Hybrid powertrain mode determination based on spatial domain route segmentation

• US 9,067,589 B1
• Filed: 02/28/2014
• Issued: 06/30/2015
• Est. Priority Date: 02/28/2014
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Zhao, Yanan, Liang, Wei, Kuang, Ming Lang
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): Dunn, Alex C
• Application Number:
  US14/193,558
• Time in Patent Office: 487 Days
• Field of Search: 701/22
• US Class Current: 1/1
• 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 20/12 using control strategies taking into account route information estimation or calculation of non-directly measurable driving parameters B60W40/00
• CPC Class Codes: B60W 20/13 in order to stay within battery power input or output limits; in order to prevent overcharging or battery depletion
• CPC Class Codes: B60W 2710/244 Charge state
• CPC Class Codes: Y02T 10/62 Hybrid vehicles
• CPC Class Codes: Y10S 903/93 Conjoint control of different elements

Abstract

A vehicle includes a powertrain having an engine and an electric machine, and a battery configured to power the electric machine. The vehicle further includes a controller programmed to operate the powertrain according to a forecasted torque allocation between the engine and the electric machine. The controller generates forecasted torque allocation for each of a plurality of predetermined route segments based on predicted driver demand. The forecasted torque allocation is confirmed for each of the route segments based on a target battery state of charge corresponding to an endpoint of the route segment while an actual state of charge is within a threshold value of the target battery state of charge.

Claims

1. A vehicle comprising:

a powertrain having an engine and an electric machine;

a battery configured to power the electric machine; and

a controller programmed to operate the powertrain according to a forecasted torque allocation between the engine and the electric machine (i) generated for each of a plurality of predetermined route segments based on predicted driver demand and (ii) confirmed for each of the route segments based on a target battery state of charge corresponding to an endpoint of the route segment while an actual state of charge is within a threshold value of the target battery state of charge.

2. The vehicle of claim 1 wherein each of the plurality of predetermined route segments are further defined by a startpoint and the endpoint corresponding to changes in predicted driver demand.

3. The vehicle of claim 2 wherein the controller is further programmed to forecast an activation of the engine during an electric machine powertrain mode in response to the predicted driver demand increasing to greater than a first predetermined threshold during one of the plurality of route segments.

4. The vehicle of claim 2 wherein the controller is further programmed to forecast a deactivation of the engine during a hybrid-electric powertrain mode in response to the predicted driver demand decreasing to less than a second predetermined threshold during one of the plurality of route segments.

5. The vehicle of claim 1 wherein the controller is further programmed to subdivide a route segment if a powertrain mode switch is forecasted during the route segment such that the subdivided route segment includes no powertrain mode switch.

6. The vehicle of claim 1 wherein the driver demand comprises at least one of a vehicle speed demand and a wheel power demand, and the forecasted torque allocation is based on the one of the vehicle speed demand or the wheel power demand that causes a longer engine-on duration during a route segment relative to the other of the vehicle speed demand or the wheel power demand.

7. The vehicle of claim 1 wherein the controller is further programmed to affirm an electric machine powertrain mode forecast for one of the plurality of route segments in response to vehicle speed being equal to zero at either a startpoint or the endpoint of the route segment.

8. The vehicle of claim 1 wherein the controller is further programmed to affirm an electric machine powertrain mode forecast for one of the plurality of route segments in response to a time duration of the route segment being less than a predetermined engine-on time threshold.

9. The vehicle of claim 1 wherein the controller is further programmed to affirm an electric machine powertrain mode forecast for one of the plurality of route segments in response to driver deceleration demand being greater than a predetermined braking threshold.

10. The vehicle of claim 1 wherein the controller is further programmed to affirm an electric machine powertrain mode forecast for one of the plurality of route segments in response to a difference between a predicted wheel power and available battery power being less than an engine-on threshold.

11. A method for operating a hybrid-electric powertrain comprising:

allocating a forecasted torque demand between a motor and an engine for a plurality of segments of a predetermined route based on one of a predicted vehicle speed and a predicted wheel power; and

selectively activating the engine at locations along the predetermined route such that a target battery state of charge corresponding to an endpoint of each of the segments is achieved.

12. The method of claim 11 further comprising subdividing a segment of the predetermined route if the engine is activated or deactivated during the route segment such that there is no change in engine activation during each of the subdivided route segments.

13. The method of claim 11 further comprising forecasting the engine to remain inactive during a segment of the predetermined route in response to predicted vehicle speed being equal to zero at either a startpoint or an endpoint of the segment.

14. The method of claim 11 further comprising forecasting the engine to remain inactive during a segment of the predetermined route in response to a predicted driver deceleration demand being greater than a predetermined braking threshold during the segment.

15. The method of claim 11 further comprising forecasting the engine to remain inactive during a segment of the predetermined route in response to a time duration of the segment being less than a minimum engine-on time threshold.

16. The method of claim 11 further comprising forecasting the engine to be deactivated during a segment of the predetermined route in response to a forecasted battery discharge event during the segment.

17. A vehicle comprising:

a powertrain having an engine and an electric machine;

a battery configured to power the electric machine; and

a controller programmed to (i) forecast a change in an activation state of the engine during any of a plurality of predetermined route segments in response to predicted driver demand crossing a predetermined threshold during the route segment, (ii) monitor a state of charge of the battery, and (iii) forecast a torque output allocation between the engine and the electric machine such that a target state of charge is achieved at an endpoint of each of the predetermined route segments.

18. The vehicle of claim 17 wherein the driver demand comprises at least one of a vehicle speed demand and a wheel power demand, and the forecasted torque output allocation is based on the one of a vehicle speed demand or a wheel power demand that causes a longer engine-on duration during a route segment relative to the other of the vehicle speed demand or the wheel power demand.

19. The vehicle of claim 17 wherein the controller is further programmed to forecast the engine to remain inactive during a segment in response to a time duration of the route segment being less than a minimum engine-on time threshold.

20. The vehicle of claim 17 wherein the controller is further programmed to forecast the engine to remain inactive during a route segment in response to predicted vehicle speed being equal to zero at either a startpoint or the endpoint of the route segment.