A lateral path tracking method and device based on weight coefficient adaptation, equipment and storage medium

Abstract

The application belongs to the field of vehicle driving assistance, and specifically provides a lateral path tracking method and device based on adaptive weight coefficients, equipment and storage medium, the method comprises the following steps: calculating the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller; calculating the control variable to eliminate the feedback error through the feedforward control; using the improved sliding mode control algorithm to design the stability compensation controller of the additional torque, calculating the additional yaw moment for the compensation of the total driving torque; judging the current stability state through the phase plane of the center of mass side slip angle and the yaw angular velocity, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state; calculating the distribution of the additional yaw torque in real time through the adaptive adjusted weight coefficient. Through the sliding mode control theory, the stability is determined. Through the adaptive adjustment of the weight coefficient, the additional yaw torque is calculated in real time, and the control stability is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle driving assistance, in particular to a lateral path tracking method based on adaptive weight coefficient, device, equipment and storage medium. BACKGROUND

[0002] Intelligence is the future development trend of the automobile industry, and intelligence requires vehicles to ensure stable driving according to the trajectory output by decision planning. However, sudden events and poor road conditions will increase the difficulty of stability control, and stability control is a key factor of path following control. In the prior art, the vehicle longitudinal control system is relatively mature, but the research on lateral control is less, which makes it difficult to ensure safety and stability of the vehicle in complex road conditions.

[0003] The sliding mode control method is a commonly used and effective control method in dealing with nonlinear models, and has good anti-interference performance. At present, the lateral control is mostly reduced by sliding mode control to reduce the influence of lateral disturbance. However, there are certain deficiencies in increasing the lateral stability by using the classical sliding film control theory, and the shaking problem, smooth transition and convergence speed cannot be balanced.

[0004] The existing tracking method designs a longitudinal speed sliding mode surface, derives a speed sliding mode law, and uses a candidate Lyapunov function to prove the closed-loop stability of the speed control system. It can ensure that the tracking controller has high stability and high real-time performance, and at the same time, the adaptive law solves the problem of tracking error divergence in the steering process, and the controller decoupling solves the problem of poor real-time performance of model predictive control. However, the weight coefficient of the phase plane cannot be automatically adjusted, which reduces its adaptability. SUMMARY

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

[0006] In the first aspect, the present application provides a lateral path tracking method based on adaptive weight coefficient, which comprises the following steps:

[0007] The front wheel steering angle is calculated by the linear quadratic regulation algorithm in the upper controller;

[0008] The control variable is calculated by feedforward control to eliminate feedback error;

[0009] An improved sliding mode control algorithm is used to design a stability compensation controller of additional torque to calculate an additional yaw moment for compensation of total driving torque;

[0010] The current stability state is judged by the phase plane diagram of the center of mass side slip angle and the yaw rate, and the weight of the phase plane is automatically adjusted based on the judgment result of the stability state.

[0011] The distribution of the additional yaw moment is calculated in real time through the self-adaptively adjusted weight coefficient.

[0012] As a further limitation of the technical solution of the application, the step of calculating the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller comprises the following steps before the step:

[0013] A vehicle dynamics model is established.

[0014] The yaw angular velocity and the mass center side slip angular velocity are calculated based on the vehicle dynamics model.

[0015] The vehicle dynamics model is as follows:

[0016]

[0017]

[0018] In the formula, m is the total vehicle mass; v is the lateral velocity; u is the longitudinal velocity; Fx i is the longitudinal force of the i th wheel; Fy i is the lateral force of the i th wheel; δf is the front wheel steering angle; I z is the moment of inertia; ψ is the yaw angle; Lf is the distance from the mass center to the front wheel; Lr is the distance from the mass center to the rear wheel; Tr is the rear wheel track; Tf is the front wheel track; and M z is the additional yaw moment.

[0019] As a further limitation of the technical solution of the application, the formula for calculating the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller is as follows:

[0020]

[0021] In the formula, K i is the side slip stiffness of the i th wheel; and the other notations are the same as above.

[0022] As a further limitation of the technical solution of the application, the formula for calculating the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller is as follows: ​​​​​​​​​​​​​​​​​​​​

[0023]

[0024] In the formula, , It is the coefficient matrix of feedback control; for Wheel lateral stiffness, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0025] As a further limitation of the technical solution of the present invention, the calculation formula in the step of designing a stability compensation controller for additional torque using an improved sliding mode control algorithm and calculating the additional yaw moment for compensation of total driving torque is as follows:

[0026]

[0027]

[0028] In the formula, is a positive parameter of the saturation function. It is the centroid sideslip angle; The angular velocity of the center of mass deflection. For the ideal centroid sideslip angular velocity, For the first The lateral stiffness of each wheel, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. These are calibration coefficients.

[0029] As a further limitation of the technical solution of the present invention, in the step of determining the current stability state by using the phase plane diagram of the centroid sideslip angle and yaw rate, and automatically adjusting the weights of the phase plane based on the determination result of the stability state, the stability boundary is described as follows:

[0030]

[0031] It is the centroid sideslip angle; The angular velocity of the center of mass deflection; and All of these are boundary coefficients for stability assessment, determined by the road surface adhesion coefficient; For system disturbance;

[0032] The formula for automatically adjusting the phase plane weights in unstable regions is as follows:

[0033]

[0034] in, The distance to reach the lower boundary of stability, This indicates that the state point is above the lower boundary. is the distance between the two stable boundaries. is the distance between the two stable boundaries.

[0035] As a further limitation of the technical solution of the application, the formula for real-time calculation of the distribution of the additional yaw moment through the self-adaptive weight coefficient is as follows:

[0036]

[0037] wherein, is the working radius of the tire; is the driving torque respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the total driving torque to achieve the target speed;

[0038]

[0039] wherein, is the left distribution coefficient, is the right distribution coefficient;

[0040] solving with the minimum tire slip and the minimum working load as the objective function and parameters; wherein the summation weight is ;

[0041]

[0042] wherein, is the road adhesion coefficient, is the longitudinal slip rate respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the longitudinal force of the wheel; is the lateral force of the wheel; is the tire load of the wheel perpendicular to the ground.

[0043] In a second aspect, the technical solution of the application provides a lateral path tracking device based on weight coefficient adaptation, which comprises a first processing and calculation module, a feedback error elimination module, a second processing and calculation module, a weight self-adaptive adjustment module, and a torque distribution module.

[0044] The first processing and calculation module is used to calculate the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller.

[0045] The feedback error elimination module is used to eliminate feedback error by calculating the control variable through feedforward control.

[0046] The second processing and calculation module is used to design a stability compensation controller for the additional torque using an improved sliding mode control algorithm, and to calculate the additional yaw moment for compensation of the total driving torque.

[0047] The weight adaptive adjustment module is used to determine the current stability state by using the phase plane diagram of the centroid sideslip angle and yaw rate, and automatically adjust the weights of the phase plane based on the determination of the stability state.

[0048] The torque distribution module is used to calculate the distribution of additional yaw torque in real time using adaptively adjusted weighting coefficients.

[0049] 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 rate and the center-of-gravity sideslip rate based on the vehicle dynamics model.

[0050] Among them, the vehicle dynamics model:

[0051]

[0052]

[0053] In the formula, For the overall vehicle weight; For lateral velocity; Longitudinal velocity; For the first The longitudinal force of each wheel; For the first Lateral force on each wheel; These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. This refers to the front wheel steering angle; It is the moment of inertia; It is the horizontal swing angle; This is the distance from the center of gravity to the front wheel; This is the distance from the center of gravity to the rear wheel; This refers to the front wheel track. This refers to the rear wheel track. To add yaw moment.

[0054] As a further limitation of the technical solution of the present invention, the formulas for calculating the yaw rate and the sideslip rate of the center of gravity based on the vehicle dynamics model in the preprocessing module are as follows:

[0055]

[0056] In the formula, For the first Side stiffness of each wheel These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. .

[0057] 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:

[0058]

[0059] In the formula, , It is the coefficient matrix of feedback control; for Wheel lateral stiffness, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0060] As a further limitation of the technical solution of the present invention, a stability compensation controller for additional torque is designed using an improved sliding mode control algorithm, and the calculation formula for the additional yaw moment used for compensation of the total driving torque is as follows:

[0061]

[0062]

[0063] In the formula, is a positive parameter of the saturation function. It is the centroid sideslip angle; The angular velocity of the center of mass deflection. For the ideal centroid sideslip angular velocity, For the first The lateral stiffness of each wheel, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. These are calibration coefficients.

[0064] As a further limitation of the technical solution of the present invention, the stability boundary is described as follows:

[0065]

[0066] It is the centroid sideslip angle; The angular velocity of the center of mass deflection; and All of these are boundary coefficients for stability assessment, determined by the road surface adhesion coefficient; For system disturbance;

[0067] The formula for automatically adjusting the phase plane weights in unstable regions is as follows:

[0068]

[0069] in, The distance to reach the lower boundary of stability, represents that the state point is above the lower boundary, represents that the state point is below the lower boundary; represents the distance between the two stable boundaries.

[0070] As a further limitation of the technical solution of the application, the formula for real-time calculation of the distribution of the additional yaw moment through the self-adaptive weight coefficient is as follows:

[0071]

[0072] wherein, is the working radius of the tire; is the driving torque respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the total driving torque to achieve the target vehicle speed;

[0073]

[0074] wherein, is the left side distribution coefficient, is the right side distribution coefficient;

[0075] solving with the minimum tire slip and the minimum working load as the objective function and parameters; wherein the summation weight is ;

[0076]

[0077] wherein, is the road adhesion coefficient, is the longitudinal slip rate respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the longitudinal force of the wheel; is the lateral force of the wheel; is the tire load of the wheel perpendicular to the ground.

[0078] In a third aspect, the technical solution of the application further provides an electronic device, which comprises at least one processor and a memory in communication connection with 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 to enable the at least one processor to execute the weight coefficient adaptive lateral path tracking method as described in the first aspect.

[0079] In a fourth aspect, the present application provides a non-transitory computer readable storage medium storing computer instructions, which cause the computer to execute the lateral path tracking method based on adaptive weight coefficients according to the first aspect.

[0080] From the above technical solutions, the present application has the following advantages: the front wheel steering angle is calculated by a linear quadratic regulator algorithm in an upper controller, and the error problem of the steering trajectory tracking is solved by feedforward control. An improved sliding mode control algorithm is used to design a stability compensation controller of additional torque. The current stability state is determined by a phase plane of the center of mass side slip angle and the yaw rate, and the weight ratio of the phase plane is automatically adjusted to calculate the additional torque, so as to ensure the lateral stability of the vehicle.

[0081] In addition, the present application has reliable design principles, simple structure, and very wide application prospects. BRIEF DESCRIPTION OF DRAWINGS

[0082] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, for those of ordinary skill in the art, other drawings can also be obtained without creative labor based on these drawings.

[0083] Figure 1 is a schematic flow chart of the method of an embodiment of the present application.

[0084] Figure 2 is a vehicle model diagram.

[0085] Figure 3 is a schematic block diagram of the device of an embodiment of the present application. DETAILED DESCRIPTION

[0086] In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should be within the scope of protection of the present application.

[0087] As shown in Figure 1 , the present application provides a lateral path tracking method based on adaptive weight coefficients, including the following steps:

[0088] Step 1: calculate the front wheel steering angle by a linear quadratic regulator algorithm in an upper controller;

[0089] Step 2: Eliminate feedback error by calculating control variable through feedforward control;

[0090] Step 3: Design a stability compensation controller of additional torque by using improved sliding mode control algorithm, and calculate additional yaw moment for compensation of total driving torque;

[0091] Step 4: Determine the current stability state through the phase plane of the center of mass side slip angle and yaw rate, and automatically adjust the weight of the phase plane based on the determination result of the stability state;

[0092] Step 5: Real-time calculate the distribution of additional yaw torque through the self-adaptive weight coefficient.

[0093] It should be noted that the step of calculating the front wheel steering angle through the linear quadratic regulation algorithm in the upper controller includes:

[0094] Establish a vehicle dynamics model;

[0095] Calculate the yaw rate and center of mass side slip angle based on the vehicle dynamics model.

[0096] The vehicle model is shown in the following figure: Figure 2 The vehicle dynamics model is as follows:

[0097]

[0098]

[0099] In the formula, is the total mass of the vehicle; is the lateral velocity; is the longitudinal velocity; is the longitudinal force of the i-th wheel; is the lateral force of the i-th wheel; respectively represent the left front wheel, the right front wheel, the left rear wheel and the 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. Assuming that the tire works in the linear characteristic region and ignoring the influence of driving force on yaw motion, the longitudinal force can be expressed as:

[0100]

[0101] ​​

[0102] wherein, the side slip angle of the first wheel, is the side slip stiffness of the first wheel.

[0103]

[0104] Since the front wheel steering angle is very small, it is assumed to be 0, = 1, the calculation can be obtained:

[0105]

[0106] wherein, is the side slip stiffness of the first wheel respectively represents the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; .

[0107] In some embodiments, a path tracking algorithm based on LQR is built.

[0108]

[0109] wherein,

[0110]

[0111]

[0112]

[0113] is the lateral deviation, i.e. the distance between the ideal position and the actual position of the vehicle, is the lateral deviation rate of change, is the ideal yaw rate.

[0114]

[0115]

[0116]

[0117] The control variable is solved by using the controller, and the objective function is set as:

[0118]

[0119] wherein, is the state error, For the control variable error in the feedback module. The larger, the state variable The faster the decay. The larger, the control variable Decreases. The optimal control can be expressed as:

[0120]

[0121] Wherein, is the coefficient matrix of feedback control, is a constant matrix.

[0122] To eliminate feedback error, it can be calculated:

[0123]

[0124] Wherein, the formula for calculating the front wheel steering angle by the linear quadratic regulator algorithm in the upper controller is as follows:

[0125]

[0126] In the formula, , is the coefficient matrix of feedback control; Respectively represent the left front wheel, the right front wheel, the left rear wheel, the right rear wheel;

[0127] In some embodiments, a stability compensator is established. By using the sliding mode theory, the lateral stability is determined by the yaw rate and the center of mass side slip angle, and the error expression is as follows:

[0128] First, the lateral stability is described based on the yaw rate and the center of mass side slip angle, and the comprehensive error is:

[0129]

[0130] Wherein, is the comprehensive error, is the yaw rate error, the center of mass side slip angle error, is the weight coefficient.

[0131] The sliding mode surface function can be expressed as:

[0132]

[0133] is the calibration coefficient, The larger, the shorter the time to reach a stable state, and too large will produce jitter. The optimal value can be obtained by testing.

[0134] The calculation can be obtained:

[0135]

[0136] Differentiation yields:

[0137]

[0138] Using a saturation function as the convergence law can reduce system jitter, that is:

[0139]

[0140]

[0141] in, is a positive parameter of the saturation function. This is the ideal sideslip angle.

[0142] The additional yaw moment can be calculated using the above formula:

[0143]

[0144] In the formula, is a positive parameter of the saturation function. It is the centroid sideslip angle; The angular velocity of the center of mass deflection. For the ideal centroid sideslip angular velocity, For the first The lateral stiffness of each wheel, These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. For calibration coefficients, This is the expression for the rate of convergence.

[0145] In some embodiments, the stability weighting coefficient is adaptively adjusted. Stability weighting coefficient Dynamic adjustments are needed based on the steady-state condition for sliding mode plane stability analysis. When the stability is good, The smaller the value, the more the torque is used for longitudinal following. When stability is poor, The larger the value, the more concentrated the torque becomes in the lateral stability region. The stability boundary is the boundary between the stable and unstable regions. In the process of determining the current stability state using a phase plane diagram of the center of mass sideslip angle and yaw rate, and automatically adjusting the phase plane weights based on the stability state determination, the stability boundary is described as follows:

[0146]

[0147] It is the centroid sideslip angle; The angular velocity of the center of mass deflection; and All of these are boundary coefficients for stability assessment, determined by the road surface adhesion coefficient; For system disturbance;

[0148] The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0149]

[0150] Wherein, is the distance to the lower boundary of stability, represents that the state point is above the lower boundary, is the state point below the lower boundary; is the distance between the two stable boundaries.

[0151] In some embodiments, the torque is distributed. The distribution of additional yaw moment is increased to maintain lateral stability.

[0152]

[0153] Wherein, is the working radius of the tire; is the driving torque respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the total driving torque to reach the target speed;

[0154]

[0155] Wherein, is the left distribution coefficient, is the right distribution coefficient;

[0156] The minimum tire slip and the minimum working load are taken as the objective function; wherein the summation weight is ;

[0157]

[0158] Wherein, is the road adhesion coefficient, is the longitudinal slip rate respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the longitudinal force of the th wheel; is the lateral force of the th wheel; is the inertia of the th wheel. The present application mainly aims at the method for controlling lateral stability, which determines the stability through the sliding mode control theory, and calculates the additional yaw torque in real time through adaptive adjustment of the weight coefficient, thereby improving the control stability.

[0159] Figure 3As shown, this embodiment of the invention provides a lateral path tracking device based on adaptive weight coefficients, 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;

[0160] The first processing and calculation module is used to calculate the front wheel steering angle using the linear quadratic adjustment algorithm in the upper controller;

[0161] The feedback error elimination module is used to eliminate feedback error by calculating the control variables through feedforward control;

[0162] The second processing and calculation module is used to design a stability compensation controller for the additional torque using an improved sliding mode control algorithm, and to calculate the additional yaw moment for compensation of the total driving torque.

[0163] The weight adaptive adjustment module is used to determine the current stability state by using the phase plane diagram of the centroid sideslip angle and yaw rate, and automatically adjust the weights of the phase plane based on the determination of the stability state.

[0164] The torque distribution module is used to calculate the distribution of additional yaw torque in real time using adaptively adjusted weighting coefficients.

[0165] The device also includes a preprocessing module for establishing a vehicle dynamics model; and for calculating the yaw rate and the center-of-gravity sideslip rate based on the vehicle dynamics model.

[0166] Among them, the vehicle dynamics model:

[0167]

[0168]

[0169] In the formula, For the overall vehicle weight; For lateral velocity; Longitudinal velocity; For the first The longitudinal force of each wheel; For the first Lateral force on each wheel; These represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively. This refers to the front wheel steering angle; It is the moment of inertia; It is the horizontal swing angle; This is the distance from the center of gravity to the front wheel; This is the distance from the center of gravity to the rear wheel; This refers to the front wheel track. This refers to the rear wheel track. To add yaw moment.

[0170] The formula for calculating the yaw rate and the mass side slip angle velocity based on the vehicle dynamics model in the pre-processing module is as follows:

[0171]

[0172] In the formula, is the side slip stiffness of the LFR, RFR, LRR, RRR respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; .

[0173] In some embodiments, the formula for calculating the front wheel steering angle by the linear quadratic regulator algorithm in the upper controller is as follows:

[0174]

[0175] In the formula, is the coefficient matrix of feedback control; LFR, RFR, LRR, RRR respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel;

[0176] In some embodiments, the stability compensation controller for the additional yaw moment used for the compensation of the total driving torque is designed by using the improved sliding mode control algorithm, and the calculation formula of the additional yaw moment is as follows:

[0177]

[0178]

[0179] In the formula, is the positive parameter of the saturation function, is the mass side slip angle; is the mass side slip angle velocity, is the ideal mass side slip angle velocity, is the side slip stiffness of the LFR, RFR, LRR, RRR respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, is the calibration coefficient.

[0180] In some embodiments, the stability boundary is described as:

[0181]

[0182] is the mass side slip angle; is the mass side slip angle velocity; and are both stability judgment boundary coefficients, which are determined by the road adhesion coefficient; is the system disturbance;

[0183] ​​The formula for automatically adjusting the weight of the phase plane in the unstable region is as follows:

[0184]

[0185] wherein, is the distance to the lower boundary of stability, represents that the state point is above the lower boundary, is the state point below the lower boundary; is the distance between the two stable boundaries.

[0186] In some embodiments, the formula for calculating the distribution of additional yaw moment in real time by the self-adaptive adjusted weight coefficient is as follows:

[0187]

[0188] wherein, is the working radius of the tire; is the driving torque respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; is the total driving torque to reach the target speed;

[0189]

[0190] wherein, is the left side distribution coefficient, is the right side distribution coefficient;

[0191] Solve with the minimum tire slip and the minimum working load as the objective function and parameters; wherein the summation weight is ;

[0192]

[0193] wherein, is the road adhesion coefficient, is the longitudinal slip rate respectively represent the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel; the side slip angle of the wheel; the longitudinal force of the wheel; the lateral force of the wheel; the tire load of the wheel perpendicular to the ground.

[0194] The electronic device provided by the embodiment of the present application comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication 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: calculating a front wheel steering angle through a linear quadratic regulation algorithm in an upper controller; step 2: calculating a control variable to eliminate feedback error through feedforward control; step 3: designing a stability compensation controller of additional torque by using an improved sliding mode control algorithm, and calculating an additional yaw moment for compensation of total driving torque; step 4: judging a current stability state through a phase plane of a center of mass side slip angle and a yaw angular velocity, and automatically adjusting a weight of the phase plane based on a judgment result of the stability state; and step 5: calculating a distribution of the additional yaw torque in real time through the weight coefficient adjusted adaptively.

[0195] In addition, the logic instructions in the memory described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0196] The embodiment of the present application provides a non-transitory computer readable storage medium, which stores computer instructions, and the computer instructions make a computer execute the method provided by the method embodiment described above, for example, including: step 1: calculating a front wheel steering angle through a linear quadratic regulation algorithm in an upper controller; step 2: calculating a control variable to eliminate feedback error through feedforward control; step 3: designing a stability compensation controller of additional torque by using an improved sliding mode control algorithm, and calculating an additional yaw moment for compensation of total driving torque; step 4: judging a current stability state through a phase plane of a center of mass side slip angle and a yaw angular velocity, and automatically adjusting a weight of the phase plane based on a judgment result of the stability state; and step 5: calculating a distribution of the additional yaw torque in real time through the weight coefficient adjusted adaptively.

[0197] It should be understood that the size of the serial number of each step in the above embodiments does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0198] The embodiments of the device for tracking lateral path based on adaptive weight coefficient provided by the embodiments of the present application belong to the same inventive concept as the above-mentioned embodiments of the method for tracking lateral path based on adaptive weight coefficient, and the details not described in the embodiments of the device for tracking lateral path based on adaptive weight coefficient can be referred to the above-mentioned embodiments of the method for tracking lateral path based on adaptive weight coefficient.

[0199] Although the present application has been described in detail through reference to preferred embodiments, it should be understood that the present application is not limited to those embodiments. Various equivalents or alternatives to those embodiments which are within the scope of the present application are possible and are encompassed by the present application. Any suitable changes or modifications that are made to the present application are to be considered as being within the scope of the present application.

Claims

1. A lateral path tracking method based on weight coefficient adaptation, characterized by, The method comprises the following steps: calculating the front wheel steering angle through a linear quadratic regulation algorithm in the upper controller; calculating the control variable through feedforward control to eliminate feedback error; designing a stability compensation controller for additional torque by using an improved sliding mode control algorithm to calculate additional yaw moment for compensation of total driving torque; judging the current stability state through a phase plane of the center of mass side slip angle and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state; calculating the distribution of the additional yaw torque through the weight coefficient adjusted adaptively; the formula for calculating the front wheel steering angle through a linear quadratic regulation algorithm in the upper controller is as follows: In the formula, , ; is cornering stiffness of the vehicle wheels, respectively represent the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; in the step of designing a stability compensation controller for additional torque by using an improved sliding mode control algorithm to calculate additional yaw moment for compensation of total driving torque, the calculation formula is as follows: wherein is a positive parameter for a saturation function, is a side slip angle of the center of mass; is a side slip angular velocity of the center of mass, is an ideal side slip angular velocity of the center of mass, is a side slip stiffness of the wheel, respectively represent a front left wheel, a front right wheel, a rear left wheel, a rear right wheel, is a calibration coefficient; in the step of judging the current stability state through a phase plane of the center of mass side slip angle and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state, the stable boundary is described as: is a center of mass side slip angle; is a center of mass side slip angular velocity; and are stability determination boundary coefficients determined by a road surface adhesion coefficient; is a system disturbance; the formula for automatically adjusting the weight of the phase plane in the unstable area is as follows: wherein, is the distance to the lower stability boundary, denotes that the state point is above the lower boundary, is the distance to the lower boundary; is the distance between the two stability boundaries.

2. The lateral path tracking method based on weight coefficients adaptation according to claim 1, characterized in that, before the step of calculating the front wheel steering angle through a linear quadratic regulation algorithm in the upper controller, the following steps are included: establishing a vehicle dynamics model; calculating the yaw rate and the center of mass side slip angle speed based on the vehicle dynamics model; the vehicle dynamics model is as follows: wherein is the total vehicle mass; is the lateral velocity; is the longitudinal velocity; is the longitudinal force of the i-th wheel; is the longitudinal force of the i-th wheel; is the lateral force of the i-th wheel; is the lateral force of the i-th wheel; respectively represent the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; is the front wheel steering angle; is the moment of inertia; is the yaw angle; is the yaw angular velocity; is the distance from the center of mass to the front wheel; is the yaw angular acceleration; 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 coefficients adaptation according to claim 2, characterized in that, in the step of calculating the yaw rate and the center of mass side slip angle speed based on the vehicle dynamics model, the formula is as follows: In the formula, It is the centroid sideslip angle; The angular velocity of the center of mass deflection; This refers to the yaw rate; For the first The lateral stiffness of each wheel, i=1,2,3,4 represent the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively; .

4. The lateral path tracking method based on weight coefficient adaptation according to claim 1, characterized in that, the formula for calculating the distribution of the additional yaw torque in real time through the weight coefficient adjusted adaptively is as follows: wherein, is the tire working radius; is the driving torque respectively represent the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; is the total driving torque to reach the target vehicle speed; wherein is a left side allocation coefficient, is a right side allocation coefficient; Solve for minimum tire slip and minimum work load as objective functions and parameters; where the summation weight is ; wherein, is the road adhesion coefficient, is the longitudinal slip ratio respectively denote the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; the side slip angle of the wheel; the longitudinal force of the wheel; the lateral force of the wheel; is the tire load of the i-th wheel normal to the ground.

5. A lateral path tracking device based on weight coefficient adaptation, characterized by, the method comprises a first processing calculation module, a feedback error elimination module, a second processing calculation module, a weight adaptive adjustment module and a torque distribution module; the first processing calculation module is used for calculating the front wheel steering angle through a linear quadratic regulation algorithm in the upper controller; the feedback error elimination module is used for calculating the control variable through feedforward control to eliminate feedback error; the second processing calculation module is used for designing a stability compensation controller for additional torque by using an improved sliding mode control algorithm to calculate additional yaw moment for compensation of total driving torque; the weight adaptive adjustment module is used for judging the current stability state through a phase plane of the center of mass side slip angle and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state; the torque distribution module is used for calculating the distribution of the additional yaw torque in real time through the weight coefficient adjusted adaptively; the formula for calculating the front wheel steering angle through a linear quadratic regulation algorithm in the upper controller is as follows: In the formula, , ; is cornering stiffness of the vehicle wheels, respectively represent the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; in the step of designing a stability compensation controller for additional torque by using an improved sliding mode control algorithm to calculate additional yaw moment for compensation of total driving torque, the calculation formula is as follows: wherein is a positive parameter for a saturation function, is a side slip angle of the center of mass; is a side slip angle velocity of the center of mass, is an ideal side slip angle velocity of the center of mass, is a side slip stiffness of the wheel, respectively denote a front left wheel, a front right wheel, a rear left wheel, a rear right wheel, is a calibration coefficient; in the step of judging the current stability state through a phase plane of the center of mass side slip angle and the yaw rate, and automatically adjusting the weight of the phase plane based on the judgment result of the stability state, the stable boundary is described as: is a center of mass side slip angle; is a center of mass side slip angular velocity; and are stability judgment boundary coefficients determined by a road surface adhesion coefficient; is a system disturbance; the formula for automatically adjusting the weight of the phase plane in the unstable area is as follows: wherein, is the distance to the lower stability boundary, denotes that the state point is above the lower boundary, is the distance to the lower stability boundary; is the distance between the two stability boundaries.

6. An electronic device, comprising: The electronic device comprises at least one processor; and a memory connected with the at least one processor in communication; 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 to enable the at least one processor to perform the lateral path tracking method based on the weight coefficient adaptation according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium, comprising: The non-transitory computer readable storage medium stores computer instructions, and the computer instructions enable the computer to perform the lateral path tracking method based on the weight coefficient adaptation according to any one of claims 1 to 4.

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