Marie-Cécile Péra

On-board fuel cell power supply modeling on the basis of neural network methodology

Proton exchange membranes are one of the most promising fuel cell technologies for transportation applications. Considering the aim of transportation applications, a simulation model of the whole fuel cell system is a major milestone. This would lead to the possibility of optimizing the complete vehicle (including all ancillaries, output electrical converter and their dedicated control laws). In a fuel cell system, there is a strong relationship between available electrical power and actual operating conditions: gas conditioning, membrane hydration state, temperature, current set point ... Thus, a “minimal behavioral model” of a fuel cell system able to evaluate the output variables and their variations is highly interesting. Artificial neural networks (NN) are a very efficient tool to reach such an aim. In this paper, a proton exchange membrane fuel cell (PEMFC) system neural network model is proposed. It is implemented on Matlab/Simulink ® software and will be integrated to a complete vehicle powertrain. Thus, it will be possible to carry out the development and the simulation of the control laws in order to drive energy transfers on-board fuel cell vehicles.

Energy-Management Strategy for Embedded Fuel-Cell Systems Using Fuzzy Logic

This paper presents a fuzzy-logic approach to the energy management of an embedded fuel-cell system. The main objective is to study one of the most technological bolts to be overcome for embedded fuel-cell systems: Their energy optimization. To reach this aim, experimentally validated models of a low-power 5-kW proton-exchange-membrane fuel cell and its most power-hungry ancillary (the fuel-cell air-supply system) are described. All simulation results have been performed using Matlab/Simulink environment. Two fuzzy controllers will be proposed for both the internal air-supply control loop and for the whole-embedded energy-management strategy

Energy management strategy for embedded fuel cell system using fuzzy logic

This paper presents a fuzzy-logic approach to the energy management of an embedded fuel cell system. The main objective is to study one of the most technological bolts to be overcome for embedded fuel cell systems: their energy optimization. To reach this aim, experimentally validated models of a low power 5 kW proton exchange membrane fuel cell (PEMFC) and its most power hungry ancillary (the FC air supply system) are described. All simulation results have been performed using Matlab/Simulink/spl reg/ environment. Two fuzzy controllers are proposed for both the internal air supply control loop and also for the whole embedded energy management strategy.

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.

Hybrid auxiliary power unit (APU) for automotive applications

This paper describes the design and control requirements of an auxiliary power unit (APU) for transportation applications. The design of the APU is based on an association of supercapacitors and a proton exchange membrane (PEM) fuel cell. Supercapacitors are incorporated to satisfy peak power demands in order to optimize performance of the APU and to reduce the size and therefore the cost of the fuel cell. After the system description, simulations are done to optimize the DC/DC converter between the APU components and the DC bus of the vehicle. Finally, experimental results are presented and analyzed.

Black-box modeling of proton exchange membrane fuel cell generators

Proton exchange membranes are one of the most promising fuel cell technologies for transportation applications. Considering this aim, a simulation model of the whole fuel cell system is a binding milestone. This would lead in the optimization possibility of the complete vehicle (including auxiliaries, output electrical converter and their control laws). So a minimal behavioral model of a fuel cell system, able to evaluate the output variables and their variations, is presented in this paper. In a fuel cell system, electrical quantities are dependent both on the fuel cell power level and also on the auxiliaries and gases used. Artificial neural networks are here used to model the whole system. To carry out an efficient model, it is necessary to identify the number and the nature of input and output parameters. The proposed model is implemented on Matlab/Simulink/spl reg/ software and will be integrated in a complete vehicle powertrain. Thus, it is possible to carry out the development and the simulation of the command laws intended to manage the energy transfers aboard fuel cell vehicle.

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

Dynamic behavior of a proton exchange membrane fuel cell under transportation cycle load

This paper presents a dynamic modeling of a proton exchange membrane fuel cell (PEMFC) for transportation applications. Based on an electrochemical analysis, it gives an equivalent circuit of the fuel cell which can he used in association with a power electronic converter. Experimental polarization curves and electrochemical impedance spectroscopy (EIS) are used to identify model parameters and to validate simulation results. Finally, experimental responses to a current step and to transportation solicitations is compared to those obtained using the proposed model.

Dynamical recurrent neural network towards modeling of on-board fuel cell power supply

Electric vehicle (EV) technologies are a strategic part of research and development in the automotive industry. Among the various kinds of EV prototypes presented by the car manufacturers, fuel cell powered electrical vehicles seem to be a very promising solution. When talking about EV design, a simulation model of the whole fuel cell system is a binding milestone. This would lead in the optimization possibility of the complete vehicle (including all ancillaries, output electrical converter and their dedicated control laws). Nevertheless, the fuel cell system model is strongly dependent of many physico-chemical parameters that are difficult to evaluate on a real proton exchange membrane fuel cell (PEMFC) stack. Moreover, the analytical relations governing the behavior of a PEMFC system are also far from being easy. Thus, a minimal behavioral model of a fuel cell system, able to evaluate the output variables and their variations, is highly interesting. Artificial neural networks propose a very efficient tool to reach such an aim. A dynamic recurrent neural network model of a fuel cell system based on proton exchange membrane technology is presented in this paper.

High frequency power converter for PEFC generator architecture based on a multi stacks association for transportation applications

This paper presents the study and experimental validation of a high frequency (HF) power converter used in a powertrain composed of a polymer electrolyte fuel cell (PEFC) generator based on a multi-stack association and dedicated to transportation applications. As a first approach, the architecture of the system presented in this paper has been limited to two fuel cell stacks. An original power converter structure using a HF transformer (HFT) has been chosen. This structure has the main advantage of compactness and is well adapted to the testing of fuel cell generators either in normal or degraded mode (partial failure of one stack); which correspond to real transport operating conditions. Simulation results of the power system are presented and discussed. First experimental results for a normal PEFC working mode are presented and analyzed in this paper including the experimental determination of the power converter efficiency