Method and apparatus for estimating battery life

1. A method of estimating battery life, the method comprising:

acquiring, from a battery, battery information;

calculating first status information of the battery based on the battery information, the first status information comprising a first internal parameter of the battery;

acquiring a partial cycle model modeling a battery degradation pattern caused by a number of partial cycles of the battery;

determining a partial cycle count of the battery;

calculating, by applying the partial cycle model to the partial cycle count, second status information, the second status information comprising a second internal parameter of the battery;

comparing the first status information and the second status information to generate a comparison result;

calculating the battery life based on the comparison result; and

adjusting a structure of the partial cycle model to match the second status information with the first status information, in response to the comparison result indicating that the first status information differs more than a threshold amount from the second status information.

2. The method of claim 1 , wherein the calculating comprises, upon the comparison result indicating that the first status information is within a threshold range of the second status information, using the partial cycle model to calculate the battery life based on user history information.

3. The method of claim 2 , wherein:

the battery life corresponds to a remaining useful life of the battery; and

the calculating of the battery life from the user history information comprises

extracting statistical information associated with the partial cycle model from the user history information,

calculating third status information of the battery based on the statistical information, and

calculating the remaining useful life based on the third status information.

4. The method of claim 3 , wherein the estimating of the third status information comprises:

estimating, from the statistical information and using the partial cycle model, a predictive partial cycle count of a number of future partial cycles of the battery; and

calculating, as the third status information, either one or both of a predicted future capacitance or a predicted future internal resistance based on the predictive partial cycle count by applying the partial cycle model to the predictive partial cycle count.

5. The method of claim 1 , wherein the partial cycle model is a model derived by transforming a full cycle model associated with a degradation caused by a full charge and discharge of the battery.

6. The method of claim 1 , wherein the estimating of the first status information comprises:

acquiring an equivalent model corresponding to the battery; and

estimating, as the first status information and using the battery information and the equivalent model, an internal parameter of the equivalent model.

7. The method of claim 6 , wherein the estimating of the internal parameter comprises estimating, as the first status information, the internal parameter using a state space corresponding to the equivalent model.

8. The method of claim 1 , wherein the estimating of the second status information comprises estimating, as the second status information, either one or both of a capacitance and an internal resistance estimated from a partial cycle count of the battery using the partial cycle model.

9. The method of claim 1 , wherein the battery information comprises any one or any combination of any two or more of a voltage, a current, a temperature, a cycle count, or a partial cycle count of the battery.

10. An apparatus for estimating battery life, the apparatus comprising:

a processor configured to

acquire, from a battery, battery information;

calculate first status information of the battery based on the battery information, the first status information comprising a first internal parameter of the battery,

acquire a partial cycle model modeling a battery degradation pattern caused by a number of partial cycles of the battery,

determine a partial cycle count of the battery,

calculate, by applying the partial cycle model to the partial cycle count, second status information of the battery, the second status information comprising a second internal parameter of the battery,

compare the first status information and the second status information to generate a comparison result,

calculate the battery life based on the comparison result, and

adjust a structure of the partial cycle model to match the second status information with the first status information, in response to the comparison result indicating that the first status information differs more than a threshold amount from the second status information.

11. The apparatus of claim 10 , wherein the processor is further configured to, upon the comparison result indicating that the first status information is within a threshold range of the second status information, use the partial cycle model to calculate the battery life based on user history information.

12. The apparatus of claim 11 , wherein:

the battery life corresponds to a remaining useful life of the battery; and

the processor is further configured to

extract statistical information associated with the partial cycle model from the user history information,

calculate third status information of the battery based on the statistical information, and

calculate the remaining useful life based on the third status information.

13. The apparatus of claim 12 , wherein the processor is further configured to:

estimate, from the statistical information and using the partial cycle model, a predictive partial cycle count of a number of future partial cycles of the battery; and

calculate, as the third status information, either one or both of a predicted future capacitance or a predicted future internal resistance based on the predictive partial cycle count, by applying the partial cycle model to the predictive partial cycle count.

14. The apparatus of claim 10 , further comprising:

a model storage configured to store the partial cycle model, wherein the partial cycle model is a model derived by transforming a full cycle model associated with a degradation caused by a full charge and discharge of the battery.

15. The apparatus of claim 10 , wherein the processor is further configured to:

acquire an equivalent model corresponding to the battery; and

estimate, as the first status information and using the battery information and the equivalent model, an internal parameter of the equivalent model.

16. The apparatus of claim 15 , wherein the processor is further configured to estimate, as the first status information, the internal parameter using a state space corresponding to the equivalent model.

17. The apparatus of claim 10 , wherein the second estimator is configured to estimate, as the second status information, either one or both of a capacitance and an internal resistance estimated from a partial cycle count of the battery using the partial cycle model.

18. The apparatus of claim 10 , wherein the battery information comprises any one or any combination of any two or more of a voltage, a current, a temperature, a cycle count, or a partial cycle count of the battery.

19. An apparatus for estimating battery life, the apparatus comprising:

a sensor configured to detect battery performance information of a battery that powers a device, the battery performance information comprising any one or any combination of any two or more of a voltage, a current, a temperature, a cycle count, or a partial cycle count of the battery; and

a processor configured to

extract, from the battery performance information, status information indicating either one or both of a capacitance or an internal resistance of the battery,

retrieve historic data comprising past partial charge cycles of the battery from a memory storage,

estimate a battery life of the battery based on the status information and the historic data by applying, to the battery performance information and the historic data, a partial cycle model corresponding to a battery degradation pattern to estimate the battery life, and

adjust a structure of the partial cycle model to match a second status information with a first status information, in response to the comparison results indicating that the first status information differs more than a threshold amount from the second status information,

wherein the first status information is calculated from the status information and the second status information is calculated based on the partial cycle model.

20. The apparatus of claim 19 , wherein the battery life corresponds to a remaining useful life of the battery.

21. An electric vehicle comprising:

a battery compartment configured to hold the battery; and

the apparatus of claim 19 , wherein the apparatus further comprises a display screen configured to output information regarding the battery life to a dashboard of the electric vehicle.