Proton Exchange Membrane Fuel Cell (PEMFC) Parameters Estimation Using Time-Frequency Analysis Technique

Proton Exchange Membrane Fuel cell (PEMFC) is a device that converts chemical energy into electrical energy. The performance characteristics of the PEMFC are affected by many factors either from PEMFC design specification or from the operating conditions. Improper handling the operating condition of the PEMFC will cause failure and damage to the entire system. Thus, the system needs the accurate information about the performance characteristics of PEMFC at various operating conditions with changing load demand to prevent the PEMFC from damage. In this research, periodogram and spectrogram techniques are proposed in order to determine the hydrogen (H2) inlet pressures and stack temperature performance characteristics of PEMFC. Firstly, the signal voltages of various PEMFC operating conditions are captured by using oscilloscope. The raw signals from oscilloscope are then transformed into periodogram and time-frequency distribution (TFD) which is spectrogram. The signal parameter that desired to be extracted from spectrogram are instantaneous voltage of direct current (VDC), voltage of root mean square (VRMS), and voltage of alternating current (VAC) parameters. From the parameter estimation curves and the three-dimensional maps of H2 inlet pressures result, the highest values of instantaneous VRMS and VDC are obtained at a pressure of 0.5 bars, whereby the lowest values are obtained at a pressure of 0.1 bars. These parameters are highest in open voltage conditions but decrease gradually with increasing load demand up to 35 A. The highest values of parameter estimation curves and the three-dimensional maps of stack temperatures are obtained at 40 °C whereas the lowest values are obtained at 20 °C. These parameters are highest at open voltage conditions but decrease gradually with an increase in the load demand up to 18 A. The absolute percentage error (APE) and mean absolute percentage error (MAPE) are used to justify the performance analysis of the spectrogram parameters. The highest APE is attained at a load demand of 15 A, with a value of 0.76% whereas the highest MAPE is obtained for a stack temperature of 25 °C with a value of 0.334%. Based on the results, the estimation of the VDC parameter from TFD technique for both H2 inlet pressure test and stack temperature test are acceptable since the APE and MAPE values are less than 1%. The outcome of this research verifies that the TFD technique clearly gives the information of the performance characteristics of PEMFC at various operating conditions with changing load demand

Effect of Hydrogen Inlet Pressure Analysis on open Voltage of Proton Exchange Membrane (PEM) Fuel cell by using Periodogram

Proton Exchange Membrane Fuel cell (PEMFC) is one of the renewable energy system that was recently highlighted by researchers. PEM fuel cell generates electricity through the electrochemical reaction of hydrogen and oxygen. Finite changes in the reactant inlet properties leads to unique operating changes within the fuel cell stack. The effect of hydrogen inlet pressure to the operating voltage has been detailed before using a variation of monitoring techniques. Identification analysis is required to monitor every factor that influences the performance characteristic of PEMFC. Periodogram monitoring technique applies a frequency domain waveform signal capable of tracing small changes in the phase behaviour of electrical operations as external parameters are varied. The use of this technique is provided in this paper within the scope of monitoring the signal changes in the open voltage of a 30Watt (W) PEM fuel cell stack as the hydrogen inlet pressure is varied from 0.1 bar to 0.5 bar. The open voltage increases with rise in hydrogen inlet pressure and the Periodogram amplitude signal increases accordingly. Then, the magnitudes of total tolerance voltage, the signal characteristic of direct current voltage (VDC), root means square voltage (VRMS), and alternating current voltage (VAC) were calculated from the voltage waveform where losses could be identified. Therefore, the Periodogram technique has been proven useful and practical in monitoring operation changes of a PEM fuel cell stack

Association of Physical Activity with Anthropometrics Variables and Health-Related Risks in Healthy Male Smokers

Anthropometric variables (AV) are shown to be essential in assessing health status and to serve as markers for evaluating health-related risks in different populations. Studying the impact of physical activity (PA) on AV and its relationship with smoking is a non-trivial task from a public health perspective. In this study, a total of 107 healthy male smokers (37 ± 9.42 years) were recruited from different states in Malaysia. Standard procedures of measurement of several anthropometric indexes were carried out, and the International Physical Activity Questionnaire (IPPQ) was used to ascertain the PA levels of the participants. A principal component analysis was employed to examine the AV associated with physical activity, k-means clustering was used to group the participants with respect to the PA levels, and discriminant analysis models were utilized to determine the differential variables between the groups. A logistic regression (LR) model was further employed to ascertain the efficacy of the discriminant models in classifying the two smoking groups. Six AV out of twelve were associated with smoking behaviour. Two groups were obtained from the k-means analysis, based on the IPPQ and termed partially physically active smokers (PPAS) or physically nonactive smokers (PNAS). The PNAS were found to be at high risk of contracting cardiovascular problems, as compared with the PPAS. The PPAS cluster was characterized by a desirable AV, as well as a lower level of nicotine compared with the PNAS cluster. The LR model revealed that certain AV are vital for maintaining good health, and a partially active lifestyle could be effective in mitigating the effect of tobacco on health in healthy male smokers

Association of physical activity with anthropometrics variables and health-related risks in healthy male smokers

Anthropometric variables (AV) are shown to be essential in assessing health status and to serve as markers for evaluating health-related risks in different populations. Studying the impact of physical activity (PA) on AV and its relationship with smoking is a non-trivial task from a public health perspective. In this study, a total of 107 healthy male smokers (37 ± 9.42 years) were recruited from different states in Malaysia. Standard procedures of measurement of several anthropometric indexes were carried out, and the International Physical Activity Questionnaire (IPPQ) was used to ascertain the PA levels of the participants. A principal component analysis was employed to examine the AV associated with physical activity, k-means clustering was used to group the participants with respect to the PA levels, and discriminant analysis models were utilized to determine the differential variables between the groups. A logistic regression (LR) model was further employed to ascertain the efficacy of the discriminant models in classifying the two smoking groups. Six AV out of twelve were associated with smoking behaviour. Two groups were obtained from the k-means analysis, based on the IPPQ and termed partially physically active smokers (PPAS) or physically nonactive smokers (PNAS). The PNAS were found to be at high risk of contracting cardiovascular problems, as compared with the PPAS. The PPAS cluster was characterized by a desirable AV, as well as a lower level of nicotine compared with the PNAS cluster. The LR model revealed that certain AV are vital for maintaining good health, and a partially active lifestyle could be effective in mitigating the effect of tobacco on health in healthy male smokers

Critical rate analysis for CO2 injection in depleted gas field, Sarawak Basin, offshore East Malaysia

This study aimed to address the challenges and strategies to determine the critical rate of CO2 injection into a carbonate depleted gas field. In this research, the critical rate is the maximum allowable injection rate before formation damage initiation. The cause of formation damage could be due to in-situ mobilization or trapping of migratory fines resulting in plugging the flow path. This study performed a thorough investigation of a different rock-fluid system to evaluate the safe injection limit, as the critical rate is different for each rock-fluid system. The geochemical effect of CO2 injection toward carbonate formation was also investigated in this research. Other than that, the porosity and permeability changes due to CO2-brine-rock multiphase flow characteristics were considered to understand the feasibility of CO2 sequestration into carbonate formation. This research discussed experimental design to mimic the CO2 injection scenario of CO2 into carbonate depleted gas field. Therefore, several core flooding experiments were conducted under reservoir conditions using representative native cores, CO2, and synthetic formation brine. Abrupt changes in differential pressure (ΔP), analysis of effluent collected after CO2 multi-rate flow, and pH reading are the key indicators to consider that the condition has reached a critical rate. The experimental result demonstrated the existence of fines migration, scale formation, and salt precipitation after the core was subjected to supercritical CO2 multi-rate flow. Considering these issues and challenges associated with injectivity, this study recommended a maximum injection rate prior to field scale injection