One dimensional transient numerical study of the mass heat and charge transfer in a proton exchange membrane for PEMFC

The objective of our study is to quantify the mass water transferred by various modes: diffusion, convection and migration. For the water transfer, the principal forces considered in the model are, the convection force, the osmotic force (i.e. diffusion) and the electric force (migration). The first of these forces results from a pressure gradient, the second of a concentration gradient and the third of a protons' migration from the anode to the cathode, which has an effect on the dipole of the water molecules (resistance force to the advancement). The numerical tool used to solve the equations' system is the finite element method. The results obtained numerically considering this method are concentration profiles and concentration variation with time and membrane thickness. These results illustrate the contribution of each mass transfer mode.     

Influence of the porous transport layer properties on the mass and charge transfer in a segmented PEM electrolyzer

A titanium Porous Transport Layer (PTL) is usually used at the anode side of PEM water electrolyzers to ensure both the gas/water transport and the electric charges transfer. In this paper, four different sintered Ti powder PTLs were characterized to determine some properties, such as the pore size distribution, the porosity, and the permeability. Their influence on the electrolysis performance was investigated by using a 30 cm² segmented cell which allowed measuring the current density distribution, while controlling temperature and pressure conditions. For a better understanding, in-situ techniques such as the Polarization Curves and the Electrochemical Impedance Spectroscopy (EIS) were used. A local characterization of mass transport limitations caused by oxygen saturation was carried out, paying special attention to the pressure influence when using a PTL with very small pores. The results showed that current density heterogeneities can be explained by microstructure changes along the PTL. The optimal geometric characteristics of the PTL depend not only on the operating conditions such as current density, pressure, and temperature but also on the catalyst layer properties. A new model for the constriction resistance between the catalyst layer and the PTL was proposed.     

An optimal model identification for solid oxide fuel cell based on extreme learning machines optimized by improved Red Fox Optimization algorithm

The present study proposes an efficient method for optimal model parameters estimation of the Solid Oxide Fuel Cell by considering its nonlinear dynamic behavior. The approach is relied on using a novel optimal model of Extreme Learning Machines (ELM) network based on metaheuristics. The main purpose is to minimize the Mean Squared Error (MSE) between the empirical output voltage data and the output voltage of the model by the suggested optimized ELM network. The proposed ELM network is optimized by an enhanced design of the Red Fox Optimizer (IRFO) Algorithm to provide optimal results. The suggested ELM-IRFO method is then testified on a Solid Oxide Fuel Cell case study and its results are compared with the GWO-RHNN method from the literature and ELM-RFO method to show its effectiveness. The final results showed that the proposed ELM-IRFO has the minimum value of the Mean Squared Error (MSE) against the other comparative methods.     

Research on parameter identification and state of charge estimation of improved equivalent circuit model of Li-ion battery based on temperature effects for battery thermal management

The performance and parameters of Li-ion battery are greatly affected by temperature. As a significant battery parameter, state of charge (SOC) is affected by temperature during the estimation process. In this paper, an improved equivalent circuit model (IECM) considering the influence of ambient temperatures and battery surface temperature (BST) on battery parameters based on second-order RC model have been proposed. The exponential function fitting (EFF) method was used to identify battery model parameters at 5 ambient temperatures including −10°C, 0°C, 10°C, 25°C and 40°C, fitting the relationship between internal resistance and BST. Then, the SOC of the IECM was estimated based on the extended Kalman filter (EKF) algorithm. Using the result calculated by the Ampere-hour integration method as the standard, the data of battery under open circuit voltage (OCV) test profile and dynamic stress test (DST) profile at different ambient temperatures has been compared with the ordinary second-order RC model, and the advantages of the SOC estimation accuracy with IECM was verified. The numerical results showed that the IECM can improve the estimation accuracy of battery SOC under different operating conditions.     

Development of three-dimensional model for the analysis of the mass transport in vanadium redox flow batteries

It is practical to equip the renewable energy system with the vanadium redox flow battery (VRFB) to improve energy utilization efficiency. A steady-stated, three-dimensional model is developed to study the flow and mass transfer in VRFB with serpentine flow field (SFF), and the corresponding experiments are also executed. The effect of the inlet flow rate on VRFB is analyzed by simulating the charge-discharge process, in which the uniformity factors, pressure drop, overpotential, protons concentration, and the battery efficiency are compared as indicators. Two split-SFFs are proposed to improve the pressure drop in the conventional SFF. The results show the efficiency of VRFB increase with the increase of the flow rate, but when the flow rate is higher than a critical flow rate, the performance on the VRFB is no longer sensitive to the flow rate. Compared to SFF, SFF(SY) performs well on pressure drop but poorly on discharge.     

A mathematical model for interfacial charge transfer at the semiconductor–dye–electrolyte interface of a dye-sensitised solar cell

A mathematical model for the interfacial charge transfer within dye-sensitised solar cells (DSC) is presented for the semiconductor–dye–electrolyte interface. The model explicitly accounts for each reaction at the interface involving dye molecules, electrolyte species and adsorbed electrons associated with the conduction band surface states of the semiconductor. Additionally, the model accounts for photoelectron injection via singlet and triplet excited dye states. The governing equations can be used to describe the total current produced by the DSC under illuminated and non-illuminated conditions, at steady state. Regular perturbation methods are applied to the model equations to obtain closed form analytic approximations, resulting in approximate solutions that negate the need for numerical solution of the model system. All parameter values associated with the model are obtained from the literature and from experimental data. The presented numerical results and analytic approximations compare favourably to experimental data, capturing the interfacial characteristics of current versus voltage curves of the DSC.     

A new state‐of‐charge estimation method for electric vehicle lithium‐ion batteries based on multiple input parameter fitting model

The estimation of state‐of‐charge (SOC) is crucial to determine the remaining capacity of the Lithium‐Ion battery, and thus plays an important role in many electric vehicle control and energy storage management problems. The accuracy of the estimated SOC depends mostly on the accuracy of the battery model, which is mainly affected by factors like temperature, State of Health (SOH), and chemical reactions. Also many characteristic parameters of the battery cell, such as the output voltage, the internal resistance and so on, have close relations with SOC. Battery models are often identified by a large amount of experiments under different SOCs and temperatures. To resolve this difficulty and also improve modeling accuracy, a multiple input parameter fitting model of the Lithium‐Ion battery and the factors that would affect the accuracy of the battery model are derived from the Nernst equation in this paper. Statistics theory is applied to obtain a more accurate battery model while using less measurement data. The relevant parameters can be calculated by data fitting through measurement on factors like continuously changing temperatures. From the obtained battery model, Extended Kalman Filter algorithm is applied to estimate the SOC. Finally, simulation and experimental results are given to illustrate the advantage of the proposed SOC estimation method. It is found that the proposed SOC estimation method always satisfies the precision requirement in the relevant Standards under different environmental temperatures. Particularly, the SOC estimation accuracy can be improved by 14% under low temperatures below 0 °C compared with existing methods. Copyright © 2017 John Wiley & Sons, Ltd.     

A numerical model for optimal receiver array and mass flow rate in residential solar water heating systems

In this paper, the performance of a pressurised evacuated tube solar collector system using internal heat pipes is presented. The system was optimised for the seasonal supply of hot service water for residential use in Pretoria, South Africa. The prediction of seasonal hourly performance trends along with the maximum thermal performance at the optimal receiver array and manifold mass flow rate was of major concern in this investigation. A mathematical model representing the thermal performance of the system was developed and numerically implemented in Engineering Equation Solver. The dynamic performance of collectors with 15, 20 and 25 tubes was determined throughout all the seasons. Moreover, the performance of the residential solar water heating system with a 20-tube collector was investigated in detail for mass flow rates of 0.03, 0.05 and 0.07?kg/s.     

Least‐squares based coulomb counting method and its application for state‐of‐charge (SOC) estimation in electric vehicles

Coulomb counting method is a convenient and straightforward approach for estimating the state‐of‐charge (SOC) of lithium‐ion batteries. Without interrupting the power supply, the remaining capacities of them in an electric vehicle (EV) can be calculated by integrating the current leaving and entering the batteries. The main drawbacks of this method are the cumulative errors and the time‐varying coulombic efficiency, which always lead to inaccurate estimations. To deal with this problem, a least‐squares based coulomb counting method is proposed. With the proposed method, the coulombic losses can be compensated by charging/discharging coulombic efficiency η and the measurement drift can be amended with a morbid efficiency matrix. The experimental results demonstrated that the proposed method is effective and convenient. Copyright © 2016 John Wiley & Sons, Ltd.     

The optimal performance estimation for an unknown PEMFC based on the Taguchi method and a generic numerical PEMFC model

In this paper, a new approach to estimate the optimal performance of an unknown proton exchange membrane fuel cell (PEMFC) has been proposed. This proposed approach combines the Taguchi method and the numerical PEMFC model. Simulation results obtained using the Taguchi method help to determine the value of control factors that represent the tested unknown PEMFC. The objective of reducing both fuel consumption and operation cost can be achieved by determining the parameters for the unknown PEMFC. In addition, the optimal operation power for the tested unknown PEMFC can also be predicted. Experimental results on the test equipment show that the proposed approach is effective in optimal performance estimation for the tested unknown PEMFC, thus demonstrating the success achieved by combining the Taguchi method and the numerical PEMFC model.     

A flexible model integration approach for evaluating tradeoffs between CO2 emissions and cost in solid oxide fuel cell‐based building energy systems

A simulation framework for flexible evaluation of various distributed building energy systems based on the integration of component device simulation models is presented. Device technology models were constructed for a solid oxide fuel cell (SOFC), a gas turbine, a double pipe heat exchanger, and a compressor. A scheme is proposed for defining model interfaces in order to improve the flexibility and accessibility of the models. Based on that scheme, interfaces are defined for each device model. The component device models are integrated to construct system models of (1) a hybrid system combining an SOFC and a gas turbine (SOFC/GT system) and (2) a stand‐alone SOFC system. The integrated model of the SOFC/GT system is then used to carry out a multi‐objective optimization in order to study the tradeoffs between cost and CO₂ emissions of the SOFC system operation for a given electricity demand. Through these analyses, the optimal configuration of the SOFC/GT system and the optimal operation conditions of the SOFC system for the given electricity demand were explored. Copyright © 2005 John Wiley & Sons, Ltd.     

The simulation based on CHEMKIN for homogeneous charge compression ignition combustion with on-board fuel reformation in the chamber

In order to control the combustion phase precisely and remarkably extend the operation range of Homogeneous Charge Compression Ignition (HCCI) engine, a method of on-board controllable phase fuel reformation in the reforming chamber is proposed in this paper. HCCI combustion is dominated by chemical kinetics, and H₂, OH, H and O are the key radicals and play an important role in controlling HCCI combustion. The attempt of the proposed method is to try to change the control of chemical kinetics into a manipulation of fuel reforming system. The system includes an independent reformation chamber with an injector and a controllable valve that connects reformation chamber and the main chamber. The reforming fuel is reformed into H₂-rich gas. The reformed gas enters the cylinder to change the combustion phasing at compression stroke. The model of HCCI with reforming process is built with CHEMKIN 4.1 software, and HCCI process with on-board reformation is simulated. The results show that the components of the reformed gas are influenced by initial temperature and reforming mixture concentration. The maximum fraction of H₂ may be obtained by optimizing the trap timing and reforming mixture concentration (optimal value: Φ_T = 31 °CA, λ₃ = 0.4). The optimized reformed gas does have the ability to change the combustion phasing of HCCI engine. With the help of the on-board controllable phase fuel reformation system, HCCI combustion process can be precisely controlled, and the HCCI engine is allowed to operate under lower intake temperature and higher speed condition, and to keep high IMEP and indicated thermal efficiency.     

CSA-LSSVM model for the estimation of solubility of n-alkane in supercritical CO2

Poor solubility of substantial hydrocarbons in CO₂ has constrained the use of CO₂-EOR (enhanced oil recovery) in the modern oil recovery industry to some extent. Subsequently, it is significant to research the solubility regularity of various hydrocarbons in supercritical carbon dioxide (scCO₂) in the first place. CO₂ injection as one of the popular methodologies in light of financially and environmentally friendly has wide applications in EOR. In this paper, our objective is to estimate the solubility of n-alkanes in scCO₂. This study highlights the application of a model based on least square support vector machine for estimation of solubility of n-alkanes in scCO₂. The tuning parameters of the developed model were determined by an optimization algorithm, namely coupled simulated annealing. A set of 184 data points of solubility was used to execute the new model. To assess the accuracy and effectiveness of the developed model for prediction of experimental data, statistical and graphical techniques were used. Moreover, the outcomes were compared with the results of literature correlations to predict the solubility of alkanes. Results demonstrate that the model is precise and viable for prediction of solubility data. The resulted values of R², root-mean-square error, SD, and % average absolute relative deviation for total data points are 0.99204, 0.12862, 0.6437, and 0.7753 for overall data, respectively.     

The optimal parameters estimation for rectangular cylinders installed transversely in the flow channel of PEMFC from a three-dimensional PEMFC model and the Taguchi method

The study first applies a three-dimensional model to analyze the cell performance of PEMFCs using rectangular cylinders with various numbers transversely inserted at the axis in the channel, and finds the higher performance with reasonable pressure drop. The Taguchi optimization methodology is then combined with the three-dimensional PEMFC model to determine the optimal combination of five primary operating parameters for the best arrangement of the rectangular cylinders in the channel. The results indicate that the optimal combination factor is a cell temperature of 313 K, an anode humidification temperature of 333 K, a cathode humidification temperature of 333 K, a hydrogen stoichiometric flow ratio of 1.9, and an oxygen stoichiometric flow ratio of 2.7. This study also examines the pressure drop for the channels with rectangular cylinders transversely inserted. Using experimental data verifies the numerical results of the flow field design with rectangular cylinders.     

Carbon stock estimates for forests in the Castilla y León region, Spain. A GIS based method for evaluating spatial distribution of residual biomass for bio-energy

Analysis of aboveground biomass and carbon stocks (as equivalent CO₂) was performed in the Castilla y León region, Spain. Data from the second and third Spanish Forest Inventories (1996 and 2006) were used. Total aboveground biomass was calculated using allometric biomass equations and biomass expansion factors (BEF), the first method giving higher values. Forests of Castilla y León stored 77,051,308 Mg of biomass, with a mean of 8.18 Mg ha⁻¹, in 1996 and 135,531,737 Mg of biomass, with a mean of 14.4 Mg ha⁻¹, in 2006. The total equivalent CO₂ in this region’s forests increased 9,608,824 Mg year⁻¹ between 1996 and 2006. In relation to the Kyoto Protocol, the Castilla y León forests have sequestered 3 million tons of CO₂ per year, which represents 6.4% of the total regional emission of CO₂. A Geographic Information System (GIS) based method was also used to assess the geographic distribution of residual forest biomass for bio-energy in the region. The forest statistics data on area of each species were used. The fraction of vegetation cover, land slope and protected areas were also considered. The residual forest biomass in Castilla y León was 1,464,991 Mg year⁻¹, or 1.90% of the total aboveground biomass in 1996. The residual forest biomass was concentrated in specific zones of the Castilla y León region, suitable for the location of industries that utilize biomass as energy source. The energy potential of the residual forest biomass in the Castilla y León region is 7350 million MJ per year.     

A model for the effects of temperature and structural parameters on the performance of a molten sodium hydroxide direct carbon fuel cell (MHDCFC) based on hydroxide ion mass transfer

To understand the parametric effects on the performance of a molten sodium hydroxide direct carbon fuel cell, an experimentally validated mathematical model is established to investigate the influences of temperature, temperature distribution, anode rod radius, electrode spacing, and inner cell diameter on the cell behaviour. Mass transfer, heat transfer, and secondary current distribution theories are considered in the model cell. A high temperature, small anode rod radius, small electrode spacing, and small inner diameter of the cell are recommended to enhance the cell behaviour, which are conducive to the transmission of hydroxide ions (OH⁻) based on mass and heat transfer. The small temperature difference distribution in the cell has a weak effect on the cell performance, and the three-phase boundary is the key factor influencing the cell behaviour in all cases. An orthogonal test was conducted to determine the best parameter combination for the maximum cell performance, and the Pearson correlation coefficient was used to evaluate the relevance of the investigated parameters to the cell performance. The order of the influence of each factor on the maximum power density of the cell is as follows: temperature > anode rod radius > electrode spacing > cell diameter. When the temperature is 973 K, the anode rod radius is 0.55 cm, the electrode spacing is 2.2 cm, and the inner diameter of the cell is 5 cm, and the optimized power density is 25.40 mW cm⁻².     

Analytical model for predicting the performance of photovoltaic array coupled with a wind turbine in a stand-alone renewable energy system based on hydrogen

We present the results of an analysis of the performance of a photovoltaic array that complement the power output of a wind turbine generator in a stand-alone renewable energy system based on hydrogen production for long-term energy storage. The procedure for estimating hourly solar radiation, for a clear sunny day, from the daily average solar insolation is also given. The photovoltaic array power output and its effective contribution to the load as well as to the energy storage have been determined by using the solar radiation usability concept. The excess and deficit of electrical energy produced from the renewable energy sources, with respect to the load, govern the effective energy management of the system and dictate the operation of an electrolyser and a fuel cell generator. This performance analysis is necessary to determine the effective contribution from the photovoltaic array and the wind turbine generator and their contribution to the load as well as for energy storage.     

Progress in the production and application of n-butanol as a biofuel

Butanol is a very competitive renewable biofuel for use in internal combustion engines given its many advantages. In this review, the properties of butanol are compared with the conventional gasoline, diesel fuel, and some widely used biofuels, i.e. methanol, ethanol, biodiesel. The comparison of fuel properties indicates that n-butanol has the potential to overcome the drawbacks brought by low-carbon alcohols or biodiesel. Then, the development of butanol production is reviewed and various methods for increasing fermentative butanol production are introduced in detailed, i.e. metabolic engineering of the Clostridia, advanced fermentation technique. The most costive part of the fermentation is the substrate, so methods involved in renewed substrates are also mentioned. Next, the applications of butanol as a biofuel are summarized from three aspects: (1) fundamental combustion experiments in some well-defined burning reactors; (2) a substitute for gasoline in spark ignition engine; (3) a substitute for diesel fuel in compression ignition engine. These studies demonstrate that butanol, as a potential second generation biofuel, is a better alternative for the gasoline or diesel fuel, from the viewpoints of combustion characteristics, engine performance, and exhaust emissions. However, butanol has not been intensively studied when compared to ethanol or biodiesel, for which considerable numbers of reports are available. Finally, some challenges and future research directions are outlined in the last section of this review.