Distributed and Lumped Parameter Models for Fuel Cells

The chapter presents a review of modeling techniques for three types of fuel cells that are gaining industrial importance, namely, polymer electrolyte membrane (PEMFC), direct methanol (DMFC), and solid oxide (SOFC) fuel cells (FCs). The models presented are both multidimensional, suitable for investigating distributions, gradients, and inhomogeneities inside the cells, and zero-dimensional, which allows for fast analyses of overall performance and can be easily interfaced with or embedded in other numerical tools, for example, for studying the interaction with static converters needed to control the electric power flow. Thermal dependence is considered in all models. Some special numerical approaches are presented, which allow facing specific problems. An example is the Proper Generalized Decomposition (PDG) that allows overcoming the challenges arising from the extreme aspect ratio of the thin electrolyte separating anode and cathode. The use of numerical modeling as part of identification techniques, particularly by means of stochastic optimization approaches, for extracting the material parameters from multiple in situ measurements is also discussed and examples are given. Merits and demerits of the different models are discussed

Modeling and simulations of deformation and transport in PEM fuel cells

Performance degradation and durability of PEM fuel cells depend strongly upon transport and deformation characteristics of their components especially the polymer membrane. Physical properties of the membrane, such as its ionic conductivity and Young’s modulus depend on its water content, which varies significantly with operating conditions and during transients. Recent studies indicate that cyclic transients may induce hygro-thermal fatigue that leads to the ultimate failure of the membrane shortening its lifetime, and thus, hindering the reliable use PEM fuel cells for automotive applications. In this work, we present two-dimensional simulations and analysis of coupled deformation and transport in PEM fuel cells. A two-dimensional cross-section of anode and cathode gas diffusion layers, and the membrane sandwiched between them is modeled using Maxwell-Stefan equations in gas diffusion layers, Biot’s poroelasticity and Darcy’s law for deformation and water transport in the membrane and Ohm’s law for ionic currents in the membrane and electric currents in the gas diffusion layers. Steady-state deformation and transport of water in the membrane, transient responses to step changes in load and relative humidity of the anode and cathode are obtained from simulation experiments, which are conducted by means of a commercial finite-element package, COMSOL Multiphysics

Modelling and controlling of polymer electrolyte fuel cell systems

This thesis focuses on the modelling and controlling of polymer electrolyte fuelcell (PEFC) systems. A system level dynamic PEFC model has been developedto test the system performance (output voltage, reactants gas partial pressures,and stack temperature) for different operating conditions. The simulation resultsare in good agreement with the experimental data, which indicates that thePEFC model is well qualified to capture the dynamic performance of the PEFCsystem. Controlling strategies play a significant role in improving the fuel cellsystem’s reliability. Novel model predictive control (MPC) controllers and proportional–integral–derivative (PID) controllers are proposed and implemented indifferent PEFC systems to control voltage and regulate temperature to enhancesystem performance. MPC controllers show superior performance to PID controllers in tracking the reference value, with less overshoot and faster response. Anovel hydrogen selective membrane reactor (MR) is designed for methanol steamreforming (MSR) to produce fuel cell grade hydrogen for PEFC stack use. Thebackpropagation (BP) neural network algorithm is applied to find the mappingrelation between the MR’s operating parameters and the PEFC system’s outputperformance. Simulation results show that the BP neural network algorithm canwell predict the system behaviour and that the developed mapping relation modelcan be used for practical operation guidance and future control applications

Operating Point Optimization of a Hydrogen Fueled Hybrid Solid Oxide Fuel Cell-Steam Turbine (SOFC-ST) Plant

This paper presents a hydrogen powered hybrid solid oxide fuel cell-steam turbine (SOFC-ST) system and studies its optimal operating conditions. This type of installation can be very appropriate to complement the intermittent generation of renewable energies, such as wind generation. A dynamic model of an alternative hybrid SOFC-ST configuration that is especially suited to work with hydrogen is developed. The proposed system recuperates the waste heat of the high temperature fuel cell, to feed a bottoming cycle (BC) based on a steam turbine (ST). In order to optimize the behavior and performance of the system, a two-level control structure is proposed. Two controllers have been implemented for the stack temperature and fuel utilization factor. An upper supervisor generates optimal set-points in order to reach a maximal hydrogen efficiency. The simulation results obtained show that the proposed system allows one to reach high efficiencies at rated power levels.This work has been carried out in the Intelligent Systems and Energy research group of the University of the Basque Country (UPV/EHU) and has been supported by the UFI11/28 research grant of the UPV/EHU and by the IT677-13 research grant of the Basque Government (Spain) and by DPI2012-37363-CO2-01 research grant of the Spanish Ministry of Economy and Competitiveness

Optimal PID Controller designing for voltage control of Fuel Cell

This paper is proposed a PID optimal controller in order to control of one of the most important types of fuel cell, namely proton exchange membrane fuel cell (PEMFC). At first, the introducing and implementation of PEMFC is present and next, during system load variations the proposed controller is designed. The controller should be designed against the load variations for keeping in a fixed value of Fuel cell output voltage. Here, the PID Controller is used which its coefficients are optimized based on Invasive Weed Optimization (IWO). In order to use this algorithm, at first, problem is written as an optimization problem which includes the objective function and constraints, and then to achieve the most desirable controller, IWO algorithm is applied to solve the problem. Simulation results are done for various loads in time domain, and the results show the efficiency of the proposed controller in contrast to the previous controllers

Thermodynamic analysis, modelling and control of a novel hybrid propulsion system

Stringent emission regulations imposed by governments and depleting fossil fuel reserves have promoted the development of the automotive industry towards novel technologies. Various types of hybrid power plants for transport and stationary applications have emerged. The methodology of design and development of such power plants varies according to power producing components used in the systems. The practical feasibility of such power plants is a pre-requisite to any further development. This work presents thermodynamic analysis and modelling of such a novel power plant, assesses its feasibility and further discusses the development of a suitable control system. The proposed system consists of a hybrid configuration of a solid oxide fuel cell and IC engine as the main power producing components. A reformer supplies fuel gas to the fuel cell while the IC engine is supplied with a liquid fuel. The excess fuel from the fuel cell anode and the oxygen-depleted air from cathode of the fuel cell are also supplied to the engine. This gas mixture is aspirated into the engine with the balance of energy provided by the liquid fuel. The fuel cell exhaust streams are used to condition the fuel in the engine to ensure minimum pollutants and improved engine performance. Both, fuel cell and engine share the load on the system. The fuel cell operates on a base load while the engine handles majority of the transient load. This system is particularly suitable for a delivery truck or a bus cycle. Models of the system components reformer, solid oxide fuel cell, IC engine and turbocharger were developed to understand their steady state and dynamic behaviour. These models were validated against sources of literature and used to predict the effect of different operating conditions for each component. The main control parameters for each component were derived from these models. A first law analysis of the system at steady state was conducted to identify optimum operating region, verify feasibility and efficiency improvement of the system. The results suggested reduced engine fuel consumption and a 10 % improvement in system efficiency over the conventional diesel engines. Further, a second law analysis was conducted to determine the key areas of exergy losses and the rational efficiency of the system at full load operating conditions. The results indicate a rational efficiency of 25.4 % for the system. Sensitivity to changes in internal exergy losses on the system work potential was also determined. The exergy analysis indicates a potential for process optimisation as well as design improvements. This analysis provides a basis for the development of a novel control strategy based on exergy analysis and finite-time thermodynamics. A dynamic simulation of the control oriented system model identified the transient response and control parameters for the system. Based on these results, control systems were developed based on feedback control and model predictive control theories. These controllers mainly focus on air and fuel path management within the system and show an improved transient response for the system. In a hierarchical control structure for the system, the feedback controllers or the model predictive controller can perform local optimisation for the system, while a supervisory controller can perform global optimisation. The objective of the supervisory controller is to determining the load distribution between the fuel cell and the engine. A development strategy for such a top-level supervisory controller for the system is proposed. The hybrid power plant proposed in this thesis shows potential for application for transport and stationary power production with reduced emissions and fuel consumption. The first and second law of thermodynamics can both contribute to the development of a comprehensive control system. This work integrates research areas of powertrain design, thermodynamic analysis and control design. The development and design strategy followed for such a novel hybrid power plant can be useful to assess the potential of other hybrid systems as well