Side slip angle estimation method and device and storage medium

Abstract

The invention discloses a side slip angle estimation method and device and a storage medium. The method comprises the steps that first stress data of a vehicle at the current moment are obtained; the first stress data is determined based on at least one of a road gradient and a vehicle roll angle; and estimating the side slip angle of the vehicle based on the first stress data to obtain a first estimated value of the side slip angle at the next moment. In this way, the accuracy of the estimated value of the side slip angle can be improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle safety control, and in particular to a method, device and storage medium for estimating a center of mass sideslip angle. Background Art

[0002] The center of mass slip angle is of great significance in vehicle dynamics, as it reflects the change in the vehicle's posture during a turn. A center of mass slip angle that is too large or too small may cause the vehicle to lose stability. By monitoring the center of mass slip angle, the stability of the vehicle during a turn can be improved. In addition, a suitable center of mass slip angle can make the vehicle easier to control and improve the driver's control and responsiveness of the vehicle. Therefore, how to accurately obtain an estimate of the center of mass slip angle is crucial to evaluating the stability and controllability of the vehicle. Summary of the invention

[0003] The main technical problem solved by the present application is to provide a method, device and storage medium for estimating the sideslip angle of the center of mass, which can improve the accuracy of the estimated value of the sideslip angle of the center of mass.

[0004] In order to solve the above technical problems, a technical solution adopted in the present application is: to provide a method for estimating the center of mass sideslip angle, the method comprising: obtaining first force data of the vehicle at the current moment; determining the first force data based on at least one of the road slope and the vehicle roll angle; estimating the center of mass sideslip angle of the vehicle based on the first force data, and obtaining a first estimated value of the center of mass sideslip angle at the next moment.

[0005] Among them, obtaining the first force data of the vehicle at the current moment includes: obtaining the first predicted lateral force corresponding to each wheel of the vehicle at the current moment; the first predicted lateral force is determined based on at least the road slope; based on the first predicted lateral force corresponding to each wheel, determining the first force data at the current moment.

[0006] Among them, based on the first predicted lateral force corresponding to each wheel, the first force data at the current moment is determined, including: taking the first predicted lateral force corresponding to each wheel at the current moment as the first force data at the current moment; or, comprehensively combining the first predicted lateral force corresponding to each wheel at the current moment and the first lateral force of the vehicle at the current moment to determine the first force data at the current moment; the first lateral force of the vehicle is determined based on the vehicle mass and the vehicle roll angle at the current moment.

[0007] Among them, obtaining the first predicted lateral force corresponding to each wheel of the vehicle at the current moment includes: obtaining the second lateral force corresponding to each wheel of the vehicle at a historical moment, the steering wheel angle of the vehicle at a historical moment, the first predicted longitudinal speed of the vehicle at a historical moment and the second predicted lateral force of each wheel at a historical moment; based on the second lateral force corresponding to each wheel at a historical moment, the steering wheel angle, the first predicted longitudinal speed and the second predicted lateral force of each wheel, prediction is performed to obtain the first predicted lateral force of each wheel at the current moment.

[0008] Among them, obtaining the second lateral force corresponding to each wheel of the vehicle at the historical moment includes: determining the sideslip angle and normal load of each wheel of the vehicle at the historical moment based on the first state data of the vehicle at the historical moment; determining the second lateral force of each wheel at the historical moment based on the sideslip angle and normal load of each wheel at the historical moment.

[0009] Among them, the first state data includes the vehicle's axle length, front axle track, rear axle track, distance from the center of mass to the center of the front axle, distance from the center of mass to the center of the rear axle, vehicle center of mass height, aerodynamic drag on the vehicle, equivalent height of aerodynamic drag, speed, acceleration, yaw angular velocity, and the turning angle corresponding to each wheel, at least one of the above, as well as the vehicle mass and road slope; and / or, the second lateral force of each wheel is calculated using the magic tire formula based on the sideslip angle and normal load of the corresponding wheel.

[0010] Among them, estimating the vehicle's center of mass sideslip angle based on the first force data to obtain a first estimated value of the center of mass sideslip angle at the next moment includes: acquiring the vehicle mass of the vehicle at the current moment and a number of predicted data of the vehicle at the current moment; the several predicted data include the vehicle's second predicted longitudinal speed, the vehicle's first predicted yaw angular velocity and the second estimated value of the center of mass sideslip angle; estimating based on the first force data at the current moment, the vehicle mass and the predicted data to obtain a first estimated value of the center of mass sideslip angle at the next moment.

[0011] Among them, the vehicle mass of the vehicle at each moment is predicted by using the first state transfer equation and the second state data of the vehicle at the corresponding moment, and the first state transfer equation is constructed by using the dynamic equation of the vehicle driving force; and / or, the first predicted yaw velocity of the vehicle is determined by using the second state transfer equation, the second predicted yaw velocity of the vehicle at a historical moment, and the second force data of the vehicle at a historical moment; the second longitudinal predicted velocity at the current moment is determined by using the third state transfer equation, the first longitudinal predicted velocity of the vehicle at a historical moment, the longitudinal predicted acceleration, the second predicted yaw velocity and the third estimated value of the sideslip angle of the center of mass at a historical moment.

[0012] Among them, the second state data includes: the vehicle's steering wheel angle, the moment of inertia of each wheel, the moment of inertia of the flywheel, the motor torque, the vehicle's longitudinal acceleration, and at least one of the rotational mass conversion coefficient; the second state transfer equation and the third state transfer equation are constructed using the vehicle's seven-degree-of-freedom dynamics model.

[0013] To solve the above technical problems, another technical solution adopted in the present application is: to provide an electronic device, comprising a memory and a processor coupled to each other, the memory storing program instructions; the processor is used to execute the program instructions stored in the memory to implement the above method.

[0014] In order to solve the above technical problem, another technical solution adopted by the present application is: providing a computer-readable storage medium for storing program instructions, which can be executed to implement the above method.

[0015] In the above scheme, the first force data of the vehicle at the current moment is determined based on at least one of the road slope and the vehicle roll angle. Therefore, in the process of estimating the center of mass sideslip angle of the vehicle based on the first force data, the present application will consider the influence of the road slope and / or the vehicle roll angle on the center of mass sideslip angle estimation. Compared with the scheme that does not consider the influence of the road slope and the vehicle roll angle on the center of mass sideslip angle, the above scheme of the present application can more comprehensively consider the influence of the vehicle's driving state on the center of mass sideslip angle, so it can improve the accuracy of the center of mass sideslip angle estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of an embodiment of a method for estimating the sideslip angle of the center of mass provided by the present application;

[0017] Figure 2 is a schematic diagram of a flow chart of an embodiment of determining a first predicted lateral force corresponding to each wheel provided by the present application;

[0018] Figure 3 yes Figure 1 The flowchart of step S12 is shown as an embodiment;

[0019] Figure 4 is a top view of the vehicle dynamics model provided by the present application;

[0020] Figure 5 is a side view of the vehicle dynamics model provided by the present application;

[0021] Figure 6 It is a front view of the roll angle of the vehicle dynamics model provided by the present application;

[0022] Figure 7 It is a schematic diagram of the framework of an embodiment of a device for estimating sideslip angle of center of mass provided by the present application;

[0023] Figure 8 It is a schematic diagram of a framework of an embodiment of an electronic device provided by the present application;

[0024] Fig. 9 It is a schematic diagram of the framework of the computer-readable storage medium provided by this application. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and effect of the present application clearer and more specific, the present application is further described in detail below with reference to the accompanying drawings and examples.

[0026] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0027] The center of mass sideslip angle is the angle between the direction of the vehicle's total velocity and the orientation of the vehicle body. The center of mass sideslip angle is of great significance in vehicle dynamics. It reflects the changes in the vehicle's posture during cornering and is crucial for evaluating the vehicle's stability and handling.

[0028] When a vehicle turns, the sideslip angle of the center of mass will change. An excessively large sideslip angle may cause the vehicle to lose stability, while an appropriate sideslip angle can improve the vehicle's handling and responsiveness.

[0029] The role of the center of mass sideslip angle is mainly reflected in the following aspects:

[0030] Stability assessment: The center of mass slip angle can reflect the change in the vehicle's posture. Too large or too small a center of mass slip angle may cause the vehicle to lose stability. By monitoring the center of mass slip angle, the stability of the vehicle when turning can be improved.

[0031] Optimized handling: A suitable sideslip angle can make the vehicle easier to control and improve the driver's controllability and responsiveness of the vehicle.

[0032] Vehicle posture control: The sideslip angle of the center of mass is an important input parameter of many vehicle dynamic control systems, such as the electronic stability control system (ESC). By estimating the sideslip angle of the center of mass, the vehicle posture can be better controlled.

[0033] Vehicle motion control: The heading error and lateral error are the basic feedback quantities for all motion control, and play a decisive role in the feedback control of motion control. The calculation of the heading error often ignores the sideslip angle of the center of mass, and directly uses the heading angle of the desired point and the yaw angle of the vehicle as the difference. The introduction of the sideslip angle of the center of mass can correct the calculation of the heading error, thereby improving the accuracy of motion control.

[0034] It can be seen that accurate estimation of the sideslip angle of the center of mass is crucial to evaluating the stability and handling of the vehicle.

[0035] See also Figure 1 , Figure 1 is a flow chart of an embodiment of a method for estimating the sideslip angle of the center of mass provided by the present application. It should be noted that if there are substantially the same results, this embodiment does not take Figure 1 The process sequence shown is limited. Figure 1 As shown, this embodiment includes:

[0036] S11: Acquire first force data of the vehicle at the current moment; the first force data is determined based on at least one of the road slope and the vehicle roll angle.

[0037] In this embodiment, the first predicted lateral force corresponding to each wheel of the vehicle at the current moment is first obtained, and then the first force data at the current moment is determined based on the first predicted lateral force corresponding to each wheel. The first predicted lateral force is determined based on at least the road slope, that is, the first predicted lateral force corresponding to each wheel is the force data of each wheel determined on the basis of considering the influence of the road condition (road slope) on the force of the vehicle.

[0038] In one embodiment, without considering the influence of the vehicle roll angle, the first predicted lateral force corresponding to each wheel is directly used as the first force data of the vehicle at the current moment.

[0039] In another embodiment, taking into account the influence of the vehicle roll angle, after determining the first predicted lateral force predicted by each wheel of the vehicle at the current moment, the first predicted lateral force corresponding to each wheel at the current moment and the first lateral force of the vehicle at the current moment are combined to determine the first force data at the current moment. The first lateral force is determined based on the vehicle mass and the vehicle roll angle at the current moment. In this embodiment, the first predicted lateral force corresponding to each wheel at the current moment and the first lateral force of the vehicle at the current moment can be used as the first force data at the current moment.

[0040] The first lateral force can be determined by the following expression:

[0041] F bank =mg sin(φ)

[0042] In the formula, F bankrepresents the first lateral force, and φ represents the vehicle roll angle.

[0043] The first predicted lateral force is predicted by information at a previous moment, and the second lateral force is calculated by using information at a current moment.

[0044] Specifically, see Figure 2 , Figure 2 1 is a flow chart of an embodiment of determining the first predicted lateral force corresponding to each wheel provided by the present application. In this embodiment, determining the first predicted lateral force corresponding to each wheel includes:

[0045] S21: Obtaining the second lateral force corresponding to each wheel of the vehicle at the historical moment, the steering wheel angle of the vehicle at the historical moment, the first predicted longitudinal speed of the vehicle at the historical moment, and the second predicted lateral force of each wheel at the historical moment.

[0046] In one embodiment, the slip angle and normal load of each wheel in the vehicle at the historical moment are first determined based on the first state data of the vehicle at the historical moment, and then the second lateral force of each wheel at that moment (historical moment) is determined based on the slip angle and normal load of each wheel in the vehicle at the historical moment.

[0047] It should be noted that for each moment (whether it is a historical moment or the current moment), the method of determining the lateral force of the wheel at the corresponding moment is the same, and the difference is that the state data required for calculation should be the first state data at the corresponding moment. For example, if the lateral force of each wheel at the current moment is calculated, the first state data of the vehicle at the current moment can be obtained first, and then the sideslip angle and normal load of each wheel in the vehicle at the current moment can be determined based on the first state data of the vehicle at the current moment, and then the lateral force of each wheel at this moment can be determined based on the sideslip angle and normal load of each wheel in the vehicle at the current moment.

[0048] The first state data includes at least one of the vehicle's axle length, front axle track, rear axle track, distance from center of mass to front axle center, distance from center of mass to rear axle center, vehicle center of mass height, aerodynamic drag on the vehicle, equivalent height of aerodynamic drag, speed, acceleration, yaw rate, and turning angles corresponding to each wheel, as well as vehicle mass and road slope. It can be understood that in this embodiment, the first state data includes at least vehicle mass and road slope.

[0049] In a specific embodiment, the first state data includes the vehicle's axle length, front axle track, rear axle track, distance from the center of mass to the center of the front axle, distance from the center of mass to the center of the rear axle, vehicle center of mass height, aerodynamic drag on the vehicle, equivalent height of aerodynamic drag, speed, acceleration, yaw angular velocity, and the turning angle corresponding to each wheel, vehicle mass and road slope.

[0050] Based on the first state data of the vehicle at the historical moment, the calculation method for determining the sideslip angle of each wheel in the vehicle at the historical moment is as follows:

[0051]

[0052] In the formula, α fl , α fr 、a rl and α rr They represent the front left wheel slip angle, the front right wheel slip angle, the rear left wheel slip angle and the rear right wheel slip angle respectively, δ fl ,δ fr ,δ rl and δ rr Respectively represent the front left wheel angle, front right wheel angle, rear left wheel angle and rear right wheel angle, ω r represents the yaw rate of the vehicle, v y Indicates the lateral speed of the vehicle, v x represents the longitudinal velocity of the vehicle, l f and l r They represent the distance from the center of mass of the vehicle to the center of the front axle, and the distance from the center of mass of the vehicle to the center of the rear axle, respectively. ftread Indicates the front axle track, L rtread Indicates rear axle track.

[0053] Based on the first state data of the vehicle at the historical moment, the calculation method for determining the normal load of each wheel in the vehicle at the historical moment is as follows:

[0054]

[0055] In the formula, ° zfl 、F zfr 、F zrl and F zrr They represent the normal load of the front left wheel, the front right wheel, the rear left wheel and the rear right wheel respectively, and F aero Indicates the aerodynamic drag on the vehicle, h aero represents the equivalent height of aerodynamic drag, m represents the vehicle mass, represents the longitudinal acceleration, Indicates the road slope, l f and l r They represent the distance from the center of mass of the vehicle to the center of the front axle, h represents the height of the center of mass of the vehicle, is the lateral acceleration, L ftread Indicates the front axle track, L rtread It represents the rear axle track and L represents the axle length.

[0056] It should be noted that the normal load of each wheel in this embodiment is a value determined under the influence of the road slope. Compared with the normal load of each wheel determined without considering the influence of the road slope, the solution of this embodiment taking the road slope into consideration can better adapt to the road conditions at the corresponding time, and the corresponding determined normal load value is more accurate.

[0057] Among them, F aero It represents the aerodynamic drag on the vehicle, which is the value determined under the assumption that the air drag acts on the center of mass of the vehicle. The aerodynamic drag can be determined by the following expression:

[0058]

[0059] Among them, C fx (beta) represents the air resistance coefficient when the vehicle's windward angle is beta, usually a constant value; C d represents the aerodynamic drag coefficient, which can be obtained through taxiing tests; ρ represents the air mass density; v w represents wind speed, v w <0 means headwind, v w >0 means tailwind; A F Indicates the frontal area of ​​the vehicle (the effective frontal cross-sectional area of ​​the vehicle), which is related to the width and height of the vehicle. F The specific value of can be determined by the following expression:

[0060] A F =1.6+0.00056(m-765)

[0061] In one embodiment, the second lateral force of each wheel is calculated based on the sideslip angle and normal load of the corresponding wheel using the following magic tire formula:

[0062] F fl =magic(a fl ,F zfl )

[0063] In the formula, F fl represents the second lateral force of the wheel, a fl Indicates the side slip angle of the wheel, F zfl represents the normal load of the wheel, and the magic() function represents the magic formula.

[0064] In the case of pure turning, the lateral force F y With tire slip angle α f , the vertical ground load F on the tire z The relationship between them is:

[0065]

[0066] S h =a 9 γ

[0067]

[0068] In the formula, C y is a constant (e.g., 1.3), a1-a12 are fitting coefficients (optionally, longitudinal fitting coefficients), γ is a constant, α f For each wheel, the side slip angle α of the wheel is f and normal load F z , substituting into the above formula, we can get the lateral force F of the wheel y (Second lateral force).

[0069] S22: Predicting based on the second lateral force corresponding to each wheel at a historical moment, the steering wheel angle, the first predicted longitudinal speed and the second predicted lateral force of each wheel to obtain the first predicted lateral force of each wheel at a current moment.

[0070] In summary, the first predicted lateral force in step S22 is predicted based on the second lateral force corresponding to each wheel at the historical moment, the steering wheel angle, the first predicted longitudinal speed, the second predicted lateral force of each wheel and the related state transfer equation.

[0071] Wherein, based on the information in step S22, the state transfer equations corresponding to the first predicted lateral force corresponding to each wheel are determined as follows:

[0072]

[0073]

[0074] In the formula, F fl ,F fr ,F rl ,F rr Respectively represent the second lateral force of the front left, front right, rear left, and rear right wheels, F fl(k) ,F fr(k) ,F rl(k) ,F rr(k) They represent the second predicted lateral forces of the front left, front right, rear left, and rear right wheels at the historical moment, respectively, and F fl(k+1) ,F fr(k+1) ,F rl(k+1) ,F rr(k+1) Respectively represent the first predicted lateral force of the front left, front right, rear left, and rear right wheels at the current moment; v x(k) represents the first predicted longitudinal speed of the vehicle at the historical moment, δ represents the steering wheel angle of the vehicle at the historical moment, dt represents the prediction time interval, c 1 and c 2They represent the front wheel hysteresis coefficient and the rear wheel hysteresis coefficient respectively.

[0075] It should be noted that the above-mentioned state transfer equations are equations describing the change of state over time, and are specifically used to predict the state at the next moment based on the state at the previous moment, wherein the previous moment and the next moment are two adjacent moments. In one embodiment, the state transfer equations corresponding to the first predicted lateral force corresponding to each wheel are determined by constructing a seven-degree-of-freedom dynamic model of the vehicle. For details, please refer to the description of the relevant part below.

[0076] S12: Estimate the center-of-mass sideslip angle of the vehicle based on the first force data to obtain a first estimated value of the center-of-mass sideslip angle at a next moment.

[0077] Specifically, see Figure 3 , Figure 3 yes Figure 1 The flowchart of an embodiment of step S12 is shown. In this embodiment, step S12 further includes:

[0078] S31: Acquire the vehicle mass of the vehicle at the current moment and a number of predicted data of the vehicle at the current moment; the number of predicted data includes a second predicted longitudinal speed of the vehicle, a first predicted yaw angular velocity of the vehicle and a second estimated value of the center of mass sideslip angle.

[0079] In one embodiment, the vehicle mass at each moment may be set to a fixed value.

[0080] In another embodiment, considering that the mass of the vehicle will change with the number of passengers and the loading conditions, and the force on the vehicle is closely related to the mass, for example, the vertical load of each wheel in the aforementioned embodiment is closely related to the mass of the vehicle, in order to accurately obtain the force data of the vehicle, the mass of the vehicle can be detected in real time, and the real-time detected vehicle mass can be used for force analysis, or other parameters can be estimated.

[0081] In a specific embodiment, the vehicle mass of the vehicle at each moment is predicted by using the first state transfer equation and the second state data of the vehicle at the corresponding moment, and the first state transfer equation is constructed by using the dynamic equation of the vehicle driving force. The second state data is at least one of the steering wheel angle of the vehicle, the moment of inertia of each wheel, the moment of inertia of the flywheel, the motor torque, the longitudinal acceleration of the vehicle, and the rotational mass conversion coefficient.

[0082] In a specific embodiment, the second state data is the steering wheel angle of the vehicle, the moment of inertia of each wheel, the moment of inertia of the flywheel, the motor torque, the longitudinal acceleration of the vehicle, and the rotational mass conversion coefficient. The dynamic equation of the vehicle driving force is expressed as follows:

[0083]

[0084] Where, T tq is the motor torque, a l is the vehicle longitudinal acceleration / deceleration, is the slope resistance, F r is the rolling resistance, F aero is the aerodynamic resistance, r eff is the effective rotation radius of the tire, δ represents the steering wheel angle, k a is the rotation mass conversion factor, which is related to the flywheel’s moment of inertia I f 、The moment of inertia of the wheel I w , vehicle mass m, transmission ratio (transmission ratio i g and the final reduction gear ratio i o ), transmission efficiency η T In this embodiment, rolling resistance, aerodynamic resistance and slope resistance can also be used as part of the second state data.

[0085] k a The calculation formula is expressed as follows:

[0086]

[0087] Based on the dynamic equation of vehicle driving force, the vehicle mass at each moment can be estimated by Kalman filtering, wherein the first state transfer equation for estimating the vehicle mass needs to be constructed in advance. The construction of the first state transfer equation can be expressed as follows:

[0088]

[0089] m (k+1) =m k

[0090] p (k+1) =p k

[0091] In the formula, v (k+1) and v k They represent the longitudinal speed at the next moment and the current moment respectively, m represents the vehicle mass, and P represents the slope. (k+1) =m k It means that the vehicle mass at the next moment needs to be predicted based on the mass at the current moment, and it does not mean that the vehicle mass at each moment is the same. Similarly, the slope also means that the slope at the next moment needs to be predicted based on the slope at the current moment.

[0092] In this embodiment, the vehicle mass at each moment is predicted by the first state transfer equation. Of course, in one embodiment, after estimating the vehicle mass at the current moment, the predicted vehicle mass can also be filtered using relevant observations (such as longitudinal speed observations, slope observations, etc.). Since the Kalman filter method is a prior art, it will not be described in detail here.

[0093] It should be noted that the determination of the above-mentioned vehicle mass is closely related to the motor torque. In the process of estimating the vehicle mass, it is necessary to consider whether the motor torque value is available. Among them, kinetic energy recovery is generally adopted in small deceleration conditions, and the motor torque value is available, while brake disc braking is adopted in conditions with a larger braking ratio. At this time, the motor torque value is only the braking torque generated by the kinetic energy recovery part, and does not include the braking torque of the brake disc. Therefore, the torque feedback value cannot be used as a conversion into braking force to analyze the longitudinal braking force. Furthermore, when the motor torque value at a certain moment is not available, the vehicle mass estimated at the previous moment of the corresponding moment is directly used as the vehicle mass at the corresponding moment until it is determined that the motor torque value is available, and the corresponding motor torque value is used to estimate the vehicle mass.

[0094] It should be noted that the above-mentioned real-time detected mass can be used to calculate the normal load of each wheel, and then indirectly affects the calculation of the lateral force (first force data) of each wheel when determining the lateral force of each tire using the normal load, sideslip angle and magic tire equation, so that the obtained first force data is a value that takes into account the influence of the dynamic change of the vehicle mass, thereby making the obtained first force data more accurate.

[0095] In addition, considering that the lateral movement of the vehicle is affected by the steering wheel, the front wheel heading angle actually directly determines the yaw movement of the vehicle. In addition to the nonlinear mapping relationship between the steering wheel and the front wheel angle, due to vehicle manufacturing and vehicle usage, the zero offset of the steering wheel under different models and different degrees of use is widely present and varies greatly. Generally, the angle is within ±6 degrees. It is particularly important to consider the zero offset of the steering wheel under high-speed conditions. Considering this, in one embodiment, the steering wheel angle described in this application is the actual EPS steering wheel angle value minus the steering wheel zero offset.

[0096] In a specific embodiment, Kalman filtering may be used to perform zero bias estimation at each moment.

[0097] The above F aero The specific method of determining the aerodynamic resistance can refer to the relevant description above and will not be elaborated here.

[0098] F rRolling resistance is the resistance acting on the wheel hub due to the rolling resistance of the wheel contact surface. When the resistance model is set to a constant coefficient, the rolling resistance and resistance coefficient can be expressed as follows:

[0099] F r =N·μ

[0100]

[0101] Among them, F r represents rolling resistance, N represents normal load, μ represents resistance coefficient, v hub Indicates the wheel speed, μ 0 represents the asymptotic rolling resistance coefficient, v threshold Indicates the threshold speed.

[0102] In this embodiment, the first predicted yaw rate of the vehicle is determined by using the second state transfer equation, the second predicted yaw rate of the vehicle at a historical moment, and the second force data of the vehicle at a historical moment.

[0103] It should be noted that the state transfer equations in the present application are equations that describe the change of state over time, and are specifically used to predict the state at the next moment based on the state at the previous moment, wherein the previous moment and the next moment are two adjacent moments.

[0104] Among them, the second state transfer equation expression is as follows:

[0105]

[0106] In the formula, w r(k+1) represents the first predicted yaw rate of the vehicle at the current moment, w r(k) represents the second predicted yaw rate of the vehicle at the historical moment, F fl(k) 、F fr(k) 、F fl(k) and F fr(k) They respectively represent the second force data at the historical moment (substantially representing the second predicted lateral forces of the front left, front right, rear left and rear right wheels at the historical moment, respectively), wherein the method for determining the second force data at the historical moment is the same as the method for determining the first predicted lateral forces of the front left, front right, rear left and rear right wheels at the current moment mentioned above, that is, the state at the next moment is predicted by utilizing the state at the previous moment between two adjacent moments. For details, please refer to the description of the corresponding part and no further details will be given here.

[0107] The second predicted longitudinal speed at the current moment is determined by using the third state transfer equation, the first predicted longitudinal speed of the vehicle at the historical moment, the predicted longitudinal acceleration, the second predicted yaw rate and the third estimated value of the sideslip angle of the center of mass at the historical moment. The expression of the third state transfer equation is as follows:

[0108] v x(k+1) =v x(k) +(a x(k) +v x(k) *w r(k) *β (k) )*dt

[0109] In the formula, v x(k+1) represents the second longitudinal predicted speed at the current moment, v x(k) represents the first longitudinal predicted speed of the vehicle at the historical moment, a x(k) represents the longitudinal predicted acceleration at the historical moment, w r(k) represents the second predicted yaw rate of the vehicle at the historical moment, β (k) The third estimated value of the mass center sideslip angle at the historical moment is represented by: the second longitudinal predicted speed at the current moment is determined by using the third estimated values ​​of the first longitudinal predicted speed, the longitudinal predicted acceleration, the second predicted yaw rate and the mass center sideslip angle corresponding to the previous moment.

[0110] It should be noted that the above second state transfer equation and the third state transfer equation are both constructed using the vehicle's seven-degree-of-freedom dynamics model.

[0111] Specifically, the constructed vehicle seven-degree-of-freedom dynamic model includes: a lateral degree-of-freedom dynamic model, a longitudinal degree-of-freedom dynamic model, a yaw degree-of-freedom dynamic model, and normal load dynamic models corresponding to the four wheels respectively.

[0112] Figure 4 is a top view of the vehicle dynamics model provided by this application, Figure 5 is a side view of the vehicle dynamics model provided by this application, Figure 6 It is a front view of the roll angle of the vehicle dynamics model provided by this application. When the vehicle is traveling at medium and high speeds, the mechanical characteristics of the vehicle body gradually become linear. Since the lateral force caused by steering acts on the tires, it may no longer be accurate to assume that the speed direction of each wheel is the direction of the wheel. At this time, a vehicle dynamics model is needed to analyze the lateral movement of the vehicle. Unlike the vehicle kinematic model, the vehicle dynamics model takes into account the relationship between the force conditions and kinematic quantities of the vehicle, and can more accurately describe the driving state of the vehicle.

[0113] Among them, the longitudinal degree of freedom dynamic model can be expressed as:

[0114]

[0115] In the formula, represents the longitudinal acceleration, w r is the yaw rate, F xfl +F xfr is the sum of the longitudinal forces on the front axle, Fyfl +F yfr is the sum of the lateral forces on the front axle, F xr is the sum of the longitudinal forces on the rear axle, F res It is the sum of aerodynamic resistance and rolling resistance, and δ represents the steering wheel angle.

[0116] The lateral degree of freedom dynamic model can be expressed as:

[0117]

[0118] In the formula, represents the lateral acceleration, F xfl +F xfr is the sum of the longitudinal forces on the front axle, F yfl +F yfr is the sum of the lateral forces on the front axle, F yrl +F yrr Represents the sum of the longitudinal forces on the rear axle, F bank represents the first lateral force, where = sin(), φ represents the vehicle roll angle, and δ represents the steering wheel angle.

[0119] The yaw degree of freedom dynamic model can be expressed as:

[0120]

[0121] In the formula, is the yaw angular acceleration, L ftread Indicates the front axle track, L rtread Represents rear axle track, l f and l r They represent the distance from the center of mass of the vehicle to the center of the front axle, and the distance from the center of mass of the vehicle to the center of the rear axle, respectively. xfl +F xft is the sum of the longitudinal forces on the front axle, F yfl +F yfr is the sum of the lateral forces on the front axle, F xfl -F xfr is the difference in longitudinal force on the front axle, F yfl -F yfr is the difference in lateral force on the front axle, F xrr -F xrl Indicates the difference in lateral force on the rear axle, F yrl +F yrr represents the sum of the longitudinal forces on the rear axle, and Iz represents the moment of inertia about the vehicle's z-axis.

[0122] The normal load dynamics models corresponding to the four wheels are:

[0123]

[0124] In the formula, F zfl 、Fzfr 、F zrl and F zrr They represent the normal load of the front left wheel, the front right wheel, the rear left wheel and the rear right wheel respectively, and F aero Indicates the aerodynamic drag on the vehicle, h aero represents the equivalent height of aerodynamic drag, m represents the vehicle mass, represents the longitudinal acceleration, Indicates the road slope, l f and l r They represent the distance from the center of mass of the vehicle to the center of the front axle, h represents the height of the center of mass of the vehicle, is the lateral acceleration, L ftread Indicates the front axle track, L rtread It represents the rear axle track and L represents the axle length.

[0125] According to the above seven-degree-of-freedom dynamics model, the second state transfer equation and the third state transfer equation are respectively:

[0126]

[0127] v x(k+1) =v x(k) +(a x(k) +v x(k) *w r(k) *β (k) )*dt

[0128] Among them, the fourth state transfer equation, the fifth state transfer equation, the sixth state transfer equation, and the seventh state transfer equation can also be constructed according to the above seven-degree-of-freedom dynamics model as follows:

[0129]

[0130] Among them, the fourth state transfer equation, the fifth state transfer equation, the sixth state transfer equation, and the seventh state transfer equation are respectively the state transfer equations corresponding to the first predicted lateral force corresponding to each wheel determined as mentioned above.

[0131] S32: Estimation is performed based on the first force data at the current moment, the vehicle mass and various predicted data to obtain a first estimated value of the center of mass sideslip angle at the next moment.

[0132] In one embodiment, the first estimated value of the center of mass sideslip angle at the next moment can be directly estimated using the following formula:

[0133]

[0134] In the formula, F fl(k) 、F fr(k) 、F rl(k)、F rr(k) and F bank are the first force data at the current moment, v x(k) 、w r(k) and β (k) are the above-mentioned prediction data respectively, and m is the vehicle mass at the current moment.

[0135] Of course, in some embodiments, the first estimated value of the center of mass sideslip angle at the next moment may also be estimated using the following formula:

[0136]

[0137] In the formula, F fl(k) 、F fr(k) 、F rl(k) 、F rr(k) are the first force data at the current moment, v x(k) 、w r(k) and β (k) are the above-mentioned prediction data respectively, and m is the vehicle mass at the current moment.

[0138] It should be noted that the formulas for estimating the first estimated value of the sideslip angle of the center of mass at the next moment recorded in step S32 can be constructed using the above-mentioned seven-degree-of-freedom dynamics model. Specifically, the formulas for estimating the first estimated value of the sideslip angle of the center of mass at the next moment recorded in step S32 are state transfer equations constructed using the above-mentioned seven-degree-of-freedom dynamics model.

[0139] In the above scheme, the first force data of the vehicle at the current moment is determined based on at least one of the road slope and the vehicle roll angle. Therefore, in the process of estimating the center of mass sideslip angle of the vehicle based on the first force data, the present application will consider the influence of the road slope and / or the vehicle roll angle on the center of mass sideslip angle estimation. Compared with the scheme that does not consider the influence of the road slope and the vehicle roll angle on the center of mass sideslip angle, the above scheme of the present application can more comprehensively consider the influence of the vehicle's driving state on the center of mass sideslip angle, so it can improve the accuracy of the center of mass sideslip angle estimation.

[0140] In some embodiments, the above-mentioned method of using each state transfer equation and the state estimate at the previous moment to obtain the state at the next moment (for example, estimating the center of mass sideslip angle, yaw angular velocity, predicted lateral force of each wheel, vehicle speed, etc. at the next moment) is essentially a Kalman filtering method, wherein when using each state transfer equation and the state estimate at the previous moment to obtain the state at the next moment, the estimated state value can be corrected using relevant observables (for example, the vehicle's lateral acceleration, yaw angular velocity and longitudinal speed). Since the Kalman filtering method is a prior art, it will not be introduced in detail here.

[0141] See also Figure 7 , Figure 7 It is a schematic diagram of the framework of an embodiment of a center of mass sideslip angle estimation device provided by the present application. In this embodiment, the center of mass sideslip angle estimation device 70 includes an acquisition module 71 and an estimation module 72. Among them, the acquisition module 71 is used to obtain the first force data of the vehicle at the current moment; the first force data is determined based on at least one of the road slope and the vehicle roll angle; the estimation module 72 is used to estimate the center of mass sideslip angle of the vehicle based on the first force data, and obtain the first estimated value of the center of mass sideslip angle at the next moment.

[0142] In some embodiments, the acquisition module 71 acquires the first force data of the vehicle at the current moment, including: acquiring the first predicted lateral force corresponding to each wheel of the vehicle at the current moment; the first predicted lateral force is determined based at least on the road slope; based on the first predicted lateral force corresponding to each wheel, determining the first force data at the current moment.

[0143] In some embodiments, based on the first predicted lateral force corresponding to each wheel, the first force data at the current moment is determined, including: taking the first predicted lateral force corresponding to each wheel at the current moment as the first force data at the current moment; or, combining the first predicted lateral force corresponding to each wheel at the current moment and the first lateral force of the vehicle at the current moment to determine the first force data at the current moment; the first lateral force of the vehicle is determined based on the vehicle mass and the vehicle roll angle at the current moment.

[0144] In some embodiments, obtaining a first predicted lateral force corresponding to each wheel of the vehicle at the current moment includes: obtaining a second lateral force corresponding to each wheel of the vehicle at a historical moment, a steering wheel angle of the vehicle at a historical moment, a first predicted longitudinal speed of the vehicle at a historical moment, and a second predicted lateral force of each wheel at a historical moment; making a prediction based on the second lateral force corresponding to each wheel at a historical moment, the steering wheel angle, the first predicted longitudinal speed, and the second predicted lateral force of each wheel to obtain the first predicted lateral force of each wheel at the current moment.

[0145] In some embodiments, obtaining a second lateral force corresponding to each wheel of a vehicle at a historical moment includes: determining a sideslip angle and a normal load of each wheel of the vehicle at the historical moment based on first state data of the vehicle at the historical moment; determining a second lateral force of each wheel at the historical moment based on the sideslip angle and the normal load of each wheel at the historical moment.

[0146] In some embodiments, the first state data includes at least one of the vehicle's axle length, front axle track, rear axle track, distance from the center of mass to the center of the front axle, distance from the center of mass to the center of the rear axle, height of the vehicle's center of mass, aerodynamic drag on the vehicle, equivalent height of aerodynamic drag, speed, acceleration, yaw angular velocity, and turning angle corresponding to each wheel, as well as vehicle mass and road slope; and / or, the second lateral force of each wheel is calculated using the magic tire formula based on the sideslip angle and normal load of the corresponding wheel.

[0147] In some embodiments, the estimation module 72 estimates the vehicle's center of mass sideslip angle based on the first force data to obtain a first estimated value of the center of mass sideslip angle at the next moment, including: obtaining the vehicle mass of the vehicle at the current moment and a number of predicted data of the vehicle at the current moment; the several predicted data include the vehicle's second predicted longitudinal speed, the vehicle's first predicted yaw angular velocity and the second estimated value of the center of mass sideslip angle; estimating based on the first force data at the current moment, the vehicle mass and the predicted data to obtain a first estimated value of the center of mass sideslip angle at the next moment.

[0148] In some embodiments, the vehicle mass of the vehicle at each moment is predicted using a first state transfer equation and second state data of the vehicle at the corresponding moment, and the first state transfer equation is constructed using a dynamic equation of the vehicle driving force; and / or, the first predicted yaw velocity of the vehicle is determined using the second state transfer equation, the second predicted yaw velocity of the vehicle at a historical moment, and the second force data of the vehicle at a historical moment; the second longitudinal predicted velocity at the current moment is determined using a third state transfer equation, the first longitudinal predicted velocity of the vehicle at a historical moment, the longitudinal predicted acceleration, the second predicted yaw velocity, and a third estimated value of the sideslip angle of the center of mass at a historical moment.

[0149] In some embodiments, the second state data includes: the vehicle's steering wheel angle, the moment of inertia of each wheel, the moment of inertia of the flywheel, the motor torque, the vehicle's longitudinal acceleration, and at least one of the rotational mass conversion coefficient; the second state transfer equation and the third state transfer equation are constructed using the vehicle's seven-degree-of-freedom dynamics model.

[0150] See also Figure 8 , Figure 8 1 is a schematic diagram of a framework of an electronic device according to an embodiment of the present application. In this embodiment, the electronic device 80 includes a memory 81 and a processor 82 coupled to each other.

[0151] The memory 81 stores program instructions, and the processor 82 is used to execute the program instructions stored in the memory 81 to implement the steps of any of the above method implementations. In a specific implementation scenario, the electronic device 80 may include, but is not limited to: a microcomputer, a server, and in addition, the electronic device 80 may also include a mobile device such as a laptop computer and a tablet computer, which is not limited here.

[0152] Specifically, the processor 82 is used to control itself and the memory 81 to implement the steps of any of the above-mentioned embodiments. The processor 82 can also be called a CPU (Central Processing Unit). The processor 82 may be an integrated circuit chip with signal processing capabilities. The processor 82 can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor 82 can be implemented by an integrated circuit chip.

[0153] See also Fig. 9 , Fig. 9 It is a schematic diagram of the framework of the computer-readable storage medium provided by the present application. The computer-readable storage medium 90 of the embodiment of the present application stores a program instruction 91, and when the program instruction 91 is executed, the method provided by any embodiment of the above method and any non-conflicting combination is implemented. Among them, the program instruction 91 can form a program file and be stored in the above-mentioned computer-readable storage medium 90 in the form of a software product, so that a computer device (which can be a personal computer, a server, or a network device, etc.) executes all or part of the steps of each implementation method of the present application. The aforementioned computer-readable storage medium 90 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, and a tablet.

[0154] In the above scheme, the first force data of the vehicle at the current moment is determined based on at least one of the road slope and the vehicle roll angle. Therefore, in the process of estimating the center of mass sideslip angle of the vehicle based on the first force data, the present application will consider the influence of the road slope and / or the vehicle roll angle on the center of mass sideslip angle estimation. Compared with the scheme that does not consider the influence of the road slope and the vehicle roll angle on the center of mass sideslip angle, the above scheme of the present application can more comprehensively consider the influence of the vehicle's driving state on the center of mass sideslip angle, so it can improve the accuracy of the center of mass sideslip angle estimation.

[0155] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0156] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0157] In the several embodiments provided in the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0159] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0160] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0161] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for estimating a sideslip angle of a center of mass, characterized in that: The method comprises: Acquire first force data of the vehicle at a current moment; the first force data is determined based on at least one of a road slope and a vehicle roll angle; The center-of-mass sideslip angle of the vehicle is estimated based on the first force data to obtain a first estimated value of the center-of-mass sideslip angle at a next moment.

2. The method according to claim 1, characterized in that The obtaining of the first force data of the vehicle at the current moment includes: Acquire a first predicted lateral force corresponding to each wheel of the vehicle at a current moment; the first predicted lateral force is determined at least based on the road slope; Based on the first predicted lateral force corresponding to each of the wheels, the first force data at the current moment is determined.

3. The method according to claim 2, characterized in that The determining the first force data at the current moment based on the first predicted lateral force corresponding to each of the wheels includes: The first predicted lateral force corresponding to each wheel at the current moment is used as the first force data at the current moment; or, The first force data at the current moment is determined by comprehensively analyzing the first predicted lateral force corresponding to each wheel at the current moment and the first lateral force of the vehicle at the current moment; the first lateral force of the vehicle is determined based on the vehicle mass at the current moment and the vehicle roll angle.

4. The method according to claim 2, characterized in that: The obtaining of the first predicted lateral force corresponding to each wheel of the vehicle at the current moment includes: Obtaining a second lateral force corresponding to each wheel of the vehicle at a historical moment, a steering wheel angle of the vehicle at a historical moment, a first predicted longitudinal speed of the vehicle at a historical moment, and a second predicted lateral force of each wheel at a historical moment; Based on the second lateral force corresponding to each of the wheels at a historical moment, the steering wheel angle, the first predicted longitudinal speed and the second predicted lateral force of each of the wheels, a prediction is performed to obtain the first predicted lateral force of each of the wheels at a current moment.

5. The method according to claim 4, characterized in that The obtaining of the second lateral force corresponding to each wheel of the vehicle at the historical moment includes: Determine the sideslip angle and normal load of each wheel of the vehicle at the historical moment based on the first state data of the vehicle at the historical moment; The second lateral force of each of the wheels at a historical moment is determined based on the sideslip angle and the normal load of each of the wheels at a historical moment.

6. The method according to claim 5, characterized in that The first state data includes at least one of the axle length, front axle track, rear axle track, distance from the center of mass to the center of the front axle, distance from the center of mass to the center of the rear axle, vehicle center of mass height, aerodynamic drag on the vehicle, equivalent height of the aerodynamic drag, speed, acceleration, yaw rate, and turning angles corresponding to each wheel, as well as vehicle mass and the road slope; And / or, the second lateral force of each wheel is calculated using the magic tire formula based on the sideslip angle and normal load of the corresponding wheel.

7. The method according to claim 1, characterized in that The estimating the center of mass sideslip angle of the vehicle based on the first force data to obtain a first estimated value of the center of mass sideslip angle at a next moment includes: Acquire the vehicle mass of the vehicle at the current moment and a number of predicted data of the vehicle at the current moment; the number of predicted data includes a second predicted longitudinal velocity of the vehicle, a first predicted yaw angular velocity of the vehicle, and a second estimated value of the center of mass sideslip angle; An estimation is performed based on the first force data, the vehicle mass and each of the predicted data at the current moment to obtain a first estimated value of the center of mass sideslip angle at the next moment.

8. The method according to claim 7, characterized in that The vehicle mass of the vehicle at each moment is predicted by using a first state transfer equation and second state data of the vehicle at the corresponding moment, wherein the first state transfer equation is constructed by using a dynamic equation of vehicle driving force; and / or, the first predicted yaw rate of the vehicle is determined by using a second state transfer equation, a second predicted yaw rate of the vehicle at a historical moment, and second force data of the vehicle at a historical moment; The second predicted longitudinal speed at the current moment is determined by using a third state transfer equation, the first predicted longitudinal speed of the vehicle at a historical moment, the predicted longitudinal acceleration, the second predicted yaw rate and a third estimated value of the sideslip angle of the center of mass at a historical moment.

9. The method according to claim 8, characterized in that The second state data includes: at least one of a steering wheel angle of the vehicle, a moment of inertia of each wheel, a moment of inertia of a flywheel, a motor torque, a longitudinal acceleration of the vehicle, and a rotational mass conversion coefficient; The second state transfer equation and the third state transfer equation are constructed using a seven-degree-of-freedom dynamics model of the vehicle.

10. An electronic device, characterized in that: comprising a memory and a processor coupled to each other, The memory stores program instructions; The processor is used to execute the program instructions stored in the memory to implement the method according to any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program instructions that can be run by a processor, and the program instructions can be executed by the processor to implement the method according to any one of claims 1 to 9.

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