Battery Run-Time Prediction System

• US 20110054817A1
• Filed: 09/01/2010
• Published: 03/03/2011
• Est. Priority Date: 09/02/2009
• Status: Abandoned Application

• Current Assignee: Jeff Burgett
• Original Assignee: Jeff Burgett
• Inventors: Burgett, Jeff
• Application Number:
  US12/874,198
• Publication Number:
  US 20110054817A1
• Time in Patent Office: Days
• US Class Current: 702/63
• CPC Class Codes: G01R 31/367 Software therefor, e.g. for battery testing using modelling or look-up tables
• CPC Class Codes: G01R 31/371 with remote indication, e.g. on external chargers
• CPC Class Codes: G01R 31/396 Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
• CPC Class Codes: H01M 10/06 Lead-acid accumulators semi-lead accumulators H01M10/20
• CPC Class Codes: H01M 10/48 Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte constructional details of current conducting connections for detecting conditions inside cells or batteries, e.g. details of voltage sensing terminals, H01M50/569
• CPC Class Codes: Y02E 60/10 Energy storage using batteries

Abstract

Embodiments of the present disclosure include a computer implemented method and system for sampling battery runtime-related information from the batteries to provide an ongoing estimate of the remaining runtime left at a remote location based, at least in part, on a combination of computing techniques and statistical and mathematical models.

Claims

1. A method for sampling battery runtime-related information from one or more battery strings to provide an ongoing estimate of a remaining runtime left at a remote location, the method comprising:

receiving input data for each battery string of the one or more battery strings;

evaluating the input data and synthesizing one or more pieces of supplemental data;

filtering the input data and the one or more pieces of supplemental data;

storing the previously filtered data;

generating a discharge model based on the stored filtered data;

determining a remaining runtime for the one or more battery strings based on the discharge model; and

communicating a return code for the one or more battery strings based on the corresponding remaining runtime and average string voltage.

2. The method of claim 1, wherein filtering the input data comprises normalizing the voltage of at least one of the one or more battery strings.

3. The method of claim 1, wherein the input data does not include the voltage measurements of an individual battery of the one or more battery strings.

4. The method of claim 1, wherein determining a remaining runtime for the one or more battery strings comprises predicting an unadjusted cutoff time and a non-linear discharge correction element.

5. The method of claim 4, wherein predicting an unadjusted cutoff time is based, at least in part, on linear extrapolation.

6. The method of claim 4, wherein the non-linear discharge correction element is a decay function.

7. The method of claim 1 further comprising determining a remaining runtime for the entire remote location.

8. The method of claim 7 wherein determining a remaining runtime for the entire remote location comprises smoothing results using a combination of voting scheme, averaging, and case based heuristics.

9. An apparatus for sampling battery runtime-related information from one or more battery strings to provide an ongoing estimate of a remaining runtime left at a remote location, the apparatus comprising:

means for receiving input data for each battery string of the one or more battery strings;

means for evaluating the input data and synthesizing one or more pieces of supplemental data;

means for filtering the input data and the one or more pieces of supplemental data;

means for storing the previously filtered data;

means for generating a discharge model based on the stored filtered data;

means for determining a remaining runtime for the one or more battery strings based on the discharge model; and

means for communicating a return code for the one or more battery strings based on the corresponding remaining runtime and average string voltage.

10. The apparatus of claim 9, wherein the means for filtering the input data comprises normalizing the voltage of at least one of the one or more battery strings.

11. The apparatus of claim 9, wherein the input data does not include the voltage measurements of an individual battery of the one or more battery strings.

12. The apparatus of claim 9, wherein the means for determining a remaining runtime for the one or more battery strings comprises the means for predicting an unadjusted cutoff time and a non-linear discharge correction element.

13. The apparatus of claim 12, wherein the means for predicting an unadjusted cutoff time is configured to utilize, at least in part, linear extrapolation.

14. The apparatus of claim 12, wherein the means for a non-linear discharge correction element is configured to utilize a decay function.

15. The apparatus of claim 9 further comprising a means for determining a remaining runtime for the entire remote location.

16. The apparatus of claim 15 wherein the means for determining a remaining runtime for the entire remote location is configured to utilize a means for smoothing results using a combination of voting scheme, averaging, and case based heuristics.

17. A computer program product for sampling battery runtime-related information from one or more battery strings to provide an ongoing estimate of a remaining runtime left at a remote location, the computer program product comprising:

code for receiving input data for each battery string of the one or more battery strings;

code for evaluating the input data and synthesizing one or more pieces of supplemental data;

code for filtering the input data and the one or more pieces of supplemental data;

code for storing the previously filtered data;

code for generating a discharge model based on the stored filtered data;

code for determining a remaining runtime for the one or more battery strings based on the discharge model; and

code for communicating a return code for the one or more battery strings based on the corresponding remaining runtime and average string voltage.

18. The computer program product of claim 17, wherein code for filtering the input data comprises normalizing the voltage of at least one of the one or more battery strings.

19. The computer program product of claim 17, wherein the input data does not include the voltage measurements of an individual battery of the one or more battery strings.

20. The computer program product of claim 17, wherein code for determining a remaining runtime for the one or more battery strings comprises predicting an unadjusted cutoff time and a non-linear discharge correction element.

21. The computer program product of claim 20, wherein code for predicting an unadjusted cutoff time is based, at least in part, on linear extrapolation.

22. The computer program product of claim 20, wherein the non-linear discharge correction element is a decay function.

23. The computer program product of claim 17 further comprising code for determining a remaining runtime for the entire remote location.

24. The computer program product of claim 23 wherein code for determining a remaining runtime for the entire remote location comprises smoothing results using a combination of voting scheme, averaging, and case based heuristics.