IP Library Granted Patent US 10,369,893
Granted Patent B2
US 10,369,893 · App. 15/790,687 · Granted Aug 6, 2019

Intelligent vehicle control for wireless power transfer (WPT)

Inventors: Ashok Krishnaji Moghe (Pleasanton, CA); John George Apostolopoulos (Palo Alto, CA)
Assignee: Cisco Technology, Inc.
B60L11/1829B60L11/182G05D1/0212H01M10/44H02J7/025H02J50/10H02J50/90
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Quick Facts
Patent No.
US 10,369,893
App. No.
15/790,687
Granted
Aug 6, 2019
Kind
B2
Abstract

In some embodiments, a device in a network receives vehicle characteristic data regarding one or more autonomous vehicles. Each autonomous vehicle of the one or more autonomous vehicles is equipped with a vehicle-based charging coil configured to receive electrical power from a ground-based charging coil of a wireless power transfer (WPT) system. The device, based on the received vehicle characteristic data, identifies one or more ground-based charging coils of the WPT system available to provide power to the one or more autonomous vehicles. The device determines driving parameters for the one or more autonomous vehicles to optimize power transfer from the one or more ground-based charging coils to the one or more autonomous vehicles. The device sends the driving parameters to the one or more autonomous vehicles to control movement of the one or more autonomous vehicles.

Claims (51)

1. A method comprising:

receiving, at a device in a network, vehicle characteristic data regarding one or more autonomous vehicles, wherein each autonomous vehicle of the one or more autonomous vehicles is equipped with a vehicle-based charging coil configured to receive electrical power from a ground-based charging coil of a wireless power transfer (WPT) system;

identifying, by the device and based on the received vehicle characteristic data, one or more ground-based charging coils of the WPT system available to provide power to the one or more autonomous vehicles;

determining, by the device, driving parameters for the one or more autonomous vehicles to optimize power transfer from the one or more ground-based charging coils to the one or more autonomous vehicles; and

sending, by the device, the driving parameters to the one or more autonomous vehicles to control movement of the one or more autonomous vehicles.

2. The method as in claim 1 , wherein the determining the driving parameters for the one or more autonomous vehicles comprises:

determining, by the device, a minimum amount of time needed to power a particular ground-based charging coil after the particular ground-based charging coil transfers power to a first autonomous vehicle of the one or more autonomous vehicles.

3. The method as in claim 2 , wherein the determining the driving parameters for the one or more autonomous vehicles further comprises:

determining, by the device, an optimal speed for a second autonomous vehicle of the one or more autonomous vehicles, based on the minimum amount of time needed to power the particular ground-based charging coil after the particular ground-based charging coil transfers power to the first autonomous vehicle of the one or more autonomous vehicles.

4. The method as in claim 2 , wherein the determining the driving parameters for the one or more autonomous vehicles further comprises:

determining, by the device, an optimal spacing between the first autonomous vehicle of the one or more autonomous vehicles and a second autonomous vehicle of the one or more autonomous vehicles, based on the minimum amount of time needed to power the particular ground-based charging coil after the particular ground-based charging coil transfers power to the first autonomous vehicle of the one or more autonomous vehicles.

5. The method as in claim 1 , wherein the received vehicle characteristic data is indicative of a non-charging vehicle in proximity of the one or more autonomous vehicles, and wherein the determining the driving parameters comprises:

determining, by the device, a spacing between a first autonomous vehicle of the one or more autonomous vehicles and the non-charging vehicle.

6. The method as in claim 1 , wherein the determining the driving parameters for the one or more autonomous vehicles comprises:

using, by the device, a machine learning model that receives a feedback regarding optimizing the power transfer.

7. The method as in claim 1 , wherein the determining the driving parameters for the one or more autonomous vehicles comprises:

selecting, by the device, one or more routes to be taken by the one or more autonomous vehicles.

8. The method as in claim 1 , further comprising:

providing, by the device, an indication of the driving parameters to a non-autonomous vehicle.

9. The method as in claim 1 , wherein the identifying the one or more ground-based charging coils of the WPT system comprises:

identifying, by the device, one or more ground-based charging coils of the WPT system that are located with a predefined physical region.

10. An apparatus, comprising:

one or more network interfaces to communicate with a network;

a processor coupled to the one or more network interfaces and configured to execute one or more processes; and

a memory configured to store a process executable by the processor, the process when executed configured to:

receive vehicle characteristic data regarding one or more autonomous vehicles, wherein each autonomous vehicle of the one or more autonomous vehicles is equipped with a vehicle-based charging coil configured to receive electrical power from a ground-based charging coil of a wireless power transfer (WPT) system;

identify, based on the received vehicle characteristic data, one or more ground-based charging coils of the WPT system available to provide power to the one or more autonomous vehicles;

determine driving parameters for the one or more autonomous vehicles to optimize power transfer from the one or more ground-based charging coils to the one or more autonomous vehicles; and

send the driving parameters to the one or more autonomous vehicles to control movement of the one or more autonomous vehicles.

11. The apparatus as in claim 10 , wherein the apparatus determines the driving parameters for the one or more autonomous vehicles by:

determining a minimum amount of time needed to power a particular ground-based charging coil after the particular ground-based charging coil transfers power to a first one of the autonomous vehicles.

12. The apparatus as in claim 11 , wherein the apparatus determines the driving parameters for the one or more vehicles by:

determining an optimal speed for a second one of the vehicles, based on the minimum amount of time needed to power the particular ground-based charging coil after the coil transfers power to a first autonomous vehicle of the one or more autonomous vehicles.

13. The apparatus as in claim 11 , wherein the apparatus determines the driving parameters for the one or more autonomous vehicles by:

determining an optimal spacing between the first autonomous vehicle of the one or more autonomous vehicles and a second autonomous vehicle of the one or more autonomous vehicles, based on the minimum amount of time needed to power the particular ground-based charging coil after the particular ground-based charging coil transfers power to the first autonomous vehicle of the one or more autonomous vehicles.

14. The apparatus as in claim 11 , wherein the apparatus determines the driving parameters for the one or more autonomous vehicles by:

determining a lane or lane alignment for a particular autonomous vehicle of the vehicles that maximizes overlap between the vehicle-based charging coil of the particular autonomous vehicle and the ground-based charging coil.

15. The apparatus as in claim 10 , wherein the received vehicle characteristic data is indicative of a non-charging vehicle in proximity of the one or more autonomous vehicles, and wherein the apparatus determines the driving parameters by:

determining a spacing between a first autonomous vehicle of the one or more autonomous vehicles and the non-charging vehicle.

16. The apparatus as in claim 10 , wherein the apparatus determines the driving parameters for the one or more autonomous vehicles by:

using a machine learning model that receives a feedback regarding optimizing the power transfer.

17. The apparatus as in claim 10 , wherein the process when executed is further configured to:

provide an indication of the driving parameters to a non-autonomous vehicle.

18. The apparatus as in claim 10 , wherein the apparatus identifies the one or more ground-based charging coils of the WPT system by:

identifying one or more ground-based charging coils of the WPT system that are located with a predefined physical region.

19. The apparatus as in claim 10 , wherein the apparatus comprises a fog computing capable road side unit.

20. A tangible, non-transitory, computer-readable medium storing program instructions that cause a device to execute a process comprising:

receiving, at the device, vehicle characteristic data regarding one or more autonomous vehicles, wherein each autonomous vehicle of the one or more autonomous vehicles is equipped with a vehicle-based charging coil configured to receive electrical power from a ground-based charging coil of a wireless power transfer (WPT) system;

identifying, by the device and based on the received vehicle characteristic data, one or more ground-based charging coils of the WPT system available to provide power to the one or more autonomous vehicles;

determining, by the device, driving parameters for the one or more autonomous vehicles to optimize power transfer from the one or more ground-based charging coils to the one or more autonomous vehicles; and

sending, by the device, the driving parameters to the one or more autonomous vehicles to control movement of the one or more autonomous vehicles.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2017
From: MOGHE, ASHOK KRISHNAJI; APOSTOLOPOULOS, JOHN GEORGE
To: CISCO TECHNOLOGY, INC.
Reel/Frame 044070/0547 →
Continuity (2)
Provisional Application 62541816 · Aug 7, 2017
Related Publication 20190039470A1 · Feb 7, 2019
Cited By (2)
US 12,640,566 US 12,662,005