Design optimal temperature control system based on effective informed adaptive particle swarm optimization for proton exchange membrane fuel cell

Challenges and opportunities in modelling of proton exchange membrane fuel cells (PEMFC)

Performance study of a dual power source residential CCHP system based on PEMFC and PTSC

Nonlinear multivariable modeling of locomotive proton exchange membrane fuel cell system

Control of proton exchange membrane fuel cell system breathing based on maximum net power control strategy

- Polymer electrolyte membrane fuel cell(PEMFC) requires cooling system to maintain the proper operating temperature(about 65℃∼75℃) because the efficiency and power are affected by operating temperature. In order to retain the operating temperature of PEMFC, cooling system and coolant control logic are needed. Hardware-in-the-loop simulation(HILS) is one of effective methods to study and evaluate control algorithm. In this paper, the HILS system was designed to study the coolant control algorithm. The models of HILS system consisted of PEMFC, heat exchanger, and external environment associated with temperature. The hardwares in HILS system are 3-way valves, pumps, and a heat exchanger. The priority control and the control target temperature were investigated to improve the control performance using HILS. The 3-way valve in 1 st cooling circuit was selected as priority control target. The under limit value of 2 nd 3-way valve set as a function of PEMFC power and 2 nd circuit coolant temperature to correct temperature control performance. As a result, the temperature of PEMFC is stably controlled.

Electric propulsors powered by Proton Exchange Membrane Fuel Cells (PEMFCs) offer a net zero solution to aircraft propulsion. Heat generated by the PEMFCs can be transferred to atmospheric air via a liquid cooling system; however, the cooling system results in parasitic power and adds mass to the propulsion system, thereby affecting system specific power. The design of the cooling system is sensitive to the choice of liquid coolant and so informed coolant selection is required if associated parasitic power and mass are to be minimized. Two approaches to selection of coolants for PEMFC-powered aircraft are presented in this paper for operating temperatures in the range 80-200°C (this covers low, intermediate, and high temperature PEMFCs). The first approach uses a Figure of Merit (FoM) alongside minimum and maximum operating temperature requirements. The FoM supports the selection of coolants that minimize pumping power and mass while maximizing heat transfer rate. The second approach uses a cooling system model to select ȜPareto efficientȝ coolants. A hybrid-electric aircraft using a PEMFC stack is used as a representative case study for the two approaches. Hydrocarbon-based coolants are shown to be favorable for the case study considered here (aromatics for PEMFCs operating at <130°C and aliphatics for PEMFCs operating at >130°C). As the PEMFC operating temperature increases, the parasitic power and mass of the TMS decreases. Operating at elevated temperatures is therefore beneficial for liquid cooled PEMFC-powered aircraft. Nevertheless, there are diminishing performance gains at higher operating temperatures.

Proton exchange membrane fuel cell has advantages of high energy conversion efficiency, high reliability, no pollution, low operating temperature and rapid start-up. It has become an ideal method of hydrogen energy utilization and is also ideally suited to be used as the main source of energy for automobiles. Currently, it constitutes a research hot spot in the field of new energy vehicles. Based on the working mechanism of proton exchange membrane fuel cells and empirical models, a terminal voltage dynamic model, an open circuit voltage model and three voltage loss models are established. Matlab/Simulink software is utilized to simulate the model and perform analyses in response to the impact of operating temperature and pressure on its performance. To enhance the efficiency of the proton exchange membrane fuel cell, the operating temperature should be increased in the medium and low current density zones and the operating pressure should be increased in the high current density zone.

Proton exchange membrane fuel cell (PEMFC) is considered as a clean and high-efficient power source for portable and on-site applications. Perfluorosulfonic acid (PFSA) polymer is the most common used electrolyte membrane material in PEMFC due to its high proton conductivity and excellent long-term stability under fully hydrated condition. However, its low glass transition temperature limits the operating temperature of PEMFC below 80oC. High operating temperature results in lowered mechanical and dimensional stabilities of PFSA polymer though high temperature operation has many other advantages for PEMFC including higher catalytic and anti-poisoning activities of electrical catalysts, and better controlled water and heat management. Moreover, proton transport capability of PFSA polymer is sensitive to environmental humidity. Membrane dehydration at high temperature sharply decreases its proton conductivity. The required external humidification equipment complicates the design and operation of fuel cell systems and lowers system reliability and energy utilization efficiency, as well as increases their weight and size. Therefore, to develop proton exchange membrane which can be operated under high temperature and low humidity conditions has become a very active research topic. PEMFC has been stably operated under high temperature and low humidity conditions by adding inorganic fillers (e.g., zirconium phosphate, metal oxides, zeolites) into PFSA polymer to prepare polymer-inorganic composite membranes. However, main issues are the increase of proton transport resistance, the aggregation of inorganic filler particles and the appearance of phase separation for the above-mentioned composite membranes. Recently, we have developed and patented a new kind of high-temperature self-humidifying proton exchange membrane (i.e., confined structural composite membrane) by confining PFSA polymer into zeolite-coated porous substrate. Confined structural composite membrane harmonizes the structure and function of different membrane compositions to utilize water retention property of zeolite and avoid the formation of discontinuous phase within PFSA matrix. Confinement effect further improves the performance of structural composite membrane. New confined structural composite membrane can be stably operated up to 160oC without humidification. Self-humidifying hydrogen PEMFC and passive direct methanol fuel cell with new confined structural composite membrane output one order of magnitude higher maximum power densities than those with commercial Nafion 117 membrane. The effect of preparation parameters including zeolite type (e.g., silicate-1, NaZSM-5, HZSM-5, HY), coating thickness, coating morphology (e.g., single-layered, multi-layered, continuous, discontinuous) and PFSA precursor (e.g., solvent, incorporated material) on membrane physicochemical properties and fuel cell performance is also investigated to explore formation mechanisms of high thermal stability and self-humidifying property. On one hand, zeolite coating regulates water within confined structural composite membrane through adsorption of reaction generated water and catalytic formation of water. On the other hand, the confinement of PFSA polymer within zeolite-coated porous substrate limits the shrinkage and swelling of polymer caused by temperature and humidity changes, and induces the oriented rearrangement of polymer chains within confined space.

In this article we describe a novel Adaptive particle swarm optimization (APSO) algorithm based on population diversity information. It is presented to solve the precocious convergence problem of particle swarm optimization algorithm. The APSO algorithm uses the information of the population diversity to adjust nonlinearly inertia weight. Velocity mutation factor and position interchange factor are both introduced and the global performance is clearly improved. The APSO algorithm is applied to optimization of parameters in the optimal model based on support vector machine (SVM). SVM is a popular classification method with many diverse applications. A novel Adaptive particle swarm optimization (APSO) based approach for parameter determination and feature selection of the SVM, termed APSO+SVM is developed. The illustrating example shows that the classification accuracy of APSO+SVM is higher than other traditional methods of classification, so using APSO+SVM method to classify is feasible and effective.

This paper is the outcome of a small scale fuel cell project. Fuel cell is an electrochemical device that converts energy from chemical reaction to electrical work. Proton Exchange Membrane Fuel Cell (PEMFC) is one of the different types of fuel cell, which is more efficient, having low operational temperature and fast start up capability results in high energy density. In this study, a mathematical model of 1.2 W PEMFC is developed and simulated using MATLAB software. This model describes the PEMFC behaviour under steady-state condition. This mathematical modeling of PEMFC determines the polarization curve, power generated, and the efficiency of the fuel cell. Simulation results were validated by comparing with experimental results obtained from the test of a single PEMFC with a 3 V motor. The performance of experimental PEMFC is little lower compared to simulated PEMFC, however both results were found in good agreement. Experiments on hydrogen flow rate also been conducted to obtain the amount of hydrogen consumed to produce electrical work on PEMFC.

Heat and mass transfer performance of proton exchange membrane fuel cells with electrode of anisotropic thermal conductivity

A hybrid system using direct contact membrane distillation for water production to harvest waste heat from the proton exchange membrane fuel cell

So far, most of the proton exchange membrane fuel cell (PEMFC) models are difficult to apply in the control system design. In this paper, a dynamic control model of PEMFC system is set up. Based on this model, a self-adaptive fuzzy PID controller and a PID controller are respectively used to control the output voltage. The simulation results show that, this adaptive fuzzy PID controller can control the output characteristics more effectively than the PID controller, which can ensure PEMFC operate stably.

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified.

Investigating and quantifying the effects of catalyst layer gradients, operating conditions, and their interactions on PEMFC performance through global sensitivity analysis