IP Library Granted Patent US 12,627,151
Granted Patent B2
US 12,627,151 · App. 18/456,485 · Granted May 12, 2026

Devices, methods, and media for charging dispatching

Inventors: Rui Ding (San Marcos, TX); Junshuai Wang (San Marcos, TX)
Assignee: XCHARGE ENERGY USA INC.
H02J3/32H02J3/003H02J2101/24
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,627,151
App. No.
18/456,485
Granted
May 12, 2026
Kind
B2
Abstract

The present disclosure provides a device, a method, and a medium for charging. The device for charging includes a first sensor, a second sensor, a third sensor, a charging pile, and a processor. The first sensor obtains first sensing information from a battery connected with the charging pile. The second sensor obtains second sensing information from a photovoltaic system connected with the charging pile. The third sensor obtains third sensing information from a power grid connected with the charging pile. The charging pile transmits power to a target object. The processor is configured to determine power storage information of the battery, photovoltaic power supply information of the photovoltaic system, and power grid power supply information of the power grid, respectively; determine the target object to be charged based on the power pile; determine a source object, and, control the charging pile to transmit power to the target object.

Claims (74)

1 . A device for charging dispatching, comprising: a first sensor, a second sensor, a third sensor, a charging pile, and a processor, wherein

the first sensor is configured to obtain first sensing information from a battery connected with the charging pile, wherein the first sensing information includes power situation information of the battery;

the second sensor is configured to obtain second sensing information from a photovoltaic system connected with the charging pile, wherein the second sensing information includes power situation information of the photovoltaic system;

the third sensor is configured to obtain third sensing information from a power grid connected with the charging pile, wherein the third sensing information includes power situation information of the power grid;

the charging pile is configured to transmit power to a target object, wherein the target object includes at least one of the power grid, the battery, and an electric load; and

the processor is configured to:

determine, based on the first sensing information, the second sensing information, and the third sensing information, power storage information of the battery, photovoltaic power supply information of the photovoltaic system, and power grid power supply information of the power grid, respectively;

determine the target object that needs to be charged based on the charging pile;

determine, based on at least one of the power storage information, the photovoltaic power supply information, and the power grid power supply information, a source object charging the target object, wherein the source object includes at least one of the power grid, the photovoltaic system, and the battery; during a same charging process, the source object is different from the target object;

control the charging pile to transmit, based on the source object, power to the target object, wherein to control the charging pile to transmit, based on the source object, power to the target object, the processor is configured to:

determine, based on a charging demand of the target object and power supply information of the source object, an output power when the source object supplies power to the target object;

wherein when the target object includes the battery and one or more other objects, the processor is further configured to:

determine estimated charging demand information of the electric load, estimated photovoltaic power supply information of the photovoltaic system, and estimated power grid power supply information and estimated grid connection demand information of the power grid within a target time period; and

determine a saturation capacity of the battery within the target time period based on the estimated charging demand information, the estimated photovoltaic power supply information, the estimated power grid power supply information, and the estimated grid connection demand information;

determine, based on the saturation capacity, the charging demand, and the power supply information, a plurality of output powers, each of the plurality of output powers being for the source object supplying power to one of the battery and the one or more other objects within one of a plurality of sub-time periods of the target time period.

2 . The device of claim 1 , wherein the processor is further configured to:

obtain a plurality of power supply priorities of a plurality of candidate source objects, wherein the plurality of candidate source objects include the power grid, the photovoltaic system, and the battery; and

determine the source object that meets the charging demand of the target object from the plurality of candidate source objects by processing, based on the plurality of power supply priorities, power supply information corresponding to the plurality of candidate source objects, wherein the power supply information corresponding to the battery is the power storage information, the power supply information corresponding to the photovoltaic system is the photovoltaic power supply information, and the power supply information corresponding to the power grid is the power grid power supply information

the processor is further configured to:

determine whether a candidate source object with a highest priority among the plurality of candidate source objects has a possibility of supplying power based on the power supply information of the candidate source object with the highest priority;

in response to a determination that the candidate source object with the highest priority has no possibility of supplying power, sequentially determine whether candidate source objects with lower priorities have the possibility of supplying power, until that a candidate source object with the possibility of supplying power is determined or none of the plurality of candidate source objects having the possibility of supplying power is determined.

3 . The device of claim 2 , wherein a power supply priority of the photovoltaic system is the highest power supply priority in the plurality of power supply priorities of the plurality of candidate source objects, indicating that the photovoltaic system is preferentially used for power supply.

4 . The device of claim 1 , further comprising a fourth sensor, wherein

the fourth sensor is configured to obtain fourth sensing information from the electric load connected with the charging pile, and the fourth sensing information is power situation information of the electric load; and

the processor is further configured to:

determine battery charging demand information of the battery based on the first sensing information;

determine grid connection demand information of the power grid based on the third sensing information, wherein the grid connection demand information is used to indicate demand information that the power grid needs to transmit power together with the source object;

determine load charging demand information of the electric load based on the fourth sensing information; and

determine the target object based on the battery charging demand information, the load charging demand information, and the grid connection demand information.

5 . The device of claim 1 , wherein the processor is further configured to:

the power supply information corresponding to the battery is the power storage information, the power supply information corresponding to the photovoltaic system is the photovoltaic power supply information, and the power supply information corresponding to the power grid is the power grid power supply information.

6 . The device of claim 1 , wherein a plurality of source objects and a plurality of target objects are determined, the processor is further configured to:

determine an input power of the plurality of target objects based on the charging demand;

determine a difference between an output power of the plurality of source objects and a sum of the input power and a useless power corresponding to the plurality of source objects;

in response to a determination that the difference is less than or equal to 0 kW, determine the output power of each of the plurality of source objects based on the plurality of power supply priorities of the plurality of source objects, and determine that the source object transmits power to the target object based on the output power of the source object;

in response to a determination that the difference is greater than 0 kW, determine, based on a plurality of charging properties of the plurality of target objects, the output power of one of the plurality of source objects transmitting power to one of the plurality of target objects, and determine that the source object transmits power to the target object based on the output power of the one of the plurality of source objects.

7 . The device of claim 1 , wherein the processor is further configured to:

through an estimation model, determine the estimated charging demand information of the estimated electric load, the estimated photovoltaic power supply information of the photovoltaic system, and the estimated power grid power supply information and the estimated grid connection demand information of the power grid within the target time period, based on weather information and specific time information within the target time period, wherein the estimation model is a deep learning model.

8 . The device of claim 1 , wherein the processor is further configured to:

obtain historical charging demand information of a historical electric load and historical grid connection demand information of the power grid within a historical time period; and

determine a time duration of the target time period based on the historical charging demand information and the historical grid connection demand information, wherein the target time period refers to a time period during which a reserved saturation capacity of the battery needs to be evaluated.

9 . The device of claim 8 , wherein the processor is further configured to:

determine historical mutations in the historical time period based on the historical charging demand information and the historical grid connection demand information, the historical mutations reflecting a sudden change in the historical charging demand information of the historical electric load and/or a sudden change in the historical grid connection demand information of the power grid within the historical time period, and the time duration of the target time period being negatively correlated with an occurrence frequency of the historical mutation.

10 . A method for charging dispatching, executed by a processor in a device for charging, comprising:

determining, based on first sensing information, second sensing information, and third sensing information, power storage information of a battery connected with a charging pile, photovoltaic power supply information of a photovoltaic system connected with the charging pile, and power grid power supply information of a power grid connected with the charging pile, respectively, wherein the first sensing information includes power situation information of the battery obtained through a first sensor of the device for charging, the second sensing information includes power situation information of the photovoltaic system obtained through a second sensor of the device for charging, and the third sensing information includes power situation information of the power grid obtained through a third sensor of the device for charging;

determining a target object that needs to be charged based on the charging pile, wherein the target object includes at least one of the power grid, the battery, and the electric load;

determining, based on at least one of the power storage information, the photovoltaic power supply information, and the power grid power supply information, a source object charging the target object, wherein the source object includes at least one of the power grid, the photovoltaic system, and the batteries; during a same charging process, the source object is different from the target object;

controlling the charging pile to transmit, based on the source object, power to the target object, including:

determining, based on a charging demand of the target object and power supply information of the source object, an output power when the source object supplies power to the target object;

wherein when the target object includes the battery and one or more other objects, the processor is further configured to:

determine estimated charging demand information of the electric load, estimated photovoltaic power supply information of the photovoltaic system, and estimated power grid power supply information and estimated grid connection demand information of the power grid within a target time period; and

determine a saturation capacity of the battery within the target time period based on the estimated charging demand information, the estimated photovoltaic power supply information, the estimated power grid power supply information, and the estimated grid connection demand information;

determine, based on the saturation capacity, the charging demand, and the power supply information, a plurality of output powers each of the plurality of output powers being for the source object supplying power to one of the battery and the one or more other objects within one of a plurality of sub-time periods of the target time period.

11 . The method of claim 10 , wherein the determining, based on at least one of the power storage information, the photovoltaic power supply information, and the power grid power supply information, a source object charging the target object comprises:

obtaining a plurality of power supply priorities of a plurality of candidate source objects, wherein the plurality of candidate source objects include the power grid, the photovoltaic system, and the battery; and

determine the source object that meets the charging demand of the target object from the plurality of candidate source objects by processing, based on the plurality of power supply priorities, power supply information corresponding to the plurality of candidate source objects, wherein the power supply information corresponding to the battery is the power storage information, the power supply information corresponding to the photovoltaic system is the photovoltaic power supply information, and the power supply information corresponding to the power grid is the power grid power supply information.

12 . The method of claim 11 , wherein a power supply priority of the photovoltaic system is the highest power supply priority in the plurality of power supply priorities of the plurality of candidate source objects, indicating that the photovoltaic system is preferentially used for power supply.

13 . The method of claim 10 , wherein the determining a target object that needs to to be charged based on the charging pile comprises:

determining battery charging demand information of the battery based on the first sensing information;

determining grid connection demand information of the power grid based on the third sensing information, wherein the grid connection demand information is used to indicate demand information that the power grid needs to transmit power together with the source object;

determining load charging demand information of the electric load based on the fourth sensing information, wherein the fourth sensing information is power situation information of the electric load obtained through a fourth sensor of the device for charging; and

determine the target object based on the battery charging demand information, the load charging demand information, and the grid connection demand information.

14 . The method of claim 10 , further comprising:

determining, based on a charging demand of the target object and power supply information of the source object, an output power when the source object supplies power to the target object, wherein the power supply information corresponding to the battery is the power storage information, the power supply information corresponding to the photovoltaic system is the photovoltaic power supply information, and the power supply information corresponding to the power grid is the power grid power supply information.

15 . The method of claim 14 , wherein when the target object includes the battery and one or more other objects, the determining, based on a charging demand of the target object and power supply information of the source object, an output power when the source object supplies power to the target object comprises:

determining a saturation capacity of the battery within a target time period; and

determining, based on the saturation capacity, the charging demand, and the power supply information, a plurality of output powers each of which is when the source object supplies power to the battery and one or more output powers when the source object supplies power to the one or more other objects within one of a plurality of sub-time periods of the target time period.

16 . The method of claim 15 , wherein the determining a saturation capacity of the battery within a target time period comprises:

determining estimated charging demand information of an estimated electric load, estimated photovoltaic power supply information of the photovoltaic system, and estimated power grid power supply information and estimated grid connection demand information of the power grid within the target time period; and

determining the saturation capacity of the battery within the target time period based on the estimated charging demand information, the estimated photovoltaic power supply information, the estimated power grid power supply information, and the estimated grid connection demand information.

17 . The method of claim 15 , wherein a time duration of the target time period is determined according to:

obtaining historical charging demand information of a historical electricload and historical grid connection demand information of the power grid within a historical time period; and

determining the time duration of the target time period based on the historical charging demand information and the historical grid connection demand information.

18 . A non-transitory computer-readable storage medium storing computer instructions that, when executed by at least one processor, direct the at least one processor to perform the method for charging dispatching of claim 10 .

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2023
From: DING, RUI; WANG, JUNSHUAI
To: XCHARGE ENERGY USA INC.
Reel/Frame 065461/0708 →
Continuity (2)
Continuation PCTUS2023072685 · Aug 22, 2023
Related Publication 20250070559A1 · Feb 27, 2025
References Cited (84)
US D669026S · Oda et al. · 2012 [cited by applicant]
US D674335S · Yamashita et al. · 2013 [cited by applicant]
US D733647S · Farrell · 2015 [cited by applicant]
US D833387S · Baxter et al. · 2018 [cited by applicant]
US D907574S · Yang et al. · 2021 [cited by applicant]
US D908614S · Chaudhuri et al. · 2021 [cited by applicant]
US D914593S · Frerichs et al. · 2021 [cited by applicant]
US D922943S · Reitenbach et al. · 2021 [cited by applicant]
US D942378S · Park et al. · 2022 [cited by applicant]
US D942937S · Kihl et al. · 2022 [cited by applicant]
US D943518S · Kihl et al. · 2022 [cited by applicant]
US D947776S · Semboloni · 2022 [cited by applicant]
US D948425S · Erni · 2022 [cited by applicant]
US D961502S · Hwang · 2022 [cited by applicant]
US D962856S · Mercer et al. · 2022 [cited by applicant]
US D966185S · Gupta et al. · 2022 [cited by applicant]
US D967011S · Mercer et al. · 2022 [cited by applicant]
US D967012S · Mercer et al. · 2022 [cited by applicant]
US 11532943B1 · Zauli · 2022 [cited by examiner]
US D976812S · Hwang · 2023 [cited by applicant]
US D977428S · Hikita · 2023 [cited by applicant]
US D988992S · Moreira Da Silva et al. · 2023 [cited by applicant]
US 11668432B1 · Ledesma et al. · 2023 [cited by applicant]
US D996357S · Steenwyk · 2023 [cited by applicant]
US D996365S · Frazier · 2023 [cited by applicant]
US D1005937S · Mercer et al. · 2023 [cited by applicant]
US D1005938S · Mercer et al. · 2023 [cited by applicant]
US D1005939S · Zhong · 2023 [cited by applicant]
US D1005941S · Zhong · 2023 [cited by applicant]
US D1008950S · Prodaniuk et al. · 2023 [cited by applicant]
US D1015266S · Yoon et al. · 2024 [cited by applicant]
US D1019547S · Yan et al. · 2024 [cited by applicant]
US D1021775S · Fan et al. · 2024 [cited by applicant]
US D1021776S · Fan et al. · 2024 [cited by applicant]
US D1021777S · Fan et al. · 2024 [cited by applicant]
US D1021778S · Fan et al. · 2024 [cited by applicant]
US D1021779S · Fan et al. · 2024 [cited by applicant]
US D1022882S · Fan et al. · 2024 [cited by applicant]
US D1022883S · Fan et al. · 2024 [cited by applicant]
US D1022884S · Fan et al. · 2024 [cited by applicant]
US D1022885S · Fan et al. · 2024 [cited by applicant]
US D1029755S · Gehrmann et al. · 2024 [cited by applicant]
US D1030641S · Jung · 2024 [cited by applicant]
US D1030642S · Jung · 2024 [cited by applicant]
US D1030650S · Speidel · 2024 [cited by applicant]
US D1037143S · Koz et al. · 2024 [cited by applicant]
US D1038014S · Cumming et al. · 2024 [cited by applicant]
US D1040740S · Bauer · 2024 [cited by applicant]
US D1040744S · Koz et al. · 2024 [cited by applicant]
US D1040745S · Cumming et al. · 2024 [cited by applicant]
US D1040746S · Cumming et al. · 2024 [cited by applicant]
US D1044704S · Fan et al. · 2024 [cited by applicant]
US D1050023S · Peng · 2024 [cited by applicant]
US D1053802S · Helgesson et al. · 2024 [cited by applicant]
US D1059272S · Mercer et al. · 2025 [cited by applicant]
US D1060223S · Ledesma et al. · 2025 [cited by applicant]
US D1060226S · Yao et al. · 2025 [cited by applicant]
US D1061426S · Wang · 2025 [cited by applicant]
US D1061429S · Kim et al. · 2025 [cited by applicant]
US D1063827S · Ye et al. · 2025 [cited by applicant]
US D1063828S · Ye et al. · 2025 [cited by applicant]
US D1063834S · Letombe et al. · 2025 [cited by applicant]
US D1065062S · Ye et al. · 2025 [cited by applicant]
US D1065072S · Wang · 2025 [cited by applicant]
US D1066242S · Mercer et al. · 2025 [cited by applicant]
US D1068646S · Riggs et al. · 2025 [cited by applicant]
US D1068650S · Yoon et al. · 2025 [cited by applicant]
US 20120299529A1 · Guo · 2012 [cited by examiner]
US 20140142774A1 · Katayama et al. · 2014 [cited by applicant]
US 20220067850A1 · Bhasme et al. · 2022 [cited by applicant]
US 20220140610A1 · Bangalore · 2022 [cited by examiner]
US 20220161687A1 · Al-Sagheer et al. · 2022 [cited by applicant]
US 20220247179A1 · Orihashi et al. · 2022 [cited by applicant]
US 20220314831A1 · Abe · 2022 [cited by applicant]
US 20230001803A1 · Raaijmakers et al. · 2023 [cited by applicant]
US 20230026182A1 · Bae et al. · 2023 [cited by applicant]
US 20230256855A1 · Sartipizadeh · 2023 [cited by examiner]
US 20240109450A1 · Hair · 2024 [cited by examiner]
US 20240174102A1 · Molchanov et al. · 2024 [cited by applicant]
US 20240326622A1 · Shin et al. · 2024 [cited by applicant]
US 20250074221A1 · Lee et al. · 2025 [cited by applicant]
US 20250074222A1 · Lee et al. · 2025 [cited by applicant]
International Search Report in PCT/US23/72685 mailed on Nov. 14, 2023, 3 pages. [cited by applicant]
Written Opinion in PCT/US23/72685 mailed on Nov. 14, 2023, 6 pages. [cited by applicant]