Samuel Cruz-Manzo

Inductive Effect on the Fuel Cell Cathode Impedance Spectrum at High Frequencies

The high frequency electrochemical impedance measurements with positive imaginary components in the impedance complex plot of a polymer electrolyte fuel cell (PEFC) are attributable to the inductance of the electrical cables of the measurement system. This study demonstrates that the inductive effect of the electrical cables deforms the high frequency region of the cathode impedance spectrum and as such leads to an erroneous interpretation of the electrochemical mechanisms in the cathode catalyst layer (CCL). This study is divided into a theoretical analysis and an experimental analysis. In the theoretical analysis a validated model that accounts for the impedance spectrum of the CCL as reported in the authors’ previous study is applied with experimental impedance data reported in the literature. The results show that the ionic resistance of the CCL electrolyte which skews the oxygen reduction reaction (ORR) current distribution toward the membrane interface is masked in the cathode impedance spectrum by the inductive component. In the experimental analysis cathode experimental impedance spectra were obtained through a three-electrode configuration in the measurement system and with two different electrical cables connected between the electronic load and the PEFC. The results agree with the theoretical analysis and also show that the property of causality in the Kramers-Kronig mathematical relations for electrochemical impedance spectroscopy (EIS) measurements is violated by the external inductance of the measurement cables. Therefore the experimental data presenting inductance at high frequencies do not represent the physics and chemistry of the PEFC. The study demonstrates that a realistic understanding of factors governing EIS measurements can only be gained by applying fundamental modeling which accounts for underlying electrochemical phenomena and experimental observations in a complementary manner.

The Low Current Electrochemical Mechanisms of the Fuel Cell Cathode Catalyst Layer Through an Impedance Study

Based on the fundamental electrode theory and the impedance experimental study, a numerical model to simulate the low current distribution in the time domain and the electrochemical impedance spectra of the cathode catalyst layer (CCL) of polymer electrolyte fuel cells (PEFCs) has been developed in this study. The model development consists of two stages: to establish the fundamental equations for the low current distribution in the CCL in the time domain and to resolve the fundamental theory in the frequency domain. It was validated by comparing the simulated impedance of the CCL directly against the impedance data measured from an operational test cell. The simulated frequency response agrees well with the experimental data. The model was applied in the time domain to simulate the effects of the proton resistance and the double-layer capacitance across the CCL on the transitory and steady-state current distribution. The results showed that the model has established a backbone understanding of how the low current electrochemical mechanisms relate to the electrochemical impedance spectra of the CCL. It establishes a wider scope to relate the electrochemical impedance data to the fundamental theory of PEFCs.

A Thermodynamic Transient Model for Performance Analysis of a Twin Shaft Industrial Gas Turbine

In this study, a Simulink model based on fundamental thermodynamic principles to predict the dynamic and steady state performance in a twin shaft Industrial Gas Turbine (IGT) has been developed. The components comprising the IGT have been implemented in the modelling architecture using a thermodynamic commercial toolbox (Thermolib, EUtech Scientific Engineering GmbH) and Simulink environment. Measured air pressure and air temperature discharged by compressor allowed the validation of the modelling architecture. The model assisted the development of a computational tool based on Artificial Neural Network (ANN) for compressor fault diagnostics in IGTs. It has been demonstrated that modelling plays an important role to predict and monitor gas turbine system performance at different operating and ambient conditions.

Start-up vibration analysis for novelty detection on industrial gas turbines

This paper focuses on industrial application of start-up vibration signature analysis for novelty detection with experimental trials on industrial gas turbines (IGTs). Firstly, a representative vibration signature is extracted from healthy start-up vibration measurements through the use of an adaptive neuro-fuzzy inference system (ANFIS). Then, the first critical speed and the vibration level at the critical speed are located from the signature. Finally, two (s- and v-) health indices are introduced to detect and identify different novel/fault conditions from the IGT start-ups, in addition to traditional similarity measures, such as Euclidean distance and cross-correlation measures. Through a case study on IGTs, it is shown that the presented approach provides a convenient and efficient tool for IGT condition monitoring using start-up field data.

Evaluate the validity of electrochemical impedance measurements of polymer electrolyte fuel cells using a computational algorithm based on Fast Fourier Transform

The validity of electrochemical impedance measurements of polymer electrolyte fuel cells (PEFCs) have to be evaluated before an attempt is made to interpret the electrochemical mechanisms represented in the Nyquist plot. This evaluation can be carried out by data transformation of impedance measurements using Kramers-Kronig (K-K) relations. However, this evaluation has been commonly neglected in the fuel cell area due to the complexity of applying the mathematical K-K relations to real-world impedance measurements. In this study a computational algorithm, based on the Fast Fourier Transform (FFT) theory, the Hilbert transformation of impedance data, and a validated impedance model for PEFCs, for evaluating data transformation (real to imaginary Z’→Z’’ and imaginary to real Z’’→Z’) and hence validity of impedance measurements of PEFCs has been developed in Matlab®. With this computational algorithm it is possible to identify the factors that lead to incorrect EIS measurements of PEFCs such as inductance effect from the electrical cables of the measurement system, incorrect AC amplitude signal, and instability during EIS measurements. The computational algorithm developed in this study enables more accurate impedance results to be obtained to study the performance and state of health of PEFCs.

Performance analysis of a twin shaft Industrial Gas Turbine at fouling conditions

In this study, the performance of a twin-shaft Industrial Gas Turbine (IGT) at fouling conditions is simulated through a Simulink model based on fundamental thermodynamics. Engine measurements across a twin-shaft IGT system during compressor fouling conditions were considered to validate this study. By implementing correlation coefficients in the compressor model, it is possible to predict the performance of the IGT system during compressor fouling conditions. The change of compressor air flow and the compressor efficiency in the twin-shaft IGT during fouling conditions is estimated. The results show that the reduction of air flow rate is the dominating parameter in the decrease of power generation in an IGT under fouled conditions. The model can provide an insight into the effect of compressor fouling conditions on system IGT performance.

Condition Monitoring of Combustion System on Industrial Gas Turbines Based on Trend and Noise Analysis

In this paper, a scheme of an ‘early warning’ system is developed for the combustion system of Industrial Gas Turbines (IGTs), which attains low computational workload and simple programming requirements, being therefore employable at an industrial level. The methodology includes trend analysis, which examines when the measurement shows different trends from the other measurements in the correlated sensor group, and noise analysis, which examines when the measurement is displaying higher levels of noise compared to those of the other sensors. In this research, difficulties encountered by other data-driven methods due to temperature varying with load conditions of the IGT’s have also been overcome by the proposed approach. Furthermore, it brings other advantages, for instance, no historic training data is needed, and there is no requirement to set thresholds for each sensor in the system. The efficacy and effectiveness of the proposed approach has been demonstrated through experimental trials of previous pre-chamber burnout cases. And the resulting outcomes of the scheme will be of interest to IGT companies, especially in condition monitoring of the combustion system. Future work and possible improvements are also discussed at the end of the paper.