Determining remaining life fraction for battery networks in-situ

• US 8,831,897 B2
• Filed: 11/14/2010
• Issued: 09/09/2014
• Est. Priority Date: 11/14/2010
• Status: Expired due to Fees

• Current Assignee: Biourja Energy Systems, Llc
• Original Assignee: Global Energy Innovations, Inc. (GEI Global Energy Corp.)
• Inventors: McHardy, John
• Primary Examiner(s): Huynh, Phuong
• Application Number:
  US12/945,886
• Publication Number:
  US 20120123712A1
• Time in Patent Office: 1,395 Days
• Field of Search: 702 63- 65, 702182-190
• US Class Current: 702/63
• CPC Class Codes: G01R 31/389 Measuring internal impedance, internal conductance or related variables
• CPC Class Codes: G01R 31/392 Determining battery ageing or deterioration, e.g. state of health

Abstract

Determination of a remaining life fraction for a network of batteries during use in an electrical circuit is disclosed. A state of health of the battery network can be determined by measuring a change in impedance characteristics of the individual battery units and/or the battery network as a whole. More specifically, a mode and a severity of a failure can be determined for individual battery units.

Claims

1. A computer-implemented method for determining a remaining life fraction for a network of battery units, comprising:

receiving information describing an application for the network of battery units;

receiving historical impedance data concerning the network of battery units;

measuring an instantaneous impedance response to a perturbation signal applied to each of the battery units while in operation for the application;

determining a mode and estimating a severity of a failure for at least one individual battery unit from a change in impedance characteristics between historical and instantaneous impedance; and

predicting a remaining life fraction for the network of battery units based on the mode and the severity of failure of the at least one individual battery unit.

2. The method of claim 1, wherein the application comprises a passive application of the network of battery units while in operation as a back-up source of power to a primary source of power, and wherein predicting the remaining life fraction is also based on the application.

3. The method of claim 1, wherein the application comprises an active application of the network of battery units while in operation as a primary source of power, and wherein predicting the remaining life fraction is also based on the application.

4. The method of claim 1, wherein identifying the change in impedance comprises identifying an increased spread among individual battery units in the degree of change of at least one of the impedance characteristics.

5. The method of claim 1, wherein the perturbation signal comprises a multi-frequency perturbation signal, and wherein estimating the mode and severity of the failure comprises identifying a change in impedance characteristics across multiple frequencies.

6. The method of claim 5, wherein determining the mode and estimating the severity of the failure is based on the impedance response of the at least one battery unit to the multi-frequency perturbation signal.

7. The method of claim 5, wherein the failure mode comprises corrosion of the positive electrode grid.

8. The method of claim 5, wherein the failure mode comprises loss of water.

9. The method of claim 5, wherein the failure mode comprises sulfation.

10. The method of claim 5, wherein the failure mode comprises a manufacturing defect.

11. The method of claim 1, wherein the measured impedance response comprises a real component, an imaginary component, and a phase shift, and wherein determining the mode and the severity of the failure is based on a change in at least one of the real component, the imaginary component and the phase shift.

12. The method of claim 11, wherein a change in the imaginary component indicates that the failure mode is sulfation.

13. The method of claim 1, further comprising:

identifying a temperature differential between negative and positive terminals of the at least one individual battery, wherein the temperature differential indicates that the failure mode is grid corrosion.

14. The method of claim 1, further comprising:

receiving information describing a topology of the network of battery units that describes a relative location of individual battery units; and

adjusting the estimation of the severity of the failure in accordance with a relative location for the at least one battery unit.

15. A non-transitory computer-readable medium storing a computer product for a method for determining a life fraction for a network of battery units, the method comprising:

receiving information describing an application for the network of battery units;

receiving historical impedance data concerning the network of battery units;

measuring an instantaneous impedance response to a perturbation signal applied to each of the battery units while in operation for the application;

determining a mode and estimating a severity of a failure for at least one individual battery unit from a change in impedance characteristics between historical and instantaneous impedance; and

predicting a remaining life fraction for the network of battery units based on the mode and the severity of failure of the at least one individual battery unit.

16. A testing device to determine a life fraction for a network of battery units, comprising:

a user interface module to receive information describing an application for the network of battery units;

a data input to receive historical impedance data concerning the network of battery units;

a signal input to measure an instantaneous impedance response to a perturbation signal applied to each of the battery units while in operation for the application; and

an analyzing engine communicatively coupled to the user interface module, the data input and the signal input, the analyzing engine determining a mode and estimating a severity of a failure for at least one individual battery unit from a change in impedance characteristics between historical and instantaneous impedance response, and the analyzing engine predicting a remaining life fraction for the network of battery units based on the mode and the severity of failure of the at least one individual battery unit.