Systems and methods for determining engine start time during predicted acceleration events

Patent metadata

Field	Value
Publication number	US-10946852-B2
Application number	US-201816143064-A
Country	US
Kind code	B2
Filing date	Sep 26, 2018
Priority date	Sep 26, 2018
Publication date	Mar 16, 2021
Grant date	Mar 16, 2021

Abstract

A method may include predicting an acceleration event of a vehicle. The method may further include predicting a maximum speed of the predicted acceleration event. The method may also include determining an engine start time based on the predicted maximum speed. The method may still further include starting an engine of the vehicle at the engine start time.

First claim

What is claimed is:

1. A method comprising:
predicting an acceleration event of a vehicle;
predicting a maximum speed of the predicted acceleration event;
determining an engine start time based on the predicted maximum speed; and
starting an engine of the vehicle at the engine start time.

2. The method of claim 1 , wherein:
the engine start time is determined to be an earlier engine start time when the predicted maximum speed is a higher predicted maximum speed;
the engine start time is determined to be a later engine start time when the predicted maximum speed is a lower predicted maximum speed;
the earlier engine start time is earlier than the later engine start time; and
the lower predicted maximum speed is lower than the higher predicted maximum speed.

3. The method of claim 1 , further comprising:
determining a baseline engine start time within a duration of the predicted acceleration event; and
modifying the baseline engine start time to the engine start time determined based on the predicted maximum speed of the predicted acceleration event.

4. The method of claim 1 , wherein the vehicle is a hybrid electric vehicle comprising a battery, further comprising:
utilizing the battery until the modified engine start time.

5. The method of claim 1 , further comprising maintaining the engine start time when the predicted maximum speed of the acceleration event is between the higher predicted maximum speed and the lower predicted maximum speed.

6. The method of claim 1 , wherein the predicted maximum speed of the predicted acceleration event is determined based upon one or more acceleration event criteria.

7. The method of claim 6 , wherein the acceleration event criteria comprise vehicle location data, stop location data, speed limit data, traffic conditions, driver history, and weather conditions.

8. A system comprising:
an engine in a vehicle; and
a processor, communicatively coupled to the engine, configured to output commands to:
predict an acceleration event of a vehicle;
predict a maximum speed of the predicted acceleration event;
determine an engine start time based on the predicted maximum speed; and
start an engine of the vehicle at the engine start time.

9. The system of claim 8 , wherein:
the engine start time is determined to be an earlier engine start time when the predicted maximum speed is a higher predicted maximum speed;
the engine start time is determined to be a later engine start time when the predicted maximum speed is a lower predicted maximum speed;
the earlier engine start time is earlier than the later engine start time; and
the lower predicted maximum speed is lower than the higher predicted maximum speed.

10. The system of claim 8 , wherein the processor is further configured for:
determining a baseline engine start time within a duration of the predicted acceleration event; and
modifying the baseline engine start time to the engine start time determined based on the predicted maximum speed of the predicted acceleration event.

11. The system of claim 8 , wherein the predicted maximum speed of the predicted acceleration event is determined based upon one or more acceleration event criteria.

12. The system of claim 8 , wherein the vehicle is a hybrid electric vehicle comprising a battery, further comprising:
utilizing the battery until the modified engine start time.

13. The system of claim 8 , wherein the maximum speed is dynamically determined by one or more of a maximum vehicle speed, vehicle temperature, and a rate of acceleration to maximum speed.

14. The system of claim 8 , wherein the engine start time is determined based upon a neural network implementation utilizing one or more factors including time of year, a quantity of vehicles within an area around the vehicle, and traffic light timing data.

15. A vehicle comprising:
an engine; and
a processor, communicatively coupled to the engine, configured to output commands to:
predict an acceleration event of a vehicle;
predict a maximum speed of the predicted acceleration event;
determine an engine start time based on the predicted maximum speed; and
start an engine of the vehicle at the engine start time.

16. The vehicle of claim 15 , wherein:
the engine start time is determined to be an earlier engine start time when the predicted maximum speed is a higher predicted maximum speed;
the engine start time is determined to be a later engine start time when the predicted maximum speed is a lower predicted maximum speed;
the earlier engine start time is earlier than the later engine start time; and
the lower predicted maximum speed is lower than the higher predicted maximum speed.

17. The vehicle of claim 15 , wherein the processor is further configured for:
determining a baseline engine start time within a duration of the predicted acceleration event; and
modifying the baseline engine start time to the engine start time determined based on the predicted maximum speed of the predicted acceleration event.

18. The vehicle of claim 15 , wherein the predicted maximum speed of the predicted acceleration event is determined based upon one or more acceleration event criteria.

19. The vehicle of claim 15 , wherein the vehicle is a hybrid electric vehicle comprising a battery, further comprising:
utilizing the battery until the modified engine start time.

20. The vehicle of claim 15 , wherein the engine start time, the predicted maximum speed of the acceleration event, or the maximum speed threshold is based upon a force amount applied to an accelerator by a driver of the vehicle.

Assignees

• Toyota Eng & Mfg North America
• Univ Colorado State Res Found

Inventors

• Payne Joshua
• Stefanon Heraldo
• Geller Benjamin
• Aoki Takanori
• Bradley Thomas
• Asher Zachary
• Trinko David

Classifications

• F02N2200/123

  Information about vehicle position, e.g. from navigation systems or GPS signals · CPC title

• F02N2300/2006

  using prediction of future conditions · CPC title

• B60W2720/10

  Longitudinal speed · CPC title

• B60W20/19

  for achieving enhanced acceleration · CPC title

• Y02T10/40

  Engine management systems · CPC title