COMPUTER-IMPLEMENTED METHODS FOR BATTERY MONITORING, BATTERY REPLACEMENT, AND FLEET MANAGEMENT
Computer-implemented methods of monitoring one or more batteries of an electric vehicle (EV) include (i) receiving, from an electronic device associated with the EV, telematics data generated by one or more sensors associated with the electronic device that is indicative of operation of the EV; (ii) determining a battery status of the one or more batteries based upon the telematics data; and (iii) mapping the battery status of the one more batteries to a digital record corresponding to the EV in a database.
1 . A computer-implemented method of monitoring one or more batteries of an electric vehicle (EV), carried out by one or more processors, the method comprising:
receiving, by the one or more processors and from an electronic device associated with the EV, telematics data generated by one or more sensors associated with the electronic device that is indicative of operation of the EV;
determining, by the one or more processors, a battery status of the one or more batteries based upon the telematics data; and
mapping, by the one or more processors, the battery status of the one more batteries to a digital record corresponding to the EV in a database.
2 . The computer-implemented method of claim 1 , wherein the determining is further based upon a baseline reading of the one or more batteries originating from a battery sensor contained in the EV and coupled to the one or more batteries.
3 . The computer-implemented method of claim 1 , wherein the determining is further based upon a battery charging mode associated with the one or more batteries.
4 . The computer-implemented method of claim 1 , wherein the telematics data comprises data indicating an accident associated with the EV or a predicted accident associated with the EV.
5 . The computer-implemented method of claim 1 , wherein the telematics data comprises data indicating flat towing of the EV, pushing of the EV, bi-directional jump charging of the EV with another EV, or whether the EV is coupled to another vehicle.
6 . The computer-implemented method of claim 1 , wherein the determining is further based upon a machine learning algorithm trained to predict the battery status using training data that associates different types of telematics data with the battery status.
7 . The computer-implemented method of claim 1 , further comprising:
accessing, by the one or more processors, the database to retrieve the battery status of the one more batteries and corresponding recommendation data that includes instructions for improving the battery status; and
transmitting, by the one or more processors and to the electronic device or a user device, at least one of the battery status and the recommendation data.
8 . The computer-implemented method of claim 1 , further comprising:
determining, by the one or more processors, an insurance premium or discount associated with the EV based upon the battery status; and
transmitting, by the one or more processors and to the electronic device or a user device, the insurance premium or the discount.
9 . The computer-implemented method of claim 1 , further comprising:
updating, by the one or more processors and in the database, the digital record to designate that the one or more batteries are to be, based upon the battery status in relation to a predetermined threshold, at least one of (1) replaced, (2) transferred to another EV, (3) recycled, (4) used as an emergency power source, or (5) recharged.
10 . The computer-implemented method of claim 1 , wherein:
the EV is a first EV,
the battery status is a first battery status,
the digital record is a first digital record including the first battery status, the method further comprising:
mapping, by the one or more processors, a second battery status of one more batteries of a second EV to a second digital record corresponding to the second EV in the database.
11 . The computer-implemented method of claim 10 , further comprising:
detecting, by the one or more processors, that the first battery status does not satisfy a predetermined threshold and the second battery status satisfies the predetermined threshold; and
in response to the detecting, determining, by the one or more processors, to replace the one or more batteries of the first EV with the one or more batteries of the second EV.
12 . The computer-implemented method of claim 10 , further comprising:
detecting, by the one or more processors, that the first battery status satisfies a predetermined threshold and that the first EV is damaged; and
in response to the detecting, determining, by the one or more processors, to transfer the one or more batteries of the first EV to the second EV.
13 . The computer-implemented method of claim 10 , wherein the first EV and the second EV belong to a fleet of vehicles, the method further comprising:
detecting, by the one or more processors, that the first battery status indicates that the one or more batteries of the first EV has less charge than the one or more batteries of the second EV indicated by the second battery status; and
in response to the detecting, maintaining, by the one or more processors, an overall battery status of the fleet by (1) rotating the one or more batteries of the second EV from the second EV to the first EV or (2) rotating out the first EV with the second EV.
14 . The computer-implemented method of claim 13 , wherein the maintaining is further based upon a machine learning algorithm trained to predict the overall battery status of the fleet using training data that associates individual battery status of each vehicle in the fleet with the overall battery status of the fleet.
15 . The computer-implemented method of claim 1 , wherein the mapping of the battery status of the one or more batteries comprises a battery location for at least one of the one or more batteries, wherein the battery location indicates a physical location onboard the EV where the battery is installed.
16 . The computer-implemented method of claim 15 , further comprising:
rendering the mapping of the battery location on a graphical user interface (GUI) indicating where the EV and the battery location are depicted.
17 . The computer-implemented method of claim 1 , wherein the electronic device is one of a mobile electronic device or a vehicle telematics system onboard the EV.
18 . The computer-implemented method of claim 1 , wherein the EV is a solar electric vehicle (EV).
19 . The computer-implemented method of claim 18 , wherein at least one of the one more batteries is a solar battery.
20 . The computer-implemented method of claim 18 , wherein the solar EV is configured to operate in either of: (a) a solar mode that allows the solar EV to use solar energy as a power source; or (b) a power mode that allows the solar EV to use EV battery power.