Renewable UAV energy via blade rotation

• US 10,120,376 B2
• Filed: 11/30/2016
• Issued: 11/06/2018
• Est. Priority Date: 11/30/2016
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Boss, Gregory J., Fox, Jeremy R., Jones, Andrew R., McConnell, Kevin C., Moore, Jr., John E.
• Primary Examiner(s): Marc-Coleman, Marthe Y
• Application Number:
  US15/364,630
• Publication Number:
  US 20180150072A1
• Time in Patent Office: 706 Days
• Field of Search: 701 3, 244 6, 244190, 703 91
• CPC Class Codes: B60L 2200/10 Air crafts
• CPC Class Codes: B60L 53/24 Using the vehicle's propulsion converter for charging
• CPC Class Codes: B60L 53/305 Communication interfaces
• CPC Class Codes: B60L 53/52 Wind-driven generators
• CPC Class Codes: B60L 53/68 Off-site monitoring or control, e.g. remote control
• CPC Class Codes: B60L 58/12 responding to state of charge [SoC]
• CPC Class Codes: B60L 8/006 Converting flow of air into electric energy, e.g. by using wind turbines
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64D 27/24 using steam or spring force jet aircraft B64D27/16
• CPC Class Codes: B64U 30/20 Rotors; Rotor supports
• CPC Class Codes: B64U 50/19 using electrically powered motors
• CPC Class Codes: B64U 50/34 In-flight charging photovoltaics B64U50/31
• CPC Class Codes: F03D 7/0224 Adjusting blade pitch
• CPC Class Codes: F03D 9/25 the apparatus being an electrical generator F03D9/22 takes precedence
• CPC Class Codes: F03D 9/32 on moving objects, e.g. vehicles
• CPC Class Codes: F05B 2220/706 an electrical generator
• CPC Class Codes: F05B 2240/92 on an airbourne structure
• CPC Class Codes: F05B 2240/923 which is a vehicle
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: G08G 5/0013 : with a ground station
• CPC Class Codes: G08G 5/0021 : located in the aircraft
• CPC Class Codes: G08G 5/0026 : located on the ground
• CPC Class Codes: G08G 5/0039 : Modification of a flight plan
• CPC Class Codes: G08G 5/0069 : specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/025 : Navigation or guidance aids radar or analogous systems specially adapted for landing purposes G01S13/913
• CPC Class Codes: Y02E 10/72 : Wind turbines with rotation axis in wind direction
• CPC Class Codes: Y02E 10/728 : Onshore wind turbines
• CPC Class Codes: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles

Abstract

A computer-implemented method includes: monitoring, by a computer device, a charge level of a battery of an unmanned aerial vehicle (UAV); determining, by the computer device and based on the monitoring, the charge level is less than a threshold level; docking the UAV on a host vehicle; charging the battery using wind-induced rotation of a rotor of the UAV while the UAV is docked on the host vehicle; determining, by the computer device, the UAV is moving away from a destination while the UAV is docked on the host vehicle; and undocking the UAV from the host vehicle based on the determining the UAV is moving away from the destination.

Claims

1. A computer-implemented method, comprising:

monitoring, by a computer device, a charge level of a battery of an unmanned aerial vehicle (UAV);

determining, by the computer device and based on the monitoring, the charge level is less than a threshold level;

determining an optimum charging location from a plurality of possible charging locations on a surface of a host vehicle;

docking the UAV on the optimal charging location of the host vehicle;

charging the battery using wind-induced rotation of a rotor of the UAV while the UAV is docked on the host vehicle;

determining, by the computer device, the UAV is moving away from a destination while the UAV is docked on the host vehicle; and

undocking the UAV from the host vehicle based on the determining the UAV is moving away from the destination.

2. The method of claim 1, further comprising determining the host vehicle from a plurality of candidate vehicles based on determining which of the plurality of candidate vehicles include a visual indicator detectable by a camera of the UAV.

3. The method of claim 1, further comprising:

determining a plurality of candidate vehicles based on broadcasts received by the computer device from respective ones of the plurality of candidate vehicles; and

determining the host vehicle from the plurality of candidate vehicles.

4. The method of claim 3, further comprising determining, by the computer device, the host vehicle based on route information received from the respective ones of the plural candidate vehicles.

5. The method of claim 1, further comprising determining a plurality of candidate vehicles by the computer device querying a database.

6. The method of claim 5, further comprising determining, by the computer device, the host vehicle based on route information of the plural candidate vehicles received from the database.

7. The method of claim 1, wherein the optimum charging location is based on one of wind tunnel test results and historical docking and charging data for particular vehicle types.

8. The method of claim 1, further comprising adjusting a position of the rotor while the UAV is docked on the host vehicle, wherein the adjusting the position of the rotor comprises:

successively adjusting a blade pitch of the rotor to each of a plurality of predefined pitch positions;

determining an optimum one of the plurality of predefined pitch positions; and

adjusting the blade pitch to the determined optimum one of the plurality of predefined pitch positions.

9. The method of claim 8, wherein the optimum one of the plurality of predefined pitch positions is determined based on rotational speed of the rotor at each of the plurality of predefined pitch positions.

10. The method of claim 1, further comprising adjusting a position of the rotor while the UAV is docked on the host vehicle, wherein the adjusting the position of the rotor comprises at least one from the group consisting of:

adjusting rotor tilt position;

adjusting rotor angular position; and

adjusting rotor blade pitch.

11. The method of claim 1, further comprising:

capturing images of the surface of the host vehicle via a camera of the UAV; and

determining, by the computer device, one or more edges of the surface of the host vehicle from the images,

wherein the docking the UAV on the optimal charging location of the host vehicle comprises controlling, by the computer device, the landing of the UAV on the optimal charging location based on the one or more edges of the surface of the host vehicle.

12. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a user device to cause the computer device to:

obtain data from a database, the data defining an optimum charging location on a surface of a host vehicle of a particular vehicle type for charging a battery of an unmanned aerial vehicle (UAV), wherein the charging location is one of multiple possible charging locations on the surface of the host vehicle, and wherein the optimum charging location is determined based on the particular vehicle type;

monitor a distance from a current location of the UAV to a destination of the UAV while the UAV is docked on the host vehicle and charging a battery using wind-induced rotation of a rotor of the UAV;

determine, based on the monitoring, the UAV is moving away from a destination while the UAV is docked on the host vehicle; and

undock the UAV from the host vehicle based on the determining the UAV is moving away from the destination.

13. The computer program product of claim 12, wherein the optimum charging location is based on one of wind tunnel test results and historical docking and charging data.

14. The computer program product of claim 12, wherein the program instructions cause the computer device to adjust a position of the rotor while the UAV is docked on the host vehicle.

15. The computer program product of claim 14, wherein the adjusting the position of the rotor comprises:

successively adjusting a blade pitch of the rotor to each of a plurality of predefined pitch positions;

determining an optimum one of the plurality of predefined pitch positions; and

adjusting the blade pitch to the determined optimum one of the plurality of predefined pitch positions.

16. The computer program product of claim 12, wherein the program instructions cause the computer device to receive route information of the host vehicle from the host vehicle.

17. The computer program product of claim 12, wherein the program instructions cause the computer device to receive route information of the host vehicle from the database.

18. An unmanned aerial vehicle (UAV) system, comprising:

a processor, a computer readable memory, and a computer readable storage medium;

a rechargeable battery;

a propulsion system comprising a motor and a rotor;

a generator configured to recharge the battery using wind-induced rotation of the rotor;

program instructions to determining an optimum charging location on a surface of a host vehicle to recharge the battery of the UAV, wherein the optimum charging location is selected from a plurality of possible charging locations on the surface of a host vehicle based on a type of the host vehicle; and

program instructions to determine an optimum blade pitch of the rotor for recharging the battery when the UAV is docked on the host vehicle, and the host vehicle is in motion,

wherein the program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory.

19. The UAV system of claim 18, wherein the optimum blade pitch is determined based on:

successively adjusting the blade pitch of the rotor to each of a plurality of predefined pitch positions; and

determining a respective wind-induced rotational speed of the rotor at each of the plurality of predefined pitch positions.

20. The UAV system of claim 18, further comprising:

program instructions to capture images of the surface of the host vehicle via a camera of the UAV; and

program instructions to land the UAV on the optimal charging location based on one or more edges of the surface of the host vehicle determined from the captured images.