PREDICTIVE ENERGY MANAGEMENT CONTROL SCHEME FOR A VEHICLE INCLUDING A HYBRID POWERTRAIN SYSTEM

• US 20110066308A1
• Filed: 09/16/2009
• Published: 03/17/2011
• Est. Priority Date: 09/16/2009
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations Incorporated (Motors Liquidation Co. GUC Trust)
• Inventors: Yang, Hong, Maguire, Joel M.
• Granted Patent: US 8,825,243 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60L 2240/421 Speed
• CPC Class Codes: B60L 2240/423 Torque
• CPC Class Codes: B60L 2240/441 Speed
• CPC Class Codes: B60L 2240/443 Torque
• CPC Class Codes: B60L 2240/445 Temperature
• CPC Class Codes: B60W 10/06 including control of combustion engines
• CPC Class Codes: B60W 10/08 including control of electric propulsion units, e.g. motors or generators
• CPC Class Codes: B60W 10/26 for electrical energy, e.g. batteries or capacitors
• CPC Class Codes: B60W 20/00 Control systems specially adapted for hybrid vehicles hybrid vehicle design, B60K6/00; electric vehicles B60L
• CPC Class Codes: B60W 20/11 using model predictive control [MPC] strategies, i.e. control methods based on models predicting performance utilising navigation and traffic information in the control strategy B60W20/12
• CPC Class Codes: B60W 20/12 using control strategies taking into account route information estimation or calculation of non-directly measurable driving parameters B60W40/00
• CPC Class Codes: B60W 2510/0638 Engine speed
• CPC Class Codes: B60W 2510/0657 Engine torque
• CPC Class Codes: B60W 2510/0676 Engine temperature
• CPC Class Codes: B60W 2510/081 Speed
• CPC Class Codes: B60W 2510/083 Torque
• CPC Class Codes: B60W 2510/244 Charge state
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2540/10 Accelerator pedal position
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2554/00 : Input parameters relating to objects
• CPC Class Codes: B60W 2556/50 : of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2710/0644 : Engine speed
• CPC Class Codes: B60W 2710/0666 : Engine torque
• CPC Class Codes: B60W 2710/083 : Torque
• CPC Class Codes: B60W 50/0097 : Predicting future conditions
• CPC Class Codes: Y02T 10/40 : Engine management systems
• CPC Class Codes: Y02T 10/62 : Hybrid vehicles
• CPC Class Codes: Y02T 10/64 : Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/84 : Data processing systems or methods, management, administration

Abstract

A method for controlling a vehicle having a hybrid powertrain includes monitoring vehicle navigation and traffic patterns associated with a predicted travel path. It extends the powertrain instantaneous controller into a predictive control framework, and utilizes previewed traffic and geographic information based on on-board sensing and navigation information. An impending road load is predicted from which a fuel cost factor is optimized under a model predictive control framework. A state-of-charge trajectory is predicted from the impending road load and operation of the hybrid powertrain system is controlled in response thereto.

Claims

1. Method for operating a vehicle including a hybrid powertrain system comprising an internal combustion engine operatively coupled to an input member of a hybrid transmission including a torque machine operative to exchange power with an energy storage device, the hybrid transmission configured to transfer torque among the input member, the torque machine and an output member, the method comprising:

monitoring vehicle navigation and traffic patterns associated with a predicted travel path for the vehicle;

predicting an impending road load associated with the vehicle navigation and traffic patterns;

estimating vehicle propulsion power associated with the predicted impending road load;

determining a desired state-of-charge trajectory for the energy storage device;

predicting a state-of-charge trajectory for the energy storage device corresponding to the estimated vehicle propulsion power and the desired state-of-charge trajectory for the energy storage device; and

controlling operation of the hybrid powertrain system in response to the predicted state-of-charge trajectory for the energy storage device.

2. The method of claim 1, further comprising:

determining boundary conditions associated with the predicted state-of-charge trajectory for the energy storage device; and

controlling operation of the hybrid powertrain system in response to a commanded output torque and the boundary conditions associated with the predicted state-of-charge trajectory for the energy storage device.

3. The method of claim 1, further comprising executing a load prediction control scheme to predict the impending road load associated with the vehicle navigation and traffic patterns to estimate the vehicle propulsion associated with the predicted travel path for the vehicle.

4. The method of claim 3, further comprising executing a predictive control scheme comprising a receding horizon control scheme to predict the impending road load associated with the vehicle navigation and traffic patterns.

5. The method of claim 4, further comprising:

optimizing a fuel cost factor associated with the impending road load; and

dynamically adjusting the predicted state-of-charge trajectory for the energy storage device based upon the optimized fuel cost factor.

6. The method of claim 4, wherein optimizing the fuel cost factor minimizes at least one of fuel cost and total power cost over the receding horizon.

7. The method of claim 6, wherein the model predictive control scheme comprises a power-based quasi-static model of total hybrid powertrain losses.

8. The method of claim 1, further comprising determining a preferred power split between a power output from the engine and a power output from the torque machine, the preferred power split based upon the predicted state-of-charge trajectory for the energy storage device.

9. The method of claim 1, wherein the desired state-of-charge trajectory comprises a charge-depletion trajectory.

10. The method of claim 1, wherein the desired state-of-charge trajectory comprises a charge-sustaining trajectory.

11. Method for operating a vehicle including a hybrid powertrain system comprising an internal combustion engine operatively coupled to an input member of a hybrid transmission including a torque machine operative to exchange power with an energy storage device, the hybrid transmission configured to transfer torque among the input member and the torque machine and an output member, the method comprising:

monitoring vehicle navigation, traffic patterns, and operator driving patterns associated with a predicted travel path for the vehicle;

monitoring an operator torque request associated with operator inputs to an operator interface for the vehicle;

predicting an impending road load associated with the vehicle navigation, traffic patterns, operator driving patterns, and the operator torque request;

estimating vehicle propulsion power associated with the predicted impending road load;

determining a desired state-of-charge trajectory for the energy storage device;

predicting a state-of-charge trajectory for the energy storage device corresponding to the estimated vehicle propulsion power and the desired state-of-charge trajectory for the energy storage device; and

controlling operation of the hybrid powertrain system in response to the predicted state-of-charge trajectory for the energy storage device and the operator torque request.

12. The method of claim 11, further comprising:

estimating a predictive fuel cost factor associated with the estimated vehicle propulsion power; and

determining a preferred power split between a power output from the engine and a power output from the torque machine associated with the predictive fuel cost factor.

13. The method of claim 12, further comprising:

determining an instantaneous fuel cost factor associated with the preferred power split between the power output from the engine and the power output from the torque machine; and

wherein determining the preferred power split between the power output from the engine and the power output from the torque machine is further associated with the instantaneous fuel cost factor.

14. Method for operating a vehicle including a hybrid powertrain system, comprising:

predicting a travel path for the vehicle;

monitoring vehicle navigation and traffic patterns associated with the predicted travel path;

predicting an impending road load associated with the vehicle navigation and traffic patterns associated with the predicted travel path;

estimating vehicle propulsion power associated with the predicted impending road load;

determining a desired state-of-charge trajectory for an energy storage device configured to supply power for vehicle propulsion;

predicting a state-of-charge trajectory for the energy storage device corresponding to the estimated vehicle propulsion power and the desired state-of-charge trajectory for the energy storage device; and

controlling operation of the hybrid powertrain system in response to the predicted state-of-charge trajectory for the energy storage device.

15. The method of claim 14, further comprising:

determining boundary conditions associated with the predicted state-of-charge trajectory for the energy storage device; and

controlling operation of the hybrid powertrain system in response to a commanded output torque, the predicted state-of-charge trajectory and the boundary conditions associated with the predicted state-of-charge trajectory for the energy storage device.

16. The method of claim 14, further comprising executing a load prediction control scheme to predict the impending road load associated with the vehicle navigation and traffic patterns to estimate the vehicle propulsion associated with the predicted travel path for the vehicle.

17. The method of claim 16, further comprising executing a model predictive control scheme comprising a receding horizon control scheme to predict the impending road load associated with the vehicle navigation and traffic patterns.

18. The method of claim 17, further comprising:

optimizing a fuel cost factor associated with the impending road load; and

dynamically adjusting the predicted state-of-charge trajectory for the energy storage device based upon the optimized fuel cost factor.

19. The method of claim 14, wherein the desired state-of-charge trajectory comprises a charge-depletion trajectory.

20. The method of claim 14, wherein the desired state-of-charge trajectory comprises a charge-sustaining trajectory.