IP Library › Granted Patent US 12,548,808
Granted Patent B2
US 12,548,808 · App. 17/980,977 · Granted Feb 10, 2026

Computer-implemented systems for battery monitoring, battery replacement, and fleet management

Inventors: Ryan Michael Gross (Normal, IL); Matthew S. Megyese (Bloomington, IL); Joseph P. Harr (Bloomington, IL); Scott T. Christensen (Salem, OR); Vicki King (Bloomington, IL); Shawn Renee Harbaugh (Normal, IL)
Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
H01M10/4257G06Q40/08H01M2010/4271H01M2220/20
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Quick Facts
Patent No.
US 12,548,808
App. No.
17/980,977
Granted
Feb 10, 2026
Kind
B2
Abstract

A server and non-transitory computer-readable storage medium storing instructions for monitoring one or more batteries of an electric vehicle (EV) comprising computing instructions for (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.

Claims (45)

1 . A server for monitoring one or more batteries of an electric vehicle (EV), the server comprising:

a transceiver configured to communicate with an electronic device associated with the EV via at least one network connection;

a memory storing a set of computer-executable instructions; and

a processor interfacing with the transceiver and the memory, and configured to execute the computer-executable instructions to cause the processor to:

receive, from the electronic device, telematics data generated by one or more sensors associated with the electronic device that is indicative of operation of the EV;

determine a battery status of the one or more batteries based upon the telematics data, wherein the EV is a first EV and the battery status is a first battery status;

map the battery status of the one or more batteries to a digital record corresponding to the EV in a database, wherein the digital record is a first digital record including the first battery status;

map 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;

detect that the first battery status satisfies a predetermined threshold and that the first EV is damaged; and

in response to the detecting, determine to transfer the one or more batteries of the first EV to the second EV.

2 . The server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to cause the processor to determine the battery status 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 server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to cause the processor to determine the battery status based upon a battery charging mode associated with the one or more batteries.

4 . The server 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 server 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 server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to cause the processor to determine the battery status 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 server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to further cause the processor to:

access the database to retrieve the battery status of the one or more batteries and corresponding recommendation data that includes instructions for improving the battery status; and

transmit, to the electronic device, at least one of the battery status and the recommendation data.

8 . The server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to further cause the processor to:

determine an insurance premium or discount associated with the EV based upon the battery status; and

transmit, to the electronic device, the insurance premium or the discount.

9 . The server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to further cause the processor to:

update, 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 server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to further cause the processor to:

detect 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, determine to replace the one or more batteries of the first EV with the one or more batteries of the second EV.

11 . The server of claim 1 , wherein:

the first EV and the second EV belong to a fleet of vehicles,

the processor is configured to execute the computer-executable instructions to further cause the processor to:

detect 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, maintain 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.

12 . The server of claim 11 , wherein the processor is configured to execute the computer-executable instructions to cause the processor to maintain the overall battery status 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.

13 . The server of claim 1 , wherein the processor is configured to execute the computer-executable instructions to cause the processor to map the battery status of the one or more batteries to include a mapping of 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.

14 . The server of claim 13 , wherein the processor is configured to execute the computer-executable instructions to further cause the processor to:

render the mapping of the battery location on a graphical user interface (GUI) indicating where the EV and the battery location are depicted.

15 . The server of claim 1 , wherein the electronic device is one of a mobile electronic device or a vehicle telematics system onboard the EV.

16 . A non-transitory computer-readable storage medium storing computer-readable instructions for monitoring one or more batteries of an electric vehicle (EV) that, when executed by one or more processors, cause the one or more processors to:

receive, 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;

determine a battery status of the one or more batteries based upon the telematics data, wherein the EV is a first EV and the battery status is a first battery status;

map the battery status of the one or more batteries to a digital record corresponding to the EV in a database, wherein the digital record is a first digital record including the first battery status;

map 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;

detect that the first battery status satisfies a predetermined threshold and that the first EV is damaged; and

in response to the detecting, determine to transfer the one or more batteries of the first EV to the second EV.

17 . The non-transitory computer-readable storage medium of claim 16 , wherein the computer-readable instructions, when executed by the one or more processors, cause the one or more processors to determine the battery status 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.

18 . The non-transitory computer-readable storage medium of claim 16 , wherein the computer-readable instructions, when executed by the one or more processors, cause the one or more processors to determine the battery status based upon a battery charging mode associated with the one or more batteries.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 3, 2023
From: GROSS, RYAN MICHAEL; MEGYESE, MATTHEW S.; HARR, JOSEPH P.; CHRISTENSEN, SCOTT THOMAS; KING, VICKI; HARBAUGH, SHAWN RENEE
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 062589/0351 →
Continuity (3)
Provisional Application 63356248 · Jun 28, 2022
Provisional Application 63345588 · May 25, 2022
Related Publication 20230387481A1 · Nov 30, 2023
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