274 results about "Slip angle" patented technology

The invention discloses a vehicle state estimation method based on adaptive strong tracking extended Kalman filtering. The method comprises the following steps: constructing a nonlinear three-degree-of-freedom dynamic model containing a state equation and an observation equation based on an extended Kalman filtering algorithm to describe longitudinal, lateral and yaw states of a vehicle; state variables of the state equation are a side slip angle, a yaw velocity and a longitudinal vehicle speed; constructing a time-varying measurement noise statistical estimator based on a Sage-Husa algorithm to adaptively correct a measurement noise covariance matrix in the extended Kalman filtering algorithm; state prediction is carried out on the vehicle through the state equation, and a state prediction covariance matrix is calculated; and calculating the ratio of the sum of quadratic terms of the information sequence to the trace of the variance matrix of the information sequence based on an extended Kalman filtering algorithm, and judging whether filtering is really divergent or not. According to the method, the state quantity which is difficult to measure in the vehicle driving process is estimated in real time by establishing an adaptive strong tracking extended Kalman filter, and the vehicle state is accurately estimated.

The invention discloses a chassis coordination control method and system based on tire side deviation state evaluation, and relates to the technical field of four-wheel steering four-wheel drive vehicle dynamics control. The method comprises the steps that an expected front wheel rotation angle is determined based on an expected steering wheel rotation angle input by a driver, and a front wheel rotation angle is determined; further determining a feed-forward front wheel steering angle, a feed-forward rear wheel steering angle and an additional yaw moment based on feed-forward control and feedback control, determining a first tire slip angle and a second tire slip angle based on a road adhesion coefficient, and further determining a wheel torque control weight, a feedback front wheel steering angle control weight and a feedback rear wheel steering angle control weight; and further determining a driving yaw moment, a feedback front wheel steering angle and a feedback rear wheel steering angle, determining a total longitudinal force based on an expected longitudinal acceleration input by a driver, and performing four-wheel torque distribution based on the total longitudinal force and the driving yaw moment to obtain a four-wheel driving torque. The driving stability of the vehicle under the limiting working condition can be improved.

The invention discloses a vehicle instability active compensation method based on an angle module and related equipment, and the method comprises the steps: responding to a received steering instruction for a target vehicle, and determining a target yaw velocity and a target slip angle for the target vehicle according to the steering instruction; driving data and tire force constraint conditions of the target vehicle are obtained, and the tire force increment of the target wheel end of the target vehicle is determined according to the target yaw velocity, the target slip angle, the driving data and the tire force constraint conditions; wherein the tire force constraint condition is determined according to an adhesion coefficient estimation value of a road surface where the target vehicle is located; and controlling a target wheel end of the target vehicle to steer, brake or / and drive according to the tire force increment so as to correct a driving route of the target vehicle.

The invention discloses a tire longitudinal force and lateral force prediction method based on vehicle state parameter estimation, which adopts a seven-order spherical radius criterion to replace the original three-order spherical radial volume criterion on the basis of the traditional volume Kalman filter (CKF), and improves the estimation precision by optimizing sampling point distribution and weight configuration. And the stability of numerical calculation is ensured in combination with QR decomposition. A vehicle-mounted sensor is used for collecting real-time data such as a front wheel turning angle and longitudinal / lateral acceleration under a complex working condition, a time sequence feature set is built by combining longitudinal speed, lateral speed, a side slip angle and yaw velocity estimated by an algorithm, and meanwhile tire force calculated by a Dugoff tire model serves as target output. The TCN-GRU-based tire force prediction method is designed, the calculation complexity can be reduced while key time sequence information is kept, and the real-time prediction performance of the tire force is improved.

A computer-implemented method performed in a vehicle control unit for controlling motion of a heavy-duty vehicle. The method includes obtaining a vehicle motion request, wherein the vehicle motion request is indicative of a target curvature and a target acceleration, determining a motion support device, MSD, control allocation based on the vehicle motion request, determining a dynamic wheel slip angle limit based on the vehicle motion request, where dynamic wheel slip angle limit increases with a decreasing target acceleration, and controlling the motion of the heavy-duty vehicle based on the MSD control allocation constrained by the dynamic wheel slip angle limit.

The invention relates to the technical field of vehicle engineering, and discloses a vehicle transverse stability coordination control system based on sensing fusion, which comprises a main controller, a sensing fusion coprocessor and a transverse control coprocessor. The main controller calls and sends a stability control instruction according to the driving state; the sensing fusion coprocessor schedules a transverse control instruction in multi-source information fusion; the transverse control coprocessor analyzes the parameters to obtain basic control signals, dynamically monitors transverse acceleration, yaw velocity and tire slip angles, generates and outputs compensation signals through mode adjustment such as dynamic coordination function bypass selection and global or local parameter dynamic coordination, and controls an actuator after being fused with the basic signals. The system integrates a data fusion module, a state evaluation module and a multi-strategy dynamic adjustment module, multi-source information accurate fusion and multi-parameter cooperative control are achieved, the transverse stability and driving safety of the vehicle under the complex working condition are improved, and the method is suitable for the field of vehicle engineering control.

The invention belongs to the field of distributed driving automobile control, and discloses a distributed driving automobile path tracking and stability control optimization method and related equipment, and the method comprises the steps: firstly building a tire cornering stiffness dynamic range through multi-source sensing data, and reducing the influence of nonlinear characteristics on a model; then, through a dynamic output feedback model prediction control algorithm, an estimation state sequence and an error boundary of a vehicle side slip angle are calculated online, an optimal control gain is matched in real time based on a two-dimensional table, a combined control quantity of a four-wheel steering angle and an additional yawing moment is formed, and parameter uncertainty caused by vehicle speed change is effectively compensated; and finally, torque distribution is carried out by adopting a quadratic programming algorithm and taking tire utilization rate minimization as a target. According to the method, the vehicle path tracking precision and the transverse stability under the complex working condition are improved, meanwhile, the tire saturation risk is reduced, the tire utilization rate is reduced, the transverse tracking error is reduced, and unified optimization of safety and controllability in the automatic driving process is achieved.

The invention belongs to the field of vehicle stability control, and particularly relates to a control method suitable for integration of four-wheel independent drive and active rear wheel steering. Comprising the steps of establishing a whole vehicle dynamics model suitable for controller design, performing stable region division by combining front and rear wheel side slip angle phase planes, setting an ideal yaw velocity and an ideal side slip angle, designing a feedforward and PID feedback integrated controller, performing torque distribution and the like. According to steering wheel rotation angle input, corresponding parameters of the vehicle are combined, the vehicle stability coefficient, the ideal yaw velocity and the side slip angle are calculated, the feedforward and PID feedback integrated controller inputs the calculated rear wheel rotation angle into the controlled vehicle, the calculated additional yaw moment obtains the basic driving moment based on pedal information, and the vehicle stability coefficient, the ideal yaw velocity and the side slip angle are calculated. Torques corresponding to four wheels are input to a controlled vehicle through torque distribution, so that the purpose of integrated control is achieved, and the vehicle handling stability is improved.

The invention discloses a side slip angle fusion estimation method based on an intelligent automobile, relates to the technical field of state estimation and control of the intelligent automobile, and aims to solve the problem of how to ensure high precision and adapt to side slip angle estimation of different driving conditions when the intelligent automobile is under complex driving working conditions. The vehicle operation information acquisition module acquires motion state parameters of the vehicle in real time; the side slip angle estimation influence factor calculation module comprehensively considers multiple factors and quantifies various influence factors, so that the estimation model adapts to different driving working conditions; the side slip angle estimation execution module executes a plurality of estimation modes in parallel under different working conditions; the side slip angle fusion estimation module based on the genetic algorithm and the neural network optimizes the weight factor offline through the genetic algorithm, and the neural network predicts the weight factor of each estimation mode in real time according to the influence factor in the online reasoning stage. According to the method, accurate side slip angle estimation can be provided in real-time driving, and the driving stability of the intelligent automobile is enhanced.

The invention provides a vehicle stability control method, device and system and electronic equipment, relates to the technical field of vehicle active safety control, and aims to construct a control framework based on a two-degree-of-freedom dynamical model and realize accurate control of the yaw velocity and the side slip angle of a vehicle. By introducing the road adhesion coefficient and combining the vertical load of each wheel for independent torque distribution, the tire adhesion utilization rate and the environmental adaptability and safety of the vehicle under different road conditions (such as ice and snow, wet and slippery conditions and dry conditions) are improved. According to the scheme, calculation is easy and convenient, response is rapid, good engineering practicability is achieved, and the robustness and adaptability of the system under the complex working condition are enhanced while the vehicle stability and the path tracking capacity are improved.

The application discloses a kind of distributed drive electric vehicle stability control method and system, desired centroid side slip angle and yaw angular velocity are calculated as control target according to vehicle dynamics model, actual centroid side slip angle and yaw angular velocity are estimated in real time by Kalman filtering.Further through stability judging law, vehicle state is identified using phase plane method.According to vehicle state, it is divided into: stable domain, coordination domain and non-stable domain.Further control target value and actual value are input into model reference adaptive controller, and the size of additional yaw moment and front wheel angle is respectively solved.The weight size of the two is calculated by the vehicle stability region determined in stability law.Additional front wheel angle can be directly input into vehicle actuator, if direct torque control is needed, additional yaw moment size needs to be input into torque distribution module for real-time solution, and finally left and right wheel torque value of front axle is output to vehicle actuator.

The invention discloses a 15-degree-of-freedom whole vehicle dynamics modeling method for a steer-by-wire system, and the method comprises the steps: dividing a whole vehicle model into six dynamics modules: a vehicle body model, a nonlinear tire model, a suspension model, a wheel motion model, a motor model, and a steer-by-wire model; in addition, a tire slip angle and slip rate state quantity calculation module and a steer-by-wire control module are adopted, a whole vehicle dynamic model is established and comprises six degrees of freedom of longitudinal, lateral, yawing, pitching, tilting and vertical movement of a vehicle body, two degrees of freedom of rotation and vertical movement of four distributed wheels and one degree of freedom of vehicle steering, and the total number of the degrees of freedom is 15. The method designed by the invention is suitable for common vehicle driving conditions so as to research the control performance, the stability, the safety, the dynamic response and the characteristics of a steer-by-wire system of the vehicle and vehicle performance under different working conditions, and theoretical support is provided for optimization of future vehicle design and control strategies.

The present invention discloses a four-wheel steering control method for a distributed drive electric vehicle, which relates to the technical field of vehicle control. The front wheel steering angle δ is output by a driver model f , the throttle pedal opening α p , and the throttle pedal opening change rate Δα p . The ideal center-of-mass side slip angle β d and the ideal yaw angular velocity γ d are obtained through the two-degree-of-freedom dynamics equation of the front-wheel-steering vehicle. Then, based on the characteristics of the distributed drive torque vector control method and the rear-wheel active steering control method, and in combination with the actual center-of-mass side slip angle β and the actual yaw angular velocity γ of the vehicle, the vehicle target motion state tracking under different working conditions is carried out, and the additional yaw moment ΔM z and / or the rear wheel steering angle δ r are obtained. Finally, the coordinated control of the vehicle is realized through the four-wheel steering distributed drive vehicle model. While considering the control effect, the present invention takes into account the driving habits and driving needs of the driver to the greatest extent, not only improving the overall performance of the vehicle control system, but also ensuring the sensitivity, maneuverability and stability of the vehicle.

The invention provides a vehicle drifting control method, device and equipment, a computer readable storage medium and a computer program product. The method comprises the steps that based on target state information and actual state information of a vehicle, a first slip rate component and a second slip rate component are obtained, the first slip rate component is used for slip angle stability control, and the second slip rate component is used for yaw velocity control; determining a left rear wheel slip rate target and a right rear wheel slip rate target based on a basic slip rate target, the first slip rate component and the second slip rate component; and rotating speed calculation is conducted based on the actual state information, the left rear wheel slip rate target and the right rear wheel slip rate target, and the vehicle is controlled based on the obtained left rear wheel rotating speed target and the obtained right rear wheel rotating speed target. According to the invention, a driver can maintain stable drifting of the vehicle only by operating the steering wheel and the accelerator.

The invention discloses a vehicle kinetic parameter identification method based on constrained nonlinear optimization, which comprises the following steps: establishing a vehicle two-degree-of-freedom transverse kinetic model based on a small-slip-angle tire and a road cross slope, acquiring a vehicle historical driving data measurement value, acquiring a to-be-estimated vehicle kinetic parameter, and identifying the to-be-estimated vehicle kinetic parameter according to the to-be-estimated vehicle kinetic parameter. Constructing a constrained nonlinear optimization problem about the yaw velocity, solving to obtain an estimated value sequence of the kinetic parameters of the vehicle, carrying out statistics on the sequence, and taking a statistical median as a final estimated value; on one hand, a vehicle transverse dynamics model including a road cross slope is adopted; on the other hand, the constraint of vehicle parameters is considered, a nonlinear optimization problem is constructed, and the vehicle front axle distance (the longitudinal distance from a front axle to the vehicle mass center), the vehicle rear axle distance (the longitudinal distance from a rear axle to the vehicle mass center), the front wheel cornering stiffness, the rear wheel cornering stiffness and the vehicle total mass are identified at the same time.

The invention relates to the technical field of automobiles, and discloses a vehicle state estimation method and device, equipment and a storage medium. The method comprises the steps that vehicle state parameters of a vehicle under the current working condition are obtained; constructing a vehicle dynamics model according to the vehicle state parameters; performing transverse dynamic correction on the nonlinear dynamic model according to the tire force and the slip angle of the vehicle to obtain a corrected vehicle dynamic model; and carrying out adaptive Kalman filtering on the target state variable in the corrected vehicle dynamics model, and updating process noise information and measurement noise information by adopting a regularization method in the adaptive Kalman filtering process so as to obtain estimation information of the target state variable at the current moment. According to the embodiment of the invention, the vehicle state evaluation precision can be improved, and the filtering divergence in the vehicle state process can be suppressed.

The invention discloses an active steering and braking integrated control system based on roll angle feedback, and belongs to the technical field of vehicle dynamics control. In order to solve the problems of slow control response and multi-actuator action conflict of the vehicle under the limit working condition, the method quantifies the comprehensive instability risk of the whole vehicle by constructing a dynamic virtual potential field. The potential field is based on key state variables such as a roll angle and a side slip angle, and the topological structure (namely the weight of each variable) of the potential field is remodeled in real time by a dynamic risk factor reflecting the intention urgency degree of a driver and the environmental danger level. The system evaluates the instantaneous control efficiency by calculating the contribution degree of each actuator to the reduction of the potential field gradient in a distributed manner. According to the method, the complex control problem is converted into the process of finding the minimum potential energy point, prospective suppression of the instability trend and conflict-free efficient cooperation between the actuators are achieved, and the limit stability and safety of the vehicle are remarkably improved.

The invention relates to a vehicle steering control method and device, vehicle-mounted equipment, a vehicle, a medium and a product. The method comprises the following steps: acquiring an ideal Ackerman corner of each wheel in a vehicle in a current driving state; according to the ideal Ackerman rotation angle of each wheel and the current driving state, estimating the side slip angle of each wheel to obtain an estimated side slip angle of each wheel; determining whether the vehicle is in a high-speed steering state according to the current driving state; determining a target steering angle according to whether the vehicle is in a high-speed steering state, the estimated slip angle of each wheel and the ideal Ackerman steering angle of each wheel; and controlling each wheel of the vehicle according to the target steering angle. By adopting the method, the deviation of the ideal Ackerman angle in the steering process can be compensated by estimating the slip angle, so that the handling stability and the steering precision of the vehicle can be improved, and the stability and the safety of the vehicle in the running process are further improved.

The invention discloses a distributed steering control method, and belongs to the technical field of vehicle steering. The control method comprises the following steps: acquiring real-time driving data of a vehicle, wherein the real-time driving data comprises a steering wheel angle, a vehicle speed, a road adhesion coefficient and a side slip angle; determining a target Ackerman rate according to the real-time driving data; and controlling the wheels of the vehicle according to the target Ackerman rate and the real-time driving data. According to the real-time driving data of the vehicle, the Ackerman rate is determined, the vehicle turning angle control value is determined according to the Ackerman rate determined in real time and the real-time driving data, and then vehicle wheels are controlled according to the vehicle turning angle control value. Namely, the Ackerman rate of the vehicle in the driving process can adapt to different real-time driving data of the vehicle, the real-time driving data of the vehicle is fully considered, the control stability of the vehicle in key scenes such as high speed, low attachment and low speed is effectively improved, the driving burden of a driver is relieved, and the risk that the vehicle is unstable or even out of control is reduced.

The invention provides a redundant braking method and system based on an automatic wheel intelligent traveling chassis, and belongs to the field of vehicle braking. When braking of a single wheel of the vehicle fails, braking force distribution is conducted on the remaining wheels, and when the braking strength is large, the stability of the vehicle is guaranteed through the driving four-wheel steering system. When the wheels on the two different sides fail to brake, the required braking force is averagely distributed, so that the braking force on the two sides is equal, and the stability of the vehicle is ensured. When two or three wheels on the same side fail to brake, the braking force is guaranteed through the remaining wheels, and the stability of the vehicle is guaranteed through the driving four-wheel steering system. When braking of the four wheels all fails, the front wheel toe-in angle and the rear wheel toe-in angle are increased, the side slip angle of a vehicle tire is changed, the lateral force of the tire is increased, the longitudinal force of the vehicle is provided through the lateral force of the wheels, the stability of the vehicle is guaranteed, and the vehicle is braked. The method can effectively cope with different vehicle failure conditions, coordinates braking steering and vehicle stability control, and prevents the vehicle from being out of control.

Methods and systems are provided for estimating lateral adhesion of vehicle tires are provided. The methods include receiving sensor signals, processing the signals to estimate a self-aligning torque (SAT) rate, a lateral force rate, and a slip angle rate, performing a state synchronize process to reduce a time mismatch between the lateral force rate and the slip angle rate, performing a filtering process to provide a lateral slope estimation and a SAT slope estimation, performing a normalization process on the lateral slope estimation and the SAT slope estimation, classifying the normalized SAT slope estimation, and performing an arbitration and fusion process to adjust the normalized lateral slope estimation based on the classification of the normalized SAT slope estimation to estimate a final lateral adhesion level indicator.

The invention relates to a vehicle state parameter joint estimation method based on a fuzzy event triggering mechanism. Comprising the following steps: step 1, establishing a four-wheel steering vehicle kinematics and dynamics model; 2, combining a joint estimation method of a four-wheel steering vehicle kinematics and dynamics model, and constructing a vehicle state and parameter joint estimator based on a three-degree-of-freedom equation; and step 3, designing an event trigger mechanism based on a fuzzy rule, and dynamically adjusting a trigger threshold of state estimation. According to the method, the vehicle state and the tire cornering stiffness are estimated in parallel in the estimation process, the influence of different to-be-estimated quantities on the estimation of the other party is reduced, the estimation precision of the vehicle side slip angle is effectively improved, the updating frequency can be dynamically adjusted and corrected according to the change of the observation residual error and the measurement error covariance, and the estimation precision of the vehicle side slip angle is improved. Unnecessary updating is reduced to avoid accumulative errors caused by integration, meanwhile, the use of computing resources is reduced, and a new solution is provided for estimation of the side slip angle of the vehicle.

The invention discloses a slip rate control method for a turning working condition of a distributed driving vehicle, and belongs to the field of vehicle dynamics control. The method comprises the following steps: firstly, establishing a Brush tire model to accurately represent the mechanical properties of the tire, secondly, determining the optimal slip rate considering the tire slip angle by combining the normalized measurement of tire slip and the tire workload, introducing the road holding allowance, optimizing the optimal slip rate, and finally, determining the optimal slip rate based on nonlinear model predictive control. And the NMPC is used for realizing dynamic tracking and constraint control of the slip rate. By means of the method, it can be guaranteed that the vehicle tire force is maximized under the extreme working conditions such as sharp turning on the wet and slippery road surface, and meanwhile the safety of the vehicle is improved by reserving the road holding allowance.

The invention relates to the technical field of vehicle driving behavior quantitative evaluation, in particular to a vehicle drifting behavior real-time evaluation method and device based on GPS-INS equipment and a medium. Respectively designing a scoring mechanism, wherein an extra scoring region is quantized and scored from four dimensions of speed, angle, distance and area; a common area adopts a score deduction system, scores are deducted according to the slip angle stability, the average value, the speed and the out-of-bound condition, and finally the total score is calculated. According to the method, accurate quantitative evaluation of the drift action can be realized through GPS-INS fusion data, score fluctuation caused by judgment experience difference is eliminated, millisecond-level real-time feedback and cloud visualization are supported, and competition fairness and ornamental value are remarkably improved.

The invention provides a side slip angle estimation method based on an intelligent tire and related equipment, and relates to the field of vehicle motion state estimation.The method comprises the steps that an on-line circulation estimation process is carried out, and the one-time process comprises the steps that the friction coefficient dynamic adjusting amount in the last estimation process is obtained; acquiring a current first friction coefficient output by the intelligent tire system and a corresponding confidence coefficient; outputting a second friction coefficient at the current time according to a second friction coefficient, the friction coefficient dynamic adjusting quantity, the first friction coefficient and the corresponding confidence coefficient which are output by the self-adaptive Kalman filtering last time through the self-adaptive Kalman filtering; and inputting the chassis signal and the second friction coefficient into a nonlinear observer to obtain an estimated value of the side slip angle of the vehicle. A new friction coefficient information source is provided for side slip angle estimation, the side slip angle is estimated through friction coefficients of multiple sources, and decoupling estimation is achieved.

The invention relates to a low-adhesion road surface automobile instability risk quantification method and device and a vehicle, and the method comprises the steps: calculating the longitudinal force and lateral force of the vehicle based on a preset Fiala tire model and a double-track two-degree-of-freedom vehicle model, so as to determine a front and rear slip angle phase plane graph of the vehicle; based on the front and rear slip angle phase plane graphs, determining stable areas and stable boundaries of front and rear wheel slip angle states of the vehicle under different vehicle states and different attachment coefficients so as to determine a low attachment road surface reference stable area and a reference stable boundary of the vehicle; on the basis of the influence of the reference stable boundary and the road adhesion coefficient on the stable boundary of the vehicle and the influence of the vehicle speed and the front wheel rotation angle on the stable boundary, the distance between the state of the vehicle and the original point is scaled to obtain the scaled vehicle state, and the scaled vehicle state is compared with the reference stable boundary to generate the vehicle stability margin index of the low adhesion road. Therefore, the problems that the state of the vehicle on the low-adhesion road surface and the change of the adhesion coefficient of the ice and snow covered road surface are difficult to accurately describe due to the limitation of a linear two-degree-of-freedom model, the vehicle model parameters have time-varying characteristics, the instability risk is influenced, and the instability risk quantification method is complicated and difficult to generalize in the related technology are solved.

The invention belongs to the field of vehicle trajectory tracking control, and discloses an intelligent vehicle trajectory tracking control method and system based on differential programming, and the method comprises the steps: constructing a vehicle dynamics model; a reference trajectory time-varying curvature is introduced, delay of a steering execution mechanism is expressed as pure delay plus a first-order inertia link, and construction of a road tracking model is completed; assuming that the system is in a steady state, calculating reference values of a state quantity and a control quantity; constructing an MPC optimization problem, converting the MPC optimization problem into a QP problem, and calculating to obtain an MPC loss value; constructing a differential programming training calculation network diagram; a hypercube is used for sampling the state quantity of a vehicle, the driving speed and the time-varying reference items of a road, and construction of a network training initial state data set is completed; carrying out MPC trajectory tracking task integration, and constructing a physical model in network training; using a full-link layer network, adding tire slip angle soft constraints, completing the construction of a strategy network, carrying out end-to-end network training, and completing the control of a turning angle instruction. According to the method, the MPC online solving optimization problem can be avoided.

The invention relates to the technical field of active safety control of intelligent automobiles, in particular to a multi-source fusion estimation method and system for a side slip angle and a road adhesion coefficient, and aims to realize step-by-step estimation of the side slip angle and the road adhesion coefficient through a cascade nonlinear observer architecture, solve the problem of joint estimation caused by dynamic coupling of the side slip angle and the road adhesion coefficient, and improve the safety of the side slip angle and the road adhesion coefficient. Based on an estimation result of a cascade nonlinear observer, a joint estimation method for the side slip angle and the road adhesion coefficient based on an exogenous Kalman filtering framework is provided, the problem that stability and optimality / suboptimum are difficult to consider in a traditional method is solved, lane line information is recognized through visual recognition, and a vehicle kinematics model is combined, so that the road adhesion coefficient is estimated. According to the method, a Kalman filter of the vehicle side slip angle is constructed to output expectation and variance, so that the uncertainty of visual estimation of the side slip angle is quantified, meanwhile, after visual-based road surface classification, the expectation and variance of a visual estimation road surface adhesion coefficient are obtained by adopting a Bayesian method, and subsequent multi-source information fusion is facilitated.

The invention provides a vehicle dynamic stability control method based on reinforcement learning and variable pole assignment, and relates to the field of vehicle dynamics control. According to the method, the stability state and the energy evolution trend of the vehicle are recognized in real time by constructing a multi-dimensional criterion of a side slip angle phase plane and an energy phase plane; a reinforcement learning agent is utilized to make an expected closed-loop pole position of a system according to a current state online decision, aggressive poles are configured under a stable working condition to improve the flexibility, and conservative poles are configured under an unstable working condition to guarantee the stability. Besides, a safety monitoring mechanism containing pole physical domain constraints is further designed, the dynamic characteristics of the vehicle are remodeled through feedback control on the premise that the steering intention of a driver is not changed, and the problem of real-time balance of flexibility and safety in intelligent chassis control is effectively solved.

The invention provides a lateral movement sensing method and a vehicle, the method is applied to the technical field of vehicle control, and the method comprises the steps that a tire slip angle value at the current moment is obtained in response to a target calculation instruction of the vehicle; calculating an actual lateral force value at the current moment based on the tire slip angle value and the current wheel slip rate of the vehicle; and calculating the actual lateral motion acceleration of the vehicle according to the actual lateral force value, and evaluating the axle load transfer amount in the vehicle steering process according to the actual lateral motion acceleration. According to the method, the actual lateral force can be calculated in real time according to the tire slip angle and the wheel slip rate in various running states of the vehicle, then the actual lateral motion acceleration of the vehicle is accurately output, different working conditions can be adapted, and the real-time performance and accuracy of vehicle dynamics control are improved.