CONTROL AND COORDINATION OF DRIVERLESS FUEL REPLENISHMENT FOR AUTONOMOUS VEHICLES

• US 20190016312A1
• Filed: 07/14/2017
• Published: 01/17/2019
• Est. Priority Date: 07/14/2017
• Status: Active Grant

• Current Assignee: NIO Technology Company Limited (Shanghai Anbin Technology Co., Ltd.)
• Original Assignee: Nio Usa Inc.
• Inventors: Carlson, Jamie P., Yellambalese, Yadunandana
• Granted Patent: US 10,369,974 B2
• Time in Patent Office: Days
• CPC Class Codes: B60L 2240/24 Steering angle
• CPC Class Codes: B60L 2240/622 by satellite navigation
• CPC Class Codes: B60L 2260/32 Auto pilot mode
• CPC Class Codes: B60L 53/65 involving identification of vehicles or their battery types
• CPC Class Codes: B60L 53/66 Data transfer between charging stations and vehicles
• CPC Class Codes: B60S 5/02 Supplying fuel to vehicles; General disposition of plant in filling stations apparatus for transferring measured quantities of petrol, oil, or the like from storage space to vehicles B67D
• CPC Class Codes: B62D 15/0285 Parking performed automatically
• CPC Class Codes: F17C 13/02 Special adaptations of indicating, measuring, or monitoring equipment measuring in general G01
• CPC Class Codes: F17C 2221/012 Hydrogen
• CPC Class Codes: F17C 2221/033 Methane, e.g. natural gas, CNG, LNG, GNL, GNC, PLNG
• CPC Class Codes: F17C 2223/0123 gaseous, e.g. CNG, GNC
• CPC Class Codes: F17C 2223/0161 cryogenic, e.g. LNG, GNL, PLNG
• CPC Class Codes: F17C 2223/033 Small pressure, e.g. for liquefied gas
• CPC Class Codes: F17C 2223/036 Very high pressure (>80 bar)
• CPC Class Codes: F17C 2250/034 using wireless transmissions
• CPC Class Codes: F17C 2250/0478 Position or presence
• CPC Class Codes: F17C 2250/0621 Volume
• CPC Class Codes: F17C 2265/065 for refueling vehicle fuel tanks
• CPC Class Codes: F17C 2270/0139 Fuel stations
• CPC Class Codes: F17C 5/007 for individual gas tanks or containers, e.g. in vehicles filling with liquid fuel not under pressure, B60S5/02, B67D7/00
• CPC Class Codes: G05D 1/0088 : characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06Q 10/00 : Administration; Management
• CPC Class Codes: G06Q 10/04 : Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: Y02E 60/32 : Hydrogen storage
• 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 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing

Abstract

Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computing software, including autonomy applications, image processing applications, etc., computing systems, and wired and wireless network communications to facilitate autonomous control of vehicles, and, more specifically, to systems, devices, and methods configured to control driverless vehicles to facilitate coordination of driverless fuel replenishment. In some examples, a method may include monitoring an amount of fuel relative to a threshold, predicting fuel expenditure of an autonomous vehicle, identifying a candidate time frame, transmitting electronic messages from the autonomous vehicle to reserve a replenishment station, and activating the autonomous vehicle to drive autonomously to receive fuel replenishment.

Claims

1. A method comprising:

monitoring an amount of fuel units relative of data representing a threshold indicative of a portion of fuel reservoir capacity;

predicting fuel expenditure of an autonomous vehicle to identify a predicted fuel expenditure during a range of time in which the amount of fuel units is predicted to be equivalent to the threshold;

identifying a subset of time during the range of time as a candidate time frame to replenish at least a portion of the fuel reservoir capacity;

transmitting electronic messages from the autonomous vehicle to reserve a replenishment station at a specific time associated with the candidate time frame and geographic location; and

activating, via an autonomy controller, the autonomous vehicle to drive autonomously to the geographic location to receive fuel replenishment.

2. The method of claim 1 wherein the amount of fuel units indicate an amount of charge.

3. The method of claim 2 wherein the amount of charge is expressed in either kilowatts-hours (“

kWh”

) or ampere-hours (“

A-hr”

).

4. The method of claim 2 wherein predicting the fuel expenditure comprises:

accessing an energy expenditure profile describing rates of energy expended during time intervals during the range of time; and

calculating an amount of energy expenditure over one or more of the time intervals at which the amount of fuel units is predicted to be equivalent to the threshold.

5. The method of claim 4 further comprising:

identifying one or more intervening time periods as candidate time frames during which the autonomous vehicle is vacant.

6. The method of claim 2 further comprising:

transmitting a request to reserve the replenishment station in a network of replenishment stations as a function of the candidate time frame and the predicted fuel expenditure.

7. The method of claim 6 wherein transmitting the request to reserve the replenishment station comprises:

transmitting data representing autonomous vehicle characteristics with which to determine the replenishment station.

8. The method of claim 7 wherein transmitting the data representing the autonomous vehicle characteristics comprises:

transmitting a type of replenishment interface with which to receive the fuel replenishment and a range of charge rates with which a battery of the autonomous vehicle is charged.

9. The method of claim 6 further comprising:

receiving an electronic message including data specifying a list of replenishment stations from a coordination computing system; and

causing presentation of the list of replenishment stations in a user interface for selection.

10. The method of claim 9 wherein the user interface is disposed on a mobile computing device.

11. The method of claim 9 further comprising:

detecting a user input including data representing a selected replenishment station as the replenishment station; and

transmitting a confirmatory electronic message to logic in the autonomous vehicle to enable driverless transit to receive the fuel replenishment.

12. The method of claim 1 further comprising:

receiving data representing a preprogrammed path of travel from an entry point to the replenishment station;

executing a subset of instructions to implement the data representing the preprogrammed path of travel; and

controlling the autonomous vehicle to terminate driverless transit at the replenishment station.

13. The method of claim 1 further comprising:

detecting the amount of fuel units is equivalent to the threshold;

transmitting state of fuel to request authorization to replenish the fuel;

receiving authorization to replenish the fuel; and

causing, via the autonomy controller, the autonomous vehicle to drive autonomously to the geographic location to receive fuel replenishment.

14. The method of claim 1 further comprising:

detecting an amount of the fuel replenishment is equivalent to data representing a targeted amount of fuel replenishment;

releasing a lock automatically that engages a type of charging interface to the autonomous vehicle; and

causing the autonomous vehicle to drive autonomously from the replenishment station.

15. The method of claim 1 wherein the amount of fuel units indicate an amount of hydrogen fuel.

16. An apparatus comprising:

a memory including executable instructions; and

a processor, responsive to executing the instructions, is configured to;

monitor an amount of fuel units relative of data representing a threshold indicative of a portion of fuel reservoir capacity;

predict fuel expenditure of an autonomous vehicle to identify a predicted fuel expenditure during a range of time in which the amount of fuel units is predicted to be equivalent to the threshold;

identify a subset of time during the range of time as a candidate time frame to replenish at least a portion of the fuel reservoir capacity;

transmit electronic messages from the autonomous vehicle to reserve a replenishment station at a specific time associated with the candidate time frame and geographic location; and

activate, via an autonomy controller, the autonomous vehicle to drive autonomously to the geographic location to receive fuel replenishment.

17. The apparatus of claim 16, wherein the amount of fuel units indicate an amount of charge and the fuel is electricity.

18. The apparatus of claim 17, wherein the processor is further configured to:

access an energy expenditure profile describing rates of energy expended during time intervals during the range of time;

calculate an amount of energy expenditure over one or more of the time intervals at which the amount of fuel units is predicted to be equivalent to the threshold; and

identify one or more intervening time periods as candidate time frames during which the autonomous vehicle is vacant.

19. The apparatus of claim 17, wherein the processor is further configured to:

transmit a request to reserve the replenishment station in a network of replenishment stations as a function of the candidate time frame and the predicted fuel expenditure.

20. The apparatus of claim 16, wherein the processor is further configured to:

detect the amount of fuel units is equivalent to the threshold;

transmit state of fuel to request authorization to replenish the fuel;

receive authorization to replenish the fuel; and

cause, via the autonomy controller, the autonomous vehicle to drive autonomously to the geographic location to receive fuel replenishment.