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CN-122009217-A - Vehicle obstacle avoidance control method, control equipment and vehicle for fusing stability boundaries under transverse and longitudinal coupling working conditions

CN122009217ACN 122009217 ACN122009217 ACN 122009217ACN-122009217-A

Abstract

The invention discloses a vehicle obstacle avoidance control method, control equipment and a vehicle for fusing stability boundaries under a transverse and longitudinal coupling working condition. Secondly, taking an improved model prediction path integration algorithm as a core, accumulating the control sequences in the tire transverse and longitudinal adhesion constraint through a cost function, and adjusting the lateral adhesion margin through braking torque to update the stable steering boundary. And finally, under dangerous working conditions, according to real-time vehicle state estimation, generating a preferable risk avoiding path by adopting steering-braking cooperative guidance, so that the vehicle can stably run within a limit operating range.

Inventors

  • LIN YONGFENG
  • YUAN CHAOCHUN
  • HE YOUGUO
  • CAI YINGFENG
  • WENG SHUOFENG
  • WANG TONG

Assignees

  • 江苏大学

Dates

Publication Date
20260512
Application Date
20260330

Claims (10)

  1. 1. A vehicle obstacle avoidance control method for fusing stability boundaries under transverse and longitudinal coupling conditions is characterized by comprising the following steps: Step 1, a five-degree-of-freedom nonlinear dynamics model of a front wheel steering vehicle is established, longitudinal braking and steering combined action working conditions are considered, longitudinal force and lateral force of a tire are calculated according to a classical magic formula, basic stress under pure longitudinal and lateral working conditions is corrected according to combined sliding working conditions, meanwhile, the resultant force provided by the ground to the tire is considered to be limited by a grounding friction limit, and finally the vehicle nonlinear model suitable for analyzing transverse and longitudinal coupling working conditions is obtained; Step 2, based on the Darling principle, counteracting an inertia item generated by vehicle braking by introducing an equivalent virtual longitudinal force, enabling a vehicle nonlinear dynamics model under a braking-steering coupling working condition to be equivalent to a quasi-steady autonomous system at any instant speed, then solving stable points of the system based on a bifurcation analysis method to obtain a balance point set of vehicle braking and steering parameters at different speeds, and extracting a stability boundary point set based on the feature value change of a jacobian matrix, namely a critical point set; Step 3, selecting a cubic polynomial function to fit a discrete stability boundary point set to the braking moment Steering angle of front wheel And the speed of the vehicle Is provided with a three-dimensional boundary surface, obtaining a stable boundary surface; Step 4, constructing a control algorithm based on the improved model prediction path integral, fusing the established stable domain boundary surface, and determining the current vehicle speed And braking demand Lower allowable front wheel rotation angle upper limit And guiding the braking action by utilizing the boundary of the stable domain, acquiring a large steering margin, and finally realizing the optimal control sequence decision in obstacle avoidance.
  2. 2. The vehicle obstacle avoidance control method according to claim 1, wherein in the step 1, the five-degree-of-freedom nonlinear dynamics model of the vehicle is as shown in formula (1): Wherein, the whole car quality The longitudinal and transverse forces of the tyre are , Representing the front and rear axles, respectively, the longitudinal speed Lateral velocity of Front wheel steering angle Longitudinal and transverse component of air resistance Yaw rate Yaw acceleration Yaw inertia of vehicle The wheelbase from the center of mass of the vehicle to the front and rear axles is respectively The equivalent moment of inertia of the front wheel and the rear wheel is The rotation speed of the front and rear wheels is The braking forces of the front axle and the rear axle of the vehicle are respectively The total braking force is Equivalent radius of wheel 。
  3. 3. The vehicle obstacle avoidance control method of claim 2 wherein in step 1, the base tire longitudinal and lateral forces are corrected under combined slip conditions by: Wherein, the Representing a tire force mixture slip condition correction function, And The pure sliding tire force calculated by the pure sliding magic formula, The coefficient is corrected for the tire force mixture slip condition, And Representing slip angle and slip ratio of different wheels, Representing the front wheel and the rear wheel respectively, and can be calculated by the following formula: 。
  4. 4. the vehicle obstacle avoidance control method of claim 3 wherein in step 1, the resultant force provided by the ground to the tire is expressed as being constrained by the ground friction limit Is the road adhesion coefficient.
  5. 5. The vehicle obstacle avoidance control method of claim 4 wherein the autonomous system of step 2 is embodied as follows: Defining a state vector At a given parameter vector = Down-force introduction virtual force The virtual force is required to satisfy the longitudinal acceleration constraint At this time, the equilibrium solution of the equivalent autonomous system is defined by constraint equations And (3) determining: By back-pushing the longitudinal dynamics equation of the vehicle, the virtual acceleration required by maintaining equivalent constraint is obtained : Balance point stability is determined by jacobian eigenvalues of the linearization system: Jacobian matrix Maximum real part of (2) The equilibrium point is asymptotically stable if there is Destabilization occurs; Is a boundary situation.
  6. 6. The vehicle obstacle avoidance control method of claim 5 wherein the balance point solution is as follows: Step 2.1 building a dynamically scaled trust region In the process of solving the vehicle equilibrium state, the core is to search the solution of state quantity about parameter items through a nonlinear equation set, so as to construct a dynamically scaled trust domain sub-problem: wherein D is a diagonal scaling matrix for adjusting the influence of different physical quantity magnitude differences in a state space on convergence by updating the reliability region radius in real time in an iteration step Robustness of aggressiveness and convergence of the self-adaptive balance calculation step length when the second-order model If the fitting degree with the actual nonlinear model is high, the step length is increased to accelerate convergence, otherwise, the trust domain is contracted to ensure that the evolution of the solution is always positioned in the safe area; step 2.2 constructing a reflection mapping mechanism of the boundary neighborhood Introducing a reflection mapping mechanism aiming at a bounded constraint space formed by the tire attachment limit, constructing a trust zone sub-problem with physical constraint in each iteration, and carrying out reflection processing on a search vector according to the gradient direction of the boundary when the algorithm search direction tries to cross the physical boundary defined by tire force saturation; Step 2.3, formulating a hot start strategy for fusing bifurcation path continuity In order to improve the calculation efficiency of traversing in a large-range parameter space, a hot start iteration logic based on a bifurcation theory is introduced, wherein when parameter step iteration is carried out, a solver does not adopt a random initial value, but directly uses a balanced solution state vector obtained by convergence of a parameter step k-1 as an initial guess value of the parameter step k, meanwhile, an attraction domain locking strategy is introduced, and the search process of the solver is strictly limited in an attraction domain of a stable branch by utilizing the continuous evolution characteristic of a nonlinear system solution.
  7. 7. The vehicle obstacle avoidance control method of claim 6 wherein the stable boundary surface constructed by the cubic polynomial in step 3 is as follows: 。
  8. 8. The vehicle obstacle avoidance control method of claim 7 wherein the improved model predictive path integration algorithm of step 4 is as follows: Defining system state vectors And controlling the input vector : In the formula, The position of the vehicle under an inertial coordinate system; The model prediction path integration algorithm comprises a variational control sequence sampling process and a weight iteration process based on free energy minimization, wherein the variational control sequence sampling process is to superimpose Gaussian noise following multivariate normal distribution on the basis of a current control sequence Generating within a control space Candidate control paths: ,k=1,2,...,K The weight iterative process based on free energy minimization utilizes an exponential weighting update law to deduce the generated accumulated cost under a dynamic model according to each sampling track Assigning weights : Wherein, the Is a temperature parameter; Is the minimum cost among all samples; Finally, probability fusion is carried out on the sampling sequence to generate an optimal control increment capable of avoiding local minimum value points, and the updating control sequence is as follows: constructing cost function based on the boundary surface of the stable operating domain of the vehicle under the coupling of steering and braking and considering the variation of the stable operating domain of the vehicle along with the speed and the braking moment Determining a vehicle stability angle constraint: Constructing stability margin penalties : Wherein, the Weight coefficients for a stability margin penalty function; P is the punishment growth rate when controlling the approach boundary; in order to obtain the maximum steering space of the vehicle in the obstacle avoidance process, firstly, solving the braking moment which makes the allowable rotation angle maximum on a discrete speed set And maximum rotation angle Current steering demand Mapping to braking target : Wherein, the Braking proportional coefficient corresponding to steering requirement; construction of a brake guiding cost function The driving system achieves the control objective: Wherein, the The weight coefficient of the brake guide item; Is the current braking moment; For maximum braking torque of the vehicle, the guiding item makes the braking tend to be near the most point of the stable domain when the steering requirement is large, so that reasonable braking is exchanged for steering margin; to ensure the stability of the vehicle control, the cost function also comprises a global control smooth term : Wherein, the Smooth control coefficients of the steering system and the braking system, respectively; Finally, constructing a comprehensive objective function: 。
  9. 9. a control apparatus, wherein the vehicle obstacle avoidance control method of claim 1 is deployed in the control apparatus.
  10. 10. A vehicle capable of performing the vehicle obstacle avoidance control method of claim 1 to achieve obstacle avoidance.

Description

Vehicle obstacle avoidance control method, control equipment and vehicle for fusing stability boundaries under transverse and longitudinal coupling working conditions Technical Field The invention relates to a vehicle obstacle avoidance control method fusing stability boundaries under a transverse-longitudinal coupling working condition, and belongs to the field of vehicle safety active control. Background The driving safety of vehicles is a long-term concern in the automotive field, and the collision avoidance control under dangerous working conditions is particularly critical. When the front is suddenly dangerous, the braking and the steering often happen simultaneously, and the vehicle mobility is limited by longitudinal force-lateral force coupling and road surface attachment conditions. Active safety system intervention should avoid introducing new risks such as rollover, tail flicking, departure from road safety boundaries, or increased occupant injury. The existing research is explored from the aspects of bifurcation analysis, nonlinear model predictive control algorithm (nonlinear MPC), potential field method and the like, such as utilizing bifurcation and prolongation analysis to perform instability mechanism under transverse and longitudinal combined acceleration, unifying motion re-planning, path tracking and stability constraint to a nonlinear MPC framework, constructing potential field functions capable of adapting to road and obstacle shapes and the like. However, the existing method does not explicitly describe the brake-steering coupling stable steering boundary when the transverse and longitudinal accelerations exist at the same time, and lacks an explicit safety boundary expression which can be used for on-line fast decision. Therefore, it is necessary to study the stable steering boundary of the vehicle under the transverse and longitudinal coupling condition and define the physical/dynamic limitation thereof so as to improve the active safety control performance and effect in dangerous situations. Disclosure of Invention Aiming at the problems, the invention provides a vehicle local path planning and obstacle avoidance control method based on an improved Model Predictive Path Integral (MPPI) algorithm, which is used for collision avoidance control under a horizontal-longitudinal coupling dangerous working condition. The method is based on tire attachment constraint, and longitudinal force and lateral force are distributed in a coordinated mode so as to improve controllability and stability under limit working conditions. When the steering and braking are combined, the controller calls a pre-obtained control stability boundary and determines a feasible control range according to the information such as the vehicle speed and the obstacle position. And the controller calculates the accumulated cost in the sampling period under the dynamic model, then performs weight normalization and probability fusion on the sampling sequence, outputs the optimal control increment for collision avoidance, and realizes the optimal collision avoidance control sequence decision. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: a vehicle local path planning and obstacle avoidance control method based on an improved model predictive path integral algorithm. Firstly, a front wheel steering vehicle five-degree-of-freedom nonlinear dynamics model considering wheel movement is established, and a tire magic formula for combined slip correction is introduced in tire force calculation so as to represent vehicle movement under a transverse-longitudinal coupling working condition. And secondly, introducing equivalent virtual longitudinal force based on the Dalangbeil principle, and enabling the nonlinear system to be equivalent to a quasi-steady autonomous system capable of carrying out static bifurcation analysis at any instantaneous speed. And thirdly, converting the dynamic braking process into a quasi-static balance point searching problem by utilizing a fused trust domain reflection algorithm, and defining a vehicle operation stability boundary according to the dynamic braking process. And then, fitting the discrete boundary points by adopting a cubic polynomial to obtain an explicit boundary function of braking torque, front wheel rotation angle and vehicle speed. Finally, a control framework based on the improvement MPPI is constructed, and the front wheel rotation angle and the braking torque control quantity are determined by taking the boundary as a constraint. The method comprises the following steps: Step 1, a five-degree-of-freedom nonlinear dynamics model of a front wheel steering vehicle is built by considering wheel movement, longitudinal force and lateral force of a tire are calculated by a classical magic formula under the working conditions of longitudinal braking and steering combined action, and then basic stress under the working conditions of pure