Broadband excitation of fuel cells for online condition monitoring using different switch-mode DC-DC mode topologies
type: CreativeWork
description: There is a great demand for renewable energy sources, and these include solar and wind energy sources. However, a renewable energy source with a continuous energy supply is desired, but energy sources from wind and solar energy sources are intermittent, i.e., solar energy is only available during the day, and wind energy's availability is dependent on the season of the year and climate in the area. This, in essence, makes fuel cell systems desirable as a renewable energy source and storage in the form of green gases obtained from electrolysis or other processes using these intermittent green energy sources. Online condition monitoring of fuel cell systems without the need for additional hardware is desired in both stationery and transportation applications. Recent work has explored the use of online impedance spectroscopy for batteries using multi-sine signals through a single dc-dc converter. However, for fuel cells, the non-linearity of both the converter and the fuel cell poses a challenge to the online monitoring process. There is also a need for faster diagnostics due to the internal operating conditions of the fuel cell needing immediate control and regulation. This study demonstrates the use of the pseudo-random binary sequence (PRBS) to perform impedance spectroscopy in comparison to a single sinusoid injection. This is done to show the comparison between the two signals and to show the decrease in impedance estimation time brought about by PRBS in comparison to multi-sine signals. PRBS is a faster and easier technique to implement compared to the single-sine signals used in the condition monitoring of batteries. The tolerance of error brought by the implementation of impedance spectroscopy through PRBS and single-sine signals through a dc-dc converter is compared to the benchmarked theoretical results. This is demonstrated in simulation and experimentally. Results obtained from the Frequency Response Analyzer (FRA) are compared to the results obtained throu…
abstract: There is a great demand for renewable energy sources, and these include solar and wind energy sources. However, a renewable energy source with a continuous energy supply is desired, but energy sources from wind and solar energy sources are intermittent, i.e., solar energy is only available during the day, and wind energy's availability is dependent on the season of the year and climate in the area. This, in essence, makes fuel cell systems desirable as a renewable energy source and storage in the form of green gases obtained from electrolysis or other processes using these intermittent green energy sources. Online condition monitoring of fuel cell systems without the need for additional hardware is desired in both stationery and transportation applications. Recent work has explored the use of online impedance spectroscopy for batteries using multi-sine signals through a single dc-dc converter. However, for fuel cells, the non-linearity of both the converter and the fuel cell poses a challenge to the online monitoring process. There is also a need for faster diagnostics due to the internal operating conditions of the fuel cell needing immediate control and regulation. This study demonstrates the use of the pseudo-random binary sequence (PRBS) to perform impedance spectroscopy in comparison to a single sinusoid injection. This is done to show the comparison between the two signals and to show the decrease in impedance estimation time brought about by PRBS in comparison to multi-sine signals. PRBS is a faster and easier technique to implement compared to the single-sine signals used in the condition monitoring of batteries. The tolerance of error brought by the implementation of impedance spectroscopy through PRBS and single-sine signals through a dc-dc converter is compared to the benchmarked theoretical results. This is demonstrated in simulation and experimentally. Results obtained from the Frequency Response Analyzer (FRA) are compared to the results obtained throu…
author: Mahlangu, Surprise
keywords: Engineering
date published: 2023
date modified: 2026-07-24T01:33:49Z
provider: University of Cape Town
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Department of Electrical Engineering

PropertyValue
property ID: Handle
value: http://hdl.handle.net/11427/39614