Weight coefficient self-adaption-based transverse path tracking method, apparatus and device, and storage medium

Abstract

The invention belongs to the field of vehicle driving assistance, and particularly provides a transverse path tracking method, device and equipment based on weight coefficient self-adaption and a storage medium, and the method comprises the following steps: calculating a front wheel steering angle through a linear quadratic form adjustment algorithm in an upper controller; calculating a control variable through feedforward control to eliminate a feedback error; designing a stability compensation controller of the additional torque by using an improved sliding mode control algorithm, and calculating an additional yaw moment for compensation of the total driving torque; the current stability state is judged through the phase plane graph of the side slip angle and the yaw velocity, and the weight of the phase plane is automatically adjusted based on the judgment result of the stability state; and calculating the distribution of the additional yaw torque in real time through the self-adaptively adjusted weight coefficient. And the stability is balanced through a sliding mode control theory. The additional yaw torque is calculated in real time by adaptively adjusting the weight coefficient, and the control stability is improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle driving assistance technology, and in particular to a lateral path tracking method, device, equipment and storage medium based on weight coefficient adaptation. Background Art

[0002] Intelligence is the future development trend of the automotive industry. Intelligence requires that vehicles can ensure stable driving according to the trajectory output by decision-making planning. However, problems such as emergencies and bad road conditions will increase the difficulty of stability control, which is a key factor in path following control. In the existing technology, the longitudinal control system of the vehicle is relatively mature, but there is little research on lateral control, which makes it difficult to ensure the safety and stability of the vehicle under complex road conditions.

[0003] Sliding mode control is a common and effective control method for dealing with nonlinear models, and has good anti-interference performance. At present, sliding mode control is mostly used to reduce the impact of lateral interference. However, there are certain shortcomings in using the classic sliding film control theory to increase lateral stability, such as jitter problems, and the inability to achieve a balance between smooth transition and convergence speed.

[0004] The existing tracking method designs the longitudinal velocity sliding surface, derives the velocity sliding law, and uses the candidate Lyapunov function to prove the closed-loop stability of the velocity control system. It can ensure that the tracking controller has high stability and high real-time performance. At the same time, the adaptive law is used to solve the problem of tracking error divergence in the steering process, and the controller decoupling is used to solve the problem of poor real-time performance of the model predictive control. However, the phase plane cannot automatically adjust the weight coefficient, which reduces its adaptability. Summary of the invention

[0005] In view of the problems existing in the existing path tracking methods, the present invention provides a lateral path tracking method, device, equipment and storage medium based on weight coefficient adaptation.

[0006] In a first aspect, the technical solution of the present invention provides a lateral path tracking method based on weight coefficient adaptation, comprising the following steps: The front wheel steering angle is calculated by a linear quadratic adjustment algorithm in the upper controller; Eliminate feedback errors by calculating control variables through feedforward control; The stability compensation controller of the additional torque is designed by using the improved sliding mode control algorithm to calculate the additional yaw torque used to compensate the total driving torque. The current stability state is determined by the phase plane diagram of the sideslip angle and the yaw rate, and the weight of the phase plane is automatically adjusted based on the determination result of the stability state; The distribution of the additional yaw torque is calculated in real time through the adaptively adjusted weight coefficients.

[0007] As a further limitation of the technical solution of the present invention, the step of calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller includes: Build vehicle dynamics models; The yaw rate and sideslip rate are calculated based on the vehicle dynamics model.

[0008] The vehicle dynamics model is:

[0009]

[0010] In the formula, is the vehicle mass; is the lateral velocity; is the longitudinal velocity; For the The longitudinal force of each wheel; For the The lateral force of each wheel; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the distance from the center of mass to the front wheel; is the distance from the center of mass to the rear wheel; is the front wheel track; is the rear wheel track; is the additional yaw moment.

[0011] As a further limitation of the technical solution of the present invention, the formula in the step of calculating the yaw rate and the sideslip rate of the center of mass based on the vehicle dynamics model is as follows:

[0012] In the formula, For the Cornering stiffness of each wheel Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; .

[0013] As a further limitation of the technical solution of the present invention, the formula for calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller is as follows:

[0014] In the formula, , is the coefficient matrix of feedback control; for The cornering stiffness of the wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively.

[0015] As a further limitation of the technical solution of the present invention, the stability compensation controller of the additional torque is designed by using the improved sliding mode control algorithm, and the calculation formula in the step of calculating the additional yaw torque for compensating the total driving torque is as follows:

[0016]

[0017] In the formula, is the positive parameter of the saturation function, is the sideslip angle of the center of mass; The sideslip angular velocity of the center of mass, is the ideal center-of-mass sideslip angular velocity, For the The cornering stiffness of each wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. is the calibration factor.

[0018] As a further limitation of the technical solution of the present invention, in the step of judging the current stability state by the phase plane diagram of the sideslip angle of the center of mass and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state, the stability boundary is described as:

[0019] is the sideslip angle of the center of mass; Center of mass sideslip angular velocity; and All are stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance; The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0020] in, is the distance to the lower stability boundary, Indicates that the state point is above the lower boundary, For the state point is below the lower boundary; is the distance between two stable boundaries.

[0021] As a further limitation of the technical solution of the present invention, the formula for calculating the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient is as follows:

[0022] in, is the tire working radius; For driving torque Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; Total drive torque to achieve target vehicle speed;

[0023] in, is the left side distribution coefficient, is the right-hand side distribution coefficient; Solve the problem with minimum tire slip and minimum working load as the objective function and Parameters; where the summation weight is ;

[0024] in, is the road adhesion coefficient, is the longitudinal slip rate Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; For the The longitudinal force of each wheel; For the The lateral force of each wheel; The tire load of each wheel perpendicular to the ground.

[0025] In a second aspect, the technical solution of the present invention provides a lateral path tracking device based on weight coefficient adaptation, comprising a first processing and calculation module, a feedback error elimination module, a second processing and calculation module, a weight adaptive adjustment module and a torque distribution module; A first processing and calculation module is used to calculate the front wheel steering angle by using a linear quadratic adjustment algorithm in an upper controller; A feedback error elimination module is used to eliminate feedback errors by calculating control variables through feedforward control; A second processing and calculation module is used to design a stability compensation controller of an additional torque by using an improved sliding mode control algorithm, and calculate an additional yaw moment for compensating the total driving torque; A weight adaptive adjustment module is used to determine the current stability state through the phase plane diagram of the center of mass sideslip angle and the yaw rate, and automatically adjust the weight of the phase plane based on the determination result of the stability state; The torque distribution module is used to calculate the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient.

[0026] As a further limitation of the technical solution of the present invention, the device also includes a preprocessing module for establishing a vehicle dynamics model; and calculating the yaw angular velocity and the center of mass sideslip angular velocity based on the vehicle dynamics model.

[0027] The vehicle dynamics model is:

[0028]

[0029] In the formula, is the vehicle mass; is the lateral velocity; is the longitudinal velocity; For the The longitudinal force of each wheel; For the The lateral force of each wheel; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the distance from the center of mass to the front wheel; is the distance from the center of mass to the rear wheel; is the front wheel track; is the rear wheel track; is the additional yaw moment.

[0030] As a further limitation of the technical solution of the present invention, the formula for calculating the yaw rate and the sideslip rate of the center of mass based on the vehicle dynamics model by the preprocessing module is as follows:

[0031] In the formula, For the Cornering stiffness of each wheel Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; .

[0032] As a further limitation of the technical solution of the present invention, the formula for calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller is as follows:

[0033] In the formula, , is the coefficient matrix of feedback control; for The cornering stiffness of the wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively.

[0034] As a further limitation of the technical solution of the present invention, an additional torque stability compensation controller is designed using an improved sliding mode control algorithm, and the calculation formula for the additional yaw torque used to compensate the total driving torque is calculated as follows:

[0035]

[0036] In the formula, is the positive parameter of the saturation function, is the sideslip angle of the center of mass; The sideslip angular velocity of the center of mass, is the ideal center-of-mass sideslip angular velocity, For the The cornering stiffness of each wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. is the calibration factor.

[0037] As a further limitation of the technical solution of the present invention, the stability boundary is described as:

[0038] is the sideslip angle of the center of mass; Center of mass sideslip angular velocity; and All are stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance; The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0039] in, is the distance to the lower stability boundary, Indicates that the state point is above the lower boundary, For the state point is below the lower boundary; is the distance between two stable boundaries.

[0040] As a further limitation of the technical solution of the present invention, the formula for calculating the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient is as follows:

[0041] in, is the tire working radius; For driving torque Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; Total drive torque to achieve target vehicle speed;

[0042] in, is the left side distribution coefficient, is the right-hand side distribution coefficient; Solve the problem with minimum tire slip and minimum working load as the objective function and Parameters; where the summation weight is ;

[0043] in, is the road adhesion coefficient, is the longitudinal slip rate Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; For the The longitudinal force of each wheel; For the The lateral force of each wheel; The tire load of each wheel perpendicular to the ground.

[0044] In a third aspect, the technical solution of the present invention also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores computer program instructions executable by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can execute the lateral path tracking method based on weight coefficient adaptation as described in the first aspect.

[0045] In a fourth aspect, the technical solution of the present invention further provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the lateral path tracking method based on weight coefficient adaptation as described in the first aspect.

[0046] It can be seen from the above technical solutions that the present invention has the following advantages: the front wheel steering angle is calculated by the linear quadratic adjustment algorithm in the upper controller, and the steering trajectory tracking error problem is solved by feedforward control. The stability compensation controller of the additional torque is designed by using the improved sliding mode control algorithm. The current stability state is judged by the phase plane diagram of the center of mass sideslip angle and yaw rate, and the weight ratio of the phase plane is automatically adjusted to calculate the additional torque to ensure that the vehicle maintains lateral stability.

[0047] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0050] Figure 2 It is a diagram of a vehicle model.

[0051] Figure 3 is a schematic block diagram of an apparatus according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0053] like Figure 1 As shown, an embodiment of the present invention provides a lateral path tracking method based on weight coefficient adaptation, comprising the following steps: Step 1: Calculate the front wheel steering angle through the linear quadratic adjustment algorithm in the upper controller; Step 2: Eliminate feedback error by calculating control variables through feedforward control; Step 3: Design an additional torque stability compensation controller using an improved sliding mode control algorithm to calculate the additional yaw torque used to compensate the total driving torque; Step 4: Determine the current stability state through the phase plane diagram of the sideslip angle and the yaw rate, and automatically adjust the weight of the phase plane based on the determination result of the stability state; Step 5: Calculate the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficients.

[0054] It should be noted that in the embodiment of the present invention, the step of calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller includes: Build vehicle dynamics models; The yaw rate and sideslip rate are calculated based on the vehicle dynamics model.

[0055] The vehicle model is as follows: Figure 2 As shown, the vehicle dynamics model:

[0056]

[0057] In the formula, is the vehicle mass; is the lateral velocity; is the longitudinal velocity; For the The longitudinal force of each wheel; For the The lateral force of each wheel; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the distance from the center of mass to the front wheel; is the distance from the center of mass to the rear wheel; is the front wheel track; is the rear wheel track; is the additional yaw moment.

[0058] Assuming that the tire operates in the linear characteristic region and ignoring the effect of the driving force on the yaw motion, the longitudinal force can be expressed as:

[0059] in, No. The slip angle of each wheel, For the The cornering stiffness of each wheel.

[0060]

[0061] Due to the front wheel angle is small, then assume is 0, =1, we can calculate:

[0062] In the formula, For the Cornering stiffness of each wheel Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; .

[0063] In some embodiments, a LQR-based path tracking algorithm is implemented.

[0064]

[0065] in,

[0066]

[0067]

[0068] is the lateral deviation, i.e. the distance between the ideal position and the actual position of the vehicle, is the lateral deviation change rate, is the ideal yaw rate.

[0069]

[0070]

[0071]

[0072] Solving for Control Variables Using a Controller , set the objective function:

[0073] in, is the state error, is the control variable error in the feedback module. The larger the state variable The faster the decay. The larger the control variable Reduce. The optimal control can be expressed as:

[0074] in, is the coefficient matrix of feedback control, is a constant matrix.

[0075] To eliminate the feedback error, it can be calculated:

[0076] Among them, the formula for calculating the front wheel steering angle through the linear quadratic adjustment algorithm in the upper controller is as follows:

[0077] In the formula, , is the coefficient matrix of feedback control; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; In some embodiments, a stability compensator is established. Using sliding mode theory, the lateral stability is determined by the yaw rate and the sideslip angle of the center of mass, and the error expression is as follows: First, the lateral stability is described based on the yaw rate and the sideslip angle of the center of mass, and the comprehensive error is:

[0078] in, is the comprehensive error, is the yaw rate error, Center of mass sideslip angle error, is the weight coefficient.

[0079] The sliding surface function can be expressed as:

[0080] is the calibration coefficient, The larger the value, the shorter the time to reach a stable state. Too large a value will cause jitter. The optimal value can be obtained through testing.

[0081] The calculation can be obtained:

[0082] The derivative is:

[0083] Using the saturation function as the convergence law can reduce system jitter, that is:

[0084]

[0085] in, is the positive parameter of the saturation function, is the ideal slip angle.

[0086] Through the above formula, the additional yaw moment can be calculated:

[0087] In the formula, is the positive parameter of the saturation function, is the sideslip angle of the center of mass; The sideslip angular velocity of the center of mass, is the ideal center-of-mass sideslip angular velocity, For the The cornering stiffness of each wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. is the calibration coefficient, is the expression of the convergence rate.

[0088] In some embodiments, the stability weight coefficient is adaptively adjusted. It needs to be dynamically adjusted through stable state for sliding plane stability analysis. When the stability is good, The smaller the torque, the more torque is used for longitudinal following. The larger the value, the more the torque is concentrated on lateral stability. The stability boundary is the boundary line between the stable area and the unstable area. The current stability state is judged by the phase plane diagram of the center of mass sideslip angle and the yaw rate, and the weight of the phase plane is automatically adjusted based on the judgment result of the stability state. The stability boundary is described as:

[0089] is the sideslip angle of the center of mass; Center of mass sideslip angular velocity; and All are stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance; The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0090] in, is the distance to the lower stability boundary, Indicates that the state point is above the lower boundary, The state point is below the lower boundary; is the distance between two stable boundaries.

[0091] In some embodiments, the torque distribution increases the distribution of additional yaw torque to maintain lateral stability.

[0092]

[0093] in, is the tire working radius; For driving torque Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; Total drive torque to achieve target vehicle speed;

[0094] in, is the left side distribution coefficient, is the right-hand side distribution coefficient; The minimum tire slip and the minimum working load are used as the objective function; the sum weight is ;

[0095] in, is the road adhesion coefficient, is the longitudinal slip rate Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; For the The longitudinal force of each wheel; For the The lateral force of each wheel; The invention mainly focuses on the method of lateral control stability, and determines the stability through sliding mode control theory. By adaptively adjusting the weight coefficient, the additional yaw torque is calculated in real time to improve the control stability. like Figure 3 As shown, an embodiment of the present invention provides a lateral path tracking device based on weight coefficient adaptation, including a first processing and calculation module, a feedback error elimination module, a second processing and calculation module, a weight adaptive adjustment module and a torque distribution module; A first processing and calculation module is used to calculate the front wheel steering angle by using a linear quadratic adjustment algorithm in an upper controller; A feedback error elimination module is used to eliminate feedback errors by calculating control variables through feedforward control; A second processing and calculation module is used to design a stability compensation controller of an additional torque by using an improved sliding mode control algorithm, and calculate an additional yaw moment for compensating the total driving torque; A weight adaptive adjustment module is used to determine the current stability state through the phase plane diagram of the center of mass sideslip angle and the yaw rate, and automatically adjust the weight of the phase plane based on the determination result of the stability state; The torque distribution module is used to calculate the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient.

[0096] The device also includes a preprocessing module for establishing a vehicle dynamics model; and calculating a yaw angular velocity and a sideslip angular velocity of the center of mass based on the vehicle dynamics model.

[0097] The vehicle dynamics model is:

[0098]

[0099] In the formula, is the vehicle mass; is the lateral velocity; is the longitudinal velocity; For the The longitudinal force of each wheel; For the The lateral force of each wheel; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the distance from the center of mass to the front wheel; is the distance from the center of mass to the rear wheel; is the front wheel track; is the rear wheel track; is the additional yaw moment.

[0100] The formula used by the preprocessing module to calculate the yaw rate and the sideslip rate of the center of mass based on the vehicle dynamics model is as follows:

[0101] In the formula, For the Cornering stiffness of each wheel Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; .

[0102] In some embodiments, the formula for calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller is as follows:

[0103] In the formula, is the coefficient matrix of feedback control; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; In some embodiments, an additional torque stability compensation controller is designed using an improved sliding mode control algorithm, and the additional yaw torque for compensating the total driving torque is calculated as follows:

[0104]

[0105] In the formula, is the positive parameter of the saturation function, is the sideslip angle of the center of mass; The sideslip angular velocity of the center of mass, is the ideal center-of-mass sideslip angular velocity, For the The cornering stiffness of each wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. is the calibration factor.

[0106] In some embodiments, the stability boundary is described as:

[0107] is the sideslip angle of the center of mass; Center of mass sideslip angular velocity; and All are stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance; The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0108] in, is the distance to the lower stability boundary, Indicates that the state point is above the lower boundary, The state point is below the lower boundary; is the distance between two stable boundaries.

[0109] In some embodiments, the formula for calculating the distribution of the additional yaw torque in real time by using the adaptively adjusted weight coefficient is as follows:

[0110] in, is the tire working radius; For driving torque Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; Total drive torque to achieve target vehicle speed;

[0111] in, is the left side distribution coefficient, is the right-hand side distribution coefficient; Solve the problem with minimum tire slip and minimum working load as the objective function and Parameters; where the summation weight is ;

[0112] in, is the road adhesion coefficient, is the longitudinal slip rate Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; No. The slip angle of each wheel; For the The longitudinal force of each wheel; For the The lateral force of each wheel; The tire load of each wheel perpendicular to the ground.

[0113] The embodiment of the present invention also provides an electronic device, which includes: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The communication bus can be used for information transmission between the electronic device and the sensor. The processor can call the logic instructions in the memory to execute the following method: Step 1: Calculate the front wheel steering angle through the linear quadratic adjustment algorithm in the upper controller; Step 2: Calculate the control variable through feedforward control to eliminate the feedback error; Step 3: Design the stability compensation controller of the additional torque using the improved sliding mode control algorithm, and calculate the additional yaw torque for compensating the total driving torque; Step 4: Determine the current stability state through the phase plane diagram of the center of mass sideslip angle and yaw angular velocity, and automatically adjust the weight of the phase plane based on the judgment result of the stability state; Step 5: Calculate the distribution of the additional yaw torque in real time through the weight coefficient adjusted adaptively.

[0114] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. 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, etc., which can store program code.

[0115] An embodiment of the present invention provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable a computer to execute the method provided by the above method embodiment, for example, including: Step 1: Calculate the front wheel steering angle through a linear quadratic adjustment algorithm in an upper-level controller; Step 2: Calculate the control variable through feedforward control to eliminate feedback errors; Step 3: Design a stability compensation controller for additional torque using an improved sliding mode control algorithm, and calculate the additional yaw torque for compensating the total driving torque; Step 4: Determine the current stability state through a phase plane diagram of the center of mass sideslip angle and yaw angular velocity, and automatically adjust the weight of the phase plane based on the judgment result of the stability state; Step 5: Calculate the distribution of the additional yaw torque in real time through the weight coefficient after adaptive adjustment.

[0116] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0117] An embodiment of a lateral path tracking device based on adaptive weight coefficient is provided in an embodiment of the present invention. The device and the lateral path tracking method based on adaptive weight coefficient in the above-mentioned embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the lateral path tracking device based on adaptive weight coefficient, reference can be made to the embodiment of the above-mentioned lateral path tracking method based on adaptive weight coefficient.

[0118] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A lateral path tracking method based on adaptive weight coefficient, characterized in that: The steps include: The front wheel steering angle is calculated by a linear quadratic adjustment algorithm in the upper controller; Eliminate feedback errors by calculating control variables through feedforward control; The stability compensation controller of the additional torque is designed by using the improved sliding mode control algorithm to calculate the additional yaw torque used to compensate the total driving torque. The current stability state is determined by the phase plane diagram of the sideslip angle and the yaw rate, and the weight of the phase plane is automatically adjusted based on the determination result of the stability state; The distribution of the additional yaw torque is calculated in real time through the adaptively adjusted weight coefficients.

2. The lateral path tracking method based on weight coefficient adaptation according to claim 1, characterized in that: The step of calculating the front wheel steering angle by the linear quadratic adjustment algorithm in the upper controller includes: Build vehicle dynamics models; Calculate the yaw rate and the sideslip rate based on the vehicle dynamics model; The vehicle dynamics model is: In the formula, is the vehicle mass; is the lateral velocity; is the longitudinal velocity; For the The longitudinal force of each wheel; For the The lateral force of each wheel; Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the distance from the center of mass to the front wheel; is the distance from the center of mass to the rear wheel; is the front wheel track; is the rear wheel track; is the additional yaw moment.

3. The lateral path tracking method based on weight coefficient adaptation according to claim 2, characterized in that: The formula for calculating the yaw rate and the sideslip rate based on the vehicle dynamics model is as follows: In the formula, For the Cornering stiffness of each wheel Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; .

4. The lateral path tracking method based on weight coefficient adaptation according to claim 3, characterized in that: The formula for calculating the front wheel steering angle through the linear quadratic adjustment algorithm in the upper controller is as follows: In the formula, , is the coefficient matrix of feedback control; for The cornering stiffness of the wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively.

5. The lateral path tracking method based on weight coefficient adaptation according to claim 4, characterized in that: The stability compensation controller of the additional torque is designed by using the improved sliding mode control algorithm, and the calculation formula in the step of calculating the additional yaw torque for compensating the total driving torque is as follows: In the formula, is the positive parameter of the saturation function, is the sideslip angle of the center of mass; Center of mass sideslip angular velocity, is the ideal center-of-mass sideslip angular velocity, For the The cornering stiffness of each wheel, They represent the left front wheel, right front wheel, left rear wheel, and right rear wheel respectively. is the calibration factor.

6. The lateral path tracking method based on weight coefficient adaptation according to claim 5, characterized in that: In the step of judging the current stability state by the phase plane diagram of the sideslip angle and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state, the stability boundary is described as: is the sideslip angle of the center of mass; Center of mass sideslip angular velocity; and All are stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance; The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows: in, is the distance to the lower stability boundary, Indicates that the state point is above the lower boundary, The state point is below the lower boundary; is the distance between two stable boundaries.

7. The lateral path tracking method based on weight coefficient adaptation according to claim 6, characterized in that: The formula for calculating the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient is as follows: in, is the tire working radius; For driving torque Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; Total drive torque to achieve target vehicle speed; in, is the left side distribution coefficient, is the right-hand side distribution coefficient; Solve the problem with minimum tire slip and minimum working load as the objective function and Parameters; where the summation weight is ; in, is the road adhesion coefficient, is the longitudinal slip rate Respectively represent the left front wheel, right front wheel, left rear wheel, and right rear wheel; No. The slip angle of each wheel; For the The longitudinal force of each wheel; For the The lateral force of each wheel; The tire load of each wheel perpendicular to the ground.

8. A lateral path tracking device based on adaptive weight coefficient, characterized in that: It includes a first processing and calculation module, a feedback error elimination module, a second processing and calculation module, a weight adaptive adjustment module and a torque distribution module; A first processing and calculation module is used to calculate the front wheel steering angle by using a linear quadratic adjustment algorithm in an upper controller; A feedback error elimination module is used to eliminate feedback errors by calculating control variables through feedforward control; A second processing and calculation module is used to design a stability compensation controller of an additional torque by using an improved sliding mode control algorithm, and calculate an additional yaw moment for compensating the total driving torque; A weight adaptive adjustment module is used to determine the current stability state through the phase plane diagram of the center of mass sideslip angle and the yaw rate, and automatically adjust the weight of the phase plane based on the determination result of the stability state; The torque distribution module is used to calculate the distribution of the additional yaw torque in real time through the adaptively adjusted weight coefficient.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; the memory stores computer program instructions executable by the at least one processor, and the computer program instructions are executed by the at least one processor so that the at least one processor can execute the lateral path tracking method based on weight coefficient adaptation as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the lateral path tracking method based on weight coefficient adaptation according to any one of claims 1 to 7.

Images