Performance optimization of polymer electrolyte membrane fuel cells using the Nelder-Mead algorithm

The direct-search simplex method for function optimization has been adapted to performance optimization of polymer electrolyte membrane fuel cells (PEMFCs). The established method is strongly application oriented and uses only experimentally determined data for optimization. It is not restricted to discrete parameters optimums and does not require the use of third-party software or computational resources. Hence, it is easy to implement in fuel cell testing stations. The optimization consists of finding, for a given fuel cell load, an optimum set of values of the 7 fuel cell operating parameters: the fuel cell temperature, the reactants' stoichiometric ratios, the reactants' inlet relative humidity, and the reactants' outlet pressures, resulting in the highest fuel cell performance. The performance is measured using a scalar function of the operating parameters and the load and can be defined according to needs.Two PEMFC performance functions: the fuel cell voltage and the system-related fuel cell efficiency were optimized using the procedure for practically sized PEMFC stacks of two designs. With respect to the nominal operating conditions defined as optimal for each stack design by its manufacturer, the gains from the optimization procedure were up to over 12% and up to over 7% for the stack voltage and efficiency, respectively. The validation of the procedure involved 5 stack specimens and four laboratories and consistent results were obtained.     

Toward the optimization of operating conditions for hydrogen polymer electrolyte fuel cells

A study is performed to find the optimal operating conditions of hydrogen polymer electrolyte fuel cells using an efficient optimization approach based on validated multi-resolution fuel cell simulation tool developed in house. Through the design of experiment method, a set of designed simulation runs were carried out using the fuel cell simulation tool. Based on the simulation results, an analytic metamodel was then constructed using the radial basis function approach. A feasible sequential quadratic programming scheme was then employed to optimize the metamodel to achieve the global optimal solutions. To illustrate the optimization approach, four control parameters including cell temperature, cathode stoichiometry, cathode pressure, and cathode relative humidity were considered. The optimization objective is defined as the maximization of the overall efficiency of the fuel cell system under ideal or realistic system assumptions. The study shows that different optimal solutions exist for different system assumptions, as well as different current loading levels, classified into small, medium, and large current densities. The approach adopted in this study is generic and can be readily applied to a larger number of control parameters and further to the fuel cell design optimizations.     

Thermal management oriented steady state analysis and optimization of a kW scale solid oxide fuel cell stand-alone system for maximum system efficiency

This research attempts to ensure system safety while to maximize system efficiency by addressing steady state analysis and optimization for solid oxide fuel cell (SOFC) systems. Firstly, a thermal management oriented kW scale SOFC stand-alone system (primarily comprising a planar SOFC stack, a burner, and two heat exchangers) is developed, in which a special consideration for stack spatial temperature management is conducted by introducing an air bypass manifold around heat exchangers. The dynamic model of the system is performed using transient energy, species, and mass conservation equations. Secondly, based on the system model, the effects of operating parameters including fuel utilization (FU), air excess ratio (AE), bypass ratio (BR), and stack voltage (SV) on the system steady-state performances (e.g. system efficiency, stack inlet, stack outlet, and burner temperatures) are revealed. Particularly, an optimal relationship between the system efficiency and the operating parameters is proposed; the maximum system efficiency can certainly be obtained at the inlet outlet temperature critical point of the BR-AE or FU-AE planes for all SV operating points. Finally, according to the optimal relationship, a traverse optimization process is designed, and the maximum system efficiency and safe operating parameters at any efficient SV operating point are calculated. The results provide an optimal reference trajectory for control design, where the system is safe and efficiency optimization. Moreover, the results reveal two important system characteristics: (1) the burner operates within safe temperature zone as long as the temperature of the upstream stack is well controlled; (2) the control design for the system is a nonlinear optimal control with switching structure, which is a challenging control issue.     

Optimized rule-based energy management for a polymer electrolyte membrane fuel cell/battery hybrid power system using a genetic algorithm

The polymer electrolyte membrane fuel cell (PEMFC) coupled with the battery is a promising hybrid power system for future energy supply application. Fuel cell durability, battery charge sustenance, and fuel consumption strongly rely on the energy management strategy (EMS). This paper puts forward an optimized rule-based EMS using genetic algorithm (GA) to optimally allocate the power between the fuel cell and the battery system. Control variables in real-time rule-based EMS are optimally adjusted with single objective of battery charge sustenance considering the fuel cell durability and efficiency. The proposed optimized rule-based EMS is simulated and experimentally verified via MATLAB/Simulink and LabVIEW-based experimental rig, respectively. The conventional rule-based EMS, fuzzy logic EMS, and dynamic programming (DP) EMS are also examined for comparison. The comparison results elucidate that the optimized rule-based EMS realizes a large performance improvement over the conventional rule-based and fuzzy logic EMSs. Near optimal performance is verified compared with DP EMS in terms of fuel economy, battery charge sustenance, fuel cell efficiency, and system durability. The combination of rule-based EMS and GA optimization algorithm has the advantage of having expert experience and global optimization properties, realizing optimal power allocation in real-time application with lower computation burden, which could be applied easily to other EMS system without loss of validity.     

Determination of optimal operating conditions for a polymer electrolyte membrane fuel cell stack: optimal operating condition based on multiple criteria

A methodology for optimal control of the polymer electrolyte membrane fuel cell (PEMFC) with multiple criteria is presented here. In this regard, thermoelectric objectives and thermoeconomic objective are considered, simultaneously. The proposed fuel cell is a 1200 W Ballard PEMFC namely Nexa? power module. The net power density and exergetic efficiency of the PEMFC are maximized, and the unit cost of the generated power is minimized in a multi‐objective optimization procedure using the NSGA‐II (non‐dominated sorting genetic algorithm). Operating temperature and pressure, air stoichiometric coefficient at the cathode and the current density are considered as controlling parameters in order to acquire optimal performance of the PEMFC. A set of optimal solution namely the Pareto frontier is obtained, and a final optimal solution is selected from available solutions located on the Pareto frontier using the fuzzy decision‐making process based on the Bellman–Zadeh approach. Results are compared with corresponding results obtained previously in single objective optimization scenarios. It has been shown that the optimal operating condition obtained based on the multiple criteria approach has least deviation from the ideal features of the fuel cell in comparison to the corresponding optimal solution obtained in conventional single‐objective optimization approaches. Copyright © 2013 John Wiley & Sons, Ltd.     

Hydrogen from ethanol: Theoretical optimization of a PEMFC system integrated with a steam reforming processor

In this paper the energetic optimization of a proton exchange membrane fuel cell integrated with a steam reforming system using ethanol as fuel is analysed. In order to obtain high hydrogen production, a thermodynamic analysis of the steam reforming process has been carried out and the optimal operating conditions has been defined. Moreover, the overall efficiency of the PEMFC-SR system has been investigated as a function of the fuel utilization factor and the effects of the anodic off-gas recirculation have been evaluated.     

Model-based control of fuel cells (2): Optimal efficiency

A dynamic PEM fuel cell model has been developed, taking into account spatial dependencies of voltage, current, material flows, and temperatures. The voltage, current, and therefore, the efficiency are dependent on the temperature and other variables, which can be optimized on the fly to achieve optimal efficiency. In this paper, we demonstrate that a model predictive controller, relying on a reduced-order approximation of the dynamic PEM fuel cell model can satisfy setpoint changes in the power demand, while at the same time, minimize fuel consumption to maximize the efficiency. The main conclusion of the paper is that by appropriate formulation of the objective function, reliable optimization of the performance of a PEM fuel cell can be performed in which the main tunable parameter is the prediction and control horizons, V and U, respectively. We have demonstrated that increased fuel efficiency can be obtained at the expense of slower responses, by increasing the values of these parameters.     

Exergy analysis and optimization of a HT-PEMFC using developed Manta Ray Foraging Optimization Algorithm

This paper analyzes the efficiency of a high-temperature proton exchange membrane fuel cell (HT-PEMFC) by calculating the output voltage of the cell in different working conditions, using the semi-experimental relationships. The irreversibility and the exergy efficiency of the fuel cell is calculated under different working conditions and the effect of temperature and pressure has been studied. To achieve optimal design for the PEMFC, its parameters are optimized based on irreversibility, exergy efficiency, and its work. The system optimization is applied by a modified version of the Manta Ray Foraging Optimization Algorithm. The suggested algorithm is then compared with other algorithms from the literature and also simulation results and showed a high agreement between the suggested algorithm and the simulation results.     

Thermal–economic–environmental analysis and multi-objective optimization of an internal-reforming solid oxide fuel cell–gas turbine hybrid system

In this article, an internal-reforming solid oxide fuel cell–gas turbine (IRSOFC–GT) hybrid system is modeled and analyzed from thermal (energy and exergy), economic, and environmental points of view. The model is validated using available data in the literature. Utilizing the genetic algorithm optimization technique, multi-objective optimization of modeled system is carried out and the optimal values of system design parameters are obtained. In the multi-objective optimization procedure, the exergy efficiency and the total cost rate of the system (including the capital and maintenance costs, operational cost (fuel cost), and social cost of air pollution for CO, NO_x, and CO₂) are considered as objective functions. A sensitivity analysis is also performed in order to study the effect of variations of the fuel unit cost on the Pareto optimal solutions and their corresponding design parameters. The optimization results indicate that the final optimum design chosen from the Pareto front results in exergy efficiency of 65.60% while it leads to total cost of 3.28 million US$ year⁻¹. It is also demonstrated that the payback time of the chosen design is 6.14 years.     

Optimization of fuel cell system operating conditions for fuel cell vehicles

Proton exchange membrane fuel cell (PEMFC) technology for use in fuel cell vehicles and other applications has been intensively developed in recent decades. Besides the fuel cell stack, air and fuel control and thermal and water management are major challenges in the development of the fuel cell for vehicle applications. The air supply system can have a major impact on overall system efficiency. In this paper a fuel cell system model for optimizing system operating conditions was developed which includes the transient dynamics of the air system with varying back pressure. Compared to the conventional fixed back pressure operation, the optimal operation discussed in this paper can achieve higher system efficiency over the full load range. Finally, the model is applied as part of a dynamic forward-looking vehicle model of a load-following direct hydrogen fuel cell vehicle to explore the energy economy optimization potential of fuel cell vehicles.     

Methods of choosing the optimal parameters for solid fuel combustion in stoker-fired boilers

Stoker-fired boilers are used for the combustion of coal and solid wastes. The most important disadvantage is their low thermal efficiency. The authors present methods of choosing the optimal rate of travel of the grid and height of the fuel layer basing on both realscale and laboratory measurements. Basing on industrial-scale experiments the authors calculated the optimal thermal efficiency and main energy losses using the least squares adjustment method. The stepwise regression method was used to correlate the main energy losses as functions of grid operating parameters. These correlations were used in the optimization method to estimate the optimal rate of travel of the grid and height of the fuel layer. The minimum retention time of the coal can be also calculated.     

Efficiency improvement of a PEMFC power source by optimization of the air management

The increase of fuel cell (FC) system efficiency requires an optimal management of all its sub-systems. This paper discusses and analyses the possibilities of the improvement of the performance of a proton exchange membrane fuel cell (PEMFC) power source via the implementation of an optimal operating design of the air management sub-system. The steady-state PEMFC operation has been taken into account. This work takes into account a numerical and mixed technique for modeling of FC sub-systems, based on moving least squares approach. In has been analyzed the opportunity of using an adjustable backpressure valve. The work proposes a numerical optimization of air management, computing the optimal speed of the compressor and the optimal throttle opening, in correlation with an imposed operating point of PEMFC system. A Constrained Optimization By Linear Approximation (COBYLA) algorithm has been implemented to solve the optimization problem. The results are useful to design the control of PEMFC system and to develop an optimal configuration of it.     

A new analytical approach to model and evaluate the performance of a class of irreversible fuel cells

An irreversible model of a class of hydrogen–oxygen fuel cells working at steady-state is established, in which the irreversibilities resulting from electrochemical reaction, electrical resistance, and heat transfer to the environment are taken into account. The entropy production analysis is introduced and applied to investigate the physical and chemical performances of the fuel cell by using the theory of electrochemistry and non-equilibrium thermodynamics. Expressions for the power output and efficiency of the fuel cell are derived by introducing the equivalent internal and leakage resistances. With the help of the model being applied to high temperature solid oxide fuel cells, the performance characteristic curves of the fuel cell are presented and the influence of some design and operating parameters on the performance of the fuel cell are discussed in detail. Moreover, the optimum criteria of some important parameters such as the power output, efficiency, and current density are given. The results obtained may provide a theoretical basis for both the optimal design and operation of real fuel cells. This new method can also be used in the investigation and optimization of similar energy conversion settings and electrochemistry systems.     

Performance improvement of centrifugal compressors for fuel cell vehicles using the aerodynamic optimization and data mining methods

Centrifugal compressors are one of the most important auxiliary components in polymer electrolyte membrane fuel cell vehicles, which tend to operate at a narrow area with low specific speed. Here, the optimal design goals of centrifugal compressors are investigated on the basis of a lumped model for fuel cell systems. A three-dimensional multi-objective and multi-point aerodynamic optimization and data mining method for centrifugal compressors named ODM is presented via integrating a multi-island genetic algorithm, Reynolds-Average Navier-Stokes solver technique and self-organization map based data mining technique. Data mining indicates that compressor geometry would move to a small inlet diameter ratio and a narrow region of the outlet width ratio. Based on the optimization results, a centrifugal compressor for 100 kW fuel cell stack is manufactured. The experimental results show that the improvement of isentropic efficiency near low mass flow has been achieved, which indicates that the proposed ODM is effective in the performance improvement of centrifugal compressors for fuel cell vehicles.     

Multi‐objective exergoeconomic optimization of an Integrated Solar Combined Cycle System using evolutionary algorithms

In this study, a multi‐objective optimization scheme is developed and applied for an Integrated Solar Combined Cycle System that produces 400 MW of electricity to find solutions that simultaneously satisfy exergetic as well as economic objectives. This corresponds to a search for the set of Pareto optimal solutions with respect to the two competing objectives. The optimization process is carried out by a particular class of search algorithms known as multi‐objective evolutionary algorithms. An example of decision‐making has been presented and a final optimal solution has been introduced. The analysis shows that optimization process leads to 3.2% increasing in the exergetic efficiency and 3.82% decreasing of the rate of product cost. Finally, sensitivity analysis is carried out to study the effect of changes in the Pareto optimal solutions to the system important parameters, such as interest rate, fuel cost, solar operation period, and system construction period. Copyright © 2010 John Wiley & Sons, Ltd.     

Power management and design optimization of fuel cell/battery hybrid vehicles

Power management strategy is as significant as component sizing in achieving optimal fuel economy of a fuel cell hybrid vehicle (FCHV). We have formulated a combined power management/design optimization problem for the performance optimization of FCHVs. This includes subsystem-scaling models to predict the characteristics of components of different sizes. In addition, we designed a parameterizable and near-optimal controller for power management optimization. This controller, which is inspired by our stochastic dynamic programming results, can be included as design variables in system optimization problems. Simulation results demonstrate that combined optimization can efficiently provide excellent fuel economy.     

Comparison among various energy management strategies for reducing hydrogen consumption in a hybrid fuel cell/supercapacitor/battery system

The aim of this study is to introduce a comprehensive comparison of various energy management strategies of fuel cell/supercapacitor/battery storage systems. These strategies are utilized to manage the energy demand response of hybrid systems, in an optimal way, under highly fluctuating load condition. Two novel strategies based on salp swarm algorithm (SSA) and mine-blast optimization are proposed. The outcomes of these strategies are compared with commonly used strategies like fuzzy logic control, classical proportional integral control, the state machine, equivalent fuel consumption minimization, maximization, external energy maximization, and equivalent consumption minimization. Hydrogen fuel economy and overall efficiency are used for the comparison of these different strategies. Results demonstrate that the proposed SSA management strategy performed best compared with all other used strategies in terms of hydrogen fuel economy and overall efficiency. The minimum consumed hydrogen and maximum efficiency are found 19.4 gm and 85.61%, respectively.     

开式回热燃气轮机热电冷联产装置性能优化

建立了考虑压降的开式回热燃气轮机热电冷联产装置的有限时间热力学模型,导出了各个部件的相对压降和各个热流率与压气机进口相对压降的关系式,以第一定律效率、[火用]输出率、[火用]效率和利润率为目标,在无燃料消耗和装置尺寸约束下,通过数值计算发现分别存在最佳的压气机进口相对压降使[火用]输出率和利润率取得最优值,进一步优化压比,得到了最大[火用]输出率和利润率,分别存在最佳的供热温度使最大[火用]输出率和利润率取得双重最大值,以利润率为设计目标能够减小装置的尺寸.在燃料消耗和装置尺寸约束下,优化了压气机进口相对压降,得到了最优效率,同时各部件流通面积分配也得到了优化.回热能够增大装置的利润率和效率.     

Design of an adaptive EMS for fuel cell vehicles

This paper addresses the energy management strategy (EMS) for a fuel cell hybrid electric vehicle (FC-HEV). In this work, model parameters are identified online by using the square root unscented Kalman filter (SR-UKF) method to seek a variation in the fuel cell performances. Then, an optimization algorithm is used on the updated model to find the best efficiency and power operating points. This process is used into two strategies: (i) A hysteresis energy management strategy (EMS) and (ii) an optimal EMS based on Pontryagin's minimum principle, for a FC-HEV. The effectiveness of the proposed EMSs is demonstrated by conducting studies on a FC-HEV model.     

The role of renewable fuel supply in the transport sector in a future decarbonized energy system

Battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) have been identified as two electromobility options which can help to achieve GHG emission reduction targets in the transport sector. However, both options will also impact the future energy system characterized by integration of various demand sectors and increasing intermittent power generation. The objective of this paper is to examine the optimal mix of both propulsion systems and to analyze the cost for renewable fuel supply. We propose a generic approach for dimensioning of fast charging and hydrogen refueling stations and optimization of the fuel supply system. The model is applied in a case study for passenger cars on German highways. The results indicate that a parallel build-up of stations for both technologies does not increase the overall costs. Moreover, the technology combination is also an optimal solution from the system perspective due to synergetic use of hydrogen but limited efficiency losses. Hence, BEVs and FCEVs should jointly contribute to the decarbonization of the future energy system.