CN-122009204-A - Method and system for estimating yaw rate of vehicle, vehicle and storage medium

CN122009204ACN 122009204 ACN122009204 ACN 122009204ACN-122009204-A

Abstract

The invention provides a method, a system, a vehicle and a storage medium for estimating the yaw rate of a vehicle, wherein the method for estimating the yaw rate of the vehicle comprises the steps of acquiring wheel speed information of the vehicle and the motion state of the vehicle; the method comprises the steps of calculating a first yaw rate of the vehicle according to wheel speed information, correcting the first yaw rate according to motion states and the wheel speed information to obtain a second yaw rate, designing a first Kalman filter according to a dynamics model, introducing a disturbance state into the first Kalman filter to obtain a disturbance Kalman filter, and filtering the second yaw rate by the disturbance Kalman filter to obtain a third yaw rate. The invention solves the technical problem that in the existing method for estimating the transverse angular velocity, the transverse angular velocity of the vehicle body is usually calculated according to the wheel speed information and used as a pre-estimated value, and the estimation error of the estimation method on the transverse angular velocity is larger.

Inventors

WANG JIANQIN
WANG YANMING

Assignees

宁波均胜智能汽车技术研究院有限公司

Dates

Publication Date: 20260512
Application Date: 20260205

Claims (10)

1. A method of estimating a yaw rate of a vehicle, the method comprising: Acquiring wheel speed information of a vehicle and a motion state of the vehicle; Calculating a first yaw rate of the vehicle from the wheel speed information; correcting the first yaw rate according to the motion state and the wheel speed information to obtain a second yaw rate; Designing a first Kalman filter according to the dynamics model; introducing a disturbance state into the first Kalman filter to obtain a disturbance Kalman filter; Filtering the second yaw rate by adopting the disturbance Kalman filter to obtain a third yaw rate; The wheel speed information comprises a front left wheel angular speed, a front right wheel angular speed, a rear left wheel angular speed and a rear right wheel angular speed, and the motion states comprise a braking state and an acceleration state.
2. The estimation method according to claim 1, wherein, The calculating a first yaw rate of the vehicle from the wheel speed information includes: Obtaining a first rear yaw rate from the rear left wheel angular rate and the rear right wheel angular rate is: ; Obtaining a first front yaw rate from the front left wheel angular velocity and the front right wheel angular velocity is: ; wherein R represents the wheel radius of the vehicle, Representing the angular velocity of the front left wheel, Representing the angular velocity of the front right wheel, Representing the angular velocity of the rear left wheel, Representing the rear right wheel angular velocity; Representing the front axle width of the vehicle, Representing the rear axle width of the vehicle, A front wheel corner for the vehicle; representing the first yaw rate estimated from a kinematic relationship and front wheel speed information of the vehicle; and representing the first yaw rate estimated from the kinematic relationship and the rear wheel speed information of the vehicle.
3. The estimation method according to claim 2, wherein, The correcting the first yaw rate according to the motion state and the wheel speed information to obtain a second yaw rate includes: according to the motion state and the longitudinal wheel speed of each wheel on the vehicle, the longitudinal slip rate of each wheel in the current state is obtained; And correcting the first yaw rate according to the longitudinal wheel speed and the longitudinal slip rate to obtain a second yaw rate.
4. The estimation method according to claim 3, wherein, The correcting the first yaw rate according to the motion state and the wheel speed information to obtain a second yaw rate includes: When the motion state is the braking state, obtaining a second rear yaw rate according to the motion state and the wheel speed information is as follows: ; Wherein, the Indicating the speed of the vehicle through the on-board CAN bus, The slip rate of the rear right wheel is indicated, Indicating the slip rate of the rear left wheel, t indicating the current time, The time step is represented by a time step, Representing said second yaw rate at time t, Representation of The second yaw rate at the moment.
5. The estimation method according to claim 3, wherein, The correcting the first yaw rate according to the motion state and the wheel speed information to obtain a second yaw rate, further includes: when the motion state is the braking state, obtaining a second front yaw rate according to the motion state and the wheel speed information is as follows: ; in the case where the motion state is the acceleration state, obtaining a second front yaw rate from the motion state and the wheel speed information is: ; Wherein, the The slip rate of the front right wheel is indicated, The slip rate of the front left wheel is indicated, Representing said second yaw rate at time t, Representation of The second yaw rate at the moment.
6. The estimation method according to claim 1, wherein, The first Kalman filter is: ; ; Wherein, the As an estimated value of the state vector x, , Represents the transverse vehicle speed, Indicating the yaw rate of the vehicle body, Representing an additional state quantity; Is a measured value Is used for the estimation of the (c), , In order to measure the noise level of the light, Represents lateral acceleration on the centroid; k is the gain of the first kalman filter; The matrices A, B, C, d are respectively: , , , ; Wherein, the Representing the cornering stiffness of the front wheels of the vehicle, Represents the cornering stiffness of the rear wheels of the vehicle, m represents the body mass of the vehicle, For the moment of inertia of the wheel, For the distance of the front axle from the center of mass along the longitudinal axis of the body, For the distance of the rear axle from the center of mass along the longitudinal axis of the body, As the extreme point of the acceleration sensor model, Is the gain of the accelerometer model.
7. The estimation method according to claim 6, wherein, The disturbance Kalman filter is as follows: ; ; Matrix array 、、、 The method comprises the following steps of: , , , ; Wherein, the Is a state vector Is used to determine the estimated value of (c) for the model, , For the gain of the perturbation kalman filter, For yaw disturbance values, the estimated measurement output is And 。
8. A system for estimating yaw rate of a vehicle, the system comprising: The first acquisition module is used for acquiring wheel speed information of a vehicle and a motion state of the vehicle; a first calculation module for calculating a first yaw rate of the vehicle from the wheel speed information; The second calculation module is used for correcting the first yaw rate according to the motion state and the wheel speed information so as to obtain a second yaw rate; The first construction module is used for designing a first Kalman filter according to a dynamics model; the second construction module is used for introducing a disturbance state into the first Kalman filter so as to obtain a disturbance Kalman filter; and the execution module is used for filtering the second yaw rate by adopting the disturbance Kalman filter so as to obtain a third yaw rate.
9. A vehicle comprising a processor, a memory and a program or instruction stored on the memory and executable on the processor, which when executed by the processor, carries out the steps of the method of estimating the yaw rate of a vehicle as claimed in any one of claims 1 to 7.
10. A readable storage medium, characterized in that the readable storage medium has stored thereon a program or instructions which, when executed by a processor, implement the steps of the method of estimating a yaw rate of a vehicle according to any one of claims 1 to 7.

Description

Method and system for estimating yaw rate of vehicle, vehicle and storage medium Technical Field The present invention relates to the technical field, and in particular, to a method for estimating a yaw rate of a vehicle, a system for estimating a yaw rate of a vehicle, and a storage medium. Background In extreme lateral operation of the vehicle or lateral operation under extreme conditions (icy or snowy road surfaces, flat tires and crosswinds), the lateral stability of the vehicle body is critical for the safety of the driver and passengers. Under extreme conditions, vehicle body stability control systems such as ESP (electronic stability program), VDC (VEHICLE DYNAMICS control), YSC (yaw stability control), and the like can improve the lateral stability of the vehicle body. Yaw rate is a very important variable that not only affects the driver and passenger perceived vehicle maneuver attempt, but also characterizes the safety of the vehicle driving. Therefore, in a vehicle body stabilization system, yaw rate is one of the most important variables that need to be known. However, in the actual construction process, there is a problem in that in the conventional method of estimating the lateral angular velocity, the lateral angular velocity of the vehicle body is generally calculated from the wheel speed information as a pre-estimated value, and the estimation error of the estimation method for the lateral angular velocity is large. Disclosure of Invention The invention solves the technical problem that in the existing method for estimating the transverse angular velocity, the transverse angular velocity of the vehicle body is usually calculated according to the wheel speed information and used as a pre-estimated value, and the estimation error of the estimation method on the transverse angular velocity is larger. In order to solve the problems, the invention provides a vehicle yaw rate estimation method, which comprises the steps of obtaining wheel speed information of a vehicle and a motion state of the vehicle, calculating a first yaw rate of the vehicle according to the wheel speed information, correcting the first yaw rate according to the motion state and the wheel speed information to obtain a second yaw rate, designing a first Kalman filter according to a dynamics model, introducing a disturbance state into the first Kalman filter to obtain the disturbance Kalman filter, and filtering the second yaw rate by adopting the disturbance Kalman filter to obtain a third yaw rate, wherein the wheel speed information comprises a front left wheel angular rate, a front right wheel angular rate, a rear left wheel angular rate and a rear right wheel angular rate, and the motion state comprises a braking state and an accelerating state. Compared with the prior art, the technical scheme has the advantages that the motion state of the vehicle is judged through the brake and accelerator information, and the first yaw rate estimated according to the wheel speed information is corrected according to the motion state to obtain the second yaw rate, so that the estimated information is more accurate. The model disturbance information is introduced into the first Kalman filter as an expanded state quantity by adopting the first Kalman filter to process measurement noise in the estimated information (namely the second yaw rate), so that a disturbance Kalman filter is obtained, and the robustness of the estimator to model uncertainty can be increased through the disturbance Kalman filter. In one example of the present invention, calculating a first yaw rate of a vehicle from wheel speed information includes obtaining a first rear yaw rate from a rear left wheel angular rate and a rear right wheel angular rate as follows: And obtaining a first front yaw rate from the front left wheel angular rate and the front right wheel angular rate as follows: wherein R represents the wheel radius of the vehicle, Indicating the angular velocity of the front left wheel,Indicating the angular velocity of the front right wheel,Indicating the angular velocity of the rear left wheel,Indicating the rear right wheel angular velocity; Representing the width of the front axle of the vehicle, Indicating the width of the rear axle of the vehicle,Is the front wheel corner of the vehicle; representing a first yaw rate estimated from the kinematic relationship and front wheel speed information of the vehicle; And represents a first yaw rate estimated from the kinematic relationship and rear wheel speed information of the vehicle. Compared with the prior art, the technical effect achieved by adopting the technical scheme is that the yaw rate of the vehicle body is estimated primarily based on the wheel speed information, and the front wheels are considered as steering wheels, so that the rotation angle of the front wheels is considered when the first front yaw rate is obtained according to the front left wheel angular rate and the front right wheel an