J. Jia

Parameter Identification for PEM Fuel-Cell Mechanism Model Based on Effective Informed Adaptive Particle Swarm Optimization

In order to improve the inherent drawbacks of particle swarm optimization (PSO), an effective informed adaptive PSO (EIA-PSO) algorithm that has better equilibrium characteristic between global search and local search is proposed. In this paper, an electrochemical-based proton exchange membrane fuel cell (PEMFC) mechanism model suitable for engineering optimization is developed, and a parameter-identification-technique-based EIA-PSO for this mechanism model is presented. In order to verify the validity of the advanced method, comparisons between experimental data and simulation data are carried out. The results demonstrate that EIA-PSO can make the mechanism model with identified parameters fit the experimental data with higher precision even in the presence of measurement noise. Therefore, EIA-PSO is an optional effective technique for identifying the parameters of the PEMFC mechanism model.

Modeling and Dynamic Characteristic Simulation of a Proton Exchange Membrane Fuel Cell

In order to investigate the output characteristic of a proton exchange membrane fuel cell (PEMFC) based on the electrical empirical model, a novel dynamic model of the PEMFC has been developed with MATLAB/Simulink, which is distinct from the models that have been published previously. By using a fuel cell test system of the Fuel Cell Application Centre (FAC) at Temasek Polytechnic, the transient electrical responses of PEMFC were conducted and analyzed under various operating conditions. A good match is found between simulation results and experimental data. The comprehensive results of simulation manifested that the model is effective and operational. This model will be very useful to optimize the structure design, improve the operation performance, and develop the real-time control system of PEMFC.

Electrical Characteristic Study of a Hybrid PEMFC and Ultracapacitor System

This paper presents the characteristic study of a clean hybrid power supply system combining proton exchange membrane fuel cell (PEMFC) as the main power source and ultracapacitor (UC) as the energy storage unit. Unlike the conventional fuel-cell hybrid system with power conditioning unit, the study investigated the electrical characteristic of the PEMFC and UC hybrid system without dc/dc converter. As a platform to evaluate the proposed system, the fuel-cell-based electric bicycle is implemented. The platform consists of PEMFC stack, metal hydride, thermal balance system, UC, dc motor, system control and data logging unit, as well as user interface. The test results showed that the proposed architecture is functional and leads to good results. By road testing, it was verified that the PEMFC can provide the rated power to the load and that the UC can deliver the power at system startup and the peak power if needed. The road testing results showed that the design objectives are fulfilled.

Matlab/Simulink based-study on PEM fuel cell and nonlinear control

This paper presents a dynamic multi-input multi-output (MIMO) model of PEM fuel cells and a nonlinear control approach appropriate for this model based on exact linearization. Since large deviations of pressures between anode and cathode gases can cause severe membrane damage in fuel cells, it is necessary to design a corresponding controller so that the deviation can be kept as small as possible during the load variations, in the meantime, the purpose to prolong the stack lifetime of the PEM fuel cells can also be achieved. The PEM fuel cell model, nonlinear control by exact linearization and generic model control (GMC) are described and combined as a system in Matlab/Simulink environment and the results show that the system is available to simulate the transient performance of fuel cells and it is effective on fuel cell membrane protection.

Model and Operation Optimization of PEMFC Based on AFPSO

In order to obtain the optimal operating conditions local search of particle swarm optimization was an adaptive for the maximum output power of proton exchange membrane swarm intelligence optimization algorithm with preferable fuel cell (PEMFC), a PEMFC mechanism model was developed ability of global search and search rate. Based on the idea of with Matlab. Adaptive focusing particle swarm optimization division of labor, the better performance particles get larger (AFPSO) which had preferable ability of global search and inertia weight, making them explore better detection, and the search rate was proposed to estimate the parameters in this poor performance particles get smaller inertia weight, so that model. The comparison between experimental results and they can convergence in the better regions rapidly to carry out simulation results demonstrates that AFPSO can make the meticulous search. The positive constants of particles adjust simulation results fitted the experiment data with higher adaptively according to the inertia weight. When the search precision and has manifest superiority for estimating the model result is better than the personal best value of current particle, parameters. Furthermore, AFPSO was used to search the maintains the current speed of the particle to search forward, optimal operating conditions of PEMFC. Compared with the so that the particle can always maintains its personal best experimental results, the validity of AFPSO was further proved. Hence AFPSO achieves significant effect for optimizing the position in the search process, and makes this as the starting model parameters and improving the output performance of point for follow-up search. This effect is called focusing here. PEMFC. Besides, the personal best position and global best position in standard PSO algorithm are respectively replaced by the Keywords- proton exchange membrane fuel cell mechanism weighted mean of the relevant personal best positions. These modeling; adaptive focusing particle swarm optimization; strategies improve the PSO algorithm at the aspects of operation condition optimization; adaptive parameters diversity and the balance of exploration and exploitation. In this paper, in order to determine the optimal operating I. INTRODUCTION conditions for the maximum output power of PEMFC, a Fuel cells are electrochemical devices that convert PEMFC mechanism model was developed. Meanwhile, the chemical energy of the fuel into electricity without electrical response of PEMFC was tested by Fuel Cell Test combustion. High efficiency makes fuel cells an attractive System 890CL incorporating with LeCroy Waverunner LT344 option for a wide range of applications. Currently, proton which has highly precise, and AFPSO was proposed to exchange membrane fuel cell (PEMFC) is commonly used. estimate the parameters in this model for researching a set of Because of its high efficiency, good stability, and low optimized parameters. The comparison of the experiment pollution etc, PEMFC is viewed as a dependable power source results and the simulation results shows that the model can for many applications, such as distributed power generation reflect the operating characteristic of PEMFC effectively. The and automobile (1, 2). comprehensive comparison with other optimization algorithm demonstrates that AFPSO has manifest superiority for The electrical response of PEMFC to cold start, hot start, estimating the model parameters. Furthermore, AFPSO was load change, pressure change was investigated by using Fuel used to search the optimal operating conditions of PEMFC. Cell Test Systems 890CL (2). The result indicated that the Compared with the experimental results, the validity of different operation conditions exerted an influence on the AFPSO was further proved. Therefore, AFPSO makes performance of PEMFC. At present, there are a variety of fuel important effect for improving the output performance of cell models, but they have many uncertainties. A lot of PEMFC, boosting the efficiency of electricity, optimizing the optimization algorithms were adopted to optimize the model parameters. parameters, such as simulated annealing algorithm (SAA), seeker optimization algorithm (SOA), and particle swarm optimization algorithm (PSO). They obtained positive effects,

The advanced control and its experiments of a hybrid PEMFC and ultra-capacitor system

This paper presents the advanced control strategy and experimental study of a clean hybrid power system combining proton exchange membrane fuel cell (PEMFC), as the main power source, and ultra-capacitor (UC), as the energy storage unit.

Robust control based on linear matrix inequality of fuel cell system with μ analysis

In order to conquer uncertainty and disturbance, a reduced robust control strategy based on linear matrix inequality (LMI) was proposed for a proton exchange membrane fuel cell (PEMFC) system. And then the structure singular value (SSV) μ analysis method was utilized to testify the robust stability of proposed controller. The simulation results demonstrated that the control method could maintain the oxygen excess ratio (OER) better at the desired value and guarantee stable operation of the system when the vehicle running process was simulated. The comparison with other control strategies verified that the proposed method had superiority and valuable robust stability margin was obtained by μ analysis.

H ∞ optimal control for fuel cell system with adaptive focusing particle swarm optimization algorithm

In order to control a proton exchange membrane fuel cell (PEMFC) system, a novel H∞ optimal control method with adaptive focusing particle swarm optimization (AFPSO) which had preferable ability of global search and search rate was proposed. The simulation results demonstrated that the method could maintain the pressure inside supply manifold, and guarantee stable operation of the system when the vehicle running process was simulated. The comprehensive comparison with other control approaches testified that the proposed method had manifest superiority and validity.

Dynamic characteristic study of proton exchange membrane fuel cell

In order to investigate the output characteristic of proton exchange membrane fuel cell (PEMFC) based on the electrical empirical, a novel dynamic model of PEMFC has been developed with Matlab/Simulink, which is distinct from the models have previously been published. By using a fuel cell test system in Fuel Cell Application Centre in Temasek Polytechnic, the transient electrical response of PEMFC was conducted and analyzed under various operating conditions. A good match is found between simulation results and experimental data. The comprehensive results of simulation manifested that the model is effective and operational. This model will be very useful to optimize the structure design, improve the operation performance, and develop the real-time control system of PEMFC.

A clean power system combining fuel cell and ultracapacitor and its application in electric scooter

This paper presents a clean power system combining fuel cell and ultracapacitor. The fuel cell, which acts as the primary power source, is used for the continuous load requirement. The ultracapacitor, which acts as the secondary power source, is used for the peak load requirement. A controller also is designed to determine and assign the power between the fuel cell, ultracapacitor and motor..and this clean power system is applied to an electric scooter. The result of experimentation shows that the system is very effective and steady.