IP Library Granted Patent US 11,053,873
Granted Patent B2
US 11,053,873 · App. 16/270,504 · Granted Jul 6, 2021

Method and system for improving vehicle motive power source stop/start control via machine learning

Inventors: Dominique Meroux (Fair Oaks, CA); Sravani Yajamanam Kidambi (Sunnyvale, CA)
Assignee: Ford Global Technologies, LLC
F02D41/042B60W30/188B60W30/18018B60W30/18054B60W30/18159G06N20/00B60W2420/42B60W2510/188B60W2540/12B60W2540/16B60W2540/30B60W2710/0627
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Quick Facts
Patent No.
US 11,053,873
App. No.
16/270,504
Granted
Jul 6, 2021
Kind
B2
Abstract

Methods and systems are presented for improving engaging automatic vehicle motive power source stopping and inhibiting automatic vehicle motive power source stopping. The methods and systems include processing driver inputs in a machine learning model and characterizing the driver in one of a plurality of driver groups. Automatic vehicle motive power source stopping and starting may be adjusted responsive to a group in which a driver is a member.

Claims (24)

1. A vehicle motive power source operating method, comprising:

identifying present operating conditions of a vehicle via a controller responsive to a combination of data provided via a camera and data provided via a range sensing device;

assigning a human driver to one of a plurality of driver groups via a trained machine learning model; and

automatically stopping a vehicle motive power source via the controller responsive to the human driver being assigned to a group included in the plurality of driver groups and the present operating conditions, where identifying present vehicle operating conditions includes identifying that the vehicle is in a predefined parking location, and further comprising:

not automatically starting the vehicle motive power source after automatically stopping the vehicle motive power source in further response to a human driver shifting a transmission to park and releasing a brake pedal.

2. A vehicle motive power source operating method, comprising:

identifying present operating conditions of a vehicle via a controller responsive to a combination of data provided via a camera and data provided via a range sensing device;

assigning a human driver to one of a plurality of driver groups via a trained machine learning model; and

automatically stopping a vehicle motive power source via the controller responsive to the human driver being assigned to a group included in the plurality of driver groups and the present operating conditions, where identifying present vehicle operating conditions includes identifying that the vehicle is at a vehicle rental facility and stopped for exit processing, and further comprising:

automatically stopping the vehicle motive power source in further response to vehicle motive power source temperature being less than a threshold temperature; and

maintaining the vehicle motive power source automatically stopped for longer than a threshold time duration in response to identifying that the vehicle is at the vehicle rental facility.

3. The method of claim 1 , where the plurality of driver groups includes a fuel saving group, a performance group, and an intermediate group.

4. The method of claim 1 , where the parking location is parking space in a parking garage.

5. The method of claim 1 , where the parking location is a delivery zone of a road.

6. The method of claim 1 , further comprising not automatically stopping the vehicle motive power source via the controller responsive to the human driver being assigned to the group included in the plurality of driver groups and the present vehicle operating conditions when the camera or the range sensing device is degraded.

7. A vehicle motive power source control system, comprising:

an internal combustion vehicle motive power source;

a distance to object sensing system that transmits a signal and receives a reflected version of the signal;

a camera; and

a controller including executable instructions stored in non-transitory memory to automatically stop the internal combustion vehicle motive power source or inhibit automatic stopping of the internal combustion vehicle motive power source based on a combination of data from the distance to object sensing system and the camera, to characterize behavior of a human driver in one of a plurality of groups via a trained machine learning model, and to adjust automatically stopping the internal combustion vehicle motive power source in response to the vehicle being staged for exiting a vehicle rental facility.

8. The vehicle motive power source system of claim 7 , where the vehicle motive power source is automatically stopped via ceasing to flow fuel to the vehicle motive power source.

9. The vehicle motive power source system of claim 7 , further comprising additional instructions to inhibit automatically stop the internal combustion vehicle motive power source in response to a vehicle being within a threshold distance of a toll station.

10. The vehicle motive power source system of claim 7 , where the one of the plurality of groups is a performance group.

11. The vehicle motive power source system of claim 7 , where the one of the plurality of groups is a fuel economy group.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2019
From: MEROUX, DOMINIQUE; YAJAMANAM KIDAMBI, SRAVANI
To: FORD GLOBAL TECHNOLOGIES, LLC
Reel/Frame 048271/0740 →
Continuity (1)
Related Publication 20200255014A1 · Aug 13, 2020
Cited By (1)
US 12,497,046