Advanced reliability analysis of polymer electrolyte membrane fuel cells in automotive applications

Hydrogen fuel cells have the potential to dramatically reduce emissions from the energy sector, particularly when integrated into an automotive application. However, there are three main hurdles to the commercialisation of this promising technology; one of which is reliability. Cur- rent standards require an automotive fuel cell to last around 5000 h of operation (equivalent to around 150,000 miles), which has proven difficult to achieve to date. This hurdle can be overcome through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA), Fault Tree Analysis (FTA) and Petri-net simulation. This research has found that the reliability field regarding hydrogen fuel cells is still in its infancy, and needs development, if the current standards are to be achieved. In this research, a detailed reliability study of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) is undertaken. The results of which are a qualitative and quantitative analysis of a PEMFC. The FMEA and FTA are the most up to date assessments of failure in fuel cells developed using a comprehensive literature review and expert opinion. Advanced modelling of fuel cell degradation logic was developed using Petri-net modelling techniques. 20 failure modules were identfied that represented the interactions of all failure modes and operational parameters in a PEMFC. Petri-net simulation was used to overcome key pitfalls observed in FTA to provide a verfied degradation model of a PEMFC in an automotive application, undergoing a specific drive cycle, however any drive cycle can be input to this model. Overall results show that the modeled fuel cell's lifetime would reach 34 hours before falling below the industry standard degradation rate of more than 5%. The degradation model has the capability to simulate fuel cell degradation under any drive cycle and with any operating parameters. A fuel cell test rig was also developed that was used to verify the simulated degradation. The rig is capable of testing single cells or stacks from 0-470W power. The results from the verification experimentation agreed strongly with the degradation model, giving confidence in the accuracy of the developed Petri-net degradation model. This research contributes greatly to the field of reliability of PEMFCs through the most up-to-date and comprehensive FMEA and FTA presented. Additionally, a degradation model based upon Petri-nets is the first degradation model to encompass a 1D performance model to predict fuel cell life time under specific drive cycles

Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods

Addressing the challenge of scaling-up epidemiological inference to complex and heterogeneous models, we introduce Poisson Approximate Likelihood (PAL) methods. In contrast to the popular ODE approach to compartmental modelling, in which a large population limit is used to motivate a deterministic model, PALs are derived from approximate filtering equations for finite-population, stochastic compartmental models, and the large population limit drives consistency of maximum PAL estimators. Our theoretical results appear to be the first likelihood-based parameter estimation consistency results which apply to a broad class of partially observed stochastic compartmental models and address the large population limit. PALs are simple to implement, involving only elementary arithmetic operations and no tuning parameters, and fast to evaluate, requiring no simulation from the model and having computational cost independent of population size. Through examples we demonstrate how PALs can be used to: fit an age-structured model of influenza, taking advantage of automatic differentiation in Stan; compare over-dispersion mechanisms in a model of rotavirus by embedding PALs within sequential Monte Carlo; and evaluate the role of unit-specific parameters in a meta-population model of measles

Comparison of bacterioneuston and bacterioplankton dynamics during a phytoplankton bloom in a fjord mesocosm

The bacterioneuston is the community of Bacteria present in surface microlayers, the thin surface film that forms the interface between aquatic environments and the atmosphere. In this study we compared bacterial cell abundance and bacterial community structure of the bacterioneuston and the bacterioplankton (from the subsurface water column) during a phytoplankton bloom mesocosm experiment. Bacterial cell abundance, determined by flow cytometry, followed a typical bacterioplankton response to a phytoplankton bloom, with Synechococcus and high nucleic acid (HNA) bacterial cell numbers initially falling, probably due to selective protist grazing. Subsequently HNA and low nucleic acid (LNA) bacterial cells increased in abundance but Synechococcus did not. There was no significant difference between bacterioneuston and bacterioplankton cell abundances during the experiment. Conversely, distinct and consistent differences between the bacterioneuston and the bacterioplankton community structure were observed. This was monitored simultaneously by Bacteria 16S rRNA gene terminal restriction fragment length polymorphism (T-RFLP) and denaturing gradient gel electrophoresis (DGGE). The conserved patterns of community structure observed in all of the mesocosms indicate that the bacterioneuston is distinctive and non-random

Images of Flowers

For the past two years, I have been making pictures of flowers. It is my intent to complicate the representational qualities of flowers in this work by juxtaposing them against and combining them with the more abstract properties of picture making. This causes the subject matter of flowers to become somewhat elusive in relation to one's perception when viewing the work. This complication of our perception of the subject matter is a result of three concepts dealing with representation--reality, illusion, and abstraction. These concepts and the way they relate and interact with each other cause different levels of perception to exist simultaneously within this body of work. There are also three distinct physical groups of work in this show; drawings, paintings, and ceramics. Each of these groups relates to the concepts of reality, illusion, and abstraction differently and causes even further complications of the images of flowers.&nbsp; With the addition of illusion to this work there is a whole new set of relationships that complicate our perception of the subject matter by adding more levels of representation. One sees in the drawings that illusion shows us not pictures of flowers but pictures of pictures of flowers. Each different picture creates a different perspective from which one can see the overall image of flowers. The images of flowers that one sees in the paintings is obstructed by different levels of illusion. The vases when seen illusionistically can become pictures of flowers. &nbsp;</p

Failure mode and effect analysis, and fault tree analysis of polymer electrolyte membrane fuel cells

Hydrogen fuel cells have the potential to dramatically reduce emissions from the energy sector, particularly when integrated into an automotive application. However there are three main hurdles to the commercialisation of this promising technology; one of which is reliability. Current standards require an automotive fuel cell to last around 5000 h of operation (equivalent to around 150,000 miles), which has proven difficult to achieve to date. This hurdle can be overcome through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) amongst others. Research has found that the reliability field regarding hydrogen fuel cells is still in its infancy, and needs development, if the current standards are to be achieved. In this work, a detailed reliability study of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) is undertaken. The results of which are a qualitative and quantitative analysis of a PEMFC. The FMEA and FTA are the most up to date assessments of failure in fuel cells made using a comprehensive literature review and expert opinion

Enhanced Fault Tree analysis and modelling considerations of a Polymer Electrolyte Membrane Fuel Cell

With the recent increase in interest in environmental issues and climate change concerns, the scientific community have been tasked with developing low carbon technologies to mitigate against climate change. One of the most promising technologies is the hydrogen fuel cell, particularly when integrated into an automobile. Hydrogen Fuel Cells are an electro-chemical, zero-emission energy conversion and power generation device. Their only output products are heat, electrical energy, and water vapour. There are three main hurdles to the commercial uptake of this technology; Infrastructure, Cost and Reliability. An understanding of the reliability of fuel cells can be obtained through in-depth reliability analysis including techniques such as Failure Mode and Effect Analysis (FMEA) and Fault Tree analysis (FTA) amongst others. As hydrogen fuel cells are a relatively new technology this in-depth analysis is still in its infancy, and needs development. This research has extended the work on FTA of the Polymer Electrolyte Membrane Fuel Cell (PEMFC) systems. Detailed analysis has explored the inherent complexity of the PEMFC system where issues with using a basic FTA for a PEMFC, such as dependencies between failure modes, and disparities between failure mode operating principles, are discussed. The integration of the Markov technique, which can deal with dependencies, within the Fault tree approach is suggested as a mechanism to enhance the accuracy of the modelling of a PEMFC

Fault Tree Analysis of Polymer Electrolyte Fuel Cells to predict degradation phenomenon

Hydrogen Fuel Cells are an electro-chemical, zero-emission energy conversion and power generation device. Their only products are heat and electrical energy, and water vapour. One of the major hurdles to the uptake of this technology is the reliability of the fuel cell system. This hurdle can be overcome through in depth reliability analysis including Failure Mode and Effect Analysis (FMEA) and Fault Tree analysis (FTA) amongst others. Research has found that the reliability research area regarding hydrogen fuel cells is still in its infancy, and needs development. This paper looks at the current state of the art in reliability analysis regarding Polymer Electrolyte Fuel Cells (PEMFC). A recent fault tree (FT) from the literature is qualitatively analysed to ascertain its practicality in relation to PEMFC degradation analysis. The fault tree was found to harbour certain aspects that could be improved upon. There was no FMEA undertaken to precede the FT which would have given a greater understanding of the possible failure modes in a PEMFC system and their relationships. The FT was found to be lacking dependant relationships which are apparent in a PEMFC system. The data from the literature was also analysed to check its relevance in today’s fast moving PEMFC research. Conclusions are given to the way forward for future reliability evaluation of PEMFCs

Comparative study of energy management systems for a hybrid fuel cell electric vehicle - A novel mutative fuzzy logic controller to prolong fuel cell lifetime

Hybrid fuel cell battery electric vehicles require complex energy management systems (EMS) in order to operate effectively. Poor EMS can result in a hybrid system that has low efficiency and a high rate of degradation of the fuel cell and battery pack. Many different types of EMS have been reported in the literature, such as equivalent consumption minimisation strategy and fuzzy logic controllers, which typically focus on a single objective optimisations, such as minimisation of H2 usage. Different vehicle and system specifications make the comparison of EMSs difficult and can often lead to misleading claims about system performance. This paper aims to compare different EMSs, against a range of performance metrics such as charge sustaining ability and fuel cell degradation, using a common modelling framework developed in MATLAB/Simulink - the Electric Vehicle Simulation tool-Kit (EV-SimKit). A novel fuzzy logic controller is also presented which mutates the output membership function depending on fuel cell degradation to prolong fuel cell lifetime – the Mutative Fuzzy Logic Controller (MFLC). It was found that while certain EMSs may perform well at reducing H2 consumption, this may have a significant impact on fuel cell degradation, dramatically reducing the fuel cell lifetime. How the behaviour of common EMS results in fuel cell degradation is also explored. Finally, by mutating the fuzzy logic membership functions, the MFLC was predicted to extend fuel cell lifetime by up to 32.8%

The effects of gas diffusion layers structure on water transportation using X-ray computed tomography based Lattice Boltzmann method

© 2017 Elsevier B.V. The Gas Diffusion Layer (GDL) of a Polymer Electrolyte Membrane Fuel Cell (PEMFC) plays a crucial role in overall cell performance. It is responsible for the dissemination of reactant gasses from the gas supply channels to the reactant sites at the Catalyst Layer (CL), and the adequate removal of product water from reactant sites back to the gas channels. Existing research into water transport in GDLs has been simplified to 2D estimations of GDL structures or use virtual stochastic models. This work uses X-ray computed tomography (XCT) to reconstruct three types of GDL in a model. These models are then analysed via Lattice Boltzmann methods to understand the water transport behaviours under differing contact angles and pressure differences. In this study, the three GDL samples were tested over the contact angles of 60°, 80°, 90°, 100°, 120° and 140° under applied pressure differences of 5 kPa, 10 kPa and 15 kPa. By varying the contact angle and pressure difference, it was found that the transition between stable displacement and capillary fingering is not a gradual process. Hydrophilic contact angles in the region of 60° < θ < 90° showed stable displacement properties, whereas contact angles in the region of 100° < θ < 140° displayed capillary fingering characteristics

Automatic detection of pitching and throwing events in baseball with inertial measurement sensors

Purpose: Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit. Methods: Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts). Results: The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%). Conclusions: These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology. © 2017 Human Kinetics, Inc