Numerical modeling and simulation of PEM fuel cells: Progress and perspective

This paper provides a comprehensive review on the research and development in multi-scale numerical modeling and simulation of PEM fuel cells. An overview of recent progress in PEM fuel cell modeling has been provided. Fundamental transport phenomena in PEM fuel cells and the corresponding mathematical formulation of macroscale models are analyzed. Various important issues in PEM fuel cell modeling and simulation are examined in detail, including fluid flow and species transport, electron and proton transport, heat transfer and thermal management, liquid water transport and water management, transient response behaviors, and cold-start processes. Key areas for further improvements have also been discussed.

Efficient Thickness of Solid Oxide Fuel Cell Composite Electrode

The efficient thickness of a composite electrode for solid oxide fuel cells was directly calculated by developing a physical model taking into account of the charge transfer process, the oxygen ion and electron transportation, and the microstructure characteristics of the electrode. The efficient thickness, which is defined as the electrode thickness corresponding to the minimum electrode polarization resistance, is formulated as a function of charge transfer resistivity, effective resistivity to ion and electron transport, and three-phase boundary length per unit volume. The model prediction is compared with the experimental reports to check the validity. Simulation is performed to show the effect of microstructure, intrinsic material properties, and electrode reaction mechanism on the efficient thickness. The results suggest that when an electrode is fabricated, its thickness should be controlled regarding its composition, particle size of its components, the intrinsic ionic and electronic conductivities,and its reaction mechanisms as well as the expected operation temperatures. The sensitivity of electrode polarization resistance to its thickness is also discussed.

Hybrid dynamic model of polymer electrolyte membrane fuel cell stack using variable neural network

The polymer electrolyte membrane（PEM） fuel cell has been regarded as a potential alternative power source,and a model is necessary for its design,control and power management.A hybrid dynamic model of PEM fuel cell,which combines the advantages of mechanism model and black-box model,is proposed in this paper.To improve the performance,the static neural network and variable neural network are used to build the black-box model.The static neural network can significantly improve the static performance of the hybrid model,and the variable neural network makes the hybrid dynamic model predict the real PEM fuel cell behavior with required accuracy.Finally,the hybrid dynamic model is validated with a 500 W PEM fuel cell.The static and transient experiment results show that the hybrid dynamic model can predict the behavior of the fuel cell stack accurately and therefore can be effectively utilized in practical application.

Modeling and Experimental Study of PEM Fuel Cell Transient Response for Automotive Applications

This paper presents an analysis of the dynamic response of a low pressure proton exchange membrane （PEM） fuel cell stack to step changes in load, which are charactedstic of automotive fuel cell system applications. The goal is a better understanding of the electrical and electrochemical processes when accounting for the characteristic cell voltage response during transients. The analysis and expedment are based on a low pressure 5 kW proton exchange membrane fuel cell （PEMFC） stack, which is similar to those used in several of Tsinghua＇s fuel cell buses. The experimental results provide an effective improvement reference for the power train control scheme of the fuel cell buses in Olympic demonstration in Beijing 2008.

A new artificial bee swarm algorithm for optimization of proton exchange membrane fuel cell model parameters

An appropriate mathematical model can help researchers to simulate,evaluate,and control a proton exchange membrane fuel cell (PEMFC) stack system.Because a PEMFC is a nonlinear and strongly coupled system,many assumptions and approximations are considered during modeling.Therefore,some differences are found between model results and the real performance of PEMFCs.To increase the precision of the models so that they can describe better the actual performance,opti-mization of PEMFC model parameters is essential.In this paper,an artificial bee swarm optimization algorithm,called ABSO,is proposed for optimizing the parameters of a steady-state PEMFC stack model suitable for electrical engineering applications.For studying the usefulness of the proposed algorithm,ABSO-based results are compared with the results from a genetic algo-rithm (GA) and particle swarm optimization (PSO).The results show that the ABSO algorithm outperforms the other algorithms.

A linear quadratic regulator control of a stand-alone PEM fuelcell power plant

This paper introduces a technique based on linear quadratic regulator （LQR） to control the output voltage at the load point versus load variation from a stand- alone proton exchange membrane （PEM） fuel cell power plant （FCPP） for a group housing use. The controller modifies the optimal gains ki by minimizing a cost function, and the phase angle of the AC output voltage to control the active and reactive power output from an FCPP to match the terminal load. The control actions are based on feedback signals from the terminal load, output voltage and fuel cell feedback current. The topology chosen for the simulation consists of a 45 kW proton exchange membrane fuel cell （PEMFC）, boost type DC/ DC converter, a three-phase DC/AC inverter followed by an LC filter. Simulation results show that the proposed control strategy operated at low commutation frequency （2 kHz） offers good performances versus load variations with low total harmonic distortions （THD）, which is very useful for high power applications.

Vehicles PEMFC Power System Mathematical Model for Integrated Design

In this paper, the mathematical dynamical model of a PEMFC （proton exchange membrane fuel cells） stack, integrated with an automotive synchronous electrical power drive, developed in Matlab environment, is shown. Lots of simulations have been executed in many load conditions. In this paper, the load conditions regarding an electrical vehicle for disabled people is reported. The innovation in this field concerns the integration, in the PEMFC stack mathematical dynamic model, of a synchronous electrical power drive for automotive purposes. Goal of the simulator design has been to create an useful tool which is able to evaluate the behaviour of the whole system so as to optimize the components choose. As regards the simulations with a synchronous electrical power drive, the complete mathematical model allows to evaluate the PEMFC stack performances and electrochemical efficiency.