Distributed driving pre-stabilization control system and method based on state estimation

Abstract

The invention is applicable to the technical field of distributed driving electric vehicle control, and provides a distributed driving pre-stabilization control system and method based on state estimation, and the system comprises a data acquisition module, a central processing module and a control execution module. The method comprises the following steps: firstly, receiving signals of each sensor, a gyroscope and a vehicle parameter unit; calculating a longitudinal force and a lateral force of a vehicle driving wheel; state parameters of the vehicle are calculated according to the longitudinal force and the lateral force; state trend prediction is carried out through the state trend; according to the predicted future automobile state, pre-stability judgment is carried out through the principle of a phase plane and a yaw velocity threshold value; when the automobile is about to be unstable, needed yaw moment is calculated, a pre-stability control mode is started, four-wheel torque distribution is carried out through a torque vector distribution method, and torque needing to be distributed by four wheels is obtained; and then a torque control instruction is sent to the driving motor through the execution module, so that the four-wheel torque reaches the calculated torque.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed drive electric vehicle control, and in particular relates to a distributed drive pre-stabilization control system and method based on state estimation. Background Art

[0002] Distributed drive vehicles are a type of new energy vehicles. The wheel drive and braking force of distributed motor drive vehicles only need to be generated through the action of motors and motor controllers, eliminating the traditional transmission system, so the response speed is faster, the response accuracy is higher, and the torque controllability and measurability are stronger. In all-wheel drive hub motor electric vehicles, each hub motor can generate driving torque or braking torque at the same time, and then generate a yaw torque to correct the driving state of the vehicle. Therefore, the motor torque distribution method is no longer limited to single-wheel control or dual-wheel control, and the distribution method can be extended to optimize the distribution of multiple targets. Therefore, distributed motor drive vehicles have obvious advantages over traditional vehicles in terms of driving torque distribution, active safety control, and space layout.

[0003] Existing research mainly focuses on judging the stability of the vehicle based on the current state feedback signal collected by the sensor, and only intervenes when the vehicle is already unstable. How to judge the pre-stability of the vehicle in the future still needs further research. In addition, the existing stability control method only relies on the current state feedback from the sensor to judge whether the vehicle is in an unstable state. There is a certain control lag in the vehicle stability control, resulting in a greater risk of vehicle instability. With the development of vehicles, the power is getting stronger and the maximum speed is getting higher, which puts higher requirements on the control function. Feedback control is difficult to ensure vehicle safety. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a distributed drive pre-stabilization control system and method based on state estimation, aiming to solve the problems raised in the above background technology.

[0005] The embodiment of the present invention is implemented as follows: a distributed drive pre-stabilization control system based on state estimation includes a data acquisition module, a central processing module and a control execution module; The data acquisition module includes a steering wheel angle sensor, a wheel speed sensor, an acceleration sensor, a gyroscope and a vehicle parameter unit, wherein the vehicle parameter unit stores fixed parameter information of the vehicle structure; The central processing module is used to execute the control method calculation, first receiving the signals from the steering wheel angle sensor, the wheel speed sensor, the acceleration sensor, the gyroscope and the vehicle parameter unit; calculating the longitudinal force and lateral force of the vehicle driving wheel according to the sliding film observer principle; calculating the main state parameters such as the yaw rate and the sideslip angle of the center of mass of the vehicle according to the longitudinal force and the lateral force through the unscented Kalman filter principle; predicting the state trend through the state trend based on the Taylor expansion, predicting the state measured in the future time; based on the predicted future state of the vehicle, pre-stability judgment is performed through the principle of phase plane and yaw rate threshold value; when the vehicle is about to lose stability, the required yaw moment is calculated and the pre-stability control mode is turned on, and the torque distribution of the four wheels is performed through the torque vector distribution method to obtain the torque required to be distributed to the four wheels; The control execution module is used to send a torque control instruction to the drive motor according to the result calculated by the central processing module, so that the four-wheel torque reaches the calculated torque.

[0006] According to a further technical solution, the fixed parameter information of the vehicle structure includes the wheel moment of inertia, the effective radius of the tire, the body moment of inertia and the distance from the center of mass to the front and rear axles.

[0007] Another object of an embodiment of the present invention is to provide a distributed drive pre-stabilization control method based on state estimation, comprising the following steps: Step 1: Use the steering wheel angle sensor to collect the steering wheel angle, use the wheel speed sensor to collect the wheel speed of the four wheels, use the acceleration sensor to collect the longitudinal and lateral acceleration of the vehicle, and receive the vehicle parameters from the vehicle parameter unit; Step 2: Calculate the longitudinal forces of the four wheels of the vehicle using the sliding film observer principle based on the wheel torque, wheel moment of inertia and effective tire radius; Step 3: Calculate the front wheel angle of the vehicle based on the steering wheel angle and the transmission ratio of the vehicle's own steering system; Step 4: Calculate the lateral force of the front axle and the lateral force of the rear axle of the vehicle using the sliding film observer principle based on the vehicle's yaw moment of inertia, the distance from the center of mass to the front axle, and the distance from the center of mass to the rear axle; Step 5: According to the longitudinal force and lateral force of the tires and the vehicle's own parameters, the unscented Kalman filter principle is used to calculate the vehicle's center of mass sideslip angle, yaw angular velocity and vehicle speed; Step 6: According to the vehicle's center of mass slip angle, yaw angular velocity, center of mass slip angle acceleration and yaw angular acceleration, based on the trend prediction principle of Taylor expansion, predict the state of the vehicle at the next moment; Step 7: According to the obtained predicted yaw rate and sideslip angle of the vehicle, based on the phase plane theory and the principle of yaw rate threshold value, the pre-stability of the vehicle is determined; Step 8: According to the ideal yaw rate and the yaw rate deviation, based on the principle of the model predictive control algorithm, the yaw rate required to restore stability when the vehicle is about to become unstable is calculated; Step 9: According to the method of minimizing the wheel load on the four wheels of the vehicle, torque vector distribution is performed based on the quadratic programming method; Step 10: Based on the calculated torque, use the PID algorithm to control the drive motor to output the ideal torque.

[0008] According to a further technical solution, in step 2, the calculation formula of the longitudinal force of the automobile tire is as follows: ; ; In the formula, is the driving wheel torque, i=fl, fr, rl, rr; is the longitudinal force of the driving wheel, i=fl, fr, rl, rr; is the effective radius of the tire; is the wheel moment of inertia; is the longitudinal tire force synovial gain; is the longitudinal tire force feedback gain; is the driving wheel angular velocity; is the observed value of the driving wheel angular velocity; is the observed value of the driving wheel angular acceleration; To adjust the parameters.

[0009] According to a further technical solution, in step 3, the calculation formula of the front wheel turning angle of the vehicle is as follows: ; In the formula, Steering wheel angle ， Front wheel angle ， Q is the steering gear ratio.

[0010] According to a further technical solution, in step 4, the calculation formula of the longitudinal force of the automobile tire is as follows: ; ; ; In the formula, is the observed value of yaw angular acceleration, is the observed value of yaw angular velocity, is the vehicle yaw angular velocity, is the longitudinal acceleration of the vehicle's center of mass, m is the vehicle's mass, is the distance from the center of mass to the front axle, is the distance from the center of mass to the rear axle, is the moment of inertia, is the longitudinal force on the front axle of the vehicle, is the lateral force on the front axle of the vehicle, is the lateral force on the rear axle of the vehicle, is the front axle lateral tire force synovia gain, is the front axle lateral tire force feedback gain, is the lateral tire force synovia gain on the rear axle, is the rear axle lateral tire force feedback gain.

[0011] A further technical solution is that in step 5, the observation method of the vehicle state based on the unscented Kalman filter is as follows: The state variables of the system , input variable , observation quantity , the system state equation is: ; ; The observation equation is: ; ; In the formula, is the vehicle yaw rate ， is the vehicle's center of mass sideslip angle ， is the vehicle longitudinal velocity.

[0012] A further technical solution is that in step 6, the automobile state is predicted based on the trend prediction of Taylor expansion as follows: ; ; Where: T is the current time, For the prediction time.

[0013] A further technical solution is that in step 7, the trend prediction predicts the state of the car as: ; ; Where: , is the stability boundary coefficient, is the ideal yaw rate, is the yaw rate threshold.

[0014] According to a further technical solution, in step 8, the yaw moment is calculated based on the model predictive control theory as follows: ; ; Where: ; ; ; ; ; ; is the vehicle longitudinal velocity, is the vehicle front axle lateral stiffness, is the vehicle rear axle lateral stiffness, is the yaw moment.

[0015] A further technical solution is that in step 9, the cost function of the torque distribution based on the minimum tire load is: ; Where: J is the cost function, is the vertical force of each driving wheel (i=fl, fr, rl, rr), is the road adhesion coefficient.

[0016] According to a further technical solution, in step 10, the torque of the four wheels is distributed as follows: ; ; In the formula, is the proportionality coefficient; is the proportionality factor ； is the integration time; is the expected torque of each driving wheel, i=fl, fr, rl, rr; is the actual torque of each driving wheel, i=fl, fr, rl, rr.

[0017] The embodiment of the present invention provides a distributed drive pre-stabilization control system and method based on state estimation, which can estimate the tire force and driving state of the vehicle during driving according to the current feedback signal collected by the sensor, and judge the stability of the vehicle in the future through state estimation and prediction value, and intervene when the vehicle is about to become unstable. Compared with the traditional stability control method, the pre-stabilization control strategy can activate the vehicle stability control system in advance, effectively overcoming the problem of certain control lag in vehicle stability control. It reduces the average error of yaw rate and center of mass sideslip angle, and significantly improves the stability performance of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 An execution process of a distributed drive pre-stabilization control system based on state estimation provided by an embodiment of the present invention; Figure 2 A flow chart of a distributed drive pre-stabilization control method based on state estimation provided by an embodiment of the present invention; Figure 3 for Phase plane diagram; Figure 4 This is a conceptual diagram of pre-stabilization control. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0021] like Figure 1 As shown, a distributed drive pre-stabilization control system based on state estimation is provided in one embodiment of the present invention, including a data acquisition module, a central processing module and a control execution module; The data acquisition module includes a steering wheel angle sensor, a wheel speed sensor, an acceleration sensor, a gyroscope and a vehicle parameter unit, wherein the vehicle parameter unit stores fixed parameter information of the vehicle structure; The central processing module is used to execute the control method calculation, first receiving the signals from the steering wheel angle sensor, the wheel speed sensor, the acceleration sensor, the gyroscope and the vehicle parameter unit; calculating the longitudinal force and lateral force of the vehicle driving wheel according to the sliding film observer principle; calculating the main state parameters such as the yaw rate and the sideslip angle of the center of mass of the vehicle according to the longitudinal force and the lateral force through the unscented Kalman filter principle; predicting the state trend through the state trend based on the Taylor expansion, predicting the state measured in the future time; based on the predicted future state of the vehicle, pre-stability judgment is performed through the principle of phase plane and yaw rate threshold value; when the vehicle is about to lose stability, the required yaw moment is calculated and the pre-stability control mode is turned on, and the torque distribution of the four wheels is performed through the torque vector distribution method to obtain the torque required to be distributed to the four wheels; The control execution module is used to send a torque control instruction to the drive motor according to the result calculated by the central processing module, so that the four-wheel torque reaches the calculated torque.

[0022] As a preferred embodiment of the present invention, the vehicle structure fixed parameter information of the vehicle includes wheel rotational inertia, tire effective radius, vehicle body rotational inertia and distance from center of mass to front and rear axles.

[0023] like Figure 2 As shown, a distributed drive pre-stabilization control method based on state estimation is provided in another embodiment of the present invention, comprising the following steps: Step 1: Use the steering wheel angle sensor to collect the steering wheel angle, use the wheel speed sensor to collect the wheel speed of the four wheels, use the acceleration sensor to collect the longitudinal and lateral acceleration of the vehicle, and receive the vehicle parameters from the vehicle parameter unit; Step 2: Calculate the longitudinal forces of the four wheels of the vehicle using the sliding film observer principle based on the wheel torque, wheel moment of inertia and effective tire radius; Step 3: Calculate the front wheel angle of the vehicle based on the steering wheel angle and the transmission ratio of the vehicle's own steering system; Step 4: Calculate the lateral force of the front axle and the lateral force of the rear axle of the vehicle using the sliding film observer principle based on the vehicle's yaw moment of inertia, the distance from the center of mass to the front axle, and the distance from the center of mass to the rear axle; Step 5: According to the longitudinal force and lateral force of the tires and the vehicle's own parameters, the unscented Kalman filter principle is used to calculate the vehicle's center of mass sideslip angle, yaw angular velocity and vehicle speed; Step 6: According to the vehicle's center of mass slip angle, yaw angular velocity, center of mass slip angle acceleration and yaw angular acceleration, based on the trend prediction principle of Taylor expansion, predict the state of the vehicle at the next moment; Step 7: According to the obtained predicted yaw rate and sideslip angle of the vehicle, based on the phase plane theory and the principle of yaw rate threshold value, the pre-stability of the vehicle is determined; Step 8: According to the ideal yaw rate and the yaw rate deviation, based on the principle of the model predictive control algorithm, the yaw rate required to restore stability when the vehicle is about to become unstable is calculated; Step 9: According to the method of minimizing the wheel load on the four wheels of the vehicle, torque vector distribution is performed based on the quadratic programming method; Step 10: Based on the calculated torque, use the PID algorithm to control the drive motor to output the ideal torque.

[0024] As a preferred embodiment of the present invention, in step 2, the calculation formula of the longitudinal force of the automobile tire is as follows: ; ; In the formula, is the driving wheel torque, i=fl, fr, rl, rr; is the longitudinal force of the driving wheel, i=fl, fr, rl, rr; is the effective radius of the tire, is the wheel moment of inertia, is the longitudinal tire force synovial gain, is the longitudinal tire force feedback gain, is the driving wheel angular velocity, is the observed value of the driving wheel angular velocity, is the observed value of the driving wheel angular acceleration, To adjust the parameters.

[0025] As a preferred embodiment of the present invention, in step 3, the calculation formula of the front wheel turning angle of the vehicle is as follows: ; In the formula, Steering wheel angle ， Front wheel angle ， Q is the steering gear ratio.

[0026] As a preferred embodiment of the present invention, in step 4, the calculation formula of the longitudinal force of the automobile tire is as follows: ; ; ; In the formula, is the observed value of yaw angular acceleration, is the yaw angular velocity observation value, is the vehicle yaw angular velocity, is the longitudinal acceleration of the vehicle's center of mass, m is the vehicle's mass, is the distance from the center of mass to the front axle, is the distance from the center of mass to the rear axle, is the moment of inertia, is the longitudinal force on the front axle of the vehicle, is the lateral force on the front axle of the vehicle, is the lateral force on the rear axle of the vehicle, is the front axle lateral tire force synovia gain, is the front axle lateral tire force feedback gain, is the lateral tire force synovia gain on the rear axle, is the rear axle lateral tire force feedback gain.

[0027] As a preferred embodiment of the present invention, in step 5, the observation method of the vehicle state based on the unscented Kalman filter is as follows: The state variables of the system , input variable , observation quantity , the system state equation is: ; ; The observation equation is: ; ; In the formula, is the vehicle yaw rate ， is the vehicle's center of mass sideslip angle ， is the vehicle longitudinal velocity.

[0028] As a preferred embodiment of the present invention, in step 6, the automobile state is predicted based on the trend prediction of Taylor expansion: ; ; Where: T is the current time, For the prediction time.

[0029] As a preferred embodiment of the present invention, in step 7, the trend prediction predicts that the vehicle state is: ; ; Where: , is the stability boundary coefficient, is the ideal yaw rate, is the yaw rate threshold.

[0030] As a preferred embodiment of the present invention, in step 8, the yaw moment is calculated based on the model predictive control theory as follows: ; ; Where: ; ; ; ; ; ; is the vehicle longitudinal velocity, is the vehicle front axle lateral stiffness, is the vehicle rear axle lateral stiffness, is the yaw moment.

[0031] As a preferred embodiment of the present invention, in step 9, the cost function of torque distribution based on minimum tire load is: ; Where: J is the cost function, is the vertical force of each driving wheel (i=fl, fr, rl, rr), is the road adhesion coefficient.

[0032] As a preferred embodiment of the present invention, in step 10, the four-wheel torque is distributed as follows: ; ; In the formula, is the proportionality coefficient; is the proportionality factor ； is the integration time; is the expected torque of each driving wheel, i=fl, fr, rl, rr; is the actual torque of each driving wheel, i=fl, fr, rl, rr.

[0033] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed drive pre-stabilization control system based on state estimation, characterized in that: It includes data acquisition module, central processing module and control execution module; The data acquisition module includes a steering wheel angle sensor, a wheel speed sensor, an acceleration sensor, a gyroscope and a vehicle parameter unit, wherein the vehicle parameter unit stores fixed parameter information of the vehicle structure; The central processing module is used to execute the control method calculation, first receiving the signals from the steering wheel angle sensor, the wheel speed sensor, the acceleration sensor, the gyroscope and the vehicle parameter unit; calculating the longitudinal force and the lateral force of the vehicle driving wheel according to the sliding film observer principle; calculating the state parameters of the vehicle according to the longitudinal force and the lateral force through the unscented Kalman filter principle; predicting the state trend through the state trend based on the Taylor expansion, predicting the state measured in the future time; based on the predicted future state of the vehicle, pre-stability judgment is performed through the principle of phase plane and yaw rate threshold value; when the vehicle is about to lose stability, the required yaw torque is calculated and the pre-stability control mode is turned on, and the torque distribution of the four wheels is performed through the torque vector distribution method to obtain the torque required to be distributed to the four wheels; The control execution module is used to send a torque control instruction to the drive motor according to the result calculated by the central processing module, so that the four-wheel torque reaches the calculated torque.

2. The distributed drive pre-stabilization control system based on state estimation according to claim 1 is characterized in that: The vehicle structure fixed parameter information of the vehicle includes wheel rotational inertia, tire effective radius, body rotational inertia and distance from center of mass to front and rear axles.

3. A distributed drive pre-stabilization control method based on state estimation, based on the distributed drive pre-stabilization control system based on state estimation according to any one of claims 1 and 2, characterized in that: The following steps are involved: Step 1: Use the steering wheel angle sensor to collect the steering wheel angle, use the wheel speed sensor to collect the wheel speed of the four wheels, use the acceleration sensor to collect the longitudinal and lateral acceleration of the vehicle, and receive the vehicle parameters from the vehicle parameter unit; Step 2: Calculate the longitudinal forces of the four wheels of the vehicle using the sliding film observer principle based on the wheel torque, wheel moment of inertia and effective tire radius; Step 3: Calculate the front wheel angle of the vehicle based on the steering wheel angle and the transmission ratio of the vehicle's own steering system; Step 4: Calculate the lateral force of the front axle and the lateral force of the rear axle of the vehicle using the sliding film observer principle based on the vehicle's yaw moment of inertia, the distance from the center of mass to the front axle, and the distance from the center of mass to the rear axle; Step 5: According to the longitudinal force and lateral force of the tires and the vehicle's own parameters, the unscented Kalman filter principle is used to calculate the vehicle's center of mass sideslip angle, yaw angular velocity and vehicle speed; Step 6: According to the vehicle's center of mass slip angle, yaw angular velocity, center of mass slip angle acceleration and yaw angular acceleration, based on the trend prediction principle of Taylor expansion, predict the state of the vehicle at the next moment; Step 7: According to the obtained predicted yaw rate and sideslip angle of the vehicle, based on the phase plane theory and the principle of yaw rate threshold value, the pre-stability of the vehicle is determined; Step 8: According to the ideal yaw rate and the yaw rate deviation, based on the principle of the model predictive control algorithm, the yaw rate required to restore stability when the vehicle is about to become unstable is calculated; Step 9: According to the method of minimizing the wheel load on the four wheels of the vehicle, torque vector distribution is performed based on the quadratic programming method; Step 10: Based on the calculated torque, use the PID algorithm to control the drive motor to output the ideal torque.

4. The distributed drive pre-stabilization control method based on state estimation according to claim 3 is characterized in that: In step 2, the calculation formula of the longitudinal force of the automobile tire is as follows: ； ； In the formula, is the driving wheel torque, i=fl, fr, rl, rr; is the longitudinal force of the driving wheel, i=fl, fr, rl, rr; is the effective radius of the tire; is the wheel moment of inertia; is the longitudinal tire force synovial gain; is the longitudinal tire force feedback gain; is the driving wheel angular velocity; is the observed value of the driving wheel angular velocity; is the observed value of the driving wheel angular acceleration; To adjust the parameters.

5. The distributed drive pre-stabilization control method based on state estimation according to claim 4 is characterized in that: In step 3, the calculation formula of the front wheel angle of the vehicle is as follows: ； In the formula, Steering wheel angle ， Front wheel angle ， Q is the steering gear ratio.

6. The distributed drive pre-stabilization control method based on state estimation according to claim 5 is characterized in that: In step 4, the calculation formula of the longitudinal force of the automobile tire is as follows: ； ； ； In the formula, is the observed value of yaw angular acceleration, is the yaw angular velocity observation value, is the vehicle yaw angular velocity, is the longitudinal acceleration of the vehicle's center of mass, m is the vehicle's mass, is the distance from the center of mass to the front axle, is the distance from the center of mass to the rear axle, is the moment of inertia, is the longitudinal force on the front axle of the vehicle, is the lateral force on the front axle of the vehicle, is the lateral force on the rear axle of the vehicle, is the front axle lateral tire force synovia gain, is the front axle lateral tire force feedback gain, is the lateral tire force synovia gain on the rear axle, is the rear axle lateral tire force feedback gain.

7. The distributed drive pre-stabilization control method based on state estimation according to claim 6 is characterized in that: In step 5, the observation method of the vehicle state based on the unscented Kalman filter is as follows: The state variables of the system , input variable , observation quantity , the system state equation is: ； ； The observation equation is: ； ； In the formula, is the vehicle yaw rate ， is the vehicle's center of mass sideslip angle ， is the vehicle longitudinal velocity.

8. The distributed drive pre-stabilization control method based on state estimation according to claim 7 is characterized in that: In step 6, the vehicle state is predicted based on the trend prediction of Taylor expansion as follows: ； ； Where: T is the current time, For the prediction time.

9. The distributed drive pre-stabilization control method based on state estimation according to claim 8 is characterized in that: In step 7, the trend prediction predicts that the vehicle status is: ； ； Where: , is the stability boundary coefficient, is the ideal yaw rate, is the yaw rate threshold.

10. The distributed drive pre-stabilization control method based on state estimation according to claim 9, characterized in that: In step 8, the yaw moment is calculated based on the model predictive control theory as follows: ； ； Where: ; ; ; ; ; ; is the vehicle longitudinal velocity, is the vehicle front axle lateral stiffness, is the vehicle rear axle lateral stiffness, is the yaw moment.

11. The distributed drive pre-stabilization control method based on state estimation according to claim 10 is characterized in that: In step 9, the cost function of torque distribution based on minimum tire load is: ； Where: J is the cost function, is the vertical force of each driving wheel (i=fl, fr, rl, rr), is the road adhesion coefficient.

12. The distributed drive pre-stabilization control method based on state estimation according to claim 11, characterized in that: In step 10, the four-wheel torque is distributed as follows: ； ； In the formula, is the proportionality coefficient; is the proportionality factor ； is the integration time; is the expected torque of each driving wheel, i=fl, fr, rl, rr; is the actual torque of each driving wheel, i=fl, fr, rl, rr.

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