Systems and techniques for predicting life of battery, and battery management system operating the same

Patent metadata

Field	Value
Publication number	US-2023384391-A1
Application number	US-202318188916-A
Country	US
Kind code	A1
Filing date	Mar 23, 2023
Priority date	May 31, 2022
Publication date	Nov 30, 2023
Grant date	—

Abstract

A method of predicting a battery lifespan includes estimating a state of health (SOH) of a battery by integrating an amount of electric current while a state of charge (SOC) of the battery mounted in each of a plurality of systems changes, dividing the plurality of systems into a plurality of groups according to a usage pattern collected by each of the plurality of systems at every predetermined period, generating a usage scenario of the battery in each of the plurality of systems, using a usage environment of each of the plurality of groups and the usage pattern, and predicting, for each of the plurality of systems, an end-of-life time of the battery using the usage scenario and the SOH of the battery.

First claim

What is claimed is:

1 . A method of predicting a lifespan of each of batteries respectively connected in a plurality of systems, comprising:
estimating a state of health (SOH) of a battery in one of the plurality of systems by integrating an amount of an electric current of the battery while a state of charge (SOC) of the battery changes; dividing the plurality of systems into a plurality of groups according to a usage pattern collected by each of the plurality of systems at every predetermined period; generating a usage scenario of the battery in each of the plurality of systems, using a usage environment of each of the plurality of groups and the usage pattern; and predicting, for each of the plurality of systems, lifespan information of the battery using the usage scenario and the SOH of the battery.

2 . The method of claim 1 , wherein the estimating of the SOH of the battery includes,
calculating a charging energy or a discharging energy of the battery by accumulating a charging electric current or a discharging electric current, respectively, while the SOC of the battery is changing, calculating a first energy of the battery corresponding to a fully charged state of the battery using the charging energy or the discharging energy, and calculating the SOH of the battery by comparing the first energy with a second energy of the battery corresponding to a fully charged state at a time of shipment of the battery.

3 . The method of claim 1 , wherein the usage pattern includes a charging pattern and a discharging pattern of the battery mounted in each of the plurality of systems.

4 . The method of claim 1 , wherein each of the plurality of systems is an electric vehicle, and the usage scenario includes a use of the battery, a driving profile, a mileage, a driving environment, a charging habit of the electric vehicle, or combinations thereof.

5 . The method of claim 4 , wherein the driving profile and the mileage vary depending on a use of the electric vehicle, and the driving environment varies depending on a driving area of the electric vehicle.

6 . The method of claim 1 , wherein each of the plurality of systems is an energy storage device, and the usage scenario includes equipment using the energy storage device as a power source, a surrounding environment in which the equipment operates, or combinations thereof.

7 . The method of claim 1 , wherein each of the plurality of systems is an electric vehicle, and the SOH is estimated after the electric vehicle stops and a predetermined stabilization time elapses.

8 . The method of claim 1 , wherein the plurality of systems divided into the plurality of groups are updated according to the usage pattern collected by each of the plurality of systems at every predetermined period.

9 . The method of claim 1 , wherein an end-of-life time included in the lifespan information is predicted in a predetermined cycle unit.

10 . A battery management system for managing batteries respectively connected in a plurality of systems comprising:
a state of health (SOH) estimation model estimating an SOH of a battery connected in one of the systems by integrating an amount of an electric current of the battery while an SOC of the battery-changes; a scenario generation model classifying the plurality of systems into a plurality of groups based on a usage pattern collected from each of the plurality of systems, and generating a usage scenario of the battery according to a usage environment and a usage pattern of each of the plurality of groups; and a lifespan prediction model predicting an end-of-life time of the battery using the SOH of the battery estimated by the SOH estimation model and the usage scenario.

11 . The battery management system of claim 10 , wherein the SOH estimation model, the scenario generation model, and the lifespan prediction model are stored and executed in a server connected to a network that is communicable, and
the server is connected to a terminal that collects the SOC of the battery, the amount of electric current of the battery, the usage pattern of the battery and the usage environment of each of the plurality of groups in each of the plurality of systems, through the network.

12 . The battery management system of claim 11 , wherein the server guides the end-of-life time to administrators of the plurality of systems through the network.

13 . The battery management system of claim 11 , wherein the server receives and stores access information for an administrator of one or more systems among the plurality of systems from the administrator, and transmits the end-of-life time to a mobile device of the administrator.

14 . The battery management system of claim 10 , wherein the scenario generation model divides the plurality of systems into the plurality of groups based on a charging pattern and a discharging pattern of the battery, and generates the usage scenario according to a usage environment of the plurality of systems, a surrounding charging infrastructure, a type of the plurality of systems, or combinations thereof.

15 . The battery management system of claim 10 , wherein the scenario generation model collects the usage pattern at every predetermined period, re-classifies the plurality of systems into the plurality of groups, and regenerates the usage scenario at the predetermined period, and
the lifespan prediction model predicts the end-of-life time at every predetermined period, based on the SOH of the battery estimated by the SOH estimation model during the predetermined period and the usage scenario regenerated by the scenario generation model.

16 . A battery management method executed in a server communicatively connected to a system including a battery and a battery management system, the battery management method comprising:
receiving raw data collected from the battery by the battery management system for a predetermined period of time; extracting characteristic information from the raw data; grouping the system into a predetermined group based on the characteristic information; generating a usage scenario to be applied to the group by inputting the characteristic information into a scenario generation model; predicting a remaining lifespan of the battery by inputting the usage scenario into a lifespan prediction model; and transmitting the remaining lifespan of the battery to a communication terminal of a user of the system through a communication network.

17 . The battery management method of claim 16 , wherein when the system is a new system newly connected to the server, the new system is grouped by comparing the characteristic information of an existing system already connected to the server with the characteristic information of the new system.

18 . The battery management method of claim 16 , wherein the characteristic information includes a usage pattern of the battery mounted in the system.

Assignees

• Sk Innovation Co Ltd
• Sk On Co Ltd

Inventors

• Kwak Ju Eun
• Song Kyung Min
• Kwon Ky Sang

Classifications

• G01R31/392 Primary

  Determining battery ageing or deterioration, e.g. state of health · CPC title

• G01R31/367 Primary

  Software therefor, e.g. for battery testing using modelling or look-up tables · CPC title

• G01R31/371

  with remote indication, e.g. on external chargers · CPC title

• B60L58/16

  responding to battery ageing, e.g. to the number of charging cycles or the state of health [SoH] · CPC title

• B60L58/12

  responding to state of charge [SoC] · CPC title