STRATEGY TO USE AN ON-BOARD NAVIGATION SYSTEM FOR ELECTRIC AND HYBRID ELECTRIC VEHICLE ENERGY MANAGEMENT

• US 20020188387A1
• Filed: 05/09/2001
• Published: 12/12/2002
• Est. Priority Date: 05/09/2001
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Pilutti, Thomas E., Stuntz, Ross M., Patil, Prabhakar B., Woestman, Joanne T.
• Granted Patent: US 6,487,477 B1
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60K 1/02 comprising more than one electric motor
• CPC Class Codes: B60K 31/0058 responsive to externally generated signalling
• CPC Class Codes: B60K 6/00 Arrangement or mounting of plural diverse prime-movers for mutual or common propulsion, e.g. hybrid propulsion systems comprising electric motors and internal combustion engines ; Control systems therefor, i.e. systems controlling two or more prime movers, or controlling one of these prime movers and any of the transmission, drive or drive units arrangement or mounting in vehicles of electrical gearing, in which an electrical machine serves only as reduction gearing and not as the prime mover and in which no electrical storing means are used B60K17/12; control and regulation of purely electrical prime movers B60L; prime-movers comprising electrical and internal combustion motors in a common engine block or housing per se F02B65/00; electric motors or motor-generators used for starting the combustion engine F02N11/04; electric motors for synchronising gearing F16H3/12 Informative references: mechanical gearings with secondary electric drive F16H3/72; arrangements for handling mechanical energy structurally associated with the dynamo-electric machine H02K7/00; machines comprising structurally interrelated motor and generator parts H02K51/00; dynamo-electric machines not otherwise provided for in H02K see H02K99/00
• CPC Class Codes: B60K 6/365 with the gears having orbital motion
• CPC Class Codes: B60K 6/40 characterised by the assembly or relative disposition of components
• CPC Class Codes: B60K 6/445 Differential gearing distribution type
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2240/62 Vehicle position
• CPC Class Codes: B60L 2260/56 Temperature prediction, e.g. for pre-cooling
• CPC Class Codes: B60L 50/16 with provision for separate direct mechanical propulsion
• CPC Class Codes: B60L 50/61 by batteries charged by engine-driven generators, e.g. series hybrid electric vehicles
• CPC Class Codes: B60L 53/14 Conductive energy transfer
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 55/00 Arrangements for supplying energy stored within a vehicle to a power network, i.e. vehicle-to-grid [V2G] arrangements
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: B60L 58/22 Balancing the charge of battery modules
• 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 20/12 using control strategies taking into account route information estimation or calculation of non-directly measurable driving parameters B60W40/00
• CPC Class Codes: B60W 2510/244 : Charge state
• CPC Class Codes: B60W 2555/40 : Altitude
• 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: Y02E 60/00 : Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• 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 10/70 : 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 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]

Abstract

The present invention integrates an on-board navigation system to provide energy management for an electric vehicle (EV) and a hybrid electric vehicle (HEV). The HEV control strategy of the present invention accommodates the goals of fuel economy while always meeting driver demand for power and maintaining the functionality of the traction motor battery system using battery parameter controllers. In the preferred embodiment of the present strategy, a vehicle system controller tightly integrates the navigation system information with energy management while en route to a known destination. Present vehicle location is continuously monitored, expectations of driver demand are determined, and vehicle accommodations are made. The system can be configured to includes as part of its present vehicle location data on road patterns, geography with date and time, altitude changes, speed limits, driving patterns of a vehicle driver, and weather. The vehicle accommodations can be configured to use discrete control laws, fuzzy logic, or neural networks.

Claims

1. A system to manage energy in a vehicle with an electric traction motor comprising:

a powertrain comprising at least one motor and an engine;

a battery connected to the motor;

a vehicle system controller (VSC) connected to the vehicle powertrain;

a device connected to the VSC to continuously locate a present vehicle location and infer expectations of driver demand; and

the VSC further comprising a strategy to continuously accommodate fuel economy, driver demand for power and functionality of the battery.

2. The system of claim 1 wherein present vehicle location further comprises data on road patterns.

3. The system of claim 1 wherein present vehicle location further comprises data on geography with date and time.

4. The system of claim 1 wherein present vehicle location further comprises data on altitude changes.

5. The system of claim 1 wherein present vehicle location further comprises data on speed limits.

6. The system of claim 1 wherein present vehicle location further comprises data on driving patterns of a vehicle driver.

7. The system of claim 1 wherein present vehicle location further comprises data on weather.

8. The system of claim 1 wherein the strategy uses discrete control laws.

9. The system of claim 1 wherein the strategy uses fuzzy logic.

10. The system of claim 1 wherein the strategy uses neural networks.

11. The system of claim 1 wherein expectations of driver demand are inferred by a driver communicating an intended drive route.

12. The system of claim 1 wherein expectations of driver demand are inferred by a search of maps for the locale of the vehicle.

13. The system of claim 1 wherein the strategy accommodates functionality of the battery with battery parameter controllers.

14. The system of claim 13 wherein the battery parameter controllers control battery state of charge.

15. The system of claim 13 wherein the battery parameter controllers control battery charge rate.

16. The system of claim 13 wherein the battery parameter controllers control battery discharge rate.

17. The system of claim 13 wherein the battery parameter controllers control battery temperature.

18. The system of claim 13 wherein battery parameter controllers remove all loads from the battery

20. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on road patterns.

21. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on geography with date and time.

22. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on altitude changes.

23. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on speed limits.

24. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on driving patterns of a vehicle driver.

25. The method of claim 19 wherein the step of locating continuously the present vehicle location comprises data on weather.

26. The method of claim 19 wherein accommodating continuously fuel economy, driver demand for power and functionality of the battery uses discrete control laws.

27. The method of claim 19 wherein accommodating continuously fuel economy, driver demand for power and functionality of the battery uses fuzzy logic.

28. The method of claim 19 wherein accommodating continuously fuel economy, driver demand for power and functionality of the battery uses neural networks.

29. The method of claim 19 wherein inferring expectations of driver demand comprises the step of a driver communicating an intended drive route.

30. The method of claim 19 wherein inferring expectations of driver demand comprises the step of a searching of maps for the locale of the vehicle.

31. The method of claim 19 wherein accommodating continuously the functionality of the battery comprises the step of controlling battery parameters.

32. The method of claim 31 wherein the step of controlling battery parameters comprises controlling battery state of charge.

33. The method of claim 31 wherein the step of controlling battery parameters comprises controlling battery charge rate.

34. The method of claim 31 wherein the step of controlling battery parameters comprises controlling battery discharge rate.

35. The method of claim 31 wherein the step of controlling battery parameters comprises controlling battery temperature.

36. The method of claim 31 wherein the step of controlling battery parameters comprises removing all loads from the battery.

19. A method of managing energy in a vehicle comprised of a powertrain comprising a motor, an engine, and a battery connected to the motor, comprising the steps of;

locating continuously a present vehicle location;

inferring expectations of driver demand based on present vehicle location; and

accommodating continuously fuel economy, driver demand for power and functionality of the battery.