Apparatus and method for estimating stage of charge of battery

• US 9,310,441 B2
• Filed: 10/24/2013
• Issued: 04/12/2016
• Est. Priority Date: 10/26/2012
• Status: Active Grant

• Current Assignee: LG Energy Solution Limited (LG Corporation)
• Original Assignee: LG Chem Limited (LG Corporation)
• Inventors: Jo, Youngchang
• Primary Examiner(s): COSIMANO, EDWARD R
• Application Number:
  US14/359,768
• Publication Number:
  US 20150046107A1
• Time in Patent Office: 901 Days
• Field of Search: 734/321, 738/658, 738/659, 738/663, 320/127, 320/128, 320/130, 320/132, 320/134, 320/135, 320/136, 324/425, 324/426, 324/432, 324/435, 324/500, 324/537, 324/764.01, 340/500, 340/540, 340/635, 340/636.1, 340/636.19, 702/1, 702/33, 702/34, 702/57, 702/60, 702/63, 702/127, 702/182, 702/187, 702/189, 708/100, 708/105, 708/200
• US Class Current: 1/1
• CPC Class Codes: G01R 31/3648 comprising digital calculation means, e.g. for performing an algorithm
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/382 Arrangements for monitoring battery or accumulator variables, e.g. SoC
• CPC Class Codes: G06F 17/40 Data acquisition and logging for input to computer G06F3/00
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Provided are battery SOC estimating apparatus and method. The battery SOC estimating apparatus according to the present invention includes an input/output power pattern analyzing unit which analyzes an input/output power of a battery during a predetermined time to obtain an input/output power pattern of the battery; an application status determining unit which analyzes the input/output power pattern of the battery to determine a current application status of the battery; and an SOC calculating unit which calculates an SOC of the battery using a state of charge (SOC) estimation algorithm corresponding to the current application status of the battery.

Claims

1. A battery state of charging estimating apparatus, comprising:

an input/output power pattern analyzing unit which analyzes an input/output power of a battery during a predetermined time to obtain an input/output power pattern of the battery;

an application status determining unit which analyzes the input/output power pattern of the battery to determine a current application status of the battery;

an SOC calculating unit which calculates an SOC of the battery using a state of charging (SOC) estimation algorithm corresponding to the current application status of the battery; and

a battery management system receiving the SOC of the battery from the SOC calculating unit and managing the status and performance of the battery based on the SOC of the battery.

2. The apparatus of claim 1, wherein the input/output power pattern includes a short-term input/output power pattern and a long-term input/output power pattern, and

the input/output power pattern analyzing unit includes a short-term input/output power pattern analyzing unit which analyzes an input/output power of a battery during a first setting time to obtain a short-term input/output power pattern of the battery;

and

a long-term input/output power pattern analyzing unit which analyzes an input/output power of the battery during a second setting time which is longer than the first setting time to obtain a long-term input/output power pattern of the battery.

3. The apparatus of claim 1, wherein the SOC estimation algorithm includes an extended Kaman filter (EKF) SOC estimation algorithm or a smart SOC moving estimation (SSME) algorithm.

4. The apparatus of claim 3, wherein when a depth of discharge (DOD) of the input/output power pattern of the battery is a predetermined reference value or higher, the SOC calculating unit calculates the SOC of the battery using the EKF SOC estimation algorithm.

5. The apparatus of claim 3, wherein when the DOD of the input/output power pattern of the battery is lower than a predetermined reference value, the SOC calculating unit calculates the SOC of the battery using the SSME algorithm.

6. The apparatus of claim 3, further comprising:

a current sensor checking unit which checks whether a current sensor which measures a value of a current which is input/output to/from the battery is provided or the current sensor normally operates.

7. The apparatus of claim 6, wherein if the current sensor checking unit determines that no current sensor is provided or the current sensor abnormally operates, the SOC calculating unit calculates the SOC of the battery using the SSME algorithm.

8. The apparatus of claim 3, wherein the current application status of the battery includes one or more of a constant current (CC) status, a photovoltaic (PV) status, a frequency regulation (FR) status, and a peak shaving (PS) status.

9. The apparatus of claim 8, wherein when the current application status of the battery is the CC status or the PV status, the SOC calculating unit calculates the SOC of the battery using the EKF SOC estimation algorithm.

10. The apparatus of claim 8, wherein when the current application status of the battery is the FR status or the PS status, the SOC calculating unit calculates the SOC of the battery using the SSME algorithm.

11. A battery state of charging estimating method, comprising:

obtaining an input/output power pattern of a battery by analyzing an input/output power of the battery during a predetermined time;

determining a current application status of the battery by analyzing the input/output power pattern of the battery;

calculating a state of charging (SOC) of the battery using an SOC estimation algorithm corresponding to the current application status of the battery; and

managing the status and performance of the battery with a battery management system based on the SOC of the battery received from the SOC calculating unit.

12. The method of claim 11, wherein the input/output power pattern includes a short-term input/output power pattern and a long-term input/output power pattern, and

the obtaining of an input/output power pattern of a battery includes:

obtaining a short-term input/output power pattern of the battery by analyzing an input/output power of a battery during a first setting time; and

obtaining a long-term input/output power pattern of the battery by analyzing an input/output power of the battery during a second setting time which is longer than the first setting time.

13. The method of claim 11, wherein the SOC estimation algorithm includes an extended Kaman filter (EKF) SOC estimation algorithm or a smart SOC moving estimation (SSME) algorithm.

14. The method of claim 13, wherein when a depth of discharge (DOD) of the input/output power pattern of the battery is a predetermined reference value or higher, the calculating of an SOC of the battery includes calculating the SOC of the battery using the EKF SOC estimation algorithm.

15. The method of claim 13, wherein when the DOD of the input/output power pattern of the battery is lower than a predetermined reference value, the calculating of an SOC of the battery includes calculating the SOC of the battery using the SSME algorithm.

16. The method of claim 13, further comprising:

checking whether a current sensor which measures a value of a current which is input/output to/from the battery is provided or the current sensor normally operates.

17. The method of claim 16, wherein if it is determined that no current sensor is provided or the current sensor abnormally operates in the checking whether a current sensor is provided, the calculating of an SOC of the battery includes calculating the SOC of the battery using the SSME algorithm.

18. The method of claim 13, wherein the current application status of the battery includes one or more of a constant current (CC) status, a photovoltaic (PV) status, a frequency regulation (FR) status, and a peak shaving (PS) status.

19. The method of claim 18, wherein when the current application status of the battery is the CC status or the PV status, the calculating of an SOC of the battery includes calculating the SOC of the battery using the EKF SOC estimation algorithm.

20. The method of claim 18, wherein when the current application status of the battery is the FR status or the PS status, the calculating of an SOC of the battery includes calculating the SOC of the battery using the SSME algorithm.