Robust tire forces estimation system

• US 9,752,962 B2
• Filed: 10/09/2015
• Issued: 09/05/2017
• Est. Priority Date: 10/09/2015
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Singh, Kanwar Bharat
• Primary Examiner(s): ALLEN, ANDRE J
• Application Number:
  US14/879,457
• Publication Number:
  US 20170102293A1
• Time in Patent Office: 697 Days
• Field of Search: None
• CPC Class Codes: B60T 2240/06 Wheel load; Wheel lift
• CPC Class Codes: B60T 2270/86 Optimizing braking by using ESP vehicle or tire model
• CPC Class Codes: B60T 8/172 Determining control parameters used in the regulation, e.g. by calculations involving measured or detected parameters B60T8/17551 takes precedence
• CPC Class Codes: B60W 2050/0031 Mathematical model of the vehicle
• CPC Class Codes: B60W 2510/0657 Engine torque
• CPC Class Codes: B60W 2510/18 Braking system
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2520/125 Lateral acceleration
• CPC Class Codes: B60W 2520/14 Yaw
• CPC Class Codes: B60W 2520/16 Pitch
• CPC Class Codes: B60W 2520/18 Roll
• CPC Class Codes: B60W 2520/28 Wheel speed
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: B60W 40/12 related to parameters of the vehicle itself , e.g. tyre models
• CPC Class Codes: B60W 40/13 Load or weight
• CPC Class Codes: G01G 19/08 for incorporation in vehicles
• CPC Class Codes: G01G 19/086 wherein the vehicle mass is dynamically estimated
• CPC Class Codes: G01M 1/122 Determining position of centre of gravity
• CPC Class Codes: G01M 17/02 : Tyres

Abstract

A tire state estimation system is provided for estimating normal force, lateral force and longitudinal forces based on CAN-bus accessible sensor inputs; the normal force estimator generating the normal force estimation from a summation of longitudinal load transfer, lateral load transfer and static normal force using as inputs lateral acceleration, longitudinal acceleration and roll angle derived from the input sensor data; the lateral force estimator estimating lateral force using as inputs measured lateral acceleration, longitudinal acceleration and yaw rate; and the longitudinal force estimator estimating the longitudinal force using as inputs wheel angular speed and drive/brake torque derived from the input sensor data.

Claims

1. A tire state estimation system for estimating normal force, lateral force, and longitudinal force on a tire mounted to a wheel and supporting a vehicle, comprising:

the vehicle including a CAN-bus;

a plurality of sensors mounted to the vehicle and in electronic communication with the CAN-bus;

the sensors generating input sensor data, the input sensor data comprising;

acceleration and angular velocities, steering wheel angle measurement, angular wheel speed of the wheel, roll rate, pitch rate, and yaw rate;

a normal force estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the normal force estimator being operable to estimate a normal force on the tire from a summation of longitudinal load transfer, lateral load transfer and static normal force using as inputs lateral acceleration, longitudinal acceleration and roll angle derived from the input sensor data;

a lateral force estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the lateral force estimator being operable to estimate a lateral force on the tire from a planar vehicle model using as inputs measured lateral acceleration, longitudinal acceleration and yaw rate derived from the input sensor data; and

a longitudinal force estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the longitudinal force estimator being operable to estimate a longitudinal force on the tire from a wheel rotational dynamics model using as inputs wheel angular speed and drive/brake torque derived from the input sensor data.

2. The tire state estimation system of claim 1, further comprising:

a roll and pitch angle estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the roll and pitch angle estimator being operable to generate a roll angle estimation and a pitch angle estimation from the input sensor data;

an acceleration bias compensation estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the acceleration bias compensation estimator being operable to generate bias-compensated acceleration data from the roll estimation, the pitch estimation and the input sensor data;

a center of gravity estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the center of gravity estimator being operable to generate a center of gravity height estimation from the roll angle estimation, the pitch angle estimation and the input sensor data;

a tire rolling radius estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the tire rolling radius estimator being operable to generate a tire rolling radius estimation from the input sensor data;

a mass estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the mass estimator being operable to generate a vehicle mass estimation from the tire longitudinal force estimation and a road grade angle input;

a center of gravity longitudinal position estimator in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the center of gravity longitudinal position estimator being operable to generate a vehicle longitudinal center of gravity estimation; and

a yaw inertia adaptation model in electronic communication with the CAN-bus and receiving the input sensor data from the sensors, the yaw inertia adaptation model being operable to generate a yaw inertia output from the vehicle mass estimation.

3. The tire state estimation system of claim 2, wherein the longitudinal force estimator is operable to generate the tire longitudinal force estimation from the tire rolling radius estimation, an engine torque input, and a braking torque input.

4. The tire state estimation system of claim 2, wherein the normal force estimator is operable to generate the normal force on the tire estimation from the center of gravity height estimation, the center of gravity longitudinal position estimation and the vehicle mass estimation.

5. The tire state estimation system of claim 2, wherein the lateral force estimator is operable to generate the lateral force on the tire from the input sensor data including a measured lateral acceleration, a measured longitudinal acceleration and the yaw rate.

6. The tire state estimation system of claim 5, further comprising:

an axle force estimator in electronic communication with the CAN-bus, the axle force estimator being operable to generate a lateral force estimation from the vehicle mass estimation, the yaw inertia output, the tire dynamic load estimation, the center of gravity longitudinal position estimation, the bias-compensated acceleration data, a steering wheel angle input, a yaw rate input and the tire dynamic load estimation.

7. The tire state estimation system of claim 2, wherein the acceleration and angular velocities, the pitch rate, the yaw rate and the roll rate are generated from a six degree inertial measuring unit mounted to the vehicle.

8. The tire state estimation system of claim 2, wherein the roll and pitch angle estimator is based upon a kinematics model of the vehicle.

9. The tire state estimation system of claim 2, wherein the center of gravity estimator is based upon a one degree of freedom roll model employing a recursive least squares algorithm.

10. The tire state estimation system of claim 2, the tire longitudinal force estimator is based upon an application of a wheel dynamics model using as model inputs the wheel angular speed and a measured drive and brake torque.