US-12626200-B1 - Charge control

US12626200B1US 12626200 B1US12626200 B1US 12626200B1US-12626200-B1

Abstract

An electric vehicle (EV) charge management system is configured to monitor, manage, and optimize EV charging processes. The system can continuously monitor charge-related data from various sources, including the EVs themselves, charging infrastructure providers, schedule data, and/or other relevant systems, to identify charging issues in real-time. Users can define customized charge profiles for each EV or groups of EVs, such as target charge levels (e.g., 80%), low charge levels (e.g., 20%), charging schedules, maximum charging rates, and/or other criteria that are indicative of a potential charging issue. These charge profiles allow users to have greater control over the charging process, ensuring that their EVs are charged in a way that reduces fleet downtime (e.g., charging time in the middle of a driver's shift) and optimizes productivity of the fleet.

Inventors

Alan Liu
Fatma Kevser Akcay
Andrii Sliusar
Paolo Caminiti
Andrea Harpprecht
Joe Downard
Deepti Yenireddy
Ethan Wood

Assignees

SAMSARA INC.

Dates

Publication Date: 20260512
Application Date: 20240419

Claims (19)

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.

Description

TECHNICAL FIELD Implementations of the present disclosure relate to charge management of a fleet of electronic vehicles. BACKGROUND The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. The task of managing charging for electric vehicles (EVs) is a significant challenge in the operation of such vehicles. Due to the lengthy charge times, which can last several hours, fleet managers must ensure that EVs have enough charge to successfully complete their assigned routes or shifts. Effective charge management is essential to maintain the smooth functioning and productivity of an EV fleet. SUMMARY The systems, methods, and devices described herein each have several aspects, no single one of which is solely responsible for its desirable attributes. Without limiting the scope of this disclosure, several non-limiting features will now be described briefly. As the transition to electric vehicles (EVs) progresses, depot/fleet managers and drivers must adapt their daily routines to accommodate the necessary charging times for these vehicles. It is important that EVs are charged to the required level at specified intervals to maintain operational smoothness. If a driver fails to plug in an EV or if a charger malfunctions during a charging session, fleet managers may not become aware of the issue until several hours later or, even worse, only discover the problem when it is time for the vehicle to depart for its next assignment. As fleets expand and increase the number of EVs and drivers, real-time charge monitoring becomes important due to the impracticality of manual charge monitoring for these large fleets. “Charge Control,” as may be used herein, generally describes the functionality and/or hardware that is implemented to provide the various fleet management functions related to monitoring and/or managing charging of EVs. In some implementations, certain Charge Control functions are performed by a Backend, such as a fleet management system (that may include a charge monitoring system), a charge control dashboard (e.g., that is viewed by a fleet manager) and/or gateways or other devices associated with EVs. A charge monitoring system may be configured to detect issues related to EV charging and battery levels in real-time so that they may be proactively addressed. For example, if a vehicle's charge level drops to a critically low level, the fleet manager can contact the driver to ensure they have a plan in place to reach a nearby charging station. In emergency situations, the charge monitoring system could even assist the driver in locating a suitable charging station, such as by automatically providing suggested charging locations to the driver's navigation system (e.g., a driver app on the driver's mobile device). This proactive approach helps prevent vehicles from running out of energy and becoming stranded. As another example, if a driver forgets to plug in an EV at the appropriate time, the charge monitoring system may alert the manager of this oversight and/or provide a notification directly to the driver. These notifications decrease risk of the vehicle not reaching its expected charge state by the time the next driver arrives for their shift. As another example, a charge monitoring system can also help manage unexpected interruptions during charging sessions. For example, if an EV stops charging in the middle of a session, the charge monitoring system can quickly identify this issue and initiate necessary actions such as checking the vehicle and/or charging station to determine the root cause of the interruption. In cases where alternative charging options are available, the charge monitoring system may be configured to automatically identify alternate chargers to ensure that the vehicle is fully charged by the time the next driver arrives for their shift. By addressing these unexpected issues proactively, the charge monitoring system can help streamline EV fleet operations and minimize disruptions due to charging-related problems. As discussed further herein, a charge monitoring system may provide functionality that provides one or more of the features below: Monitors and manages electric vehicle (“EV”) charging processes, including real-time and historical charge reporting. Historical charge reporting provides historical data on completed charging sessions, including location, duration, and energy consumption information, which allows fleet managers to better understand usage patterns, identify potential issues, and optimize EV charging operations over time. Additionally, historical charging data may be used to analyze trends in energy consumption, identify problematic chargers or frequent driver errors, and allow the