Estimation of road inclination

• US 9,200,898 B2
• Filed: 04/03/2012
• Issued: 12/01/2015
• Est. Priority Date: 04/04/2011
• Status: Active Grant

• Current Assignee: Scania CV AB (Volkswagen AG)
• Original Assignee: Scania CV AB (Volkswagen AG)
• Inventors: Nilsson, Mattias, hlund, Erik
• Primary Examiner(s): Cheung, Calvin
• Assistant Examiner(s): SHUDY, ANGELINA M
• Application Number:
  US14/009,538
• Publication Number:
  US 20140032068A1
• Time in Patent Office: 1,337 Days
• Field of Search: 701/1, 701/51, 701/65, 701/99
• US Class Current: 1/1
• 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 2510/1005 Transmission ratio engaged
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2520/125 Lateral acceleration
• CPC Class Codes: B60W 2520/30 Wheel torque
• CPC Class Codes: B60W 2530/16 Driving resistance
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 40/076 Slope angle of the road
• CPC Class Codes: F16H 2059/663 Road slope
• CPC Class Codes: F16H 2061/0078 Linear control, e.g. PID, state feedback or Kalman
• CPC Class Codes: F16H 59/66 Road conditions, e.g. slope, slippery
• CPC Class Codes: G01C 9/00 Measuring inclination, e.g. by clinometers, by levels
• CPC Class Codes: G01C 9/06 Electric or photoelectric indication or reading means
• CPC Class Codes: G01C 9/08 Means for compensating acceleration forces due to movement of instrument

Abstract

A method and a system for estimating a road gradient α by using a sensor fusion: Detect whether at least one dynamic process is affecting the vehicle. Estimate gradient α by means of the sensor fusion by joint weighting of at least two input signals to the sensor fusion. The at least two input signals include a signal based on an accelerometer and an input signal based on at least one force equation. At least one of the input signals and/or at least one weighting parameter for the sensor fusion are determined on the basis of detecting whether the at least one dynamic process is affecting the vehicle.

Claims

1. A method for estimating a road gradient α

in a vehicle by using a sensor fusion comprising;

detecting whether at least one dynamic process is affecting said vehicle and outputting a detection result to at least one electronic control unit;

estimating said gradient a by conducting joint weighting of at least two input signals to said sensor fusion in said at least one electronic control unit, such that

said at least two input signals comprise an input signal based on an accelerometer received by said electronic control unit and an input signal based on at least one force equation received by said electronic control unit;

determining at least one of said input signal based on said accelerometer, said input signal based on said at least one force equation and at least one weighting parameter for said sensor fusion on the basis of said detection of whether said at least one dynamic process is affecting said vehicle; and

providing said road gradient α

to an automatic gear change system in said vehicle, said gear change system being configured to select a gear of an engine of said vehicle based at least in part on said road gradient α

,

wherein said dynamic process affects the reliability of at least one of said two input signals when used for estimating said road gradient α

.

2. The method according to claim 1, further comprising conducting said sensor fusion by means of a Kalman filter.

3. The method according to claim 2, further comprising causing said at least two input signals to serve as input signals to said Kalman filter and causing said at least one weighting parameter to serve as at least one covariance matrix for model noise Q of said Kalman filter.

4. The method according to claim 3, further comprising causing said Kalman filter to use a prediction that a next state road gradient will be equal to a current state road gradient.

5. The method according to claim 1, wherein said at least one dynamic process affecting said vehicle comprises at least a sharp turn.

6. The method according to claim 5, wherein said sharp turn comprises a smaller radius than a predetermined value.

7. The method according to claim 5, further comprising weighting said at least one of said at least two input signals for giving said input signal based on said force equation greater weight in said sensor fusion than said input signal based on said accelerometer when said detecting shows that said sharp turn is affecting said vehicle.

8. The method according to claim 1, wherein said at least one dynamic process comprises an acceleration change equal to or greater than 1 m/s².

9. The method according to claim 8, wherein said dynamic process occurs in one of the following situations:

acceleration from stationary; and

acceleration during gear change.

10. The method according to claim 8, wherein when said detecting step results in detection of said acceleration change;

weighting said at least one of said at least two input signals so that said input signal based on said accelerometer is given greater weight in said sensor fusion than said input signal based on said force equation; and

determining said at least one weighting parameter at a value such that a first sensitivity in the sensor fusion for said input signal is less than a second sensitivity for said input signal when no dynamic processes area affecting said vehicle.

11. The method according to claim 8, wherein at least said one dynamic process affects at least one of a position of a chassis and a suspension of a motor vehicle relative to a horizontal plane.

12. The method according to claim 1, wherein said dynamic process comprises a retardation change equal to or greater than 1 m/s².

13. The method according to claim 12, wherein said dynamic process occurs in one of the following situations:

retardation during gear change;

braking; and

braking to standstill.

14. The method according to claim 12, wherein when said detecting step results in detection of said retardation change,

weighting said at least one of said at least two input signals so that said input signal based on an accelerometer is given greater weight than said input signal based on said force equation;

and

determining said at least one weighting parameter at a value such that a first sensitivity in the sensor fusion for said input signal is less than a second sensitivity for said input signal when no dynamic processes are affecting said vehicle.

15. The method according to claim 1, wherein said dynamic process comprises braking during a turn.

16. The method according to claim 15, further comprising determining that said at least two input signals correspond to previous respective estimates of said road gradient if said dynamic process is detected.

17. The method according to claim 1, wherein said dynamic process comprises starting up and shutting down an engine.

18. The method according to claim 1, wherein when said detecting shows no dynamic process affecting said vehicle,

weighting said at least one of said at least two input signals so that said input signal based on an accelerometer is given greater weight than said input signal based on the force equation;

and

determining said at least one weighting parameter at a value such that a sensitivity in the sensor fusion for said input signal is adjusted to a noise level of said accelerometer.

19. The method according to claim 1, wherein said detecting is based on at least one of the following signals:

a brake signal;

a signal related to a vehicle speed;

a signal related to a radius of curvature; and

a signal related to gear choice.

20. The method according to claim 1, further comprising causing said sensor fusion to conduct joint weighting of a model with said at least two input signals, such that

said model is used in prediction of values corresponding to said at least two input signals;

and

said joint weighting of the model with said at least two input signals is based on a magnitude of measurement noise related to said at least one input signal.

21. The method according to claim 1, further comprising determining said at least one input signal is conducted by its weighting on the basis of a magnitude of measurement noise related to said at least one input signal.

22. The method according to claim 1, wherein said at least one dynamic process comprises at least one of the following:

a sharp turn,

an acceleration change equal to or greater than 1 m/s²,

a retardation change equal to or greater than 1 m/s²,

braking during a turn,

said engine starting and

said engine shutting down.

23. A system for gear choice in a motor vehicle, said system comprising:

a system for estimating a road gradient α

in a vehicle by using a sensor fusion, said system for estimating a road gradient α

comprising;

a detection device configured to detect whether at least one dynamic process is affecting said vehicle;

an estimation device configured to estimate said gradient α

by conducting joint weighting of at least two input signals to said sensor fusion, such that

said at least two input signals comprise an input signal based on an accelerometer and an input signal based on at least one force equation; and

said estimation device is configured to determine at least one of said input signal based on said accelerometer, said input signal based on said at least one force equation and at least one weighting parameter for said sensor fusion on the basis of said detection of whether said at least one dynamic process is affecting said vehicle.

24. The system for gear choice in a motor vehicle according to claim 23 further comprising:

a gear choice device configured for choosing gears of said vehicle on the basis of said gradient α

.

25. A non-transitory computer-readable medium comprising computer code contained in the computer readable medium, and which, when the program code is executed by a processor of at least one control unit, causes said at least one control unit to perform the method for estimating a road gradient α

in a vehicle by using a sensor fusion, the method comprising;

detecting whether at least one dynamic process is affecting said vehicle and outputting a detection result to at least one electronic control unit;

estimating said gradient a by conducting joint weighting of at least two input signals to said sensor fusion in said at least one electronic control unit, such that

said at least two input signals comprise an input signal based on an accelerometer received by said electronic control unit and an input signal based on at least one force equation received by said electronic control unit;

determining at least one of said input signal based on said accelerometer, said input signal based on said at least one force equation and at least one weighting parameter for said sensor fusion on the basis of said detection of whether said at least one dynamic process is affecting said vehicle; and

providing said road gradient α

to an automatic gear change system in said vehicle, said gear change system being configured to select a gear of an engine of said vehicle based at least in part on said road gradient α

,

wherein said dynamic process affects the reliability of at least one of said two input signals when used for estimating said road gradient α

.