Systems and methods for monitoring fuel cell membrane degradation
Systems and methods for real-time continuous monitoring of fuel cell membrane degradation are provided. At least one microsensor can be used as an inline sensor integrated at the cathode exhaust and/or the anode exhaust of a fuel cell, such as a proton exchange membrane fuel cell (PEMFC)). The microsensor can monitor the PEMFC degradation status by sensing the emission of fluoride.
1. A system for monitoring degradation of a fuel cell membrane in a proton exchange membrane fuel cell, the system comprising:
a first microsensor disposed inline with a first exhaust of the proton exchange membrane fuel cell, the first microsensor configured for sensing a first analyte that is fluorine or sulfate;
a processor in operable communication with the first microsensor; and
a machine-readable medium in operable communication with the processor and the first microsensor, and having instructions stored thereon that, when executed by the processor, perform the following steps:
monitoring first sensing data of the first microsensor, the first sensing data comprising a level of the first analyte present in the first exhaust of the proton exchange membrane fuel cell; and
performing a deep learning algorithm on the first sensing data to enable predictive maintenance on the fuel cell membrane of the proton exchange membrane fuel cell.
2. The system according to claim 1 , the first microsensor being an ion-sensitive field effect transistor.
3. The system according to claim 2 , the first analyte being fluorine, and
the ion-sensitive field effect transistor comprising a fluoride-sensitive membrane as a thin layer of insulator in the first microsensor.
4. The system according to claim 3 , the fluoride-sensitive membrane comprising at least one of LaF 3 and CaF 2 .
5. The system according to claim 4 , the fluoride-sensitive membrane comprising LaF 3 .
6. The system according to claim 4 , the fluoride-sensitive membrane comprising CaF 2 .
7. The system according to claim 1 , the first analyte being fluorine, and
the first microsensor comprising a fluoride-sensitive membrane as a thin layer of insulator in the first microsensor.
8. The system according to claim 7 , the fluoride-sensitive membrane comprising at least one of LaF 3 and CaF 2 .
9. The system according to claim 8 , the fluoride-sensitive membrane comprising LaF 3 .
10. The system according to claim 8 , the fluoride-sensitive membrane comprising CaF 2 .
11. The system according to claim 1 , the deep learning algorithm comprising a long-short-term memory artificial neural network.
12. The system according to claim 1 , the first exhaust of the proton exchange membrane fuel cell being an exhaust of a cathode of the proton exchange membrane fuel cell.
13. The system according to claim 1 , the first analyte being fluorine,
the first microsensor being configured to detect fluorine ions in the first exhaust of the proton exchange membrane fuel cell, based on interaction of the fluorine ions with a fluoride-sensitive membrane of the first microsensor, to give the first sensing data, and
the first microsensor being configured to transmit the first sensing data to the processor for monitoring.
14. The system according to claim 1 , further comprising a second microsensor disposed inline with a second exhaust of the proton exchange membrane fuel cell, the second microsensor configured for sensing a second analyte that is fluorine or sulfate,
the instructions when executed further performing the step of monitoring second sensing data of the second microsensor, the second sensing data comprising a level of the second analyte present in the second exhaust of the proton exchange membrane fuel cell, and
the performing of the deep learning algorithm comprising performing the deep learning algorithm on the second sensing data together with the first sensing data to enable predictive maintenance on the fuel cell membrane of the proton exchange membrane fuel cell.
15. The system according to claim 14 , the first exhaust of the proton exchange membrane fuel cell being an exhaust of a cathode of the proton exchange membrane fuel cell, and
the second exhaust of the proton exchange membrane fuel cell being an exhaust of an anode of the proton exchange membrane fuel cell.
16. The system according to claim 14 , the first analyte being fluorine,
the first microsensor being configured to detect fluorine ions in the first exhaust of the proton exchange membrane fuel cell based on interaction of the fluorine ions with a fluoride-sensitive membrane of the first microsensor, to give the first sensing data,
the first microsensor being configured to transmit the first sensing data to the processor for monitoring,
the second microsensor being configured to detect fluorine ions in the second exhaust of the proton exchange membrane fuel cell, based on interaction of the fluorine ions with a fluoride-sensitive membrane of the second microsensor, to give the second sensing data, and
the second microsensor being configured to transmit the second sensing data to the processor for monitoring.
17. A system for monitoring degradation of a fuel cell membrane in a proton exchange membrane fuel cell, the system comprising:
a first microsensor disposed inline with an exhaust of a cathode of the proton exchange membrane fuel cell, the first microsensor configured for sensing a first analyte that is fluorine;
a second microsensor disposed inline with an exhaust of an anode of the proton exchange membrane fuel cell, the second microsensor configured for sensing a second analyte that is fluorine;
a processor in operable communication with the first microsensor and the second microsensor; and
a machine-readable medium in operable communication with the processor, the first microsensor, and the second microsensor, and having instructions stored thereon that, when executed by the processor, perform the following steps:
monitoring first sensing data of the first microsensor, the first sensing data comprising a level of the first analyte present in the exhaust of the cathode;
monitoring second sensing data of the second microsensor, the second sensing data comprising a level of the second analyte present in the exhaust of the anode; and
performing a deep learning algorithm on the first sensing data and the second sensing data to enable predictive maintenance on the fuel cell membrane of the proton exchange membrane fuel cell
the first microsensor being an ion-sensitive field effect transistor comprising a first fluoride-sensitive membrane as a thin layer of insulator in the first microsensor,
the second microsensor being an ion-sensitive field effect transistor comprising a second fluoride-sensitive membrane as a thin layer of insulator in the second microsensor,
the first fluoride-sensitive membrane comprising at least one of LaF 3 and CaF 2 ,
the second fluoride-sensitive membrane comprising at least one of LaF 3 and CaF 2 , and
the deep learning algorithm comprising a long-short-term memory artificial neural network.
18. The system according to claim 17 , the first microsensor being configured to detect fluorine ions in the exhaust of the cathode of the proton exchange membrane fuel cell based on interaction of the fluorine ions with the first fluoride-sensitive membrane of the first microsensor, to give the first sensing data,
the first microsensor being configured to transmit the first sensing data to the processor for monitoring,
the second microsensor being configured to detect fluorine ions in the exhaust of the anode of the proton exchange membrane fuel cell, based on interaction of the fluorine ions with the second fluoride-sensitive membrane of the second microsensor, to give the second sensing data, and
the second microsensor being configured to transmit the second sensing data to the processor for monitoring.
19. The system according to claim 17 , the fluoride-sensitive membrane comprising LaF 3 .
20. The system according to claim 17 , the fluoride-sensitive membrane comprising CaF 2 .