SYSTEM AND METHOD FOR PREDICTIVE MAINTENANCE OF A BATTERY ASSEMBLY USING TEMPORAL SIGNAL PROCESSING

• US 20090009183A1
• Filed: 07/05/2007
• Published: 01/08/2009
• Est. Priority Date: 07/05/2007
• Status: Active Grant

• Current Assignee: ABB Schweiz AG (ABB Limited)
• Original Assignee: ABB Research Ltd. (ABB Ltd.)
• Inventors: Mousavi, Mirrasoul J., Bayoumi, Deia, Maharsi, Mohamed, McGowan, John J.
• Granted Patent: US 8,154,297 B2
• Time in Patent Office: Days
• US Class Current: 324/537
• 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: G05B 23/0232 based on qualitative trend analysis, e.g. system evolution
• CPC Class Codes: G05B 23/027 Alarm generation, e.g. communication protocol; Forms of alarm

Abstract

A technique of monitoring a battery assembly may include monitoring a parameter associated with the battery assembly to obtain a number of monitored parameter samples. A temporal sequence of monotonically increasing values may be generated from the monitored parameter samples. The temporal sequence may be analyzed for an indication of a trend in the monitored parameter toward one of an upper operational boundary or a lower operational boundary to predict a fault condition of the battery assembly.

Claims

1. A method of monitoring a battery assembly, comprising:

monitoring a parameter associated with the battery assembly to obtain a number of monitored parameter samples;

generating a temporal sequence of monotonically increasing values from the monitored parameter samples; and

analyzing the temporal sequence for an indication of a trend in the monitored parameter toward one of an upper operational boundary or a lower operational boundary to predict a fault condition of the battery assembly.

2. The method of claim 1, wherein the analyzing includes deriving an alarm signal from the temporal sequence, the alarm signal having a series of values based on an application of a Laplace test statistic to the temporal sequence values.

3. The method of claim 2, wherein the analyzing further includes comparing the alarm signal against at least one of an upper threshold or a lower threshold.

4. The method of claim 3, further comprising generating an alarm if the alarm signal violates the upper threshold or the lower threshold for a predetermined number of alarm signal values.

5. The method of claim 2, wherein the analyzing further includes normalizing the alarm signal.

6. The method of claim 5, wherein the analyzing further includes comparing the normalized alarm signal against at least one of an upper threshold or a lower threshold.

7. The method of claim 6, further comprising generating an alarm if the normalized alarm signal violates the upper threshold or the lower threshold for a predetermined number of alarm signal values.

8. The method of claim 6, further comprising generating an alarm if the normalized alarm signal violates the upper threshold or the lower threshold.

9. The method of claim 1, wherein the battery assembly is at least part of a lead acid battery system.

10. The method of claim 1, wherein the battery assembly is monitored while in use.

11. The method of claim 10, wherein the battery assembly is a primary power source for a load.

12. The method of claim 10, wherein the battery assembly is a backup power source for a load.

13. The method of claim 1, wherein the battery assembly is used in an electrical power transmission and distribution substation.

14. The method of claim 1, wherein the monitored parameter is a function of at least one of voltage, current, impedance or temperature.

15. A program stored on a machine readable medium, the program for monitoring a battery assembly and comprising:

code that generates a temporal sequence of monotonically increasing values based on a series of monitored parameter samples, the monitored parameter samples obtained by monitoring a parameter associated with the battery assembly; and

code that analyzes the temporal sequence for an indication of a trend in the monitored parameter toward one of an upper operational boundary or a lower operational boundary to predict a fault condition of the battery assembly.

16. The program of claim 15, wherein the code that analyzes derives an alarm signal from the temporal sequence, the alarm signal having a series of values based on an application of a Laplace test statistic to the temporal sequence values.

17. The program of claim 16, further comprising code that generates an alarm if a representation of the alarm signal violates an upper threshold or a lower threshold for a predetermined number of alarm signal values.

18. The program of claim 17, wherein the representation of the alarm signal is a normalized alarm signal.

19. A predictive monitoring assembly for a battery assembly, comprising an analyzer that generates a temporal sequence of monotonically increasing values based on a series of monitored parameter samples, the monitored parameter samples obtained by monitoring a parameter associated with the battery assembly, and that analyzes the temporal sequence for an indication of a trend in the monitored parameter toward one of an upper operational boundary or a lower operational boundary to predict a fault condition of the battery assembly.

20. The predictive monitoring assembly of claim 19, wherein the analyzer derives an alarm signal from the temporal sequence, the alarm signal having a series of values based on an application of a Laplace test statistic to the temporal sequence values.

21. The predictive monitoring assembly of claim 20, wherein the analyzer generates an alarm if a representation of the alarm signal violates an upper threshold or a lower threshold for a predetermined number of alarm signal values.

22. The predictive monitoring assembly of claim 19, further comprising a monitoring assembly that measures a parameter associated with the battery assembly.

23. The predictive monitoring assembly of claim 19, wherein the battery assembly is at least part of a lead acid battery system.

24. The predictive monitoring assembly of claim 19, wherein the battery assembly is monitored while in use.

25. The predictive monitoring assembly of claim 24, wherein the battery assembly is a primary power source for a load.

26. The predictive monitoring assembly of claim 24, wherein the battery assembly is a backup power source for a load.

27. The predictive monitoring assembly of claim 19, wherein the battery assembly is used in an electrical power transmission and distribution substation.

28. The predictive monitoring assembly of claim 19, wherein the monitored parameter is a function of at least one of voltage, current, impedance or temperature.