Denis Candusso

Fuzzy-Clustering Durability Diagnosis of Polymer Electrolyte Fuel Cells Dedicated to Transportation Applications

Polymer electrolyte fuel cells (FCs) are often considered as the most promising power-generation sources for next- generation electrical or hybrid electrical vehicles. However, areas needing further development are the improvements of the efficiency, durability, and reliability of the whole powertrain. Moreover, freeze start of the FC system is also a major issue. To reach these aims, diagnosis solutions of FC stacks and systems can speed up the development cycle of this new technology. The aim of this paper is, thus, to propose some guidelines within the framework of embedded FC system durability diagnosis.

Enhanced Servo-Control Performance of Dual-Mass Systems

This article gives an overview of the challenging issues addressing different technological fields in generating power using fuel cell. Continuous depletion of crude oil supply and the gradual increase in oil prices have emphasized the need for a suitable alternative to the century-old oil-based economy. Among the different technological alternatives, fuel cell (FC) power generation becomes a more promising solution for both automotive industry and stationary power plants. Among the five existing FC technologies, each type can be configured into a system focusing on the market segments that match its characteristics most favorably. Because of their quick startup potential, low-temperature is being considered for portable, residential power and transportation applications. Higher- temperature are often considered for stationary power generation. Nevertheless, due to their solid electrolyte, SOFCs are also considered for transportation applications by some car manufacturers and car suppliers. Diagnosis methods based on evolutionary parameter models, black-box models, or grey-box models must be developed to improve reliability and availability of FC systems. The equivalent circuit approach addresses electrical engineering concerns and suits the system integration issues.

Power generation by fuel cells

C ONTINUOUS DEPLETION of crude oil supply and the gradual increase in oil prices have emphasized the need for a suitable alternative to our century-old oil-based economy. A clean and efficient power-supply device based on a renewable energy source must be available to address this issue. Among the different technological alternatives, fuel cell (FC) power generation becomes a more and more interesting and promising solution for both automotive industry and stationary power plants. However, many technological hurdles must still be overcome prior to the development of industrial and competitive products in these fields. This article gives an overview of these challenging issues addressing different technological fields.

Dynamic PEM fuel cell modeling for automotive applications

This paper presents a static and dynamic modeling of a proton exchange membrane fuel cell (PEMFC) for transportation applications. Electrochemical analysis is performed to get an equivalent circuit of the fuel cell, which can be used, in the simulation of the power generator (association of the fuel cell and its converter). Experimental polarization curves and electrochemical impedance spectroscopy (EIS) are used to identify model parameters and to validate simulation results. Finally, experimental response to a current step is compared to the proposed model.

Model-based diagnosis for proton exchange membrane fuel cells

Proton Exchange Membrane Fuel Cell (PEMFC) systems are more and more presented as a good alternative to current energy converters such as internal combustion engines. They suffer however from insufficient reliability and durability for stationary and transport applications. Reliability and lifetime may be improved by suitable fault detection and localization. Traditionally, fault diagnosis in fuel cell systems needs the knowledge of number of parameters, which might require a special inner parameter monitoring setup. This is difficult, even impossible with respect to fuel cell stacks geometry. Moreover, with respect to the transportation application that aims at minimizing the embedded instrumentation, simple diagnosis methods involving non-intrusive and easy-to-monitor parameters are highly desired in PEMFC systems. We present in this paper a flooding diagnosis procedure based on black-box model. This diagnosis method allows automating the flooding diagnosis and the parameters used are minimal, low-cost and simple to monitor. The model inputs are some variables that are critical for water management in the PEMFC and consequently for fuel cell performances while the output is a variable that can be monitored in a non-intrusive way and can be used to detect flooding (namely pressure drop through the cathode). The flooding diagnosis procedure is based on the analysis of a residual obtained from the comparison between an experimental and an estimated pressure drop. The estimation of this latter is ensured by an artificial Neural Network that has been trained with flooding-free data. Fault detection is obtained by means of a residual analysis. It has been successfully tested under different experimental conditions including non-flooding and deliberately induced flooding as well as a succession of the two states of health. A proposition to include drying out problems is given as perspective to this work.

Online diagnosis of PEM Fuel Cell

This study consists on online detection of fuel cell dysfunction in embedded applications without additional hardware component. The power converter usually coupled with the fuel cell is used to perform the diagnosis strategy. The main interest of the method presented in this paper is to simultaneously optimize the performances, the cost and the size of the Proton Exchange Membrane Fuel Cell (PEMFC). In this work, we focus on a system including a fuel cell stack coupled with an isolated DC/DC power converter and controlled by a Digital Signal Processor (DSP). These elements associated with measurement sensors and adequate programmings allow the control of the power conversion and the determination of fuel cell health at the same time. The fuel cell harmonic impedance is measured using spectroscopy method for a large frequency range. Specific cases of fault detections related to membrane humidification and reactive gas feeding are treated in this paper.

Analysis of a Fuel Cell Durability Test Based on Design of Experiment Approach

The results of a durability test performed during 1000 h on a proton exchange or polymer electrolyte membrane (PEM) fuel cell are analyzed using some well-suited design of experiment techniques. The response surface methodology is adopted to model the performance degradation over ageing time from various load current--fuel cell voltage curves recorded at regular time-spaced intervals and for various air utilization rates. The dual response surface approach is employed to determine the most convenient operating conditions for the cells (load current and air stoichiometry rate levels), leading to a tradeoff between elevated electrical efficiency and low voltage variability versus ageing time and cell positions in the stack. In addition, some electrochemical impedance spectra are used to provide some physical interpretations and to corroborate the observations made from the static measurements. The work shows notably the benefit of using some variable stoichiometry rates through ageing time to get high-power levels and stable performances as well.

Diagnosis of a fuel cell stack using electrochemical impedance spectroscopy and Bayesian Networks

In the first part of the paper, a novel architecture of impedance spectrometer is presented. The instrument is dedicated to the characterization and diagnostic of large fuel cell stacks operated in galvanostatic mode. It allows impedance measurements on cells located in the middle of the stack, where common mode potentials are usually too high for commercial devices. In the second part of the article, probabilistic methods (Bayesian Networks) are used to provide efficient diagnostic of a proton exchange membrane fuel cell stack. Experiments are performed on a twenty cell assembly using electrochemical impedance spectroscopy and from the test results, a Bayesian Network is proposed to ensure the diagnosis of the investigated fuel cell (study of drying and flooding phenomena). A maximum rate of good classification equal to 91% has been reached.

Analysis of a Fuel Cell Durability Test Using the Response Surface Methodology

The design of experiment (DoE) technique and one of its important aspects, the response surface methodology (RSM), are employed to analyze the results of an ageing test performed during 1000 hours on a 100 W PEM fuel cell stack. The response surfaces are plotted thanks to load current - fuel cell voltage curves recorded at regular time-spaced intervals and for various air utilization rates. Some covariance based models are used to fit and adjust response surfaces to experimental data. An optimization of the fuel cell performances is done by taken into account the time, current and air stoichiometry rate factors

A New High Voltage Impedance Spectrometer for the Diagnostics of Fuel Cell Stacks

This paper presents a novel architecture of an impedance spectrometer dedicated to the characterization and diagnostic of large Fuel Cell (FC) stacks operated in galvanostatic mode. The validation tests are first performed on a single Proton Exchange Membrane Fuel Cell (PEMFC). Then, experiments are carried out on a twenty-cell PEMFC stack delivering more significant power levels. The proposed impedancemeter allows spectrum measurements on cells located in the middle of the stack, where common mode potentials are usually too high for commercial devices. Moreover, the impedances of different individual cells in the stack are acquired with a synchronous measurement reference (global stack impedance). This capability allows distinguishing any singular cell behavior or drift effect of operational parameters (e.g. stack temperature and polarization current).Copyright