Optimized powertrain with route-learning feature

• US 8,401,733 B2
• Filed: 12/18/2009
• Issued: 03/19/2013
• Est. Priority Date: 12/18/2009
• Status: Active Grant

• Current Assignee: FCA US LLC (Stellantis NV)
• Original Assignee: Chrysler Group LLC (Stellantis NV)
• Inventors: Weslati, Feisel, Kedar-Dongarkar, Gurunath
• Primary Examiner(s): Camby, Richard M.
• Application Number:
  US12/641,919
• Publication Number:
  US 20110153127A1
• Time in Patent Office: 1,187 Days
• Field of Search: 701/22, 701/36, 701/79, 701/77, 701/93, 701/96, 701/101, 701/102, 701/106, 701/117, 701/468, 701/70
• US Class Current: 701/36
• CPC Class Codes: B60L 15/2009 for braking
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2240/12 Speed
• CPC Class Codes: B60L 2240/16 longitudinal
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2250/16 by display
• CPC Class Codes: B60L 2250/26 by pedal actuation
• CPC Class Codes: B60L 2260/26 Transition between different drive modes
• CPC Class Codes: B60L 2260/42 by adaptive correction
• CPC Class Codes: B60L 50/16 with provision for separate direct mechanical propulsion
• CPC Class Codes: B60L 58/21 having the same nominal voltage
• 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 2540/10 Accelerator pedal position
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2540/30 Driving style
• 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 50/0097 Predicting future conditions
• CPC Class Codes: B60W 50/085 Changing the parameters of the control units, e.g. changing limit values, working points by control input
• CPC Class Codes: F02N 11/0822 related to action of the driver
• CPC Class Codes: F02N 11/0837 : Environmental conditions thereof, e.g. traffic, weather or road conditions
• CPC Class Codes: F02N 2200/106 : Driver presence, e.g. detected by door lock, seat sensor or belt sensor
• CPC Class Codes: F02N 2200/123 : Information about vehicle position, e.g. from navigation systems or GPS signals
• CPC Class Codes: F02N 2300/2004 : using adaptive control
• CPC Class Codes: G01C 21/26 : specially adapted for navigation in a road network
• CPC Class Codes: Y02T 10/40 : Engine management systems
• CPC Class Codes: Y02T 10/64 : Electric machine technologies in electromobility
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 10/84 : Data processing systems or methods, management, administration
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles

Abstract

The technology described herein provides a powertrain system with a route-learning feature. Particularly, learned information is used to optimize powertrain operation along any learned route. The learned information comprises, generally, feedback from the vehicle'"'"'s acceleration and brake sensors and information from an on-board trip computer. At the least, the powertrain is able to optimize its operation to a driver'"'"'s preference based on the feedback recorded along a particular route that the driver has specified. The route-learning powertrain control described herein is particularly useful with a hybrid powertrain, and can be used to optimize start/stop and regenerative braking control. The system described herein can also be integrated with a navigation system and GPS receiver, to provide more accurate route-learning and/or automated operation.

Claims

1. A vehicle powertrain having a route-learning control feature comprising:

at least one driver input for operating the vehicle; and

a route-learning powertrain control unit connected to the at least one driver input and operable to, for a defined route, conform powertrain operation to prior-recorded driver-specific analytical data indicating at least one driver preference associated with the defined route and used to operate the vehicle in accordance with characteristics the driver prefers.

2. The vehicle powertrain of claim 1, wherein the route-learning powertrain control unit is operable to apply a plurality of driver preferences to a plurality of segments of an active route.

3. The vehicle powertrain of claim 1, further comprising a display with an interface for a driver to activate the route-learning powertrain control unit, the interface further allowing a driver to define a new route.

4. The vehicle powertrain of claim 1, wherein the at least one driver input comprises data from at least one of a steering column, accelerator pedal sensor, brake pedal sensor, or longitudinal or lateral acceleration sensors installed in the vehicle.

5. The vehicle powertrain of claim 1, further comprising a navigation system connected to the route-learning powertrain control unit to enable powertrain control whenever a route for which powertrain programming has been generated is selected.

6. The vehicle powertrain of claim 5, wherein the route-learning powertrain control unit is adapted to automatically generate powertrain programming for routes selected in the navigation system for which no powertrain programming has been previously generated.

7. The vehicle powertrain of claim 5, wherein data from at least one navigation element is further used in determining the at least one driver preference.

8. The vehicle powertrain of claim 1, further including at least one navigation element to enable monitoring of vehicle position on an active route.

9. The vehicle powertrain of claim 8, wherein the navigation element is one of a compass, an altimeter or an accelerometer.

10. The vehicle powertrain of claim 8, wherein if data from the navigation element indicates that the vehicle is not on an active route, the route-learning powertrain control unit is operable to prompt a driver of the vehicle to confirm that the active route is correct.

11. The vehicle powertrain of claim 1, wherein the at least one driver preference corresponds to one or more modes of operation of the vehicle.

12. The vehicle powertrain of claim 1, wherein the vehicle powertrain is a hybrid powertrain.

13. The vehicle powertrain of claim 12, further including at least one of a start/stop system for activating and deactivating an internal combustion motor, a regenerative braking system, a battery conditioning system, a variable cylinder displacement systems, and an Interactive Decel Fuel Shut-Off (iDFSO) system.

14. The vehicle powertrain of claim 13, wherein the at least one driver preference controls the operating parameters of the start/stop, regenerative braking, battery conditioning, variable displacement, or iDFSO systems.

15. The vehicle powertrain of claim 1, wherein the route-learning powertrain control unit comprises a memory for storing a plurality of defined routes and driving preferences for each of the defined routes.

16. A method of controlling a powertrain of a vehicle according to a learned route the method comprising:

retrieving powertrain programming from a vehicle memory when an indication of a start of a defined route is received; and

applying the powertrain programming to conform powertrain operation to prior-recorded driver-specific analytical data indicating at least one driver preference associated with the defined route and used to operate the vehicle in accordance with characteristics the driver prefers.

17. The method of claim 16, further comprising:

determining at least one driver preference for powertrain operation on a defined route according to data from at least one driver input;

generating powertrain programming for the defined route to conform powertrain operation along the defined route to the at least one driver preference; and

storing the powertrain programming in the vehicle memory.

18. The method of claim 16, further comprising a step of collecting data from at least one driver input while the vehicle is in operation on the defined route and comparing it against previously collected data to determine if the at least one driver preference for powertrain operation on the defined route should be changed.

19. The method of claim 16, further comprising:

using navigation data to determine if the vehicle is on the desired route; and

if the navigation data indicates that the vehicle is not on the desired route, prompting a driver of the vehicle to confirm that the active route is correct.

20. The method of claim 16, wherein the vehicle powertrain is a hybrid powertrain and the driver preference controls a regenerative braking system to enable single-pedal driving for at least one segment of the defined route.