System and method with battery management

1. A processor-implemented battery management method, the method comprising:

determining a composite state of charge (SoC) of a battery by applying fractions of components in an electrode of the battery to a composite cathode model;

redetermining the composite SoC based on a comparison of the composite SoC and a predetermined composite SoC of the battery; and

predicting a state of the battery based on the redetermined composite SoC.

2. The method of claim 1 , wherein the redetermining of the composite SoC is based on the fractions of the components, a concentration of each of the components, and an individual SoC of each of the components.

3. The method of claim 1 , wherein the redetermining of the composite SoC comprises:

identifying a result of a cost function corresponding to a difference between the determined composite SoC and the predetermined composite SoC, the predetermined composite SoC being an experimental SoC of the battery that is derived through an experiment; and

determining whether to redetermine the fractions of the components, by comparing the identified result of the cost function to a predetermined threshold.

4. The method of claim 3 , wherein the determining of whether to redetermine the fractions of the components comprises determining the fractions of the components as accurately-determined fractions of the components, in response to the identified result of the cost function being less than or equal to the threshold.

5. The method of claim 3 , wherein

the determining of whether to redetermine the fraction of the components comprises determining to redetermine the fractions of the components, in response to the identified result of the cost function being greater than the threshold, and

the redetermining of the fractions of the components comprises redetermining the fractions of the components based on the fractions of the components, a rate of change in the fractions, a rate of change in previously-determined results of the cost function identified based on the fractions, and a learning rate, in response to the determination to redetermine the fractions of the components.

6. The method of claim 1 , wherein the predicting of the state of the battery comprises predicting states of batteries other than the battery in a battery pack.

7. The method of claim 6 , wherein the predicting of the states of the other batteries comprises predicting the states of the other batteries based on a change in an active material and a change in a composite SoC between the battery and the other batteries.

8. The method of claim 1 , further comprising:

calculating at least one of an intercalation rate and a deintercalation rate of lithium (Li)-ions based on a non-uniformity of a reaction rate based on a thickness of the electrode,

wherein the predicting of the state of the battery comprises predicting the state of the battery based on either one or both of the calculated intercalation rate and the calculated deintercalation rate.

9. The method of claim 1 , further comprising managing the battery based on the predicted state of the battery.

10. A non-transitory computer-readable recording medium storing instructions that, when executed by one or more processors, configure the one or more processors to perform the method of claim 1 .

11. A battery management system, the system comprising:

one or more processors configured to:

determine a composite state of charge (SoC) of a battery by applying fractions of components in an electrode of the battery to a composite cathode model;

redetermine the composite SoC based on a comparison of the composite SoC and a predetermined composite SoC of the battery; and

predict a state of the battery based on the redetermined composite SoC.

12. The system of claim 11 , wherein, for the redetermining of the composite SoC, the one or more processors are configured to redetermine the composite SoC based on the fractions of the components, a concentration of each of the components, and an individual SoC of each of the components.

13. The system of claim 11 , wherein, for the redetermining of the composite SoC, the one or more processors are configured to:

identify result of a cost function corresponding to a difference between the determined composite SoC and the predetermined composite SoC, the predetermined composite SoC being an experimental SoC of the battery that is derived through an experiment; and

determine whether to redetermine the fractions of the components, by comparing the identified result of the cost function to a predetermined threshold.

14. The system of claim 13 , wherein, for the determining of whether to redetermine the fractions of the components, the one or more processors are configured to determine the fractions of the components as accurately-determined fractions of the components, in response to the identified result of the cost function being less than or equal to the threshold.

15. The system of claim 13 , wherein the one or more processors are configured to:

for the determining of whether to redetermine the fraction of the components, determine to redetermine the fractions of the components, in response to the identified result of the cost function being greater than the minimum threshold; and

redetermine the fractions of the components based on the fractions of the components, a rate of change in the fractions, a rate of change in previously-determined results of the cost function identified based on the fractions, and a learning rate, in response to the determination to redetermine the fractions of the components.

16. The system of claim 11 , wherein the one or more processors are configured to predict states of batteries other than the battery in a battery pack.

17. The system of claim 16 , wherein the one or more processors are configured to predict the states of the other batteries based on a change in an active material and a change in a composite SoC between the battery and the other batteries.

18. The system of claim 11 , wherein the one or more processors are configured to:

calculate at least one of an intercalation rate and a deintercalation rate of lithium (Li)-ions based on a non-uniformity of a reaction rate based on a thickness of the electrode; and

predict the state of the battery based either one or both of the calculated intercalation rate and the calculated deintercalation rate.

19. The system of claim 11 , further comprising memory storing instructions that, wherein when executed by the one or more processors, configure the one or more processors to perform the determination, the redetermination, and the prediction.

20. A battery management method, the method comprising:

iteratively applying fractions of components in an electrode of a battery to a composite electrode model to determine a composite state of charge (SoC) of the battery, and updating the fractions of the components based on a comparison of the composite SoC and a predetermined composite SoC of the battery;

determining conclusory fractions of the components based on the iterative applying and updating of the fractions of the components; and

determining a conclusory composite SoC of the battery by applying the determined conclusory fractions of the components to the composite electrode model.

21. The method of claim 20 , wherein

the determining of the conclusory fractions of the components comprises determining fractions of the components, from among the iteratively updated fractions of the components, to be the conclusory fractions of the components based on a result of a cost function of the composite electrode model with the updated fractions of the components applied, and

the cost function is based on the difference between the composite SoC determined by applying the updated fractions of components to the composite electrode model and the predetermined composite SoC predetermined by experiment.

22. A battery management method, the method comprising:

determining a preliminary composite state of charge (SoC) of a battery by applying fractions of components in an electrode of the battery to a composite electrode model;

determining a result of a cost function based on a difference between the determined preliminary composite SoC and an SoC predetermined by experiment;

updating the fractions of the components based on a comparison of the result of the cost function to a predetermined threshold; and

determining a conclusory composite SoC of the battery by applying the updated fractions of components in an electrode of the battery to the composite electrode model.