System and method for detection of spun vehicle

• US 8,412,435 B2
• Filed: 10/08/2007
• Issued: 04/02/2013
• Est. Priority Date: 10/08/2007
• Status: Expired due to Fees

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Maitlen, Daniel S.
• Primary Examiner(s): Nguyen, John Q
• Assistant Examiner(s): NGUYEN, CHUONG P
• Application Number:
  US11/868,807
• Publication Number:
  US 20090093991A1
• Time in Patent Office: 2,003 Days
• Field of Search: 701/1, 701/36, 701/38, 701 69- 77, 701/80, 701/82, 701 88- 92, 303/121, 303/139, 303/140, 303/143, 303146-150, 303163-175, 180/197
• US Class Current: 701/82
• CPC Class Codes: B60G 17/0165 to an external condition, e.g. rough road surface, side wind
• CPC Class Codes: B60G 2400/0523 Yaw rate
• CPC Class Codes: B60G 2400/822 Road friction coefficient determination affecting wheel traction
• CPC Class Codes: B60G 2400/8222 Hydroplaning
• CPC Class Codes: B60G 2800/016 Yawing condition
• CPC Class Codes: B60G 2800/212 Transversal; Side-slip during cornering
• CPC Class Codes: B60G 2800/702 Improving accuracy of a sensor signal
• CPC Class Codes: B60G 2800/912 Attitude Control; levelling control
• CPC Class Codes: B60T 2210/12 Friction
• 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 40/11 Pitch movement
• CPC Class Codes: B60W 40/112 Roll movement
• CPC Class Codes: B60W 40/114 Yaw movement

Abstract

A system, method and computer program product is provided for detecting if a vehicle has spun. A normal force and a lateral force of each of a front and rear axle of a vehicle is estimated. A coefficient of friction representative of a surface is estimated. Lateral momenta of the front and rear axles based on the coefficient of friction and the normal and lateral forces is calculated. Whether a surplus momentum is present, is determined. If the surplus momentum is present, a yaw rate of the vehicle is integrated respect to time to obtain a vehicle rotation estimation.

Claims

1. A computer-implemented method, comprising:

estimating a normal force and a lateral force of each of a front and rear axle of a vehicle;

estimating a tire-surface coefficient of friction;

calculating lateral momenta of the front and rear axles based on the coefficient of friction and the normal and lateral forces;

determining whether a surplus momentum is present; and

when the surplus momentum is present, integrating a yaw rate of the vehicle with respect to time to obtain a vehicle rotation estimation.

2. The method of claim 1, further including comparing the vehicle rotation estimation against a predetermined threshold to determine if the vehicle has spun.

3. The method of claim 2, wherein comparing the vehicle rotation estimation against a predetermined threshold includes setting a predetermined threshold of about 90 degrees relative to a velocity vector direction, and when the vehicle rotation estimation exceeds the predetermined threshold, detecting that the vehicle has spun.

4. The method of claim 1, wherein estimating a normal force and a lateral force of front and rear axles of a vehicle includes applying estimation equations according to

F_zf=mg−

m(Ag−

Ca)/(A+B),

F_zr=m(Ag−

Ca_long)/(A+B),

F_yf=ma_lat−

(Ama_lat−

Iα

)/(A+B), and

F_yr=(Ama_lat−

Iα

)/(A+B),

where F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles,

A is a horizontal distance from the front axle to a vehicle center of gravity,

B is a horizontal distance from the rear axle to the vehicle center of gravity,

C is a vertical distance from ground to the vehicle center of gravity,

g is acceleration due to gravity, m is vehicle mass, I is vehicle inertia,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

α

is an angular acceleration of the vehicle about the vehicle center of gravity.

5. The method of claim 1, wherein estimating a coefficient of friction includes applying an estimation equation according to

μ

=SQRT[(a_long²+a_lat²)/g],

where μ

is the coefficient of friction,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

g is acceleration due to gravity.

6. The method of claim 1, wherein calculating lateral momenta of the front and rear axles based on the normal and lateral forces, and the coefficient includes applying estimation equations according to

M_yf=∫

max(F_yf−

F_zf·

μ

,0)dt, and

M_yr=∫

max(F_yr−

F_zr·

μ

,0)dt

where, M_yf and M_yr are the lateral momenta of the front and rear axles,

F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles, and

μ

is the coefficient of friction.

7. The method of claim 1, wherein determining whether a surplus momentum is present includes comparing the lateral momenta at the front and rear axles with a threshold value based on the coefficient of friction, wherein when either the front lateral momentum or the rear lateral momentum exceed the threshold, a surplus of momentum for the surface is detected.

8. A system for determining whether a vehicle is spun, comprising:

a processor having a plurality of sensors configured to receive a plurality of dynamic parameters of a vehicle, the processor configured to;

estimate a normal force and a lateral force of each of a front and rear axle of a vehicle,

estimate a tire-surface coefficient of friction,

calculate lateral momenta of the front and rear axles based on the coefficient of friction and the normal and lateral forces,

determine whether a surplus momentum is present, and

when the surplus momentum is present, integrate a yaw rate of the vehicle with respect to time to obtain a vehicle rotation estimation.

9. The system of claim 8, wherein the processor is further configured to compare the vehicle rotation estimation against a predetermined threshold to determine if the vehicle has spun.

10. The system of claim 9, wherein the processor is further configured to set a predetermined threshold of about 90 degrees relative to a velocity vector direction, and when the vehicle rotation estimation exceeds the predetermined threshold, detect that the vehicle has spun.

11. The system of claim 8, wherein the processor is configured to apply normal force and lateral force estimation equations according to

F_zf=mg−

m(Ag−

Ca)/(A+B),

F_zr=m(Ag−

Ca_long)/(A+B),

F_yf=ma_lat−

(Ama_lat−

Iα

)/(A+B), and

F_yr=(Ama_lat−

Iα

)/(A+B),

where F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles,

A is a horizontal distance from the front axle to a vehicle center of gravity,

B is a horizontal distance from the rear axle to the vehicle center of gravity,

C is a vertical distance from ground to the vehicle center of gravity,

g is acceleration due to gravity, m is vehicle mass, I is vehicle inertia,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

α

is an angular acceleration of the vehicle about the vehicle center of gravity.

12. The system of claim 8, wherein the processor is configured to apply a surface estimation equation according to

μ

=SQRT[(a_long²+a_lat²)/g],

where μ

is the coefficient of friction,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

g is acceleration due to gravity.

13. The system of claim 8, wherein the processor is configured to apply lateral momenta estimation equations according to

M_yf=∫

max(F_yf−

F_zr·

μ

,0)dt, and

M_yr=∫

max(F_yr−

F_zr·

μ

,0)dt

where M_yf and M_yr are the lateral momenta of the front and rear axles,

F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles, and

μ

is the coefficient of friction.

14. The system of claim 8, wherein the processor is configured to compare the lateral momenta at the front and rear axles with a threshold value based on the coefficient of friction, wherein when either the front lateral momentum or the rear lateral momentum exceed the threshold, a surplus of momentum for the surface is detected.

15. A computer program product for determining if a vehicle is spun, the computer program product comprising a computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

a first executable portion for estimating a normal force and a lateral force of each of a front and rear axle of a vehicle;

a second executable portion for estimating a tire-surface coefficient of friction;

a third executable portion for calculating lateral momenta of the front and rear axles based on the coefficient of friction and the normal and lateral forces;

a fourth executable portion for determining whether a surplus momentum is present; and

a fifth executable portion for, when the surplus momentum is present, integrating a yaw rate of the vehicle with respect to time to obtain a vehicle rotation estimation.

16. The computer program product of claim 15, further including a sixth executable portion for comparing the vehicle rotation estimation against a predetermined threshold to determine if the vehicle has spun.

17. The computer program product of claim 16, wherein the sixth executable portion for comparing the vehicle rotation estimation against a predetermined threshold includes computer-readable program code for setting a predetermined threshold of about 90 degrees relative to a velocity vector direction, and when the vehicle rotation estimation exceeds the predetermined threshold, detecting that the vehicle has spun.

18. The system of claim 15, wherein the first executable portion for estimating a normal force and a lateral force of front and rear axles of a vehicle includes computer-readable program code for applying estimation equations according to

F_zf=mg−

m(Ag−

Ca)/(A+B),

F_zr=m(Ag−

Ca_long)/(A+B),

F_yf=ma_lat−

(Ama_lat−

Iα

)/(A+B), and

F_yr=(Ama_lat−

Iα

)/(A+B),

where F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles,

A is a horizontal distance from the front axle to a vehicle center of gravity,

B is a horizontal distance from the rear axle to the vehicle center of gravity,

C is a vertical distance from ground to the vehicle center of gravity,

g is acceleration due to gravity, m is vehicle mass, I is vehicle inertia,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

α

is an angular acceleration of the vehicle about the vehicle center of gravity.

19. The system of claim 15, wherein the second executable portion for estimating a coefficient of friction includes computer-readable program code for applying an estimation equation according to

μ

=SQRT[(a_long²+a_lat²)/g],

where μ

is the coefficient of friction,

a_long is a longitudinal acceleration of the vehicle center of gravity,

a_lat is a lateral acceleration of the vehicle center of gravity, and

g is acceleration due to gravity.

20. The system of claim 15, wherein the third executable portion for calculating lateral momenta of the front and rear axles based on the normal and lateral forces, and the coefficient includes computer-readable program code for applying estimation equations according to

M_yf=∫

max(F_yf−

F_zf·

μ

,0)dt, and

M_yr=∫

max(F_yr−

F_zr·

μ

,0)dt

where M_yf and M_yr are the lateral momenta of the front and rear axles,

F_zf and F_zr are the normal forces of the front and rear axles,

F_yf, and F_yr are the lateral forces of the front and rear axles, and

μ

is the coefficient of friction.

21. The system of claim 15, wherein the fourth executable portion for determining whether a surplus momentum is present includes computer-readable program code for comparing the lateral momenta at the front and rear axles with a threshold value based on the coefficient of friction, wherein when either the front lateral momentum or the rear lateral momentum exceed the threshold, a surplus of momentum for the surface is detected.