Vehicle instability judgment method and device, storage medium, controller and vehicle

Abstract

The invention discloses a vehicle instability judgment method and device, a storage medium, a controller and a vehicle, and the method comprises the steps that state parameters of the vehicle at the current moment are obtained, and the state parameters comprise the yaw velocity and the side slip angle of the vehicle; according to the state parameters at the current moment, the yaw velocity and the side slip angle of the vehicle at the future target moment are predicted, and a predicted value of the yaw velocity and a predicted value of the side slip angle are obtained; and according to the yaw velocity predicted value and the side slip angle predicted value, whether the vehicle has an instability trend or not is judged. According to the method, the yaw velocity and the side slip angle of the vehicle at the future target moment are predicted based on the state parameters of the vehicle at the current moment, the stability of the vehicle at the future target moment is predicted before the vehicle is unstable at the current moment, and the stability of the vehicle is pre-judged in an advanced pre-judgment mode. Therefore, vehicle stability control is involved when it is judged that the vehicle tends to be unstable, and the vehicle stability is improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a vehicle instability determination method, device and storage medium, controller and vehicle. Background Art

[0002] Vehicle stability control is an important part of vehicle dynamics control, which affects the safety and comfort of the vehicle. Vehicle stability control mainly includes two aspects: one is the judgment of the vehicle's instability state, and the other is the control and correction of the vehicle's yaw rate and sideslip angle.

[0003] Regarding the judgment of vehicle instability, related technologies make judgments based on the actual yaw rate or sideslip angle of the vehicle, and some technologies use the phase plane to make judgments. However, these judgment methods of instability are passive. After judging that the vehicle is instability, the vehicle stability control effect achieved by controlling and correcting the yaw rate and sideslip angle of the vehicle is not ideal. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the related art at least to a certain extent. To this end, one object of the present invention is to provide a vehicle instability determination method to improve the vehicle stability control effect.

[0005] A second objective of the present invention is to provide a vehicle instability determination device.

[0006] A third object of the present invention is to provide a computer-readable storage medium.

[0007] A fourth object of the present invention is to provide a controller.

[0008] A fifth object of the present invention is to provide a vehicle.

[0009] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present invention proposes a vehicle instability determination method, the method comprising: obtaining state parameters of the vehicle at a current moment, wherein the state parameters include the yaw rate and the sideslip angle of the center of mass of the vehicle; predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment according to the state parameters at the current moment, to obtain a yaw rate prediction value and a sideslip angle prediction value; and determining whether the vehicle has an instability tendency according to the yaw rate prediction value and the sideslip angle prediction value.

[0010] According to the vehicle instability determination method of the embodiment of the present invention, the yaw angular velocity and the sideslip angle of the center of mass of the vehicle at a future target moment are predicted based on the state parameters of the vehicle at the current moment, and the stability of the vehicle at the future target moment is predicted before the vehicle becomes unstable at the current moment. The vehicle stability is predicted in an advanced prediction manner, so that the vehicle stability control is intervened when it is judged that the vehicle tends to become unstable, thereby improving the vehicle stability.

[0011] In addition, the vehicle instability determination method proposed in the above embodiment of the present invention may also have the following additional technical features:

[0012] According to one embodiment of the present invention, before predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment based on the state parameters at the current moment, the method further includes: determining that the vehicle is not unstable at the current moment based on the yaw rate and the sideslip angle of the center of mass at the current moment.

[0013] According to one embodiment of the present invention, the state parameters also include a road adhesion coefficient and a vehicle speed, and determining that the vehicle is not unstable at the current moment based on the yaw velocity and the sideslip angle of the center of mass at the current moment includes: obtaining a yaw velocity threshold value and a sideslip angle threshold value at the current moment based on the road adhesion coefficient and the vehicle speed at the current moment; calculating a first deviation value between the yaw velocity at the current moment and the yaw velocity threshold value at the current moment, and calculating a second deviation value between the sideslip angle at the current moment and the sideslip angle threshold value at the current moment; if the first deviation value is less than or equal to a first preset threshold value, and the second deviation value is less than or equal to a second preset threshold value, determining that the vehicle is not unstable.

[0014] According to one embodiment of the present invention, the state parameters also include the front wheel turning angle of the vehicle, and the predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment based on the state parameters at the current moment to obtain a predicted yaw rate value and a predicted center of mass sideslip angle value includes: obtaining a prediction cycle number based on the current moment, the future target moment and a preset stability control cycle; predicting a first yaw rate and a first centers of mass sideslip angle of the vehicle at a future target moment based on the preset stability control cycle, the prediction cycle number, and the front wheel turning angle, yaw rate and sideslip angle at the current moment using a preset linear two-degree-of-freedom model, and using the first yaw rate as the predicted yaw rate value, and using the first centers of mass sideslip angle as the predicted center of mass sideslip angle value.

[0015] According to one embodiment of the present invention, predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment according to the state parameters at the current moment to obtain a predicted yaw rate value and a predicted sideslip angle of the center of mass includes: obtaining a prediction cycle number according to the current moment, the future target moment and a preset stability control period; predicting a second yaw rate and a second sideslip angle of the center of mass of the vehicle at a future target moment according to the preset stability control period, the prediction cycle number, and the yaw rate and the sideslip angle of the center of mass at the current moment using a preset integral model, and using the second yaw rate as the predicted yaw rate value, and using the second sideslip angle as the predicted sideslip angle value.

[0016] According to an embodiment of the present invention, the state parameters also include the front wheel turning angle of the vehicle, and the predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time to obtain the predicted yaw rate value and the predicted sideslip angle of the center of mass includes: obtaining the number of prediction cycles according to the current time, the future target time and a preset stability control period; predicting the first yaw rate and the first sideslip angle of the center of mass of the vehicle at a future target time according to the preset stability control period, the number of prediction cycles, and the front wheel turning angle, yaw rate and sideslip angle at the current time using a preset linear two-degree-of-freedom model; predicting the second yaw rate and the second sideslip angle of the vehicle at a future target time according to the preset stability control period, the number of prediction cycles, and the yaw rate and sideslip angle at the current time using a preset integral model; obtaining the predicted yaw rate value according to the first yaw rate and the second yaw rate, and obtaining the predicted sideslip angle value according to the first sideslip angle and the second sideslip angle.

[0017] According to one embodiment of the present invention, obtaining the predicted yaw rate value according to the first yaw rate and the second yaw rate includes: determining a coordination coefficient according to the center of mass sideslip angle at the current moment and a center of mass sideslip angle threshold value at the current moment, wherein the coordination coefficient is between 0 and 1; calculating the product of the first yaw rate and (1-coordination coefficient) to obtain a first product, and calculating the product of the second yaw rate and the coordination coefficient to obtain a second product; calculating the sum of the first product and the second product, and using the sum as the predicted yaw rate value.

[0018] According to one embodiment of the present invention, a coordination coefficient is determined based on the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment, including: if the absolute value of the center of mass sideslip angle at the current moment is less than the center of mass sideslip angle threshold value at the current moment, then determining the coordination coefficient as the ratio of the center of mass sideslip angle at the current moment to the center of mass sideslip angle threshold value at the current moment; if the absolute value of the center of mass sideslip angle at the current moment is greater than or equal to the center of mass sideslip angle threshold value at the current moment, then determining the coordination coefficient to be 1.

[0019] According to one embodiment of the present invention, after determining that the vehicle has an unstable tendency or the vehicle is unstable at the current moment, the method further includes: using a PID algorithm to obtain a total required torque based on the vehicle speed and the ideal vehicle speed at the current moment; determining a target torque for each wheel of the vehicle based on the total required torque, and controlling the corresponding wheels based on the target torque.

[0020] To achieve the above-mentioned purpose, a second aspect of the present invention proposes a vehicle instability determination device, which includes: an acquisition module, used to obtain the state parameters of the vehicle at a current moment, wherein the state parameters include the yaw rate and the sideslip angle of the center of mass of the vehicle; a prediction module, used to predict the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment according to the state parameters at the current moment, and obtain a yaw rate prediction value and a sideslip angle prediction value; a judgment module, used to judge whether the vehicle has an instability trend according to the yaw rate prediction value and the sideslip angle prediction value.

[0021] To achieve the above-mentioned purpose, the third aspect of the present invention proposes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the vehicle instability determination method proposed in the first aspect of the present invention is implemented.

[0022] To achieve the above-mentioned purpose, the fourth aspect of the present invention proposes a controller, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the vehicle instability determination method proposed in the first aspect of the present invention is implemented.

[0023] To achieve the above-mentioned purpose, a fifth embodiment of the present invention proposes a vehicle, comprising a controller as proposed in the fourth embodiment of the present invention.

[0024] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1is a flow chart of a vehicle instability determination method according to an embodiment of the present invention;

[0026] Figure 2 is a flow chart of a vehicle instability determination method according to a specific embodiment of the present invention;

[0027] Figure 3 is a flow chart of determining whether a vehicle is unstable at the current moment according to an embodiment of the present invention;

[0028] Figure 4 is a relationship diagram of yaw rate threshold value-road adhesion-vehicle speed according to an embodiment of the present invention;

[0029] Figure 5 is a flow chart of obtaining a first yaw angular velocity and a first center of mass sideslip angle according to an embodiment of the present invention;

[0030] Figure 6 is a flow chart of obtaining a second yaw angular velocity and a second center of mass sideslip angle according to an embodiment of the present invention;

[0031] Figure 7 is a flow chart of obtaining a predicted value of yaw rate and a predicted value of sideslip angle of center of mass according to an embodiment of the present invention;

[0032] Figure 8 is a flow chart of calculating a predicted yaw rate value according to a specific embodiment of the present invention;

[0033] Fig. 9 is a graph showing the relationship between the center of mass sideslip angle and the coordination coefficient according to an embodiment of the present invention;

[0034] Fig.10 is a schematic diagram of a vehicle instability determination device according to an embodiment of the present invention;

[0035] Fig.11 is a structural block diagram of a controller according to an embodiment of the present invention;

[0036] Fig.12 is a schematic diagram of a vehicle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0038] The following is attached to the instruction manual Figure 1-12 And specific implementation methods are described in detail for the vehicle instability determination method, device and storage medium, controller, and vehicle of the embodiments of the present invention.

[0039] Figure 1 FIG. 1 is a flow chart of a method for determining vehicle instability according to a specific embodiment of the present invention. Figure 1 As shown, the vehicle instability determination method may include:

[0040] S101, obtaining state parameters of the vehicle at a current moment, wherein the state parameters may include a yaw rate and a sideslip angle of the center of mass of the vehicle;

[0041] S102, predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time, and obtaining a predicted yaw rate value and a predicted sideslip angle value of the center of mass;

[0042] S103: Determine whether the vehicle has an instability tendency according to the predicted value of the yaw rate and the predicted value of the sideslip angle of the center of mass.

[0043] Vehicle stability judgment is an important part of the vehicle stability control system. Judging the vehicle stability based on the vehicle's state parameters determines the timing of starting the stability control system, which directly affects the safety of the vehicle.

[0044] The embodiment of the present invention obtains the state parameters of the vehicle at the current moment, and predicts the yaw rate and the center of mass sideslip angle of the vehicle when the vehicle continues to travel to the future target moment based on the state parameters at the current moment according to the state parameters of the vehicle at the current moment, and obtains the predicted yaw rate value and the predicted center of mass sideslip angle value. According to the predicted yaw rate value and the predicted center of mass sideslip angle value at the future target moment, it is determined whether the vehicle has an instability trend at the future target moment. The vehicle stability is predicted by using an advanced prediction method, so that when it is determined that the vehicle tends to be unstable, the vehicle stability control is intervened to improve the vehicle stability.

[0045] The vehicle instability determination method of the embodiment of the present invention estimates and predicts the vehicle state at a future target time based on the state parameters of the vehicle at the current time, so as to intervene in the vehicle stability control in advance when it is predicted that the vehicle will be unstable at the future target time, thereby improving the vehicle stability control effect. It can be implemented that when it is determined that the vehicle has an instability trend at the future target time, the vehicle stability control is intervened so that the vehicle stability control system can timely control and correct the vehicle's yaw rate and center of mass sideslip angle, thereby improving the vehicle stability.

[0046] In one embodiment of the present invention, Figure 2 As shown, before predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time, the vehicle instability determination method further includes:

[0047] According to the yaw rate and sideslip angle of the center of mass at the current moment, it is determined that the vehicle is not unstable at the current moment.

[0048] The embodiment of the present invention determines the vehicle state at the current moment according to the yaw angular velocity and the sideslip angle of the center of mass of the vehicle at the current moment.

[0049] In one embodiment of the present invention, when it is determined that the vehicle is unstable at the current moment based on the yaw rate and the sideslip angle of the center of mass of the vehicle, the vehicle stability control is intervened so that the vehicle stability control system can timely control and correct the yaw rate and the sideslip angle of the center of mass of the vehicle, thereby ensuring the stability of the vehicle.

[0050] In one embodiment of the present invention, when it is determined that the vehicle is not unstable at the current moment based on the yaw rate and sideslip angle of the center of mass of the vehicle at the current moment, it is predicted that the vehicle will continue to travel to the yaw rate and sideslip angle of the center of mass at a future target moment based on the state parameters at the current moment, and it is determined whether the vehicle has an unstable trend at the future target moment, so that when it is determined that the vehicle tends to become unstable, the vehicle stability control is intervened in time to improve the vehicle stability.

[0051] In one embodiment of the present invention, Figure 3 As shown, the state parameters also include the road adhesion coefficient and the vehicle speed. According to the yaw rate and the sideslip angle of the center of mass at the current moment, it is determined that the vehicle is not unstable at the current moment, including:

[0052] S201, obtaining a yaw rate threshold value and a center of mass sideslip angle threshold value at the current moment according to the road adhesion coefficient and the vehicle speed at the current moment;

[0053] S202, calculating a first deviation between the yaw angular velocity at the current moment and the yaw angular velocity threshold value at the current moment, and calculating a second deviation between the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment;

[0054] S203: If the first deviation value is less than or equal to the first preset threshold value, and the second deviation value is less than or equal to the second preset threshold value, it is determined that the vehicle is not unstable.

[0055] In one embodiment of the present invention, a threshold value judgment method is used to judge stability. The principle of the threshold value judgment method is: compare the deviation between the actual yaw angular velocity, the actual center of mass sideslip angle and the corresponding threshold value with the preset threshold value to judge whether stability control should be intervened. The expression of the threshold value judgment method is as follows:

[0056] |ω r -ω rdes |=|Δω r |≤|ξ1|

[0057] |β-β des |=|Δβ|≤|ξ2|

[0058] Among them, ω r represents the yaw angular velocity at the current moment, ω rdes Indicates the current yaw rate threshold, Δω r represents the yaw rate difference, ξ1 represents the yaw rate threshold, β represents the sideslip angle of the center of mass at the current moment, and β des represents the center of mass sideslip angle threshold value at the current moment, Δβ represents the center of mass sideslip angle difference, and ξ2 represents the center of mass sideslip angle threshold value.

[0059] It should be noted that in the threshold value judgment method, the yaw angular velocity threshold value ω rdes are parameters related to the road adhesion coefficient and vehicle speed, which can be obtained through a large number of experiments or in the form of software simulation. In the embodiment of the present invention, different road adhesion coefficients (0.1, 0.3, 0.5, 0.7, 0.9) and vehicle speeds (30km / h, 50km / h, 80km / h, 100km / h, 120km / h) are set without stability control to form 25 working conditions. The front wheel steering angle is a sinusoidal input with different peak values. The stability boundary is found according to the yaw rate response, the center of mass sideslip angle response, and the motion trajectory, so as to obtain the following: Figure 4 The relationship diagram of yaw rate threshold value, road adhesion and vehicle speed is shown in the figure. The center of mass sideslip angle threshold value β des is a parameter related to the road adhesion coefficient, which can be obtained by the function β of the center of mass sideslip angle threshold and the road adhesion coefficient μ max =arctan(0.02μg) was obtained.

[0060] It is feasible to use the above yaw rate threshold value-road adhesion-vehicle speed relationship diagram, and obtain the yaw rate threshold value and the center of mass sideslip angle threshold value at the current moment according to the road adhesion coefficient and the vehicle speed at the current moment. Calculate the first deviation value between the yaw rate at the current moment and the yaw rate threshold value at the current moment, and calculate the second deviation value between the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment. Determine whether the vehicle is unstable at the current moment based on the magnitude relationship between the first deviation value and the first preset threshold value, and the magnitude relationship between the second deviation value and the second preset threshold value. Specifically, if the first deviation value is less than or equal to the first preset threshold value, and the second deviation value is less than or equal to the second preset threshold value, it is determined that the vehicle is not unstable. If the first deviation value is greater than the first preset threshold value, or the second deviation value is greater than the second preset threshold value, it is determined that the vehicle is unstable.

[0061] In one embodiment of the present invention, Figure 5 As shown, the state parameters also include the front wheel turning angle of the vehicle. The yaw rate and the sideslip angle of the center of mass of the vehicle at the future target time are predicted according to the state parameters at the current time, and the predicted yaw rate and the sideslip angle of the center of mass are obtained, including:

[0062] S301, obtaining a predicted number of cycles according to the current time, the future target time and a preset stability control period;

[0063] S302, using a preset linear two-degree-of-freedom model, according to a preset stability control period, the number of prediction cycles, and the front wheel angle, yaw velocity and center-of-mass sideslip angle at the current moment, predict the first yaw velocity and the first center-of-mass sideslip angle of the vehicle at a future target moment, and use the first yaw velocity as the yaw velocity prediction value, and use the first center-of-mass sideslip angle as the center-of-mass sideslip angle prediction value.

[0064] In an embodiment of the present invention, when the vehicle is in a linear region, the preset linear two-degree-of-freedom model in the embodiment of the present invention can be used to obtain a yaw velocity prediction value (the first yaw velocity at a future target moment) and a center of mass sideslip angle prediction value (the first center of mass sideslip angle at a future target moment) according to a preset stability control period, a number of prediction cycles, and the front wheel angle, yaw velocity and center of mass sideslip angle at the current moment.

[0065] Since the linear two-degree-of-freedom model is a continuous space state equation, the embodiment of the present invention uses the forward Euler method to discretize it to obtain a discrete linear two-degree-of-freedom model, so that according to the input u(k) and state x(k) at the current moment, the state x1(k+1) of the vehicle in the next stability control cycle can be calculated.

[0066] The state space equation of the continuous linear two-degree-of-freedom model is in the form of:

[0067]

[0068]

[0069]

[0070] Among them, U=(δ fw ), δ fw is the front wheel angle, state variable β is the sideslip angle of the center of mass, ω r is the yaw angular velocity, k f is the front axle stiffness, k r is the rear axle stiffness, m is the vehicle mass, u is the vehicle speed, I z is the moment of inertia of the vehicle around the Z axis, a is the distance from the front axle to the center of mass of the vehicle, and b is the distance from the rear axle to the center of mass of the vehicle.

[0071] After discretization using the forward Euler method, the state space equation of the discrete linear two-degree-of-freedom model is as follows:

[0072] x1(k+1)=A*x(k)+B*u(k)

[0073]

[0074]

[0075] in, β1(k+1) represents the sideslip angle of the center of mass in the next stability control cycle, ω 1r (k+1) represents the yaw rate of the next stability control cycle, β(k) represents the sideslip angle of the center of mass at the current moment, ω r (k) represents the yaw rate at the current moment, T represents the stability control period, k f is the front axle stiffness, k r is the rear axle stiffness, m is the vehicle mass, u is the vehicle speed, I z is the moment of inertia of the vehicle around the Z axis, a is the distance from the front axle to the center of mass of the vehicle, and b is the distance from the rear axle to the center of mass of the vehicle.

[0076] Get the predicted time interval t based on the current time and the future target time d , where t d =NT. According to the prediction time interval t d and the preset stability control period T, the prediction time interval t is obtained d The corresponding number of prediction cycles is N. Through the iterative formula, the preset linear two-degree-of-freedom model in the embodiment of the present invention can be obtained:

[0077]

[0078] in, β1(k+N) represents the first center of mass sideslip angle at the future target moment, ω 1r (k+N) represents the first yaw rate at the future target moment, N represents the number of prediction cycles, i∈[0, N-1].

[0079] The control input at the current moment is u(k), that is, the front wheel steering angle δ fw When the state x(k) remains unchanged, the vehicle state x1(k+N) at the future time can be calculated, that is, the first center of mass sideslip angle β1(k+N) and the second yaw angular velocity ω at the future target time. 1r (k+N).

[0080] In one embodiment of the present invention, Figure 6 As shown, the yaw rate and the sideslip angle of the center of mass of the vehicle at the future target time are predicted according to the state parameters at the current time, and the predicted yaw rate and the sideslip angle of the center of mass are obtained, including:

[0081] S401, obtaining a predicted number of cycles according to the current time, the future target time and a preset stability control period;

[0082] S402, using a preset integral model to predict a second yaw velocity and a second center-of-mass sideslip angle of the vehicle at a future target moment according to a preset stability control period, the number of prediction cycles, and the yaw velocity and the center-of-mass sideslip angle at the current moment, and using the second yaw velocity as a predicted yaw velocity value and the second center-of-mass sideslip angle as a predicted center-of-mass sideslip angle value.

[0083] In an embodiment of the present invention, when the vehicle is in a nonlinear zone, such as high-speed steering or icy and snowy road conditions, the preset linear two-degree-of-freedom model in the embodiment of the present invention can be used. The preset integral model is used according to the preset stability control period, the number of prediction cycles, and the yaw rate and center of mass sideslip angle at the current moment to obtain a yaw rate prediction value (a second yaw rate at the future target moment) and a center of mass sideslip angle prediction value (a second center of mass sideslip angle at the future target moment).

[0084] In an embodiment of the present invention, the expression of the preset integral model is as follows:

[0085]

[0086]

[0087] Among them, β2(k+N) represents the second center of mass sideslip angle at the future target moment, β(k) represents the center of mass sideslip angle at the current moment, Denotes the prediction time interval t d The rate of change of the inner center of mass sideslip angle, ω 2r (k+N) represents the second yaw angular velocity at the future target time, ω r (k) represents the yaw angular velocity at the current moment, Denotes the prediction time interval t d The rate of change of the internal yaw rate, T represents the preset stability control period, N represents the number of predicted cycles, where t d =NT.

[0088] Specifically, according to the current moment, the future target moment and the preset stability control period T, the predicted number of cycles N is obtained, and the preset integral model is used to predict the second yaw rate ω of the vehicle at the future target moment according to the preset stability control period, the predicted number of cycles, and the current yaw rate and the sideslip angle of the center of mass. 2r (k+N) and the second center of mass sideslip angle β2(k+N).

[0089] In one embodiment of the present invention, Figure 7As shown, the state parameters also include the front wheel turning angle of the vehicle. The yaw rate and the sideslip angle of the center of mass of the vehicle at the future target time are predicted according to the state parameters at the current time, and the predicted yaw rate and the sideslip angle of the center of mass are obtained, including:

[0090] S501, obtaining a predicted number of cycles according to the current time, the future target time and a preset stability control period;

[0091] S502, using a preset linear two-degree-of-freedom model, according to a preset stability control period, a prediction cycle number, and a front wheel steering angle, a yaw rate, and a sideslip angle of the center of mass at a current moment, to predict a first yaw rate and a first sideslip angle of the center of mass at a future target moment of the vehicle;

[0092] S503, using a preset integral model to predict a second yaw rate and a second sideslip angle of the center of mass of the vehicle at a future target moment according to a preset stability control period, a number of prediction cycles, and the yaw rate and sideslip angle of the center of mass at the current moment;

[0093] S504: Obtain a predicted yaw rate value according to the first yaw rate and the second yaw rate, and obtain a predicted center of mass sideslip angle value according to the first center of mass sideslip angle and the second center of mass sideslip angle.

[0094] Due to the complex driving conditions of the vehicle, it may be in the linear area or in the nonlinear area. The preset linear two-degree-of-freedom model is more suitable for the linear area of ​​the vehicle, but under high-speed steering or icy and snowy road conditions, the vehicle is prone to be in the nonlinear area. At this time, the results obtained using the preset linear two-degree-of-freedom model are no longer accurate. The results of predicting the nonlinear area based on the preset integral model are more accurate. The embodiment of the present invention is suitable for complex driving conditions of the vehicle and predicts the vehicle state parameters through a coordinated method.

[0095] Specifically, the predicted number of cycles N is obtained according to the current moment, the future target moment and the preset stability control cycle T. The linear two-degree-of-freedom model preset as above is used to calculate the predicted number of cycles N according to the preset stability control cycle T, the predicted number of cycles N, and the front wheel turning angle δ at the current moment. fw , yaw angular velocity ω r (k) and the sideslip angle β(k), the first yaw rate ω of the vehicle at the future target time is predicted 1r (k+N) and the first mass center sideslip angle β1(k+N). Using the above preset integral model according to the preset stability control period T, the predicted number of cycles N, and the current yaw rate ω r (k) and the sideslip angle β(k), the second yaw rate ω of the vehicle at the future target time is predicted 2r(k+N) and the second mass center sideslip angle β2(k+N). A coordinated method is used according to the first yaw angular velocity ω 1r (k+N) and the second yaw rate ω 2r (k+N) gets the predicted yaw rate ω 3r (k+N), and obtain the predicted value of the center of mass sideslip angle β3(k+N) according to the first center of mass sideslip angle β1(k+N) and the second center of mass sideslip angle β2(k+N).

[0096] The determination method of the embodiment of the present invention solves the problem that the method of the preset linear two-degree-of-freedom model is inaccurate in prediction under high-speed steering or icy and snowy road conditions, and also makes up for the shortcomings of the preset integral model in the linear region.

[0097] In one embodiment of the present invention, Figure 8 As shown, the yaw rate prediction value is obtained according to the first yaw rate and the second yaw rate, including:

[0098] S601, determining a coordination coefficient according to a sideslip angle of the center of mass at a current moment and a threshold value of the sideslip angle of the center of mass at a current moment, wherein the coordination coefficient is in a range of 0 to 1;

[0099] S602, calculating the product of the first yaw angular velocity and (1-coordination coefficient) to obtain a first product, and calculating the product of the second yaw angular velocity and the coordination coefficient to obtain a second product;

[0100] S603: Calculate the sum of the first product and the second product, and use the sum as the yaw angular velocity prediction value.

[0101] In this embodiment, the coordination coefficient λ is set according to the first yaw angular velocity ω 1r (k+N) and the second yaw rate ω 2r (k+N) gets the predicted yaw rate ω 3r (k+N). Specifically, according to the relationship between the sideslip angle of the center of mass at the current moment and the threshold value of the sideslip angle of the center of mass at the current moment, after determining the coordination coefficient λ, the yaw rate prediction value ω can be calculated using the following expression: 3r (k+N):

[0102] ω 3r (k+N)=(1-λ)ω 1r (k+N)+λω 2r (k+N)

[0103] Among them, ω 3r (k+N) represents the predicted yaw rate, ω 1r (k+N) represents the first yaw rate, ω 2r (k+N) represents the second yaw rate, and λ represents the coordination coefficient.

[0104] Similarly, the predicted value of the center of mass sideslip angle β3(k+N) can be calculated using the above method. The coordination coefficient λ is determined in the same way as above, and the corresponding expression for calculating the predicted value of the center of mass sideslip angle β3(k+N) is as follows:

[0105] β3(k+N)=(1-λ)β1(k+N)+λβ2(k+N)

[0106] Among them, β3(k+N) represents the predicted value of the center of mass sideslip angle, β1(k+N) represents the first center of mass sideslip angle, β2(k+N) represents the second center of mass sideslip angle, and λ represents the coordination coefficient.

[0107] In one embodiment of the present invention, the coordination coefficient is determined according to the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold at the current moment, including:

[0108] If the absolute value of the center of mass sideslip angle at the current moment is less than the center of mass sideslip angle threshold value at the current moment, the coordination coefficient is determined to be the ratio of the center of mass sideslip angle at the current moment to the center of mass sideslip angle threshold value at the current moment;

[0109] If the absolute value of the center of mass sideslip angle at the current moment is greater than or equal to the center of mass sideslip angle threshold value at the current moment, the coordination coefficient is determined to be 1.

[0110] Specifically, when the center of mass slip angle β at the current moment is small, the vehicle state is relatively stable, and the result predicted by the preset linear two-degree-of-freedom model is relatively accurate. As the center of mass slip angle β at the current moment increases, the vehicle gradually enters the nonlinear region, and the accuracy of the result predicted by the preset integral model increases accordingly. Normally, on dry asphalt high-adhesion roads, the vehicle is prone to lose stability when the center of mass slip angle exceeds 10 degrees, and on icy and snowy low-adhesion roads, the vehicle is prone to lose control when the center of mass slip angle exceeds 4 degrees. Therefore, the center of mass slip angle threshold value at the current moment is a function of the road adhesion coefficient μ, and the expression is as follows: β max =arctan(0.02μg).

[0111] Specifically, if the absolute value of the center of mass sideslip angle at the current moment |β| is less than the center of mass sideslip angle threshold value β at the current moment max , then the coordination coefficient is determined as the ratio of the center of mass sideslip angle at the current moment to the center of mass sideslip angle threshold value at the current moment If the absolute value of the center of mass sideslip angle at the current moment |β| is greater than or equal to the center of mass sideslip angle threshold value β at the current moment max , then the coordination coefficient is determined to be 1.

[0112] It is feasible to determine the coordination coefficient λ using the following expression:

[0113]

[0114] Among them, λ represents the coordination coefficient, β represents the sideslip angle of the center of mass at the current moment, and β max Indicates the center of mass sideslip angle threshold value at the current moment. The relationship diagram between the center of mass sideslip angle and the coordination coefficient is as follows: Fig. 9 shown.

[0115] In an embodiment of the present invention, a yaw rate prediction value is obtained according to the first yaw rate and the second yaw rate, and a center of mass sideslip angle prediction value is obtained according to the first center of mass sideslip angle and the second center of mass sideslip angle, which can be calculated using the following expression:

[0116] x3(k+N)=(1-λ)x1(k+N)+λx2(k+N)

[0117] in, β3(k+N) represents the predicted value of the sideslip angle of the center of mass, ω 3r (k+N) represents the predicted yaw rate, β1(k+N) represents the first center of mass sideslip angle at the future target moment, ω 1r (k+N) represents the first yaw rate at the future target time, β2(k+N) represents the second center of mass sideslip angle at the future target moment, ω 2r (k+N) represents the second yaw angular velocity at the future target moment, λ represents the coordination coefficient, and the coordination coefficient λ is determined in the same manner as above.

[0118] In one embodiment of the present invention, a threshold value judgment method is used to determine whether the vehicle has an instability tendency based on the yaw rate prediction value and the center of mass sideslip angle prediction value.

[0119] Specifically, a third deviation value between the predicted yaw rate at the future target moment and the corresponding yaw rate threshold value is calculated, and a fourth deviation value between the predicted center of mass sideslip angle at the future target moment and the corresponding center of mass sideslip angle threshold value is calculated. If the third deviation value is less than or equal to the first preset threshold value, and the fourth deviation value is less than or equal to the second preset threshold value, it is determined that the vehicle does not have an instability trend. If the third deviation value is greater than the first preset threshold value, or the fourth deviation value is greater than the second preset threshold value, it is determined that the vehicle has an instability trend. After determining that the vehicle has an instability trend, the determination result can be transmitted to the vehicle stability control system, or the driver can be reminded by text or voice, so as to reserve a certain correction time to avoid vehicle instability.

[0120] In one embodiment of the present invention, after determining that the vehicle has an instability trend or the vehicle is instability at the current moment, the vehicle instability determination method further includes:

[0121] The total required torque is obtained based on the current vehicle speed and the ideal vehicle speed using the PID algorithm;

[0122] The target torque for each wheel of the vehicle is determined according to the total required torque, and the corresponding wheel is controlled according to the target torque.

[0123] Specifically, the PID algorithm can be used to calculate the total required torque according to the current vehicle speed and the ideal vehicle speed. The PID algorithm expression is as follows:

[0124]

[0125] Among them, T pid (t) represents the total required torque, K P Represents the proportionality coefficient, K I represents the integration time constant, K D represents the differential time constant, and err(t) represents the difference between the current vehicle speed and the ideal vehicle speed.

[0126] The target torque of each wheel of the vehicle is determined according to the total required torque using a distribution algorithm. It is feasible to control the hub motor of the corresponding wheel to operate at the target torque according to the target torque of each wheel, thereby achieving control of each wheel of the vehicle.

[0127] The vehicle instability determination method of the embodiment of the present invention predicts the yaw angular velocity and the sideslip angle of the center of mass of the vehicle at a future target moment based on the state parameters of the vehicle at a current moment, predicts the stability of the vehicle at a future target moment before the vehicle becomes unstable at the current moment, and predicts the vehicle stability by an advanced prediction method, thereby intervening in vehicle stability control when it is judged that the vehicle tends to become unstable, thereby improving vehicle stability.

[0128] The invention provides a vehicle instability determination device.

[0129] Fig.10 FIG. 1 is a schematic diagram of a vehicle instability determination device according to an embodiment of the present invention. Fig.10 As shown, the vehicle instability determination device 100 may include: an acquisition module 10 , a prediction module 20 and a determination module 30 .

[0130] Among them, the acquisition module 10 is used to obtain the state parameters of the vehicle at the current moment, wherein the state parameters include the yaw velocity and the sideslip angle of the center of mass of the vehicle; the prediction module 20 is used to predict the yaw velocity and the sideslip angle of the center of mass of the vehicle at a future target moment according to the state parameters at the current moment, and obtain the predicted yaw velocity value and the predicted sideslip angle value of the center of mass; the judgment module 30 is used to determine whether the vehicle has an instability trend according to the predicted yaw velocity value and the predicted sideslip angle value of the center of mass.

[0131] It should be noted that other specific implementations of the vehicle instability determination device provided in the embodiment of the present invention may refer to other specific implementations of the vehicle instability determination method in the above-mentioned embodiment of the present invention.

[0132] The vehicle instability determination device of the embodiment of the present invention predicts the yaw angular velocity and the sideslip angle of the center of mass of the vehicle at a future target moment based on the state parameters of the vehicle at a current moment, and predicts the stability of the vehicle at a future target moment before the vehicle becomes unstable at the current moment, and predicts the stability of the vehicle by an advanced prediction method, thereby intervening in the vehicle stability control when it is judged that the vehicle tends to become unstable, thereby improving the vehicle stability.

[0133] The present invention provides a computer-readable storage medium.

[0134] In this embodiment, a computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, the above-mentioned vehicle instability determination method is implemented.

[0135] The invention provides a controller.

[0136] In this embodiment, the controller 500 may include a memory 503 and a processor 501 . The memory 503 stores a computer program. When the computer program is executed by the processor 501 , the vehicle instability determination method as described above is implemented.

[0137] Fig.11 It is a structural block diagram of a controller according to an embodiment of the present invention.

[0138] like Fig.11 As shown, the controller 500 includes: a processor 501 and a memory 503. The processor 501 and the memory 503 are connected, such as through a bus 502. Optionally, the controller 500 may also include a transceiver 504. It should be noted that in actual applications, the transceiver 504 is not limited to one, and the structure of the controller 500 does not constitute a limitation on the embodiments of the present invention.

[0139] Processor 501 may be a CPU (Central Processing Unit), a general purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 501 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0140] The bus 502 may include a path to transmit information between the above components. The bus 502 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 502 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.11 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0141] The memory 503 is used to store a computer program corresponding to the vehicle instability determination method of the above embodiment of the present invention, and the computer program is controlled and executed by the processor 501. The processor 501 is used to execute the computer program stored in the memory 503 to implement the content shown in the above method embodiment. Fig.11 The controller 500 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0142] The present invention provides a vehicle.

[0143] Fig.12 FIG. 1 is a schematic diagram of a vehicle according to an embodiment of the present invention. Fig.12 As shown, vehicle 1000 includes controller 500 as described above.

[0144] The vehicle of the embodiment of the present invention utilizes the above controller 500 to determine the vehicle stability, so as to intervene in the vehicle stability control when it is determined that the vehicle tends to become unstable, thereby improving the vehicle stability.

[0145] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0146] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0147] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0148] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “clockwise”, “counterclockwise”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0149] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0150] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0151] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0152] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A vehicle instability determination method, characterized in that: The method comprises: Acquire the state parameters of the vehicle at the current moment, wherein the state parameters include the yaw rate and the sideslip angle of the center of mass of the vehicle; Predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time, to obtain a predicted yaw rate value and a predicted sideslip angle value of the center of mass; It is determined whether the vehicle has an instability tendency according to the predicted yaw rate value and the predicted sideslip angle value of the center of mass.

2. The vehicle instability determination method according to claim 1, characterized in that: Before predicting the yaw rate and the sideslip angle of the vehicle at a future target moment according to the state parameters at the current moment, the method further includes: According to the yaw angular velocity and the sideslip angle of the center of mass at the current moment, it is determined that the vehicle is not unstable at the current moment.

3. The vehicle instability determination method according to claim 2, characterized in that: The state parameters also include a road adhesion coefficient and a vehicle speed. The determining that the vehicle is not unstable at the current moment according to the yaw angular velocity and the sideslip angle of the center of mass at the current moment includes: According to the road adhesion coefficient and the vehicle speed at the current moment, a yaw rate threshold value and a center of mass sideslip angle threshold value at the current moment are obtained; Calculating a first deviation value between the yaw angular velocity at the current moment and the yaw angular velocity threshold value at the current moment, and calculating a second deviation value between the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment; If the first deviation value is less than or equal to a first preset threshold value, and the second deviation value is less than or equal to a second preset threshold value, it is determined that the vehicle is not unstable.

4. The vehicle instability determination method according to claim 3, characterized in that: The state parameters also include the front wheel turning angle of the vehicle, and the step of predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time to obtain a predicted yaw rate and a predicted sideslip angle of the center of mass includes: Obtaining a predicted number of cycles according to the current moment, the future target moment, and a preset stability control period; A preset linear two-degree-of-freedom model is used to predict the first yaw velocity and the first center-of-mass sideslip angle of the vehicle at a future target moment according to the preset stability control period, the number of prediction cycles, and the front wheel turning angle, yaw velocity and center-of-mass sideslip angle at the current moment, and the first yaw velocity is used as the yaw velocity prediction value, and the first center-of-mass sideslip angle is used as the center-of-mass sideslip angle prediction value.

5. The vehicle instability determination method according to claim 3, characterized in that: The step of predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time to obtain a predicted yaw rate value and a predicted sideslip angle value of the center of mass includes: Obtaining a predicted number of cycles according to the current moment, the future target moment, and a preset stability control period; A preset integral model is used to predict a second yaw rate and a second center-of-mass sideslip angle of the vehicle at a future target moment according to the preset stability control period, the number of prediction cycles, and the yaw rate and the center-of-mass sideslip angle at the current moment, and the second yaw rate is used as the yaw rate prediction value, and the second center-of-mass sideslip angle is used as the center-of-mass sideslip angle prediction value.

6. The vehicle instability determination method according to claim 3, characterized in that: The state parameters also include the front wheel turning angle of the vehicle, and the step of predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target time according to the state parameters at the current time to obtain a predicted yaw rate and a predicted sideslip angle of the center of mass includes: Obtaining a predicted number of cycles according to the current moment, the future target moment, and a preset stability control period; Predicting a first yaw rate and a first sideslip angle of the vehicle at a future target moment using a preset linear two-degree-of-freedom model according to the preset stability control period, the number of prediction cycles, and the front wheel turning angle, yaw rate, and sideslip angle of the center of mass at the current moment; Predicting a second yaw rate and a second sideslip angle of the vehicle at a future target moment using a preset integral model according to the preset stability control period, the number of prediction cycles, and the yaw rate and sideslip angle of the center of mass at the current moment; The predicted yaw rate value is obtained according to the first yaw rate and the second yaw rate, and the predicted center of mass sideslip angle value is obtained according to the first center of mass sideslip angle and the second center of mass sideslip angle.

7. The vehicle instability determination method according to claim 6, characterized in that: The obtaining the predicted yaw rate value according to the first yaw rate and the second yaw rate includes: Determining a coordination coefficient according to the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment, wherein the coordination coefficient is 0 to 1; Calculating the product of the first yaw angular velocity and (1-coordination coefficient) to obtain a first product, and calculating the product of the second yaw angular velocity and the coordination coefficient to obtain a second product; A sum of the first product and the second product is calculated, and the sum is used as the yaw rate prediction value.

8. The vehicle instability determination method according to claim 7, characterized in that: Determining a coordination coefficient according to the center of mass sideslip angle at the current moment and the center of mass sideslip angle threshold value at the current moment includes: If the absolute value of the center of mass sideslip angle at the current moment is less than the center of mass sideslip angle threshold value at the current moment, determining the coordination coefficient as the ratio of the center of mass sideslip angle at the current moment to the center of mass sideslip angle threshold value at the current moment; If the absolute value of the center of mass sideslip angle at the current moment is greater than or equal to the center of mass sideslip angle threshold value at the current moment, the coordination coefficient is determined to be 1.

9. The vehicle instability determination method according to claim 3, characterized in that: After determining that the vehicle has an instability trend or the vehicle is instability at the current moment, the method further includes: Using a PID algorithm, a total required torque is obtained according to the vehicle speed at the current moment and the ideal vehicle speed; The target torque of each wheel of the vehicle is determined according to the total required torque, and the corresponding wheel is controlled according to the target torque.

10. A vehicle instability determination device, characterized in that: The device comprises: An acquisition module, used for acquiring the state parameters of the vehicle at a current moment, wherein the state parameters include the yaw rate and the sideslip angle of the center of mass of the vehicle; A prediction module, used for predicting the yaw rate and the sideslip angle of the center of mass of the vehicle at a future target moment according to the state parameters at the current moment, to obtain a predicted yaw rate value and a predicted sideslip angle value of the center of mass; The judgment module is used to judge whether the vehicle has an instability tendency according to the predicted value of the yaw angular velocity and the predicted value of the sideslip angle of the center of mass.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle instability determination method as described in any one of claims 1 to 9 is implemented.

12. A controller, comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the computer program is executed by the processor, the vehicle instability determination method according to any one of claims 1 to 9 is implemented.

13. A vehicle, characterized in that: Comprising a controller as claimed in claim 12.

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