System and method for controlling battery power based on predicted battery energy usage

• US 9,114,806 B2
• Filed: 01/22/2014
• Issued: 08/25/2015
• Est. Priority Date: 01/22/2014
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Wang, Xiaoyong, Liang, Wei, Wang, Qing, McGee, Ryan Abraham, Kuang, Ming Lang
• Primary Examiner(s): NGUYEN, TAN QUANG
• Application Number:
  US14/160,709
• Publication Number:
  US 20150203096A1
• Time in Patent Office: 580 Days
• Field of Search: 701/22, 701/48, 701/36, 180/65.2
• US Class Current: 1/1
• CPC Class Codes: B60K 6/365 with the gears having orbital motion
• CPC Class Codes: B60K 6/445 Differential gearing distribution type
• 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 2510/244 Charge state
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/406 Traffic density
• 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 10/40 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: Y10S 903/93 Conjoint control of different elements

Abstract

A system and method for controlling battery power in a hybrid vehicle for a given driver demand that balances battery state of charge and battery capacity limits while operating the engine at a system efficient engine power. Predictive information may be used to predict battery energy usage during a future time window that indicates a charging opportunity (excess power will be absorbed by the battery) or a boosting opportunity (battery power will be discharged). Based on this information and the current state of charge of the battery, an associated battery power for a given driver demand is determined.

Claims

1. A hybrid vehicle comprising:

an engine;

a battery; and

a controller configured to control battery power based on a current battery state of charge and a predicted battery energy usage associated with operation of the engine at system efficient engine power during a future time window, wherein the controller is further configured to operate the battery at a system efficient battery power when the current battery state of charge is less than an associated threshold and the system efficient battery power is less than zero.

2. The hybrid vehicle of claim 1, wherein the system efficient engine power is based on a predicted vehicle speed and driver demand.

3. The hybrid vehicle of claim 1, wherein the predicted battery energy usage is determined from predictive information, wherein predictive information includes at least one of map data, road attributes, real-time traffic information, historic traffic information, and past driving history.

4. The hybrid vehicle of claim 1, wherein the controller is further configured to operate the battery at a system efficient battery power when the system efficient battery power is below zero, the predicted battery energy usage is boosting, and the current battery state of charge exceeds an associated threshold.

5. The hybrid vehicle of claim 1, wherein the controller is further configured to set the battery power to zero and control the engine to deliver wheel power to meet driver demand when the current battery state of charge exceeds an associated threshold, a system efficient battery power is less than zero, and the predicted battery energy usage is charging.

6. A hybrid vehicle comprising:

an engine;

a battery; and

a controller configured to control battery power based on a current battery state of charge and a predicted battery energy usage, wherein the predicted battery energy usage is based on a difference between operation of the engine at system efficient engine power and operation of the engine at charge neutral engine power associated with zero battery power.

7. The hybrid vehicle of claim 6, wherein the controller is further configured to operate the battery at a system efficient battery power when the current battery state of charge is less than an associated threshold, the system efficient battery power is greater than zero, and the predicted battery energy usage is charging.

8. The hybrid vehicle of claim 6, wherein the controller is further configured to set the battery power to zero and control the engine to deliver wheel power to meet driver demand when the current battery state of charge is less than an associated threshold, a system efficient battery power is greater than zero, and the predicted battery energy usage is boosting.

9. The hybrid vehicle of claim 6, wherein the controller is further configured to operate the battery at a system efficient battery power when the current battery state of charge is greater than an associated threshold and the system efficient battery power is greater than zero.

10. A method for controlling a hybrid vehicle having an engine and a battery comprising:

controlling battery power based on a current battery energy usage associated with operation of the battery at system efficient battery power relative to a predicted battery energy usage associated with operation of the engine at system efficient engine power during a future time window; and

controlling the battery to operate at the system efficient battery power when a current battery state of charge is less than an associated threshold and the system efficient battery power is greater than zero.

11. The method of claim 10, wherein the system efficient engine power is based on a predicted vehicle speed and driver demand.

12. The method of claim 10, further comprising:

controlling the battery to operate at the system efficient battery power when the system efficient battery power is below zero, the predicted battery energy usage is boosting, and a current battery state of charge exceeds an associated threshold.

13. The method of claim 10, further comprising:

controlling the battery to operate at the system efficient battery power when a current battery state of charge is less than an associated threshold and the system efficient battery power is less than zero.

14. The method of claim 10, further comprising:

controlling the engine to deliver wheel power to meet driver demand when a current battery state of charge exceeds an associated threshold, the system efficient battery power is less than zero, and the predicted battery energy usage is charging.

15. The method of claim 10, further comprising:

controlling the battery to operate at the system efficient battery power when a current battery state of charge is less than an associated threshold, the system efficient battery power is greater than zero, and the predicted battery energy usage is charging.

16. The method of claim 10, further comprising:

controlling the engine to deliver wheel power to meet driver demand when a current battery state of charge is less than an associated threshold, the system efficient battery power is greater than zero, and the predicted battery energy usage is boosting.

17. The method of claim 10, wherein the predicted battery energy usage is further based on a difference between operation of the engine, over the future time window, at system efficient engine power and operation of the engine at charge neutral engine power associated with zero battery power.