INTEGRATED HYBRID VEHICLE CONTROL STRATEGY

• US 20110202216A1
• Filed: 09/09/2010
• Published: 08/18/2011
• Est. Priority Date: 09/11/2009
• Status: Active Grant

• Current Assignee: ALTe Powertrain Technologies, Inc.
• Original Assignee: ALTE
• Inventors: Thomas, John D., DeFrank, William J., Thai-Tang, Nam-Huan
• Granted Patent: US 8,548,660 B2
• Time in Patent Office: Days
• US Class Current: 701/22
• CPC Class Codes: B60L 15/2045 for optimising the use of energy
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2240/642 Slope of road
• CPC Class Codes: B60L 2240/662 Temperature
• CPC Class Codes: B60L 2250/12 by confirmation, e.g. of the input
• CPC Class Codes: B60L 2250/14 by input of vehicle departure time
• CPC Class Codes: B60L 2250/18 by enquiring driving style
• CPC Class Codes: B60L 2260/54 Energy consumption estimation
• 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 10/30 including control of auxiliary equipment, e.g. air-conditioning compressors or oil pumps
• 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 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2510/24 Energy storage means
• CPC Class Codes: B60W 2510/244 Charge state
• CPC Class Codes: B60W 2530/16 Driving resistance
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2552/20 Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
• 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 50/0097 : Predicting future conditions
• 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 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles

Abstract

A method for allocating energy within a vehicle comprises calculating an energy forecast for the vehicle based upon a plurality of strategy variables in a vehicle controller. The plurality of strategy variables includes driver profile information, GPS information, ESS information, environment information, accessory information, and system default parameters. The controller calculates a charging strategy based upon the energy forecast and the plurality of strategy variables and determines a control strategy for energy allocation based upon the strategy variables, energy forecast, and charging strategy. The energy is allocated to the vehicle systems based upon the control strategy.

Claims

1. A method for allocating energy within a vehicle comprising:

calculating an energy forecast for the vehicle based upon a plurality of strategy variables in a vehicle controller, wherein the plurality of strategy variables include driver profile information, GPS information, energy storage system (ESS) information, accessory information, and system default parameters;

calculating a charging strategy based upon the energy forecast and the plurality of strategy variables;

determining a control strategy for energy allocation based upon the strategy variables, energy forecast, and charging strategy;

allocating energy to vehicle systems based upon the control strategy including limiting at least one of a plurality of vehicle functions when the energy forecast predicts that the vehicle has insufficient power; and

monitoring the vehicle route and recalculating the energy forecast, the charging strategy and the control strategy of the vehicle when the vehicle deviates from one of a predetermined route and the calculated energy forecast.

2. The method of claim 1, further comprising inputting the driver profile information by:

inputting a driver identifier into the controller;

selecting one of a corresponding driver profile and a default driver profile; and

calculating the driver information with an algorithm based upon the selected driver profile.

3. The method of claim 2, wherein inputting the driver profile information includes inputting at least one of:

a driver route history, at least one driving habit, a preferred driver temperature setting, a preferred driver audio setting.

4. The method of claim 3, wherein inputting the driver profile information includes associating the driver route history with a time of the day driven and with an associated accessory usage.

5. The method of claim 1, further comprising inputting the GPS information, wherein the GPS information includes inputting at least one of, a current vehicle location, vehicle destination, vehicle route, 3D maps, topological data, traffic information, and points of interest.

6. The method of claim 5, wherein inputting the GPS information includes calculating the vehicle loss to drag, rolling resistance and start and stops of the vehicle for the vehicle route.

7. The method of claim 5, wherein the GPS information includes the number of stops, grades, and descents for the vehicle route.

8. The method of claim 1, wherein limiting at least one of a plurality of vehicle functions continues until one of the vehicle reaches the destination, the vehicle forecast indicates the vehicle has sufficient energy based upon the predicted energy forecast.

9. The method of claim 1, wherein limiting at least one of the plurality of vehicle functions includes at least one of limiting a vehicle acceleration level, limiting a top speed of the vehicle, and limiting non-safety accessory loads on the vehicle.

10. A method for allocating energy within a vehicle comprising:

calculating an energy forecast for the vehicle based upon a plurality of strategy variables in a vehicle controller, wherein the plurality of strategy variables include driver profile information, GPS information, energy storage system (ESS) information, accessory information, and system default parameters;

calculating a charging strategy based upon the energy forecast and the plurality of strategy variables;

determining a control strategy for energy allocation based upon the strategy variables, energy forecast, and charging strategy;

allocating energy to the vehicle systems based upon the control strategy including limiting at least one vehicle function when the energy forecast predicts that the vehicle has insufficient power for the route and charging strategy calculated; and

wherein limiting the at least one vehicle function continues until one of the vehicle reaches the destination and the vehicle forecast indicates the vehicle has sufficient energy based upon the predicted energy forecast.

11. The method of claim 10, wherein limiting at least one vehicle function includes at least one of limiting a vehicle acceleration level, limiting a top speed of the vehicle, and liming non-safety accessory loads on the vehicle.

12. The method of claim 10, further comprising inputting the driver profile information by:

inputting a driver identifier into the controller;

selecting one of a corresponding driver profile and a default driver profile; and

calculating the driver information with an algorithm based upon the selected driver profile.

13. The method of claim 12, wherein inputting the driver profile information includes inputting at least one of:

a driver route history, at least one driving habit, a preferred driver temperature setting, a preferred driver audio setting.

14. The method of claim 13, wherein inputting the driver profile information includes associating the driver route history with a time of the day driven and with an associated accessory usage.

15. The method of claim 10, further comprising inputting the GPS information, wherein the GPS information includes inputting at least one of, a current vehicle location, vehicle destination, vehicle route, 3D maps, topological data, traffic information, and points of interest.

16. The method of claim 15, wherein inputting the GPS information includes calculating the vehicle loss to drag, rolling resistance and start and stops of the vehicle for the vehicle route.

17. The method of claim 15, wherein the GPS information includes the number of stops, grades, and descents for the vehicle route.