Systems and methods for predicting polarization curves in a fuel cell system

• US 8,920,995 B2
• Filed: 03/15/2013
• Issued: 12/30/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Lebzelter, Derek R., Ganapathy, Sriram, Folmsbee, Daniel T.
• Primary Examiner(s): Cantelmo, Gregg
• Application Number:
  US13/839,261
• Publication Number:
  US 20140272652A1
• Time in Patent Office: 655 Days
• Field of Search: None
• US Class Current: 429/431
• CPC Class Codes: H01M 2008/1095 Fuel cells with polymeric electrolytes
• CPC Class Codes: H01M 2250/20 Fuel cells in motive systems, e.g. vehicle, ship, plane
• CPC Class Codes: H01M 8/04358 of the coolant
• CPC Class Codes: H01M 8/04574 Current
• CPC Class Codes: H01M 8/04865 Voltage
• CPC Class Codes: H01M 8/04992 characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
• CPC Class Codes: Y02E 60/50 Fuel cells
• CPC Class Codes: Y02T 90/40 Application of hydrogen technology to transportation, e.g. using fuel cells

Abstract

The present disclosure relates to systems and methods that may be used to predict a performance metric of a fuel cell. A system consistent with the present disclosure may include sensors in communication with the fuel cell stack, a performance metric prediction system, and a control system. The performance metric prediction system may determine a current density based on inputs provided by the sensors at a plurality of time periods, calculate a first parameter while the current density is below a lower threshold, and calculate a second parameter while the current density is above an upper threshold. The first parameter and the second parameter may be used to selectively adjust a fuel cell polarization curve over time. Based upon the polarization curve, a performance metric of the fuel cell stack may be predicted. The control system may implement a control action based upon the performance metric.

Claims

1. A system to predict a performance metric of a fuel cell (FC) stack, the system comprising:

a plurality of sensors in communication with the FC stack;

a performance metric prediction system configured to;

determine a current density based on an input from at least one of the plurality sensors at a plurality of time periods;

calculate a first parameter during a first time period in which the current density is below a lower threshold;

calculate a second parameter during a second time period in which the current density is above an upper threshold;

selectively adjust a FC polarization curve over time based upon the first parameter and the second parameter;

predict a performance metric of the FC stack based upon the FC polarization curve; and

a control system configured to implement a control action based upon the performance metric.

2. The system of claim 1, wherein the performance metric prediction system is further configured to:

measure a transient parameter based on at least one input from the plurality of sensors; and

further selectively adjusting the fuel cell polarization curve based upon the transient parameter.

3. The system of claim 2, wherein the transient parameter is based on a platinum oxide model.

4. The system of claim 1, wherein the performance metric comprises a cell voltage raw estimate calculated as:

5. The system of claim 1, wherein the performance metric comprises a maximum power estimate.

6. The system of claim 1, wherein the control action comprises scheduling a power request based on the performance metric.

7. The system of claim 1, further comprising:

a voltage suppression system; and

wherein the control action comprises establishing a voltage suppression set point based upon the performance metric.

8. The system of claim 1, wherein at least one of the plurality of sensors is configured to measure a coolant temperature, and the performance metric prediction system is configured to selectively discard current density measurements during time periods in which the coolant temperature is below the coolant temperature threshold.

9. The system of claim 1, further comprising:

a fault detection system in communication with the plurality of electrical sensors and configured to detect a fault condition based upon input from one or more of the plurality of electrical sensors.

10. The system of claim 1, wherein the first parameter comprises a mass activity parameter calculated based on a voltage measurement associated with at least one of the plurality of sensors.

11. The system of claim 10, wherein the mass activity parameter is calculated as:

12. The system of claim 1, wherein the second parameter comprises a mass transfer coefficient calculated based on a voltage measurement associated with at least one of the plurality of sensors.

13. The system of claim 12, wherein the mass transfer coefficient is calculated as

14. A method for predicting a performance metric of a fuel cell (FC) stack, the method comprising:

receiving a plurality of inputs from a plurality of sensors;

determining a current density based on at least one of the plurality of inputs at a plurality of time periods;

calculating a first parameter during a first time period in which the current density is below a lower threshold;

calculating a second parameter during a second time period in which the current density is above an upper threshold;

selectively adjusting a fuel cell polarization curve over time based upon the first parameter and the second parameter;

predicting a performance metric of the fuel cell stack based upon the fuel cell polarization curve; and

implementing a control action based upon the performance metric.

15. The method of claim 14, further comprising:

measuring a transient parameter based on at least one of the plurality of inputs from the plurality of sensors; and

wherein selectively adjusting the fuel cell polarization curve is further based upon the transient parameter.

16. The method of claim 15, wherein the transient parameter is based on a platinum oxide model.

17. The method of claim 14, wherein the performance metric comprises a maximum power estimate.

18. The method of claim 14, wherein the control action comprises scheduling a power request based on the performance metric.

19. The method of claim 14, wherein implementing the control action based upon the performance metric comprises establishing a voltage suppression set point;

and the method further comprises;

configuring a voltage suppression system to suppress a voltage below the voltage suppression set point.

20. The method of claim 14, further comprising:

measuring a coolant temperature using at least one of the plurality of sensors;

comparing the coolant temperature to a coolant temperature threshold;

selectively discarding current density measurements during time periods in which the coolant temperature is below the coolant temperature threshold.