vehicle is a preset stable state; otherwise, determining that the comprehensive instability index is less than or equal to a second preset threshold; if the comprehensive instability index is less than or equal to the second preset threshold, then determining that the actual state of the vehicle is a preset critical state; otherwise, determining that the actual state of the vehicle is a preset unstable state.

[0091] The first preset threshold is a critical value that distinguishes between a stable state and an unstable state. When the comprehensive instability index is less than this threshold, the vehicle is determined to be in a stable state. The second preset threshold is a critical value that distinguishes between a critical state and an unstable state. When the comprehensive instability index is greater than the first threshold but less than or equal to this threshold, it is determined to be in a critical state; if it exceeds this threshold, it is determined to be in an unstable state.

[0092] It should be understood that a stable state is one in which the vehicle drives smoothly without significant risk of instability (the overall instability index is below the first preset threshold). A critical state is an intermediate state where the vehicle shows slight signs of instability, such as minor sideslip or slight wheel slippage, but has not yet lost serious control; the overall instability index is between the first and second preset thresholds. An unstable state is one in which the vehicle is clearly out of control or about to lose control, such as a dangerous state with severe fishtailing or rollover risk; the overall instability index exceeds the second preset threshold.

[0093] Therefore, by first using the information in the current sensor dataset, the yaw rate error coefficient, which reflects the degree of deviation of the vehicle body rotation from the expected value, the tire slip ratio variance, which reflects the balance of wheel slip, and the energy efficiency, which helps to reflect the waste of grip and power, are calculated. Then, the comprehensive instability index is obtained by integrating these three indicators. After that, the vehicle state is determined by comparing the index with two preset thresholds. If it is less than the first preset threshold, it is in a stable state; if it is between the first and second preset thresholds, it is in a critical state; and if it is greater than the second preset threshold, it is in an unstable state. This provides a clear basis for subsequent vehicle stability control.

[0094] In step S403, a stability control strategy for the vehicle is matched according to the actual state of the vehicle, and stability control of the vehicle is performed according to the stability control strategy.

[0095] Among them, the stability control strategy is the vehicle's preset response plan, which includes specific control logic and operation instructions for different instability states.

[0096] Specifically, based on the actual vehicle state determined in the previous step, a stability control strategy is matched. After the strategy is determined, stability control is performed on the vehicle. The core of this strategy is to take precise corresponding measures based on the actual degree of danger to keep the vehicle stable and avoid loss of control.

[0097] Therefore, by utilizing sensors such as wheel speed, steering angle, and yaw rate, comprehensive real-time vehicle driving data is acquired, providing a raw basis for subsequent state determination and strategy formulation. A comprehensive instability index is obtained by calculating and fusing the yaw rate error coefficient, tire slip ratio variance, and energy efficiency. Based on the comparison of this index with a preset threshold, the vehicle state is categorized into three types: stable, critical, and unstable, clearly defining the vehicle's current dynamic state. Appropriate control strategies are matched according to different states: maintaining the existing mode in a stable state, implementing coordinated control in a critical state, and initiating emergency control in an unstable state to ensure vehicle driving safety.

[0098] Optionally, in some embodiments, the actual state is a preset stable state. The vehicle's stability control strategy is matched according to the actual state of the vehicle, and the vehicle's stability is controlled according to the stability control strategy. This includes: when the actual state is a preset stable state, determining that the stability control strategy is to maintain the current control mode of the vehicle, and performing stability control on the vehicle based on the current control mode.

[0099] The preset stable state can be a stable state pre-set by the user, a stable state obtained through a finite number of experiments, or a stable state obtained through a finite number of computer simulations; no specific limitation is made here.

[0100] It should be understood that if the vehicle's driving state remains stable, the existing control method should be maintained without any additional adjustments to the control strategy.

[0101] Optionally, in some embodiments, the actual state is a preset critical state. The vehicle's stability control strategy is matched according to the actual state of the vehicle, and the vehicle's stability is controlled according to the stability control strategy. This includes: when the actual state is a preset critical state, determining the stability control strategy as a coordinated control strategy, and based on the coordinated control strategy, performing stability control on the vehicle according to a preset wheel hub motor torque dynamic distribution algorithm and a preset steer-by-wire angle compensation amount.

[0102] The preset critical state can be a user-defined critical state, a critical state obtained through a finite number of experiments, or a critical state obtained through a finite number of computer simulations; no specific limitation is made here. The preset in-wheel motor torque dynamic distribution algorithm can be a user-defined preset in-wheel motor torque dynamic distribution algorithm, a preset in-wheel motor torque dynamic distribution algorithm obtained through a finite number of experiments, or a preset in-wheel motor torque dynamic distribution algorithm obtained through a finite number of computer simulations; no specific limitation is made here. The preset steer-by-wire angle compensation amount can be a user-defined preset steer-by-wire angle compensation amount, a preset steer-by-wire angle compensation amount obtained through a finite number of experiments, or a preset steer-by-wire angle compensation amount obtained through a finite number of computer simulations; no specific limitation is made here.

[0103] Specifically, the vehicle is in a preset critical state, meaning that the overall instability index has exceeded the first preset threshold but not reached the second preset threshold. The vehicle shows slight signs of instability but has not yet seriously lost control. At this point, active intervention is required but no forceful operation is necessary. Two preset strategies will be activated simultaneously: one is a preset wheel hub motor torque dynamic distribution algorithm, and the other is a preset steer-by-wire angle compensation amount. Through the cooperation of the drive system and the steering system, the attitude is corrected with a small intervention amplitude, which avoids escalation of risk and minimizes interference with the driving experience.

[0104] Combination Figure 6 As shown, where Figure 6 The following is a flowchart illustrating the coordinated control strategy under critical conditions in this application embodiment, with the specific steps as follows:

[0105] Step S601, Steering wheel angle input: Receive the driver's steering wheel operation signal, i.e., the steering wheel angle information. The steering wheel angle reflects the driver's steering intention and is an important basis for subsequent control strategy formulation.

[0106] Step S602, Ideal yaw moment calculation: Based on the steering wheel angle input and the vehicle's current operating parameters, such as vehicle speed, wheel speed, and center of gravity sideslip angle, the system calculates the ideal yaw moment required to achieve the steering effect desired by the driver.

[0107] Step S603, front wheel steering angle correction: Based on the calculated ideal yaw moment, the steering angle of the front wheels is corrected.

[0108] Step S604, rear wheel steering compensation, refers to adjusting the steering angle of the rear wheels according to the vehicle's driving state and ideal yaw moment.

[0109] Step S605, hub motor torque compensation: The hub motor can independently control the torque output of each wheel. By adjusting the torque of different wheels, dynamic torque distribution can be achieved, further optimizing the vehicle's steering performance and stability.

[0110] Step S606: Dynamic transmission ratio adjustment. The dynamic transmission ratio is adjusted according to the vehicle's driving status and steering requirements.

[0111] For example, this application embodiment combines emergency obstacle avoidance scenarios and slippery road surface scenarios to provide a detailed description of the control when the actual state reaches a preset critical state.

[0112] As one implementation scenario, a critical state coordination control strategy is used in emergency obstacle avoidance scenarios, as shown in the flowchart below. Figure 7 As shown, Figure 7 This is a flowchart illustrating an emergency avoidance process according to an embodiment of this application. The specific operation steps are as follows:

[0113] In step S701, the vehicle uses various sensors, such as cameras and radar, to perceive the surrounding environment and identify obstacles.

[0114] In step S702, after identifying an obstacle, the system will plan a safe and feasible obstacle avoidance path based on information such as the current vehicle status, the location of the obstacle, and its movement trend.

[0115] In step S703, based on the planned obstacle avoidance path, the system generates a corresponding turning command. This command specifies the angle and direction in which the vehicle needs to turn the steering wheel to avoid the obstacle.

[0116] In step S704, after receiving the steering command, the system needs to calculate the yaw moment required to make the vehicle turn according to the command and remain stable.

[0117] In step S705, to generate the required yaw moment, the system employs a differential braking control strategy, which involves applying different braking forces to different wheels of the vehicle.

[0118] In step S706, while performing differential braking control, the system also adjusts the vehicle's drive torque. This is to maintain the stability of the vehicle's speed and power output while ensuring the vehicle's steering performance.

[0119] As another implementation scenario, the critical state collaborative control strategy is still used in the case of slippery road surface skidding. The specific flowchart is as follows: Figure 8 As shown, Figure 8 This is a flowchart of a wet and slippery road surface control system according to an embodiment of this application. The specific operation steps are as follows:

[0120] Step S801: Receive the driver's operation signal on the accelerator pedal.

[0121] In step S802, based on the signal input from the accelerator pedal and combined with the vehicle's current operating parameters, such as vehicle speed and engine speed, the system calculates the driving torque that meets the driver's needs.

[0122] In step S803, the system detects the speed difference between the various wheels of the vehicle. Wheel difference refers to the difference in speed between the left and right wheels on the same axle, which may affect the vehicle's driving stability.

[0123] Step S804: Compare the detected wheel difference with a preset threshold. If the wheel difference is greater than the threshold, it indicates that the vehicle's driving state may be unstable, and proceed to step S805. If the wheel difference is less than or equal to the threshold, it indicates that the vehicle's driving state is normal, and proceed to step S807.

[0124] Step S805: Use appropriate torque control.

[0125] In step S806, while performing torque appropriate control, the system also applies braking control to the inner wheels of the vehicle. By applying braking force to the inner wheels, the vehicle's driving posture can be further adjusted to prevent instability such as oversteer or understeer. This works in conjunction with torque appropriate control to ensure stable vehicle operation.

[0126] In step S807, if the wheel difference is less than or equal to the threshold, it indicates that the vehicle is in normal driving condition. The system will directly output the previously calculated driving torque without any additional adjustment or control.

[0127] Therefore, when the vehicle's actual state is at a preset critical state, a coordinated control strategy will be applied. This strategy relies on a multi-level control architecture, with the chassis domain control system as hardware support, and uses data collected by multiple sources of sensors to jointly maintain the vehicle's stability in the critical state, effectively preventing the vehicle from developing into an unstable state.

[0128] Optionally, in some embodiments, the actual state is a preset instability state. The vehicle's stability control strategy is matched according to the actual state of the vehicle, and the vehicle's stability is controlled according to the stability control strategy, including: when the actual state is a preset instability state, determining the stability control strategy as an emergency control strategy; and based on the emergency control strategy, controlling the vehicle's stability according to a preset four-wheel independent braking strategy, a preset steering angle limiting strategy, and a preset drive torque cutoff strategy.

[0129] The preset instability state can be a user-defined instability state, an instability state obtained through a limited number of experiments, or an instability state obtained through a limited number of computer simulations; no specific limitation is made here. The preset four-wheel independent braking strategy can be a user-defined four-wheel independent braking strategy, a four-wheel independent braking strategy obtained through a limited number of experiments, or a four-wheel independent braking strategy obtained through a limited number of computer simulations; no specific limitation is made here. The preset steering angle limiting strategy can be a user-defined steering angle limiting strategy, a steering angle limiting strategy obtained through a limited number of experiments, or a steering angle limiting strategy obtained through a limited number of computer simulations; no specific limitation is made here. The preset drive torque cutoff strategy can be a user-defined drive torque cutoff strategy, a drive torque cutoff strategy obtained through a limited number of experiments, or a drive torque cutoff strategy obtained through a limited number of computer simulations; no specific limitation is made here.

[0130] Specifically, the vehicle is in a preset instability state, meaning the overall instability index has exceeded the second preset threshold. Without immediate intervention, an accident is highly likely. Control is achieved by matching an emergency control strategy. This strategy involves the forced application of three preset strategies: independent four-wheel braking, steering angle limiting, and drive torque cutoff, to quickly stabilize the vehicle and prevent loss of control. The specific instability level classification theory and collaborative control concept are as follows: Figure 9 As shown, Figure 9 This is a flowchart illustrating the instability level classification theory and collaborative control based on an embodiment of this application.

[0131] The perception layer 901 is mainly responsible for collecting various information required for vehicle operation, including on-board sensors and V2X (Vehicle to Everything) data 906. On-board sensors can obtain the vehicle's own status, such as vehicle speed, wheel speed and steering angle. V2X data is obtained from the vehicle's communication with the external environment, such as the position of the vehicle in front and the status of traffic lights. This data provides the basis for subsequent decision-making.

[0132] The decision-making layer 902 primarily analyzes and processes data from the perception layer to formulate control strategies. Its core components include a hierarchical controller and the GFA-PAD (Genetic Algorithm-Proportion Integration Differentiation) algorithm 905. The hierarchical controller prioritizes and allocates different control tasks to ensure coordinated operation of various systems. The GFA-PID algorithm dynamically adjusts control parameters to achieve precise control, such as calculating appropriate torque distribution and steering compensation when the vehicle is in a critical state.

[0133] The execution layer 903 primarily controls the actuators based on the decision-making layer's strategy to achieve vehicle motion control. Its actuators include in-wheel motors, the ESC (Electronic Stability Control) system, and steer-by-wire 904. The in-wheel motors mainly provide power and enable independent control of the four wheels, adjusting wheel torque output to adapt to different operating conditions. When the vehicle is unstable, the ESC system applies braking force to the wheels to help restore stability. Steer-by-wire precisely controls the steering angle, achieving compensation or limitation, improving handling and stability.

[0134] This architecture integrates instability severity classification theory with collaborative control concepts, establishing a predictive model library containing 12 typical operating conditions. These 12 conditions mainly include normal straight-line driving, emergency braking, emergency avoidance, driving on slippery surfaces, driving on snow or ice, cornering, high-speed lane changing, uphill driving, downhill braking, driving under crosswinds, vehicle load changes, and tire pressure changes, enabling pre-loading of control strategies. By combining a hybrid optimization algorithm with multimodal control, a CSI (Comprehensive Stability Index) function is set:

[0135] F=α·β / γ

[0136] Where F is the comprehensive stability index, α is the yaw rate error coefficient, β is the tire slip ratio variance, and γ is the energy efficiency index; different control parameters are adopted for different road surfaces, as shown in Table 1 below. Table 1 is a table of control variable changes for different road surfaces.

[0137] Table 1

[0138] Serial Number Operating conditions Control parameters 1 conventional road surface <![CDATA[Proportionality coefficient K p = 0.8]]> 2 low adhesion <![CDATA[Integration time T i = 0.2 s]]> 3 Extreme conditions <![CDATA[Differential coefficient K d = 1.5]]>

[0139] It should be understood that the adaptive stability evaluation model introduces the Comprehensive Instability Index (CSI) to predict the stability trend over the next 3 seconds. It then divides the control domain into three levels (stable region / transition region / critical region) to match different control strategies, including:

[0140] Stable Zone (Normal Operating Condition) Control Strategy: A conventional control mode is adopted, primarily focusing on economy and comfort. In this zone, the system will not intervene excessively to maintain the vehicle's natural driving characteristics and fuel efficiency.

[0141] Transition zone control strategy: Activate coordinated control modes, such as pre-tensioned braking intervention. Prevent vehicle instability by making slight adjustments to braking and steering, while maintaining vehicle handling and responsiveness.

[0142] A high CSI value in the critical zone indicates that the vehicle is approaching or has already reached a state of instability. Critical zone control strategy: Employ emergency control modes such as independent four-wheel braking, steering angle limiting, and drive torque cutoff. These strong interventions rapidly restore vehicle stability and prevent accidents.

[0143] For example, such as Figure 10 As shown, Figure 10 A flowchart illustrating slip ratio-based control under unstable conditions is provided in one embodiment of this application. The specific operation steps are as follows:

[0144] Step S1001: Wheel speed sensor input. The wheel speed sensors collect the rotational speed information of each wheel in real time. The wheel speed sensors are usually installed near the wheels and can accurately measure the rotational speed of the wheels and transmit this data to the electronic control unit of ABS (Anti-lock Braking System).

[0145] Step S1002, slip ratio calculation: calculate the slip ratio of the wheel based on the wheel speed information input by the wheel speed sensor.

[0146] Step S1003: Whether the threshold value has been reached, the ABS electronic control unit compares the calculated slip ratio with the preset threshold value. If the threshold value has been reached, proceed to step S1004; otherwise, proceed to step S1005.

[0147] In step S1004, ABS is activated, and the electronic control unit sends a command to the brake pressure regulator to adjust the braking pressure of each wheel.

[0148] Step S1005, conventional braking.

[0149] In summary, to further explain the content of the embodiments of this application, by combining... Figure 11 Further analysis of the collaborative operation mechanism of each link. Among them... Figure 11 A general flowchart of the main control program is provided according to one embodiment of this application.

[0150] Step S1101: Collect real-time data on vehicle operation using various sensors.

[0151] In step S1102, based on the data collected by the sensors, the system performs a comprehensive assessment of the vehicle's current dynamic state.

[0152] In step S1103, based on the results of the dynamic state assessment, the system classifies the vehicle's stability into three levels: stable state S1104, critical state S1105, and unstable state S1106.

[0153] In step S1107, when the vehicle is in a stable state, the system will enter the economy mode. The control of the vehicle is mainly dominated by the drive system in step S1110. The drive system controls the power output of the vehicle by adjusting the output power of the engine and the shift timing of the transmission, so as to improve fuel economy and driving comfort.

[0154] In step S1108, when the vehicle is in a critical state, the system enters motion mode. The vehicle adopts the steering-braking coordinated control strategy of step S1111. The steering system and braking system cooperate with each other to achieve precise control of the vehicle's trajectory and stability by adjusting the steering angle and braking pressure. For example, when the vehicle is turning, the turning radius is reduced by applying appropriate braking pressure to the inner wheels, thereby improving the vehicle's handling performance.

[0155] In step S1109, when the vehicle is in an unstable state, the system will enter emergency mode. The vehicle will adopt the four-wheel independent control strategy of step S1112. By independently controlling the braking pressure and power output of the four wheels, the vehicle attitude will be precisely adjusted to restore the vehicle to stability as soon as possible.

[0156] In this application embodiment, three modes of coverage algorithm are adopted: economic mode, sport mode and extreme mode. Different control strategies based on vehicle driving conditions correspond to different control objectives and execution methods.

[0157] Economic model: MPC-based trajectory tracking, driven by the system.

[0158] Sport mode: Combines hybrid optimization algorithms to optimize control parameters, generally using the coordination of braking and steering.

[0159] Extreme Mode: Activates emergency mode, adopting a four-wheel independent control mode.

[0160] Table 2 shows the weight allocation tables for various modes.

[0161] Table 2

[0162] Control Mode Driving weights Braking weight Shift weight economic model 0.6 0.2 0.2 Sports Mode 0.4 0.4 0.2 Emergency Mode 0.1 0.2 0.2

[0163] Thus, by acquiring sensor data, evaluating dynamic status, determining stability levels, and selecting corresponding control modes, comprehensive control and management of vehicle driving stability are achieved, improving vehicle driving safety and handling.

[0164] Furthermore, to enable those skilled in the art to better understand the vehicle steering stability control method of the embodiments of this application, the following is combined with... Figure 12 A detailed flowchart illustrating the vehicle steering stability control method is provided. Figure 12 This is a detailed flowchart of the main control program provided according to an embodiment of the present application.

[0165] Step S1201, Begin.

[0166] Step S1202: Real-time data on vehicle operation is collected using multiple sensors.

[0167] Step S1203 involves preprocessing the collected multi-source sensor data to remove noise, correct errors, and standardize the data format.

[0168] In step S1204, based on the preprocessed data, the system performs decision-level perception and calculates the comprehensive stability index.

[0169] Step S1205: Based on the calculated CSI index, the system judges the stability of the vehicle.

[0170] In step S1206, CSI < 0.3, indicating that the vehicle is in a stable state, and enters the normal control mode in step S1207, and then executes step S1208 drive torque control, step S1209 steering angle compensation, step S1210 basic brake holding and step S1211 output brake holding.

[0171] Step S1212, CSI = [0.3, 0.7], indicates that the vehicle is in a critical state, and enters step S1213 coordinated control mode, then step S1214 torque vector control, step S1215 active steering intervention, step S1216 differential braking adjustment and step S1217 composite control output.

[0172] In step S1218, CSI > 0.7, it indicates that the vehicle is in an unstable state. Step S1219 Emergency Control Mode is entered, followed by step S1220 Four-wheel Independent Braking, step S1221 Steering Angle Limitation, step S1222 Drive Torque Cutoff, and step S1223 Safety Mode Output.

[0173] Therefore, through the workflow of the vehicle stability control system based on the comprehensive stability index, by acquiring data from multiple sources of sensors, preprocessing data, calculating the CSI index, judging stability, and selecting corresponding control modes and formulating control strategies, comprehensive control and management of vehicle driving stability is achieved, thereby improving vehicle driving safety and handling.

[0174] According to the embodiments of this application, a vehicle steering stability control method is proposed. By calculating the comprehensive instability index based on the current driving data of the vehicle, a hierarchical vehicle steering stability control method with collaborative control is adopted. This method solves the problem of insufficient coordination and difficulty in leveraging the combined advantages caused by the decentralized control of subsystems in traditional electric vehicle chassis systems, which affects vehicle stability. This method greatly improves the driving safety and handling of passengers.

[0175] Next, referring to the accompanying drawings, a vehicle steering stability control device according to an embodiment of this application is described.

[0176] Figure 13This is a block diagram of a vehicle steering stability control device according to an embodiment of this application.

[0177] like Figure 13 As shown, the vehicle steering stability control device includes:

[0178] The acquisition module 100 is used to acquire the vehicle's current driving data;

[0179] The determination module 200 is used to calculate the vehicle's comprehensive instability index based on the current driving data, and determine the vehicle's actual state based on the comprehensive instability index;

[0180] The matching module 300 is used to match the vehicle's stability control strategy according to the vehicle's actual state, and to perform stability control on the vehicle according to the stability control strategy.

[0181] Optionally, in some embodiments, the current driving data includes at least one of the following: current sensor dataset, current brake pedal opening, current gear, current accelerator pedal opening, current steering wheel signal, and control commands from the intelligent driving controller.

[0182] Optionally, in some embodiments, the determining module 200 is specifically used to: calculate the vehicle's yaw rate error coefficient, tire slip ratio variance, and energy efficiency based on the sensor data in the current sensor dataset; and calculate the comprehensive instability index based on the yaw rate error coefficient, tire slip ratio variance, and energy efficiency.

[0183] Optionally, in some embodiments, the determining module 200 is further configured to: determine whether the comprehensive instability index is less than a first preset threshold; if the comprehensive instability index is less than the first preset threshold, determine that the actual state of the vehicle is a preset stable state; otherwise, determine that the comprehensive instability index is less than or equal to a second preset threshold; if the comprehensive instability index is less than or equal to the second preset threshold, determine that the actual state of the vehicle is a preset critical state; otherwise, determine that the actual state of the vehicle is a preset instability state.

[0184] Optionally, in some embodiments, the matching module 300 is specifically used to: determine the stability control strategy as maintaining the current control mode of the vehicle when the actual state is a preset stable state; and perform stability control on the vehicle based on the current control mode.

[0185] Optionally, in some embodiments, the matching module 300 is further configured to: determine the stability control strategy as a coordinated control strategy when the actual state is a preset critical state; and perform stability control on the vehicle based on the coordinated control strategy, according to a preset wheel hub motor torque dynamic distribution algorithm and a preset steer-by-wire angle compensation amount.

[0186] Optionally, in some embodiments, the matching module 300 is further configured to: determine the stability control strategy as an emergency control strategy when the actual state is a preset instability state; and perform stability control on the vehicle based on the emergency control strategy according to a preset four-wheel independent braking strategy, a preset steering angle limiting strategy, and a preset drive torque cutting-off strategy.

[0187] It should be noted that the foregoing explanation of the vehicle steering stability control method embodiment also applies to the vehicle steering stability control device of this embodiment, and will not be repeated here.

[0188] The vehicle steering stability control device proposed in this application calculates the comprehensive instability index using the vehicle's current driving data and adopts a hierarchical vehicle steering stability control method with collaborative control. This solves the problem of insufficient coordination and difficulty in leveraging combined advantages caused by the decentralized control of subsystems in traditional electric vehicle chassis systems, which affects vehicle stability and greatly improves the driving safety and handling of passengers.

[0189] Figure 14 This is a schematic diagram of a vehicle provided in an embodiment of the present invention. The vehicle may include:

[0190] The memory 1401, the processor 1402, and the computer program stored on the memory 1401 and executable on the processor 1402.

[0191] When the processor 1402 executes the program, it implements the vehicle steering stability control method provided in the above embodiments.

[0192] Furthermore, the vehicle also includes:

[0193] Communication interface 1403 is used for communication between memory 1401 and processor 1402.

[0194] The memory 1401 is used to store computer programs that can run on the processor 1402.

[0195] The memory 1401 may include high-speed RAM (Random Access Memory) memory, and may also include non-volatile memory, such as at least one disk storage.

[0196] If the memory 1401, processor 1402, and communication interface 1403 are implemented independently, then the communication interface 1403, memory 1401, and processor 1402 can be interconnected via a bus to complete communication between them. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 14 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0197] Optionally, in a specific implementation, if the memory 1401, processor 1402, and communication interface 1403 are integrated on a single chip, then the memory 1401, processor 1402, and communication interface 1403 can communicate with each other through an internal interface.

[0198] The processor 1402 may be a CPU (Central Processing Unit), an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention.

[0199] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the vehicle steering stability control method described above.

[0200] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0201] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0202] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A vehicle steering stability control method, characterized in that, Includes the following steps: Obtain the vehicle's current driving data; Based on the current driving data, calculate the comprehensive instability index of the vehicle, and determine the actual state of the vehicle based on the comprehensive instability index; The stability control strategy of the vehicle is matched according to the actual state of the vehicle, and the stability control of the vehicle is performed according to the stability control strategy.

2. The method according to claim 1, characterized in that, The current driving data includes at least one of the following: current sensor dataset, current brake pedal opening, current gear, current accelerator pedal opening, current steering wheel signal, and control commands from the intelligent driving controller.

3. The method according to claim 2, characterized in that, The calculation of the vehicle's comprehensive instability index based on the current driving data includes: The yaw rate error coefficient, tire slip variance, and energy efficiency of the vehicle are calculated based on the sensor data in the current sensor dataset. The comprehensive instability index is calculated based on the yaw rate error coefficient, the tire slip ratio variance, and the energy efficiency.

4. The method according to claim 3, characterized in that, Determining the actual state of the vehicle based on the comprehensive instability index includes: Determine whether the comprehensive instability index is less than a first preset threshold; If the comprehensive instability index is less than the first preset threshold, the actual state of the vehicle is determined to be a preset stable state; otherwise, the comprehensive instability index is determined to be less than or equal to the second preset threshold. If the comprehensive instability index is less than or equal to the second preset threshold, the actual state of the vehicle is determined to be a preset critical state; otherwise, the actual state of the vehicle is determined to be a preset instability state.

5. The method according to claim 4, characterized in that, The actual state is the preset stable state. Matching the vehicle's stability control strategy to the actual state of the vehicle, and performing stability control on the vehicle according to the stability control strategy, includes: When the actual state is the preset stable state, the stability control strategy is determined to maintain the current control mode of the vehicle. The vehicle is subjected to stability control based on the current control mode.

6. The method according to claim 4, characterized in that, The actual state is the preset critical state. Matching the vehicle's stability control strategy to the actual state of the vehicle, and performing stability control on the vehicle according to the stability control strategy, includes: When the actual state is the preset critical state, the stability control strategy is determined to be a coordinated control strategy. Based on the aforementioned coordinated control strategy, the vehicle's stability is controlled according to a preset wheel hub motor torque dynamic distribution algorithm and a preset steer-by-wire angle compensation amount.

7. The method according to claim 4, characterized in that, The actual state is the preset instability state. Matching the vehicle's stability control strategy to the actual state of the vehicle, and performing stability control on the vehicle according to the stability control strategy, includes: When the actual state is the preset unstable state, the stability control strategy is determined to be an emergency control strategy. Based on the aforementioned emergency control strategy, the vehicle's stability is controlled according to a preset four-wheel independent braking strategy, a preset steering angle limiting strategy, and a preset drive torque cutoff strategy.

8. A vehicle steering stability control device, characterized in that, include: The acquisition module is used to acquire the vehicle's current driving data; The determination module is used to calculate the comprehensive instability index of the vehicle based on the current driving data, and determine the actual state of the vehicle based on the comprehensive instability index; The matching module is used to match the stability control strategy of the vehicle according to the actual state of the vehicle, and to perform stability control on the vehicle according to the stability control strategy.

9. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle steering stability control method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the vehicle steering stability control method as described in any one of claims 1-7.

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