Granted Patent B1

US 12,626,200 · App. 18/641,201 · Granted May 12, 2026

Inventors: Alan Liu (London, GB); Fatma Kevser Akcay (London, GB); Andrii Sliusar (London, GB); Paolo Caminiti (London, GB); Andrea Harpprecht (London, GB); Joe Downard (London, GB); Deepti Yenireddy (San Jose, CA); Ethan Wood (London, GB)

Assignee: Samsara Inc.

G06Q10/06311B60L58/12G07C5/008

Abstract

Claims (65)

1 . A method for managing electric vehicle charging, performed by a computing system comprising one or more hardware computer processors and one or more non-transitory computer-readable storage devices storing software instructions executable by the computing system to perform the method comprising:

receiving first user input defining one or more charge profiles, each specifying a target charge level and a low charge level;

receiving second user input associating vehicles of a fleet of electric vehicles with respective charge profiles, wherein at least one of the charge profiles is associated with multiple vehicles of the fleet;

receiving, via a wireless communication network, real-time state of charge (SOC) information from the vehicles, wherein the vehicles each comprise one or more sensors configured to sense electrical characteristics of a battery pack that are usable to calculate a SOC;

for individual vehicles associated with a charge profile:

assigning a low charge status if a SOC of a vehicle falls below the low charge level of the associated charge profile; and

assigning a missed target charge status if the vehicle disconnects from charging before reaching the target charge level of the associated charge profile; and

for individual vehicles not associated with a charge profile:

assigning the low charge status if a SOC of a vehicle falls below a default low charge level; and

assigning a missed target charge status if the vehicle disconnects from charging before reaching a default target charge level; and

updating charge control data of the fleet of electric vehicles with any assigned low charge statuses or missed target charge statuses assigned to the individual vehicles, wherein the charge control data is viewable in a graphical user interface on a network connected computing device, wherein the graphical user interface is configured to display real-time information about the SOC of each vehicle including the updated low charge or missed statuses;

in response to assignment of the low charge status to a particular vehicle, transmitting a real-time alert to a manager device indicating the particular vehicle has reached the low charge level;

communicating, via a secure API communication link, with one or more charging stations to obtain real-time charging status and availability;

based at least on the real-time charging status and availability of respective charging stations and real-time information about the SOC of each of the vehicles, assigning the individual vehicles respective charging times and charging stations; and

controlling the charging speed and duration to optimize battery life and reduce wear and tear;

in response to detecting that the charging speed is not sufficient for the particular vehicle to reach a target charge level by a scheduled departure time, transmitting a notification to a driver to plug into a different charger at a charging station or move to a different charging station, wherein the driver moves the vehicle to the different charger or to the different charging station in response to the notification.

2 . The method of claim 1 , further comprising:

accessing historical charging data associated with the vehicles of the fleet of electric vehicles; and

generating or updating a machine learning model based on the historical charging data, where the machine learning model is configured to predict charging issues.

3 . The method of claim 1 , further comprising:

sending a notification to a fleet manager when a vehicle is assigned the low charge status or the missed target charge status.

4 . The method of claim 1 , wherein the graphical user interface further displays historical charging data of the individual vehicles of the fleet of electric vehicles.

5 . The method of claim 1 , further comprising:

adjusting a charging schedule of the individual vehicle to optimize charging times for the fleet of electric vehicles.

6 . The method of claim 1 , wherein the charge profiles further specify a preferred charging window during which the individual vehicles should be charged to reach the target charge level.

7 . The method of claim 1 , further comprising:

receiving user input to create a new charge profile associated with a default or home charging depot, wherein the new charge profile is associated with a subset of the fleet of electric vehicles assigned to the default or home charging depot.

8 . The method of claim 1 , further comprising:

integrating upcoming route information for the individual vehicles of the fleet of electric vehicles into the charge control data.

9 . The method of claim 1 , wherein the graphical user interface displays a current SOC, a time to full charge, energy consumed, and charging efficiency.

10 . The method of claim 1 , further comprising:

analyzing historical charging data to identify patterns in charging issues.

11 . The method of claim 1 , further comprising:

determining driver reimbursements based on authorized home charging.

12 . The method of claim 1 , wherein at least one of the charge profiles indicate charging time windows that align with daily operational expectations of the fleet of electric vehicles;

wherein the method further comprises:

updating a status of any vehicles of the fleet of electric vehicles not charging during charging time windows in the associated charge profiles.

13 . The method of claim 1 , wherein the default low charge level is dynamically determined for the individual vehicles or vehicle types as a minimum SOC for safe operation of the individual vehicles.

14 . The method of claim 1 , dynamically determining the low charge level or the target charge level of a vehicle based on battery capacity and range of the vehicle.

15 . The method of claim 1 , further comprising:

communicating with one or more external data sources to obtain environmental information, such as weather and traffic information; and

optimizing charging schedules and locations based on the environmental information.

16 . The method of claim 1 , wherein the graphical user interface displays a map view with the real-time SOC information for the individual vehicles in the fleet.

17 . The method of claim 1 , further comprising:

analyzing charging data to identify potential maintenance issues, such as battery degradation or charging equipment malfunctions.

18 . The method of claim 1 , further comprising:

generating a report indicating fleet energy usage and potential cost savings based on historical charging data.

19 . A computing system comprising:

a hardware computer processor; and

a non-transitory computer readable medium having software instructions stored thereon, the software instructions executable by the hardware computer processor to cause the computing system to perform operations comprising:

receiving first user input defining one or more charge profiles, each specifying a target charge level and a low charge level;

receiving second user input associating vehicles of a fleet of electric vehicles with respective charge profiles, wherein at least one of the charge profiles is associated with multiple vehicles of the fleet;

receiving, via a wireless communication network, real-time state of charge (SOC) information from the vehicles, wherein the vehicles each comprise one or more sensors configured to sense electrical characteristics of a battery pack that are usable to calculate a SOC;

for individual vehicles associated with a charge profile:

assigning a low charge status if a SOC of a vehicle falls below the low charge level of the associated charge profile; and

assigning a missed target charge status if the vehicle disconnects from charging before reaching the target charge level of the associated charge profile; and

for individual vehicles not associated with a charge profile:

assigning the low charge status if a SOC of a vehicle falls below a default low charge level; and

assigning a missed target charge status if the vehicle disconnects from charging before reaching a default target charge level; and

updating charge control data of the fleet of electric vehicles with any assigned low charge statuses or missed target charge statuses assigned to the individual vehicles, wherein the charge control data is viewable in a graphical user interface on a network connected computing device, wherein the graphical user interface is configured to display real-time information about the SOC of each of the vehicles including the updated low charge or missed statuses;

in response to assignment of the low charge status to a particular vehicle, transmitting a real-time alert to a manager device indicating the particular vehicle has reached the low charge level;

communicating, via a secure API communication link, with one or more charging stations to obtain real-time charging status and availability;

based at least on the real-time charging status and availability of respective charging stations and real-time information about the SOC of each of the vehicles, assigning the individual vehicles respective charging times and charging stations; and

controlling the charging speed and duration to optimize battery life and reduce wear and tear;

in response to detecting that a charging speed is not sufficient for a particular vehicle to reach a target charge level by a scheduled departure time, transmitting a notification to a driver to plug into a different charger at a charging station or move to a different charging station; wherein the driver moves the vehicle to the different charger or to the different charging station in response to the notification.

Assignments (1)

References Cited (400)