Reserving a charging station
An example operation includes one or more of reserving an available charging point at a charging station for a vehicle at an arrival time at the charging station when one other charging point at the charging station will be available for one other vehicle in a time less than a threshold time after the arrival time.
1. A method, comprising:
receiving, via a charging station server, a reservation request from an electric vehicle (EV) which identifies a state of charge (SoC) of a battery in the EV, a desired charge level, and an estimated arrival time of the EV at a charging station;
receiving, via the charging station server, status information from a plurality of bays that are charging a plurality of other EVs:
determining, via the charging station server, a bay from among the plurality of bays that is available for charging the EV at the estimated arrival time based on the reservation request and the status information;
reserving, via the charging station server, the bay at the charging station for the EV at the estimated arrival time at the charging station;
transmitting, via the charging station server, a message to a graphical user interface (GUI) of a display system within the EV with an identifier of the bay:
occupying the bay by the EV;
transferring energy, via a charging point, to the EV at the bay to reach the desired charge level;
stopping, via the charging station server, an ability for the EV to receive energy when one or more of the following occurs:
an amount of time that a number of other EVs waiting to receive the energy at the charging station is greater than a threshold time;
the number of other EVs waiting to receive the energy at the charging station is greater than a threshold number of EVs;
the EV is receiving the energy for a time greater than the other EVs at the charging station; and
the SoC of a-the battery in the EV is greater than a SoC of batteries in the other EVs at the charging station.
2. The method of claim 1 , comprising:
responsive to another bay at the charging station being available, notifying another EV to utilize the another bay at the charging station.
3. The method of claim 1 , wherein the reserving is based on a prediction of at least one other EV arriving at the charging station before the estimated arrival time of the EV at the charging station.
4. The method of claim 1 , comprising:
receiving telemetry data from the EV;
predicting an arrival time of the EV at the charging station based on execution of a machine learning model on the telemetry data; and
reserving the charging station based on the predicted arrival time.
5. The method of claim 1 , comprising:
receiving age attributes of the battery of the EV from the EV; and
reserving the bay at the charging station based on the received age attributes of the battery of the EV.
6. The method of claim 1 , wherein the reserving is based on an average of a time for all other EVs to receive energy at the charging station being equal to or less than the threshold time.
7. A system, comprising:
at least one processor; and
a memory,
wherein the at least one processor and the memory are communicably coupled, and wherein the at least one processor:
receives, via a charging station server, a reservation request from an electric vehicle (EV) which identifies a state of charge (SoC) of a battery in the EV, a desired charge level, and an estimated arrival time of the EV at a charging station;
receives, via the charging station server, status information from a plurality of bays that are charging a plurality of other EVs;
determines a bay from among the plurality of bays that is available for charging the EV at the estimated arrival time based on the reservation request and the status information;
reserves the bay at the charging station for a the EV at the estimated arrival time at the charging station
transmits a message to a graphical user interface (GUI) of a display system within the EV with an identifier of the bay and instructions to occupy the bay by the EV;
transfers energy, via a charging point, to the EV at the bay to reach the desired charge level; and
stops an ability for the EV to receive energy when one or more of the following occurs:
an amount of time that a number of other EVs waiting to receive the energy at the charging station is greater than a threshold time;
the number of other EVs waiting to receive the energy at the charging station is greater than a threshold number of EVs;
the EV receives the energy for a time greater than the other EVs at the charging station; and
the SoC of a-the battery in the EV is greater than a SoC of batteries in the other EVs at the charging station.
8. The system of claim 7 , wherein the at least one processor:
responsive to another bay at the charging station being available, notifies another EV to utilize the another bay at the charging station.
9. The system of claim 7 , wherein the reservation is based on a prediction of at least one other EV arriving at the charging station before the estimated arrival time of the EV at the charging station.
10. The system of claim 7 , wherein the at least one processor:
receives telemetry data from the EV;
predicts an arrival time of the EV at the charging station based on execution of a machine learning model on the telemetry data; and
reserves the charging station based on the predicted arrival time.
11. The system of claim 7 , wherein the at least one processor:
receives age attributes of the battery of the EV from the EV; and
reserve the bay at the charging station based on the received age attributes of the battery of the EV.
12. The system of claim 7 , wherein the reservation is based on an average of a time for all other EVs to receive energy at the charging station being equal to or less than the threshold time.
13. A non-transitory computer readable storage medium comprising instructions, that when read by a processor, cause the processor to perform:
receiving, via a charging station server, a reservation request from an electric vehicle (EV) which identifies a state of charge (SoC) of a battery in the EV, a desired charge level, and an estimated arrival time of the EV at a charging station;
receiving, via the charging station server, status information from a plurality of bays that are charging a plurality of other EVs:
determining a bay from among the plurality of bays that is available for charging the EV at the estimated arrival time based on the reservation request and the status information;
reserving the bay at the charging station for the EV at the estimated arrival time at the charging station;
transmitting a message to a graphical user interface (GUI) of a display system within the EV with an identifier of the bay and instructions to occupy the bay by the EV;
transferring energy, via a charging point, to the EV at the bay to reach the desired charge level; and
stopping an ability for the EV to receive energy when one or more of the following occurs:
an amount of time that a number of other EVs waiting to receive the energy at the charging station is greater than a threshold time;
the number of other EVs waiting to receive the energy at the charging station is greater than a threshold number of EVs;
the EV is receiving the energy for a time greater than the other EVs at the charging station; and
the SoC of a-the battery in the EV is greater than a SoC of batteries in the other EVs at the charging station.
14. The non-transitory computer readable storage medium of claim 13 , wherein the processor performs:
responsive to another bay at the charging station being available, notifying another EV to utilize the another bay at the charging station.
15. The non-transitory computer readable storage medium of claim 13 , wherein the reserving is based on a prediction of at least one other EV arriving at the charging station before the estimated arrival time of the EV at the charging station.
16. The non-transitory computer readable storage medium of claim 13 , wherein the processor performs:
receiving telemetry data from the EV;
predicting an arrival time of the EV at the charging station based on execution of a machine learning model on the telemetry data; and
reserving the charging station based on the predicted arrival time.
17. The non-transitory computer readable storage medium of claim 13 , wherein the processor performs:
receiving age attributes of the battery of the EV from the EV; and
reserving the bay at the charging station based on the received age attributes of the battery of the EV.
18. The non-transitory computer readable storage medium of claim 13 ,
wherein the reserving is based on an average of a time for all other EVs to receive energy at the charging station being equal to or less than the threshold time.