Predictive speed control for a motor vehicle

• US 20040068359A1
• Filed: 10/04/2002
• Published: 04/08/2004
• Est. Priority Date: 10/04/2002
• Status: Active Grant

• Current Assignee: Daimler AG (Mercedes-Benz Group AG)
• Original Assignee: Daimler Chrysler Company LLC (Stellantis NV)
• Inventors: Neiss, Konstantin, Connolly, Thomas, Terwen, Stephan
• Granted Patent: US 6,990,401 B2
• Time in Patent Office: Days
• US Class Current: 701/96
• CPC Class Codes: B60K 31/0058 responsive to externally generated signalling
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• 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: G05B 13/048 using a predictor
• CPC Class Codes: Y02T 10/40 Engine management systems

Abstract

A predictive cruise control system utilizes information about the current vehicle position, as well as upcoming terrain in order to save fuel and increase driving comfort. A vehicle operating cost function is defined, based on a plurality of environmental parameters, vehicle parameters, vehicle operating parameters and route parameters. As the vehicle travels over a particular route for which route parameters, such as road gradient and curvature, are stored in a road map, sensors aboard the vehicle detect environmental and vehicle operating parameters, including at least vehicle speed and its position relative to the road map. As the vehicle proceeds, an onboard computer iteratively calculates and stores in a memory vehicle control parameters that optimize the vehicle operating cost function for a predetermined Prediction Horizon along the route ahead of the vehicle. The optimal vehicle control parameters for the Prediction Horizon are then stored in a memory and continuously updated and replaced by new data as the vehicle moves along, thereby adjusting the “optimal” control parameters to reflect actual vehicle historical operating experience during the journey. The vehicle is then controlled by reading the optimized updated vehicle control parameters from the memory, corresponding to the current position of the vehicle.

Claims

1. A method for controlling operation of a vehicle,

defining an analytic vehicle operating cost function based on a plurality of environmental parameters, vehicle parameters, vehicle operating parameters and route parameters;

sensing said environmental and vehicle operating parameters as the vehicle travels a route for which route parameters are stored in a road map, said vehicle operating parameters including at least vehicle speed and vehicle position relative to said road map;

as the vehicle travels said route, iteratively calculating and storing in a memory, vehicle control parameters that minimize said vehicle operating cost function for a predetermined distance along said route ahead of said vehicle, as a function of at least vehicle speed, vehicle position and route parameters stored in said road map;

reading from said memory optimized vehicle control parameters corresponding to a current position of said vehicle; and

controlling current vehicle operation based on said optimized vehicle control parameters.

2. The method according to claim 1, wherein said route parameters include at least road gradient and radius of curvature.

3. The method according to claim 1, wherein:

said vehicle has an adaptive cruise control system;

said vehicle control parameters include at least a desired vehicle speed; and

said vehicle control parameters are input to said adaptive cruise control system for controlling vehicle operation.

4. The method according to claim 1, wherein said vehicle position is determined based on input signals from a GPS system, vehicle speed and route data stored in said road map.

5. The method according to claim 1 wherein said vehicle operating cost function is based on a mathematical model of vehicle dynamics for a vehicle travelling on a road.

6. The method according to claim 5, wherein said mathematical model is based on the relationship

7. The method according to claim 6, wherein Fi comprises at least forces exerted by the vehicle engine, vehicle brakes, and drag, and forces exerted by road gradient and friction.

8. The method according to claim 1, wherein said cost function comprises a desired vehicle speed range and imposes a cost penalty based on an extent to which the vehicle speed exceeds an upper or lower limit of said speed range.

9. The method according to claim 5, wherein said cost function comprises a desired vehicle speed range and imposes a cost penalty based on an extent to which( the vehicle speed exceeds an upper or lower limit of said speed range.

10. The method according to claim 1, wherein said cost function includes vehicle fuel consumption as a function of vehicle speed, road gradient and throttle position.

11. The method according to claim 5, wherein said cost function includes vehicle fuel consumption as a function of vehicle speed, road gradient and throttle position.

12. The method according to claim 1, wherein the cost function J is defined by

13. The method according to claim 1, wherein:

said operating cost function provides an analytic calculation of vehicle operating cost based on said parameters; and

parameters which minimize said analytically calculated vehicle operating cost for said predetermined distance are stored in said memory.

14. Apparatus for controlling operation of a vehicle, comprising:

sensors for sensing vehicle operating parameters, including at least vehicle speed and position; and

a predictive cruise control module which determines optimum vehicle control parameters that minimize vehicle operating costs defined by an analytic vehicle operating cost function based on said vehicle operating parameters and environmental, vehicle and route parameters and supplies said optimum vehicle control parameters to a vehicle controller that controls at least an engine operating parameter of said vehicle as a function thereof;

wherein said vehicle control parameters comprise at least a desired vehicle speed, for operation of said controller.

15. The apparatus according to claim 14, wherein said predictive cruise control module comprises:

a first memory having stored therein a road map including route parameters that characterize routes within a vehicle operating area;

a data processor programmed to calculate said optimum vehicle control parameters, based on said cost function, said vehicle operating parameters, said route parameters and an optimization algorithm stored therein; and

a second memory for storing a lookup table containing optimizing vehicle control parameters calculated by said data processor for a prediction horizon extending a predetermined distance ahead of said vehicle along a traveled route, said lookup table being accessible as a function of an estimated position of said vehicle.

16. The apparatus according to claim 14, wherein said route parameters include at least road gradient and radius of curvature.

17. The apparatus according to claim 15, wherein said second memory comprises a ring buffer memory for storing iteratively calculated values of said vehicle control parameters, said ring buffer memory having a capacity to store information for a plurality of integration intervals included in said prediction horizon.

18. The apparatus according to claim 17, wherein:

said ring buffer memory is divided into a plurality of frames which collectively correspond to said prediction horizon, each frame including a predetermined number of cells corresponding to said integration interval; and

said processor commences a new iteration of said optimization algorithm in synchronism with a beginning of each frame.

19. The apparatus according to claim 15, wherein said position estimator unit determines said vehicle position based on input signals from a GPS system, and vehicle speed and route parameters stored in said road map.

20. The method according to claim 19, wherein said vehicle operating cost function is based on a mathematical model of vehicle dynamics for a vehicle travelling on a road.

21. The method according to claim 20, wherein said mathematical model is based on the relationship

22. The method according to claim 21, wherein Fi comprises at least forces exerted by the vehicle engine, vehicle brakes and drag, and forces exerted by road gradient and friction.

23. The method according to claim 20, wherein said cost function comprises a desired vehicle speed range and imposes a cost penalty based on an extent to which the vehicle speed exceeds an upper limit or a lower limit of said speed range.

24. The method according to claim 20, wherein said cost function includes vehicle fuel consumption as a function of vehicle speed, road gradient and throttle position.

25. The method according to claim 14, wherein the cost function J is defined by

26. The method according to claim 14, wherein:

said operating cost function provides an analytic calculation of vehicle operating cost based on said parameters; and

parameters which minimize said analytically calculated vehicle operating cost for said predetermined distance are stored in said memory.

27. For a vehicle having an adaptive cruise control module that controls at least a throttle position of said vehicle as a function of vehicle control parameters, and sensors for sensing vehicle operating parameters including at least vehicle speed and position, apparatus comprising:

a predictive cruise control module which iteratively determines and updates optimum vehicle control parameters that minimize vehicle operating costs defined by an analytic vehicle operating cost function, based on said vehicle operating parameters and environmental, vehicle and route parameters;

wherein said vehicle control parameters comprise a desired vehicle speed, a desired vehicle throttle position and a controller gain value, which vehicle control parameters are input to said adaptive cruise controller for controlling at least said throttle position of said vehicle.

28. The apparatus according to claim 27, wherein said predictive cruise control module comprises:

a position estimator unit;

a first memory having stored therein a road map including route parameters that characterize routes within a vehicle operating area;

a data processor programmed to calculate said optimizing vehicle control parameters, based on said cost function, said vehicle operating parameters, said route parameters and an optimization algorithm stored therein; and

a second memory for storing a lookup table containing optimizing vehicle control parameters calculated by said data processor for a prediction horizon extending a predetermined distance ahead of said vehicle along a traveled route, said lookup table being accessible as a function of position of said vehicle determined by said position estimator unit.

29. The apparatus according to claim 27, wherein said route parameters include at least road gradient at radius of curvature.

30. The apparatus according to claim 28, wherein said second memory comprises a ring buffer memory for storing and continuously updating iteratively calculated values of said vehicle control parameters, said ring buffer memory having a capacity to store information for a plurality of integration intervals included in said prediction horizon.

31. The apparatus according to claim 30, wherein:

said ring buffer memory is divided into a plurality of frames which collectively correspond to said prediction horizon, each frame including a predetermined number of cells corresponding to said integration interval; and

said processor commences a new iteration of said optimization algorithm in synchronism with the beginning of each frame, or when said set speed changes.

32. The apparatus according to claim 28, wherein said position estimator unit determines said vehicle position based on input signals from a GPS system, vehicle speed and route parameters stored in said road map.

33. The method according to claim 32, wherein said vehicle operating cost function is based on a mathematical model of vehicle dynamics for a vehicle travelling on a road.

34. The method according to claim 33, wherein said mathematical model is based on the relationship

35. The method according to claim 34, wherein Fi comprises at least forces exerted by the vehicle engine, brakes and drag, and forces exerted by road gradient and friction.

36. The method according to claim 33, wherein said cost function comprises a desired vehicle speed range and imposes a cost penalty based on an extent to which vehicle speed exceeds an upper or lower limit of said speed range.

37. The method according to claim 33, wherein said cost function includes vehicle fuel consumption as a function of vehicle speed, road gradient and throttle position.

38. The method according to claim 27, wherein the cost function J is defined by

39. The method according to claim 27, wherein:

said operating cost function provides an analytic calculation of vehicle operating cost based on said parameters; and

parameters which minimize said analytically calculated vehicle operating cost for said predetermined distance are stored in said memory.