ADAPTIVE POWERTRAIN CONTROL FOR PLUGIN HYBRID ELECTRIC VEHICLES

• US 20120323413A1
• Filed: 06/15/2011
• Published: 12/20/2012
• Est. Priority Date: 06/15/2011
• Status: Active Grant

• Current Assignee: FCA US LLC (Stellantis NV)
• Original Assignee: Chrysler Group LLC (Stellantis NV)
• Inventors: Weslati, Feisel, Kedar-Dongarkar, Gurunath
• Granted Patent: US 8,560,155 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60K 6/442 Series-parallel switching type
• CPC Class Codes: B60K 6/46 Series type
• CPC Class Codes: B60L 9/00 Electric propulsion with power supply external to the vehicle electric propulsion for monorail vehicles, suspension vehicles or rack railways B60L13/00; in combination with batteries or fuel cells within the vehicle B60L50/53
• 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 20/10 Controlling the power contribution of each of the prime movers to meet required power demand
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2050/0088 Adaptive recalibration
• CPC Class Codes: B60W 2540/10 Accelerator pedal position
• CPC Class Codes: B60W 2540/12 Brake pedal position
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• 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 30/1882 characterised by the working point of the engine, e.g. by using engine output chart
• 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 10/84 : Data processing systems or methods, management, administration
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles

Abstract

A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle'"'"'s powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Claims

1. A powertrain control system for a plugin hybrid electric vehicle (PHEV), the system comprising:

an adaptive charge sustaining controller;

at least one internal data source operably connected to the adaptive charge sustaining controller; and

a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source,

wherein the adaptive charge sustaining controller is operable to select a mode of operation of a powertrain of the plugin hybrid electric vehicle along a given route based on programming generated from data stored in the memory associated with that route.

2. The powertrain control system of claim 1, wherein the mode is one of a charge depleting mode or charge sustaining mode.

3. The powertrain control system of claim 1, wherein the at least one internal data source is an accelerometer or speedometer.

4. The powertrain control system of claim 1, further including at least one navigational data source connected to the adaptive charge sustaining controller, wherein the memory also stores data generated by the at least one navigational data source.

5. The powertrain control system of claim 1, wherein the at least one navigational data source is a compass or GPS receiver.

6. The powertrain control system of claim 1, further including a navigation system.

7. The powertrain control system of claim 6, wherein the route is identified by selection of a destination in the navigation system.

8. The powertrain control system of claim 1, further including at least one external data source operably connected to the adaptive charge sustaining controller.

9. The powertrain control system of claim 8, wherein the at least one external data source provides one of traffic, temperature, or weather data.

10. A method of adaptively controlling operation of a plugin hybrid electric vehicle (PHEV) powertrain, the method comprising:

identifying a route being traveled;

loading the stored adaptive charge sustaining mode programming for the identified route, if stored adaptive charge sustaining mode programming exists for the identified route; and

controlling operation of the PHEV powertrain along the identified route by selecting from a plurality of operational modes, the mode selection being defined by the stored adaptive charge sustaining mode programming.

11. The method of claim 10, wherein the step of identifying the route being traveled comprises empirically matching data from an initial period of vehicle operation to route identifying data associated with the stored adaptive charge sustaining mode programming.

12. The method of claim 11, wherein the step of identifying the route being traveled includes evaluating navigational data collected in the initial period of vehicle operation.

13. The method of claim 10, further including generating adaptive charge sustaining mode programming if no stored adaptive charge sustaining mode programming exists for the identified route.

14. The method of claim 13, wherein the generating step comprises:

collecting vehicle data from a drive cycle start to end; and

analyzing the vehicle data to determine which operational mode is appropriate for each segment of the given route.

15. The method of claim 14, further including collecting navigational data from the drive cycle start to end and using the navigational data in analyzing which operational mode is appropriate for each segment of the given route.

16. The method of claim 15, wherein the navigational data includes at least one of elevation change or speed limit.

17. The method of claim 14, wherein the vehicle data includes at least one of rate of speed, rate of acceleration, distance traveled, direction of travel or battery power consumption rate.

18. The method of claim 10, further including altering the stored adaptive charge sustaining mode programming based on external data.

19. The method of claim 18, wherein the external data includes at least one of traffic data, temperature or weather conditions.

20. The method of claim 10, wherein the route is predefined.