VEHICLE DISTURBANCE ESTIMATOR AND METHOD

• US 20100049400A1
• Filed: 08/22/2008
• Published: 02/25/2010
• Est. Priority Date: 08/22/2008
• Status: Active Grant

• Current Assignee: Daimler Trucks North America LLC (Mercedes-Benz Group AG)
• Original Assignee: Daimler Trucks North America LLC (Mercedes-Benz Group AG)
• Inventors: Reckels, Dieter, Duraiswamy, Shivkumar
• Granted Patent: US 8,700,256 B2
• Time in Patent Office: Days
• US Class Current: 701/35
• CPC Class Codes: B60W 2530/10 Weight
• CPC Class Codes: B60W 2552/20 Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: Y02T 10/40 Engine management systems
• CPC Class Codes: Y02T 10/84 Data processing systems or methods, management, administration

Abstract

A Vehicle Disturbance Estimator determines estimates of a vehicle disturbance force according to vehicle operating conditions. The determined vehicle disturbance force estimate can be used, for example, in connection with controlling a cruise control system for the vehicle, in connection with fuel economy evaluations and testing, and in connection with vehicle diagnostics. A plurality of sets of inputs can be used to determine plural vehicle disturbance estimates for time periods during which a cruise control is on, the vehicle is being driven in the highest gear, and the vehicle is not being braked by any brakes. The plurality of vehicle disturbance estimates can be averaged to provide an output corresponding to an average vehicle disturbance estimate over a plurality of sampling time periods. Kalman filtering can be used to determine the vehicle disturbance estimates. Signals corresponding to the plural disturbance estimates can be provided as an input to a cruise control, with the cruise control then being operable to control the speed of the motor vehicle, based at least in part upon the vehicle disturbance estimate.

Claims

1. A vehicle disturbance estimator for a motor vehicle, the motor vehicle comprising a cruise control, a plurality of gears, at least one brake, and a vehicle bus for carrying plural signals corresponding to motor vehicle parameters, the vehicle disturbance estimator comprising:

a microprocessor comprising first, second and third sets of inputs;

the first set of inputs comprising inputs corresponding to first parameters of the motor vehicle, the first parameters comprising;

Gross Vehicle Mass;

Static Wheel Radius;

Nominal Drag Coefficient;

Nominal Rolling Resistance Coefficient; and

Vehicle Frontal Area;

the second set of inputs comprising inputs corresponding to second parameters of the motor vehicle, the second parameters comprising;

Engine Brake State;

Engine Torque;

Engine Speed;

Wheel Based Vehicle Speed; and

Service Brake State;

the third set of inputs comprising inputs corresponding to the grade of the road being travel by the motor vehicle;

the microprocessor being operable to process the first, second and third sets of inputs to determine plural vehicle disturbance estimates for time periods during which the following conditions exist;

the cruise control is on, the vehicle is being driven in the highest gear, and the vehicle is not being braked by any brakes;

the microprocessor providing signals corresponding to the plural vehicle disturbance estimates; and

memory for storing the signals corresponding to the plural vehicle disturbance estimates.

2. A vehicle disturbance estimator according to claim 1 wherein the second set of inputs comprise inputs from the vehicle bus.

3. A vehicle disturbance estimator according to claim 1 wherein all of the second set of inputs are inputs from the vehicle bus.

4. A vehicle disturbance estimator according to claim 1 wherein the first set of inputs comprises inputs corresponding to first parameters that further comprise:

Engine and Flywheel Inertia;

Total Wheel Inertia;

Transmission Efficiency per Gear; and

Rear Axle Efficiency per Gear; and

wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise;

Fan Drive State; and

Friction Torque.

5. A vehicle disturbance estimator according to claim 1 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise:

Bunk Blower Fan State;

Cab Blower Fan State;

Air Conditioning Compressor State;

Non-Driven Wheel Speed;

Transmission Driveline Engaged;

Engine Percent Load at Current Speed;

Transmission Current Gear;

Longitudinal Acceleration;

Estimated Engine Parasitic Losses—

Percent Torque for fan and fuel pump;

Barometric Pressure; and

Ambient Air Temperature.

6. A vehicle disturbance estimator according to claim 5 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise:

Transmission Shift in Process;

Transmission Output Shaft Speed; and

Transmission Input Shaft Speed.

7. A vehicle disturbance estimator according to claim 5 wherein the second set of inputs comprise inputs from the vehicle bus corresponding to second parameters that further comprise the Transmission Actual Gear Ratio.

8. A vehicle disturbance estimator according to claim 5 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise the clutch shift status or state.

9. A vehicle disturbance estimator according to claim 5 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise:

Windshield Wiper State;

Transmission Driveline Engaged;

Transmission Shift in Process;

Transmission Output Shaft Speed;

Transmission Input Shaft Speed;

Transmission Actual Gear Ratio;

Transmission Current Gear; and

The Clutch Switch State.

10. A vehicle disturbance estimator according to claim 1 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprise the Clutch Switch State.

11. A vehicle disturbance estimator according to claim 1 wherein the second set of inputs comprise inputs corresponding to second parameters that further comprises the Fuel Rate.

12. A vehicle disturbance estimator according to claim 1 wherein the first set of inputs comprises inputs corresponding to the first parameters that further comprise:

Truck Type;

Truck Model;

Truck Configuration;

Transmission Type;

Rear Axle Type;

Tractor-Trailer Gap;

Tire Pressure and Temperature;

Wind Direction and Velocity; and

Road Surface Condition.

13. A vehicle disturbance estimator according to claim 5 wherein the first set of inputs comprises inputs corresponding to first parameters that further comprise:

Truck Type;

Truck Model;

Truck Configuration;

Transmission Type;

Rear Axle Type;

Tractor-Trailer Gap;

Tire Pressure and Temperature;

Wind Direction and Velocity; and

Road Surface Condition.

14. A vehicle disturbance estimator according to claim 7 wherein the first set of inputs comprises inputs corresponding to first parameters that further comprise:

Truck Type;

Truck Model;

Truck Configuration;

Transmission Type;

Rear Axle Type;

Tractor-Trailer Gap;

Tire Pressure and Temperature;

Wind Direction and Velocity; and

Road Surface Condition.

15. A vehicle disturbance estimator according to claim 9 wherein the first set of inputs comprise inputs corresponding to first parameters that further comprise:

Truck Type;

Truck Model;

Truck Configuration;

Transmission Type;

Rear Axle Type;

Tractor-Trailer Gap;

Tire Pressure and Temperature;

Wind Direction and Velocity; and

Road Surface Condition.

16. A vehicle disturbance estimator according to claim 1 wherein the microprocessor is operable to apply Kalman filtering to the first, second and third inputs to determine the vehicle disturbance estimates.

17. A vehicle disturbance estimator according to claim 1 wherein the microprocessor is operable to determine an average vehicle disturbance estimate from a plurality of vehicle disturbance estimates.

18. A vehicle disturbance estimator according to claim 1 wherein each of the vehicle disturbance estimates corresponds to a vehicle disturbance estimate for a sampling time period.

19. A vehicle disturbance estimator according to claim 18 wherein the microprocessor is operable to average signals corresponding to plural vehicle disturbance estimates to provide an output corresponding to an average vehicle disturbance estimate over a plurality of sampling time periods.

20. A vehicle disturbance estimator according to claim 19 wherein the average vehicle disturbance estimate comprises an input to the cruise control, the cruise control being operable to control the speed of the motor vehicle based in part upon the average vehicle disturbance estimate.

21. A vehicle disturbance estimator according to claim 1 wherein signals corresponding to the stored signals comprise an input to the cruise control, the cruise control being operable to control the speed of the motor vehicle based in part upon the output signals.

22. A vehicle disturbance estimator according to claim 21 wherein the signals corresponding to the stored signals comprise signals corresponding to averages of plural vehicle disturbance estimates.

23. A vehicle disturbance estimator for a motor vehicle, the motor vehicle comprising a cruise control, a plurality of gears, at least one brake, and a vehicle bus for carrying plural signals corresponding to motor vehicle parameters, the vehicle disturbance estimator comprising:

a microprocessor comprising first, second and third sets of inputs;

the first set of inputs comprising inputs corresponding to first parameters of the motor vehicle, the first parameters comprising;

Gross Vehicle Mass;

Static Wheel Radius;

Nominal Drag Coefficient;

Nominal Rolling Resistance Coefficient; and

Vehicle Frontal Area;

the second set of inputs comprising inputs corresponding to second parameters of the motor vehicle, the second parameters comprising;

Engine Brake State;

Engine Torque;

Engine Speed;

Wheel Based Vehicle Speed; and

Service Brake State.

the third set of inputs comprising inputs corresponding to the grade of the road being travel by the motor vehicle;

the microprocessor being operable to process the first, second and third sets of inputs to determine plural vehicle disturbance estimates for time periods during which the following conditions exist;

the cruise control is on, the vehicle is being driven in the highest gear, and the vehicle is not being braked by any brakes;

the microprocessor providing signals corresponding to the plural vehicle disturbance estimates; and

wherein the signals corresponding to the plural vehicle disturbance estimates are provided as an input to the cruise control, the cruise control being operable to control the speed of the motor vehicle based at least in part upon the vehicle disturbance estimates.

24. A method of operating a motor vehicle comprising:

determining vehicle disturbance estimates, the vehicle disturbance estimates being determined for the periods corresponding to the vehicle being driven in the top gear;

the vehicle having cruise control that is on and the vehicle brakes not being applied to the vehicle;

delivering signals corresponding to the vehicle disturbance estimates as an input to a cruise control;

controlling the operation of the cruise control based in part upon the vehicle disturbance estimates.

25. A method according to claim 24 wherein vehicle disturbance estimates comprise a lumped signal corresponding to plural forces acting along the longitudinal axis of the motor vehicle.

26. A method according to claim 25 wherein the plural forces correspond at least in part to lumped contributions of rolling resistance forces and wind forces determined in real time.

27. A method according to claim 25 wherein the plural forces correspond at least in part to forces retarding the acceleration of the vehicle arising from the operation of one or more auxiliary components of the motor vehicle.

28. A method according to claim 27 wherein the auxiliary components comprise an engine cooling fan of the vehicle.

29. A method according to claim 28 wherein the auxiliary components also comprise one or more of cab and bunk blowers and vehicle air conditioning compressor.

30. A method according to claim 24 wherein the act of delivering signals comprises delivering signals corresponding to the average of a plurality of vehicle disturbance estimates.

31. A method according to claim 24 comprising using Kalman filtering to determine the vehicle disturbance estimates.

32. A method of diagnosing the operation of a motor vehicle having cruise control comprising:

operating the motor vehicle;

computing vehicle disturbance estimates as the vehicle is operated;

the vehicle disturbance estimates being computed when the vehicle is being driven in the top gear, cruise control is on and the vehicle is not being braked; and

diagnosing motor vehicle performance based upon computed vehicle disturbance estimates.

33. A method of evaluating fuel efficiency tests comprising:

conducting one fuel efficiency test run of a motor vehicle over a route;

computing at least a first vehicle disturbance estimate for said one fuel efficiency test run;

conducting another fuel efficiency test run of a motor vehicle over the route;

computing at least a second vehicle disturbance estimate for said another fuel efficiency test run;

discarding the results of a fuel efficiency test run when the vehicle disturbance estimate for the test run exceeds a threshold.

34. A method according to claim 33 wherein the first and second vehicle disturbance estimates each comprise an average of a plurality of vehicle disturbance estimates over the associated test run.