Vehicle stability judgment method considering dynamic centroid and road alignment coupling

Abstract

The invention discloses a vehicle stability judgment method considering dynamic centroid and road alignment coupling, and relates to the technical field of vehicle active safety control. The method comprises the following steps: constructing an input state quantity of a vehicle dynamics system; a parameter identification model is established, and the whole vehicle mass center height of the vehicle is estimated in real time; constructing a road geometric decoupling observer, and separating a slope angle and a pavement inclination angle of the current pavement from inertia measurement information; calculating an energy-based dynamic rolling stability index; determining a transverse stability boundary by integrating the pavement adhesion condition and the pavement geometric constraint; and a dynamic safety envelope surface is constructed according to the dynamic rolling stability index and the transverse stability boundary, and the vehicle stability is judged based on the envelope surface. According to the method, the vehicle load change and the road linear interference are decoupled in real time, so that the self-adaptive dynamic adjustment of the stability judgment boundary is realized, and the identification precision of the vehicle state parameters and the robustness of stability judgment under the variable load and complex road geometric working conditions are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of autonomous driving and vehicle active safety control technology, specifically relating to a vehicle stability judgment method that can adapt to load changes and complex road geometry conditions. Background Technology

[0002] With the development of active safety technologies in automobiles, Electronic Stability Control (ESC) and Rollover Mitigation System (RSC) have become key configurations for ensuring driving safety, and accurate, real-time stability assessment is a prerequisite for timely intervention by the system. Current assessment methods (such as patent application CN115946679A) largely rely on onboard sensors and dynamic models, utilizing offline tests to define a set stability region, which improves the accuracy of the assessment to some extent.

[0003] However, existing technologies still have significant limitations when facing complex and ever-changing real-world conditions: First, they neglect the time-varying nature of vehicle inertial parameters. Existing models typically assume a fixed center of gravity height, which cannot adapt to the center of gravity drift caused by load changes (fully loaded / empty) in SUVs or commercial vehicles, resulting in a lag in the prediction of rollover risk under high center of gravity conditions. Second, they lack decoupling from road alignment. Existing methods are mostly based on the assumption of a "flat road surface," failing to eliminate the interference of gravity components caused by road slopes or superelevation of curves on sensor readings, leading to distortion in stability index calculations in scenarios such as mountain roads or ramps. Finally, the stability boundary lacks adaptability. The static judgment space based on offline calibration cannot shrink or expand in real time according to the road inclination angle and vehicle loading status, easily leading to false judgments of "safety" on wet or sloping roads.

[0004] In summary, developing a stability assessment method that can sense the centroid height in real time, decouple road alignment interference, and dynamically reconstruct the safety boundary is a pressing technical challenge that needs to be addressed. Summary of the Invention

[0005] This invention addresses the problems existing in the prior art by providing a vehicle stability assessment method that can adapt to load changes and complex road geometry conditions. Through a multi-level observer architecture, it decouples vehicle load changes and road geometry disturbances in real time and constructs an adaptive dynamic safety envelope.

[0006] To solve the above technical problems, the present invention provides the following technical solution: a vehicle stability judgment method considering the coupling of dynamic centroid and road alignment, comprising the following steps:

[0007] S1. Obtain vehicle driving state information and suspension attitude information to construct the input state variables of the vehicle dynamics system. ;

[0008] S2. Based on the suspension attitude information and roll dynamic response, establish a parameter identification model to estimate the vehicle's center of gravity height in real time. ;

[0009] S3. Construct a road geometry decoupling observer, establish kinematic equations based on the vehicle driving state information, and separate the current road surface slope angle. and road surface slope ;

[0010] S4, combined with the aforementioned vehicle center of gravity height and road surface slope Calculate energy-based dynamic roll stability index ;

[0011] S5. Comprehensive road surface adhesion conditions and the road surface inclination angle Determine the lateral stability boundary of the vehicle under road surface geometric constraints;

[0012] S6. Based on the dynamic roll stability index A dynamic safety envelope is constructed using the lateral stability boundary to determine the real-time stability state of the vehicle.

[0013] Furthermore, in the aforementioned step S1, the input state quantity As shown in the following formula:

[0014] ,

[0015] In the formula, For the longitudinal and lateral accelerations of the vehicle; The yaw rate is angular velocity. These are the vehicle body roll rate and roll angle, respectively. For the vehicle's longitudinal and lateral speeds; The steering angle of the front wheels; These are the suspension travel distances for the left front, right front, left rear, and right rear wheels, respectively; the suspension travel distance is used to calculate the instantaneous roll stiffness.

[0016] Furthermore, step S2 described above specifically involves: establishing the differential equation of vehicle roll dynamics that includes the center of mass parameter:

[0017] ,

[0018] In the formula: This represents the moment of inertia of the entire vehicle about its roll axis. For the overall vehicle weight; The distance from the center of mass to the center of roll; This is the roll damping coefficient; For roll stiffness; It is the acceleration due to gravity; The road surface inclination angle; This refers to the vehicle body roll angle acceleration;

[0019] Transform the differential equation into a linear regression form. Construct the parameter vector to be identified and regression vector ,in Includes terms characterizing the tilt arm of the center of mass. Real-time updates using recursive least squares method From the convergent parameter vector Extract Divide the term by the total vehicle mass m to calculate the center of gravity and the roll arm. Thus, the height of the vehicle's center of gravity is obtained. .

[0020] Furthermore, the aforementioned construction of the parameter vector to be identified As shown in the following formula:

[0021] ,

[0022] Construct the corresponding regression vector As shown in the following formula:

[0023] ,

[0024] Using a more direct form of torque balance, the equations are rearranged as follows:

[0025] ,

[0026] at this time:

[0027] ,

[0028] ,

[0029] .

[0030] Furthermore, the aforementioned method utilizes recursive least squares for real-time updates. From the convergent parameter vector Extract Divide the term by the total vehicle mass m to calculate the center of gravity and the roll arm. Thus, the height of the vehicle's center of gravity is obtained. Specifically:

[0031] Perform iterative updates using recursive least squares: utilizing the forgetting factor Update the parameters to adapt to the time-varying characteristics of the quality:

[0032]

[0033]

[0034]

[0035] In the formula, Here is the gain matrix. Let be the covariance matrix.

[0036] Parameter decoupling and centroid calculation: from convergent parameter vectors Extract the third item Based on the known vehicle mass m (or the mass estimated through longitudinal dynamics), the center of gravity roll arm is calculated:

[0037]

[0038] The final vehicle center of gravity height is obtained as follows:

[0039]

[0040] In the formula The roll center height is determined by the suspension geometry.

[0041] Furthermore, in step S3 above, the road geometry decoupling observer's decoupling logic is based on the following kinematic equations describing the relationship between sensor measurements and gravity components:

[0042] ,

[0043] In the formula, , The acceleration value is directly measured by the inertial measurement unit; For the vehicle's longitudinal and lateral speeds, The yaw rate is angular velocity. It is the acceleration due to gravity;

[0044] Design an extended Kalman filter and define the state vector. The kinematic equations are used as a measurement model to estimate the road surface slope in real time. and road surface slope This eliminates the interference of the gravitational component on acceleration readings.

[0045] Furthermore, the aforementioned energy-based dynamic tumbling stability index The calculation is as follows:

[0046] ,

[0047] In the formula, , , This refers to the dynamic roll stability index value; This represents the current total energy of the tilt. This represents the critical potential energy for rollover. The static rollover threshold angle; the critical rollover potential energy With the height of the center of mass Increase and unfavorable road surface slope angle Increase and decrease To characterize the term of the tilt arm at the center of mass, This represents the height of the vehicle's center of gravity, where m is the vehicle's mass. It is the acceleration due to gravity. The body roll angle, This is the moment of inertia of the entire vehicle about the roll axis.

[0048] Furthermore, in the aforementioned step S5, the vehicle lateral stability boundary is expressed as the limiting yaw rate. The calculation is as follows:

[0049] ,

[0050] In the formula, This is an estimated value for the road surface adhesion coefficient; This is the gravity component compensation term caused by the road surface inclination, used to characterize the asymmetric correction of the vehicle's lateral stability boundary on curves with extreme steepness. This represents the vehicle's longitudinal speed.

[0051] Another aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described in the present invention.

[0052] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described in the present invention.

[0053] Compared with the prior art, the beneficial technical effects of the present invention using the above technical solution are as follows:

[0054] (1) In the vehicle stability judgment method considering the coupling between dynamic center of gravity and road alignment in this application, the height of the vehicle's center of gravity is estimated in real time by constructing a parameter identification model, which can adaptively cope with time-varying working conditions such as full load, empty load, or uneven cargo distribution. Compared with the traditional judgment method based on fixed vehicle parameters, this invention effectively solves the problem of inaccurate rollover threshold estimation caused by load changes, and significantly improves the stability judgment accuracy of SUVs, commercial vehicles, and buses under high center of gravity conditions.

[0055] (2) The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment in this invention application eliminates the reliance on the assumption of a flat road surface and uses a road surface geometry decoupling observer to achieve accurate separation of road slope and superelevation (inclination). This method can eliminate the interference of gravity component on sensor readings and distinguish between "vehicle motion acceleration" and "road surface gravity component", thereby effectively avoiding false alarms and false negatives in stability scenarios such as three-dimensional traffic, mountain roads and steep curves, and enhancing the robustness of the system under complex road conditions.

[0056] (3) In the vehicle stability judgment method considering the coupling of dynamic centroid and road alignment in this invention application, a dynamic safety envelope surface based on roll energy and gravitational potential energy correction is set up to realize the dynamic adjustment of the stability boundary. This method breaks through the limitations of the traditional fixed threshold. By introducing E-RI energy index and road surface geometric constraints, it can automatically shrink the safety boundary to provide early warning under adverse conditions and appropriately expand the boundary under favorable conditions (such as inward curve) to reduce unnecessary system intervention. While ensuring driving safety, it maximizes the smoothness of operation and vehicle passability. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the vehicle stability judgment method considering the coupling between dynamic centroid and road alignment according to the present invention.

[0058] Figure 2 This is a diagram of the vehicle roll dynamics force model including the road surface inclination angle according to the present invention;

[0059] Figure 3 This is a block diagram illustrating the principle of the real-time centroid height estimation observer of the present invention.

[0060] Figure 4 This is a schematic diagram of the road slope and inclination decoupling logic of the present invention;

[0061] Figure 5 This is a schematic diagram comparing the dynamic safety envelope of the present invention with the traditional static stability region; Detailed Implementation

[0062] To better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

[0063] In this invention, various aspects of the invention are described with reference to the accompanying drawings, in which numerous illustrative embodiments are shown. Embodiments of the invention are not limited to those depicted in the drawings. It should be understood that the invention is implemented through any of the various concepts and embodiments described above, as well as the concepts and embodiments described in detail below, because the concepts and embodiments disclosed herein are not limited to any particular implementation. Furthermore, some aspects of the invention disclosed may be used alone or in any suitable combination with other aspects of the invention disclosed.

[0064] refer to Figure 1 This embodiment provides a vehicle stability judgment method considering the coupling between dynamic centroid and road alignment, including the following steps:

[0065] S1. Obtain vehicle driving state information and suspension attitude information to construct the input state variables of the vehicle dynamics system. .

[0066] Vehicle motion information includes longitudinal acceleration, lateral acceleration, yaw rate, roll rate, roll angle, vehicle speed, and steering wheel angle. The longitudinal acceleration, lateral acceleration, yaw rate, roll rate, and roll angle are acquired by an inertial measurement unit (IMU) installed at the vehicle's center of gravity. Vehicle speed is estimated using wheel speed sensors combined with Kalman filtering. The steering wheel angle is acquired via the vehicle controller area network (CAN) bus. Suspension attitude information includes the suspension travel of the four wheels (left front, right front, left rear, and right rear). The suspension travel is acquired by linear displacement sensors or height sensors installed on the suspension arms.

[0067] state variables for: ,

[0068] In the formula, For the longitudinal acceleration of the vehicle, This refers to the vehicle's lateral acceleration, reflecting its translational state. Let yaw rate be the vehicle's angular velocity. The vehicle body roll rate. The body roll angle reflects the vehicle's rotational dynamics. For the longitudinal speed of the vehicle, The vehicle's lateral speed; This refers to the front wheel steering angle, reflecting the driver's steering intention; The four-wheel suspension dynamic travel reflects the changes in vehicle body posture under load transfer and road surface excitation, and is used for subsequent calculation of the center of gravity height.

[0069] S2. Based on the suspension attitude information and roll dynamic response, establish a parameter identification model to estimate the vehicle's center of gravity height in real time. .like Figure 2 A diagram of the vehicle roll dynamics force model including the road surface inclination angle, and Figure 3 The principle block diagram of the real-time centroid height estimation observer is shown in Figure S2. Step S2 specifically includes the following steps:

[0070] S2.1 Establish the differential equation of vehicle roll dynamics that includes the center of gravity height parameter:

[0071] ,

[0072] In the formula: This represents the moment of inertia of the entire vehicle about its roll axis. For the overall vehicle weight; The distance from the center of mass to the center of roll; This is the roll damping coefficient; For roll stiffness; It is the acceleration due to gravity; The road surface inclination angle; This refers to the vehicle body roll angle acceleration.

[0073] S2.1 Constructing the linear regression equation for recursive least squares (RLS) To identify the unknown centroid parameters, the equations in step S2.1 are rewritten, and the observation scalar is defined. and regression vector Let the main unknown parameter terms be... For the object to be identified, considering the uncertainties of rotational inertia and damping, a parameter vector to be identified is constructed. :

[0074] ,

[0075] Construct the corresponding regression vector :

[0076] ,

[0077] Using a more direct form of torque balance, the equations are rearranged as follows:

[0078] ,

[0079] at this time:

[0080] ,

[0081] ,

[0082] ,

[0083] S2.3, Perform iterative updates using the RLS algorithm: utilizing the forgetting factor (Values ​​range from 0.95 to 0.99) Parameters are updated to adapt to the time-varying characteristics of the mass:

[0084] ,

[0085] ,

[0086] ,

[0087] In the formula, Here is the gain matrix. Let be the covariance matrix.

[0088] S2.1 Parameter Decoupling and Centroid Calculation: From the convergent parameter vector Extract the third item Based on the known vehicle mass m (or the mass estimated through longitudinal dynamics), the center of gravity roll arm is calculated:

[0089] ,

[0090] The final vehicle center of gravity height is obtained as follows:

[0091] ,

[0092] In the formula The roll center height is determined by the suspension geometry.

[0093] S3. Construct a road geometry decoupling observer, establish kinematic equations based on the vehicle driving state information, and separate the current road surface slope angle. and road surface slope ,like Figure 4 The decoupling logic diagram for road slope and inclination angle is shown in the figure, which specifically includes the following sub-steps:

[0094] S3.1 Establish a kinematics-based sensor measurement model: acceleration measured by the IMU It is the vector sum of the vehicle's acceleration and the component of gravity. The following equation establishes the relationship:

[0095] ,

[0096] In the formula, , The acceleration values ​​are directly measured by the IMU. Assuming that the vehicle's longitudinal and lateral velocities change relatively smoothly over a short period of time, and that the road surface angle changes according to a random walk model, a state observer is constructed.

[0097] S3.2 Design an Extended Kalman Filter (EKF) for decoupling: Define the state vector Establish the state equation (assuming the road surface angle change rate is zero plus process noise):

[0098] ,

[0099] Establish measurement equations The residual between sensor measurements and kinematic calculations based on the flat-path assumption is used as the observation:

[0100] ,

[0101] The road slope is output in real time through the EKF prediction and update steps. and road surface slope This achieves decoupling of the gravitational component.

[0102] S4, combined with the aforementioned vehicle center of gravity height and road surface slope Calculate energy-based dynamic roll stability index Specifically, it includes the following sub-steps:

[0103] S4.1 Calculate the vehicle's current total roll energy. This includes tilt kinetic energy and tilt elastic potential energy:

[0104] ,

[0105] This energy represents the total energy currently stored in the vehicle that is used to cause a rollover.

[0106] S4.2 Calculate the critical rollover potential energy considering road surface dip correction. Critical potential energy is defined as the gravitational potential energy that a vehicle's center of gravity must overcome to rise from its current equilibrium position to the rollover threshold (when the center of gravity crosses the perpendicular line from the point of contact with the outer wheel). Based on geometric relationships, the static rollover threshold angle... Where T is the wheel track. When there is a road surface inclination angle... At this time, the direction of the gravity vector changes, causing a change in the equivalent potential energy well depth. The corrected critical potential energy is derived as follows:

[0107] ,

[0108] This formula precisely describes: when the road surface has an unfavorable slope angle (such as...) Negative (i.e., outward camber of the curve) or center of gravity When it rises, Enlargement, leading to The energy threshold required for a vehicle to roll over is reduced, thus increasing the risk.

[0109] S4.3 Calculate the dynamic roll stability index As shown in the following formula:

[0110] ,

[0111] when When the value approaches 1, it indicates that the vehicle has enough energy to overcome gravitational potential energy, which will soon lead to a rollover.

[0112] S5. Comprehensive road surface adhesion conditions and the road surface inclination angle Determining the vehicle's lateral stability boundary under road surface geometric constraints includes the following sub-steps:

[0113] S5.1 Establishing the lateral force balance equation on an inclined road surface: When a vehicle is driving on a curve, the centrifugal force needs to be balanced by the lateral force of the tires and the lateral component of gravity.

[0114] ,

[0115] Incorporating kinematic relationships and gravitational components :

[0116] ,

[0117] S5.2 Determine the tire's physical adhesion limit: Total lateral force of the tire Subject to road surface adhesion coefficient and vertical load limit:

[0118] ,

[0119] On an inclined road surface, the vertical load is approximately equal to the vertical component of gravity:

[0120] ,

[0121] Therefore, the maximum lateral force that can be provided is:

[0122] ,

[0123] S5.3, Deriving the limiting yaw rate By combining steps (51) and (52), the critical condition for transverse stability is obtained:

[0124] ,

[0125] Eliminating the mass m, we obtain the limiting yaw rate:

[0126] ,

[0127] In the formula: This term refers to the "ultra-high gain compensation term" proposed in this invention. A positive lean (inward curve) increases the limit value, allowing for faster turning speeds; if... A negative value (outward camber of the curve) indicates a decrease in the limit value, requiring early warning.

[0128] S6. Based on the dynamic roll stability index A dynamic safety envelope surface is constructed using the lateral stability boundary to determine the real-time stability state of the vehicle. This specifically includes the following sub-steps:

[0129] S6.1 Constructing a dynamic security envelope : Dynamic roll stability index The vertical axis (representing rollover risk) is defined by the normalized yaw rate. Using the horizontal axis (representing sideslip risk), construct a two-dimensional or three-dimensional dynamic stability determination space. The boundary of this envelope is not fixed, but changes with the estimation in step (2). Decoupled from step (3) It can contract or expand in real time.

[0130] S6.2: Real-time determination logic: Obtain the current vehicle status point. ,

[0131] like lie in The core safety zone determines vehicle stability;

[0132] like When the system approaches the boundary (e.g., less than 10% from the boundary threshold), a warning signal is output, and the system pre-fills the braking pressure.

[0133] like Exceeding The boundary is determined, and the vehicle is deemed to be unstable (skid or rollover), triggering ESP or RSC active control intervention.

[0134] Figure 5 This paper demonstrates a comparison between the dynamic safety envelope of this invention and the traditional static stability region. The vehicle stability assessment method of this invention, which considers the coupling between the dynamic center of gravity and road alignment, estimates the vehicle's center of gravity height in real time by constructing a parameter identification model. This enables it to adaptively handle time-varying conditions such as fully loaded, empty, or unevenly distributed cargo. Compared to traditional methods based on fixed vehicle parameters, this invention effectively solves the problem of inaccurate rollover threshold estimation caused by load variations, significantly improving the stability assessment accuracy of SUVs, commercial vehicles, and buses under high center of gravity conditions.

[0135] Another aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described in the embodiments of the present invention.

[0136] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any of the methods described in the embodiments of the present invention.

[0137] While the present invention has been described above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A method for judging vehicle stability considering the coupling between dynamic centroid and road alignment, characterized in that, Includes the following steps: S1. Obtain vehicle driving state information and suspension attitude information to construct the input state variables of the vehicle dynamics system. ; S2. Based on the suspension attitude information and roll dynamic response, establish a parameter identification model to estimate the vehicle's center of gravity height in real time. ; S3. Construct a road geometry decoupling observer, establish kinematic equations based on the vehicle driving state information, and separate the current road surface slope angle. and road surface slope ; S4, combined with the aforementioned vehicle center of gravity height and road surface slope Calculate energy-based dynamic roll stability index ; S5. Comprehensive road surface adhesion conditions and the road surface inclination angle Determine the lateral stability boundary of the vehicle under road surface geometric constraints; S6. Based on the dynamic roll stability index A dynamic safety envelope is constructed using the lateral stability boundary to determine the real-time stability state of the vehicle.

2. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 1, characterized in that, In step S1, the input state quantity As shown in the following formula: ， In the formula, For the longitudinal and lateral accelerations of the vehicle; The yaw rate is angular velocity. These are the vehicle body roll rate and roll angle, respectively. For the vehicle's longitudinal and lateral speeds; The steering angle of the front wheels; These are the suspension travel distances for the left front, right front, left rear, and right rear wheels, respectively; the suspension travel distance is used to calculate the instantaneous roll stiffness.

3. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 1, characterized in that, Step S2 specifically involves: establishing the differential equations of vehicle roll dynamics that include the center of mass parameters. ， In the formula: This represents the moment of inertia of the entire vehicle about its roll axis. For the overall vehicle weight; The distance from the center of mass to the center of roll; This is the roll damping coefficient; For roll stiffness; It is the acceleration due to gravity; The road surface inclination angle; This refers to the vehicle body roll angle acceleration; Transform the differential equation into a linear regression form. Construct the parameter vector to be identified and regression vector ,in Includes terms characterizing the tilt arm of the center of mass. ; Real-time updates using recursive least squares method From the convergent parameter vector Extract Divide the term by the total vehicle mass m to calculate the center of gravity and the roll arm. Thus, the height of the vehicle's center of gravity is obtained. .

4. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 3, characterized in that, Construct the parameter vector to be identified As shown in the following formula: ， Construct the corresponding regression vector As shown in the following formula: ， Using a more direct form of torque balance, the equations are rearranged as follows: ， at this time: ，， ， 。 5. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 3, characterized in that, The method of real-time updating using recursive least squares is mentioned. From the convergent parameter vector Extract Divide the term by the total vehicle mass m to calculate the center of gravity and the roll arm. Thus, the height of the vehicle's center of gravity is obtained. Specifically: Perform iterative updates using recursive least squares: utilizing the forgetting factor Update the parameters to adapt to the time-varying characteristics of the quality: ， ， ， In the formula, Here is the gain matrix. It is the covariance matrix; Parameter decoupling and centroid calculation: from convergent parameter vectors Extract the third item Based on the known vehicle mass m (or the mass estimated through longitudinal dynamics), the center of gravity roll arm is calculated: ， The final vehicle center of gravity height is obtained as follows: ， In the formula The roll center height is determined by the suspension geometry.

6. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 1, characterized in that, In step S3, the road geometry decoupling observer's decoupling logic is based on the following kinematic equations describing the relationship between sensor measurements and gravity components: ， In the formula, , The acceleration value is directly measured by the inertial measurement unit; For the vehicle's longitudinal and lateral speeds, The yaw rate is angular velocity. It is the acceleration due to gravity; Design an extended Kalman filter and define the state vector. The kinematic equations are used as a measurement model to estimate the road surface slope in real time. and road surface slope This eliminates the interference of the gravitational component on acceleration readings.

7. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 1, characterized in that, The energy-based dynamic tumbling stability index The calculation is as follows: ， In the formula, , , This refers to the dynamic roll stability index value; This represents the current total energy of the tilt. This represents the critical potential energy for rollover. The static rollover threshold angle; the critical rollover potential energy With the height of the center of mass Increase and unfavorable road surface slope angle Increase and decrease To characterize the term of the tilt arm at the center of mass, This represents the height of the vehicle's center of gravity, where m is the vehicle's mass. It is the acceleration due to gravity. The body roll angle, This is the moment of inertia of the entire vehicle about the roll axis.

8. The vehicle stability judgment method considering the coupling of dynamic centroid and road alignment according to claim 1, characterized in that, In step S5, the vehicle lateral stability boundary is expressed as the limiting yaw rate. The calculation is as follows: ， In the formula, This is an estimated value for the road surface adhesion coefficient; This is the gravity component compensation term caused by the road surface inclination, used to characterize the asymmetric correction of the vehicle's lateral stability boundary on curves with extreme steepness. This represents the vehicle's longitudinal speed.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

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