Fast measurement of proton exchange membrane fuel cell impedance based on pseudo-random binary sequence perturbation signals and continuous wavelet transform

Debenjak, Andrej; Boškoski, Pavle; Musizza, Bojan; Petrovĉiĉ, Janko; Juričić, Đani

doi:10.1016/j.jpowsour.2013.12.094

Cited by 56 publications

(29 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CONDITION MONITORING The embedded CM approach builds on top of a method for fast impedance estimation [30]. This method employs a PRBS excitation signal and CWT signal processing tool.…”

Section: Dc-dc Converter and Fcvm As A Condition Monitoring Systemmentioning

confidence: 99%

“…Fast impedance estimation using CWT and PRBS 1) CWT based on the complex Morlet wavelet: Following the procedure described by Debenjak et al [30], the impedance characteristic can be efficiently estimated by using complex wavelet coefficients of the CWT of the fuel cell's current i(t) and voltage u(t) using the complex Morlet mother wavelet. The CWT of a square integrable function f (t) ∈ L 2 (R) is defined as follows [41]:…”

Section: Dc-dc Converter and Fcvm As A Condition Monitoring Systemmentioning

confidence: 99%

“…164-172]. However, for practical impedance estimation purposes, the useful bandwidth f B of the PRBS excitation signal is limited to approximately onethird of the frequency f s (f B f s /3) [30]. For the case at hand, the useful frequency band f B covers frequencies from 0 to approximately 200 Hz.…”

Section: A Experimental Proceduresmentioning

confidence: 99%

“…The DC-DC converter superimposes the PRBS excitation signal onto the stack electrical current. Using the FCVM for data acquisition and signal processing, the impedance is estimated using continuous wavelet transform (CWT) with the complex Morlet mother wavelet [30].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fuel Cell Condition Monitoring System Based on Interconnected DC–DC Converter and Voltage Monitor

Debenjak

Petrovĉiĉ

Boškoski

et al. 2015

IEEE Trans. Ind. Electron.

Self Cite

View full text Add to dashboard Cite

This paper presents a comprehensive solution for condition monitoring of PEM fuel cell systems. It comprises a modular DC-DC converter, a 90-channel fuel cell voltage monitor, and embedded diagnostics algorithms. Besides providing its basic functionality, the DC-DC converter is designed to perform diagnostic probing of fuel cells by injecting current excitation waveforms. The designed voltage monitor enables the precise voltage measurement of all individual cells in the stack. The interconnection between the DC-DC converter and the voltage monitor provides a platform for an embedded condition monitoring system. It employs a novel algorithm for fast electrochemical impedance estimation and automatic tuning of the thresholds used in the fault detection algorithm. The final output is a unitfree condition indicator that describes the overall condition of the fuel cell stack. As such, the designed condition monitoring system allows the seamless integration and optimal exploitation of fuel cell power systems. The complete solution has been evaluated on an 8.5 kW PEM fuel cell power system.

show abstract

“…CONDITION MONITORING The embedded CM approach builds on top of a method for fast impedance estimation [30]. This method employs a PRBS excitation signal and CWT signal processing tool.…”

Section: Dc-dc Converter and Fcvm As A Condition Monitoring Systemmentioning

confidence: 99%

Section: Dc-dc Converter and Fcvm As A Condition Monitoring Systemmentioning

confidence: 99%

Section: A Experimental Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuel Cell Condition Monitoring System Based on Interconnected DC–DC Converter and Voltage Monitor

Debenjak

Petrovĉiĉ

Boškoski

et al. 2015

IEEE Trans. Ind. Electron.

Self Cite

View full text Add to dashboard Cite

show abstract

“…It has a good prospect and has become a hotspot at home and abroad. [1][2][3] In the acoustic temperature measurement field, the selection of the sound source signal is the key. In this paper, the linear frequency modulation signal [4] with a carrier frequency of 40 KHz [5] and sampling frequency of 120 KHz was used as the sound source.…”

Section: Introductionmentioning

confidence: 99%

Research of FTRLS Algorithm in Acoustic Signal De-noising

Sun¹

2017

JEEE

View full text Add to dashboard Cite

Abstract:In the acoustic temperature measurement system, the acoustic emission signal is easily affected by the wind field, the ambient noise and so on during the propagation process. Coupled with its own reflection, diffraction and scattering properties, the sensor receive the acoustic signals that are weak, difficult to identify, and even submerged in the background noise. In order to solve the above problem, this paper combines the principle of adaptive filter, and the FTRLS adaptive filter algorithm is designed to deal with linear frequency modulation signal, and the simulation experiment was carried out by MATLAB software. The results show that the noise-disturbing chirp signal can be effectively restored to a certain extent after denoising.

show abstract

A Comparative Study of Wavelet‐based Descriptors for Fault Diagnosis of Self‐Humidified Proton Exchange Membrane Fuel Cells

Sethi

Verstraete

2020

Fuel Cells

View full text Add to dashboard Cite

Fault diagnosis can help extend the lifetime of fuel cells and has been widely explored for externally humidified fuel cells. However, fault detection in self-humidified fuel cells is scarce, despite its importance. This paper explores various wavelet-based descriptors for identifying hydration levels in self-humidified stacks. Wavelet-based techniques are nonintrusive and provide concurrent examinations in time and frequency. Thus, they encapsulate health related data that can be used as health monitoring features. The specific wavelet-based techniques used here are (i) impedance obtained through the wavelet-based fast electrochemical impedance spectroscopy (EIS) and (ii) changes in wavelet energy through wavelet and wavelet packet decomposition. Results are compared based on their trends under dehydration con-ditions and the robustness of those trends across different currents and sampling rates. They are then assessed based on their predictive ability using RReliefF (Regression-ReliefF)-a regression based feature ranking tool. Based on the qualitative and quantitative analysis, descriptors are assessed in the context of creating a short-term health monitoring system for self-humidified fuel cells. While a modified version of the wavelet energies provides the best results for differentiating faults, fast EIS opens the possibility for analysis of more complex fault modes and is shown to be more robust.

show abstract

Fast measurement of proton exchange membrane fuel cell impedance based on pseudo-random binary sequence perturbation signals and continuous wavelet transform

Cited by 56 publications

References 19 publications

Fuel Cell Condition Monitoring System Based on Interconnected DC–DC Converter and Voltage Monitor

Fuel Cell Condition Monitoring System Based on Interconnected DC–DC Converter and Voltage Monitor

Research of FTRLS Algorithm in Acoustic Signal De-noising

A Comparative Study of Wavelet‐based Descriptors for Fault Diagnosis of Self‐Humidified Proton Exchange Membrane Fuel Cells

Contact Info

Product

Resources

About