System and method for maintaining a fleet of aircraft batteries located at multiple airports

1. A system for maintaining a fleet of aircraft batteries located at multiple airports, the system comprising:

one or more physical computer processors configured by machine-readable instructions to:

obtain charge information and battery health information for individual batteries within the fleet of aircraft batteries from charging containers located at individuals ones of the multiple airports, wherein the charge information includes charge statuses of the individual batteries and the battery health information characterizes the degradation of the individual batteries over time;

determine, based on the battery health information, predictions of one or more batteries to be re-allocated, to receive maintenance, or to be re-allocated and to receive maintenance; and

generate a battery management plan including the one or more predictions recommending one or more batteries to be re-allocated, to receive maintenance, or to be re-allocated and to receive maintenance;

obtain flight schedule information for multiple airports located in separate and distinct locations, the flight schedule information including flight times, flight departure location information, flight arrival location information, flight durations, and flight power requirements;

determine allocations of individual batteries within the fleet of aircraft batteries to individual flights on individual aircraft based on the flight schedule information;

generate a distribution plan including one or more of the allocations of the individual batteries within the fleet of aircraft batteries to individual flights on individual aircraft; and

effectuate presentation of the distribution plan via a graphical user interface.

2. The system of claim 1 , wherein the predictions of the one or more batteries to be re-allocated, to receive maintenance, or to be re-allocated and to receive maintenance are determined via machine learning.

3. The system of claim 1 , wherein the individual batteries comprise battery packs having multiple batteries.

4. The system of claim 1 , wherein the one or more processors are further configured by machine readable instructions to:

obtain utility information characterizing one or both of the cost and availability of power at the individual ones of the multiple airports, wherein the allocations of the individual batteries within the fleet of aircraft batteries to the individual flights on the individual aircraft are further determined based on the utility information.

5. The system of claim 4 , further comprising a jack for exchanging individual batteries within the fleet of aircraft batteries between one or both of individual aircraft and the charging containers according to the distribution plan.

6. The system of claim 4 , wherein the utility information includes green energy potential information.

7. The system of claim 1 , further comprising charging containers, individual ones of the charging containers comprising:

multiple charging stations with universal fleet charging ports that correspond to one or both of universal fleet charging plugs on the individual batteries and multiple charging stations with universal fleet charging plugs that correspond to universal fleet charging ports on the individual batteries; and

one or both of an external charging port and an external charging plug configured to couple with one or both of a location standard charging port and a location standard plug corresponding to the location of the charging station.

8. The system of claim 1 , wherein the one or more processors are further configured by machine-readable instructions to:

obtain flight schedule information for multiple airports located in separate and distinct locations, the flight schedule information including flight times, flight departure location information, flight arrival location information, flight durations, and flight power requirements;

determine, based on the charge information, the battery health information, and the flight schedule information, a future maintenance schedule for one or more individual batteries within the fleet of aircraft batteries.

9. The system of claim 1 , wherein the one or more processors are further configured by machine-readable instructions to:

determine based on the battery health information for a segment of batteries, leasing information characterizing leasing costs for the segment of batteries.

10. The system of claim 1 , the battery health information is obtained by pulling battery health data from the individual batteries while charging.

11. A method for maintaining a fleet of aircraft batteries located at multiple airports, the method comprising:

obtaining, via one or more physical computer processors configured by machine-readable instructions, charge information and battery health information for individual batteries within the fleet of aircraft batteries from charging containers located at individuals ones of the multiple airports, wherein the charge information includes charge statuses of the individual batteries and the battery health information characterizes the degradation of the individual batteries over time;

determining, based on the battery health information, predictions of one or more batteries to be re-allocated, to receive maintenance, or to be re-allocated and to receive maintenance via one or more physical computer processors configured by machine-readable instructions; and

generating, via one or more physical computer processors configured by machine-readable instructions, a battery management plan including the one or more predictions recommending the one or more batteries to be re-allocated to receive maintenance, or to be re-allocated and to receive maintenance; obtaining flight schedule information for multiple airports located in separate and distinct locations, the flight schedule information including flight times, flight departure location information, flight arrival location information, flight durations, and flight power requirements;

obtaining, via one or more physical computer processors configured by machine-readable instructions, utility information characterizing one or both of the cost and availability of power at the individual ones of the multiple airports;

determining, via one or more physical computer processors configured by machine-readable instructions, allocations of individual batteries within the fleet of aircraft batteries to individual flights on individual aircraft;

generating, via one or more physical computer processors configured by machine-readable instructions, a distribution plan including one or more of the allocations of the individual batteries within the fleet of aircraft batteries to individual flights on individual aircraft; and

effectuating presentation of the distribution plan via a graphical user interface.

12. The method of claim 11 , wherein the predictions of the one or more batteries to be re-allocated, to receive maintenance, or to be re-allocated and to receive maintenance are determined via machine learning.

13. The method of claim 11 , wherein the individual batteries comprise battery packs having multiple batteries.

14. The method of claim 11 , further comprising:

obtaining utility information characterizing one or both of the cost and availability of power at the individual ones of the multiple airports, wherein the allocations of the individual batteries within the fleet of aircraft batteries to the individual flights on the individual aircraft are further determined based on the utility information.

15. The method of claim 14 , further comprising exchanging individual batteries within the fleet of aircraft batteries between one or both of individual aircraft and the charging containers according to the distribution plan.

16. The method of claim 14 , wherein the utility information includes green energy potential information.

17. The method of claim 11 , wherein the charging containers comprise:

one or both of multiple charging stations with universal fleet charging ports that correspond to universal fleet charging plugs on the individual batteries and multiple charging stations with universal fleet charging plugs that correspond to universal fleet charging ports on the individual batteries, and

one or both of an external charging port and external charging plug configured to couple with one or both of a location standard charging port and a location standard plug corresponding to the location of the charging station.

18. The method of claim 11 , further comprising

obtaining flight schedule information for multiple airports located in separate and distinct locations, the flight schedule information including flight times, flight departure location information, flight arrival location information, flight durations, and flight power requirements; and

determining based on the charge information, the battery health information, and the flight schedule information, a future maintenance schedule for one or more individual batteries within the fleet of aircraft batteries.

19. The method of claim 11 , further comprising determining, based on the battery health information for a segment of batteries, leasing information characterizing leasing costs for the segment of batteries.

20. The method of claim 11 , wherein obtaining the battery health information includes pulling battery health data from the individual batteries while charging.