Guest Editorial

J. Electrochem. En. Conv. Stor.. 2017;14(1):010301-010301-2. doi:10.1115/1.4037096.

In the 1980s and 1990s, progress in fuel cell and battery research evolved mainly around materials development, empirical approaches, and efforts focusing mostly separately on either the microscale (electrodes and electrolytes) or the macroscale (systems, thermodynamics, and balance-of-plant). Since the 2000s, with the advent of more powerful computing and modeling resources, and the general progress in the field, it has seen a shift to the merging of scales, the possibility of 3D probing and quantification with fuel cell stacks and battery packs becoming the focal point. In parallel, disciplines have merged, too: a holistic and a detailed understanding in the range of underlying phenomena of chemistry, physics, materials science, and mechanical engineering has been combined with the addition of the influence of an electrical field or current. This union is essential to achieve the progress needed for the commercial breakthrough expected from the technologies. It became established that both experimental and modeling aspects deserve simultaneous and an equally weighted consideration, and it is recognized that the correspondences between models and experiments deliver among the most valuable advances to the field, due to the level of confidence and insight they provide.

Topics: Fuel cells , Modeling
Commentary by Dr. Valentin Fuster

Research Papers

J. Electrochem. En. Conv. Stor.. 2017;14(1):011001-011001-8. doi:10.1115/1.4035526.

Research into reduced-order models (ROM) for Lithium-ion batteries is motivated by the need for a real-time embedded model possessing the accuracy of physics-based models, while retaining computational simplicity comparable to equivalent-circuit models. The discrete-time realization algorithm (DRA) proposed by Lee et al. (2012, “One-Dimensional Physics-Based Reduced-Order Model of Lithium-Ion Dynamics,” J. Power Sources, 220, pp. 430–448) can be used to obtain a physics-based ROM in standard state-space form, the time-domain simulation of which yields the evolution of all the electrochemical variables of the standard pseudo-2D porous-electrode battery model. An unresolved issue with this approach is the high computation requirement associated with the DRA, which needs to be repeated across multiple SoC and temperatures. In this paper, we analyze the computational bottleneck in the existing DRA and propose an improved scheme. Our analysis of the existing DRA reveals that singular value decomposition (SVD) of the large Block–Hankel matrix formed by the system's Markov parameters is a key inefficient step. A streamlined DRA approach that bypasses the redundant Block–Hankel matrix formation is presented as a drop-in replacement. Comparisons with existing DRA scheme highlight the significant reduction in computation time and memory usage brought about by the new method. Improved modeling accuracy afforded by our proposed scheme when deployed in a resource-constrained computing environment is also demonstrated.

Commentary by Dr. Valentin Fuster
J. Electrochem. En. Conv. Stor.. 2017;14(1):011002-011002-7. doi:10.1115/1.4035891.

In this work, the use of fuel cells for valorizing agricultural-derived biogas in Switzerland is studied. The Swiss agricultural case is characterized by farms with small numbers of animals (20 cows) and high feed-in tariffs (FIT) for biogas-derived electricity (0.49 CHF/kWhel). Thus, small-scale biogas installations are reviewed and the possibility to couple them with solid oxide fuel cells (SOFCs) and photovoltaic (PV) panels is analyzed. To date, less than 5% of the Swiss agricultural biogas potential is used. It is possible to increase this value significantly up to 86% through the deployment of 2 kWel engines. The small size of the Swiss farm requires biogas installations in the kW-range. Small-scale biogas facilities are not profitable yet: the main challenge is to bring down the lifetime cost of the fuel cells to 11,000 CHF/kWel (considering a lifetime of ten years) and to reduce the investment cost (IC) of small-scale biogas facilities to around 9500 CHF/kWch. In the kW-range, solid oxide fuel cells (SOFCs) have higher electrical conversion efficiencies than internal combustion engines (ICEs). It is shown that SOFCs become competitive over combustion engines if the investment cost of the former decreases below 13,000 CHF/kWel for a lifetime of 11 years. Combining the biogas facility with a PV-battery system, which covers the digester's electricity needs, is found to be beneficial. A considerable reduction in the feed-in tariffs would make small- to medium-scale biogas installations unprofitable, at current cost. In order to reach a break-even under these conditions, the investment cost of the biogas plant needs to drop below 4000 CHF/kWch, whereas the investment cost of the SOFC needs to drop below 3400 CHF/kWel.

Commentary by Dr. Valentin Fuster
J. Electrochem. En. Conv. Stor.. 2017;14(1):011003-011003-8. doi:10.1115/1.4035902.

A three-dimensional, full-scale, single-phase finite element model has been developed for a liquid-fed direct methanol fuel cell (DMFC) with serpentine flow patterns. Equations for conservation of mass, momentum, and species are coupled with electrochemical kinetics in anode and cathode catalyst layers (CCLs). At the anode and cathode sides, only the liquid and the gas phases are considered, respectively. The significant benefit of a full-scale model is that the effect of physical parameters and distribution of the concentration of species can be realized in different channels for a desired section within the flow patterns. The model is used to study the effects of different operating parameters on fuel cell performance. Comparing numerical and experimental results demonstrate that the single-phase model slightly over-predicts the results for polarization plot. The modeling results also show that the porosity, temperature, and methanol concentration play a key role in affecting the DMFC polarization curve.

Commentary by Dr. Valentin Fuster
J. Electrochem. En. Conv. Stor.. 2017;14(1):011004-011004-19. doi:10.1115/1.4036038.

Attempts have been made to simulate numerically the conductivity degradation of solid oxide fuel cell (SOFC) YSZ electrolyte; physicochemical model has been constructed on the basis of experimental conductivities of Pt/1%NiO-doped YSZ/Pt cells under OCV condition. The temperature effect was extracted from the time constant for degradation caused by one thermal activation process (namely Y-diffusion), whereas the oxygen potential effect was determined by those Raman peak ratios between the tetragonal and the cubic phases which linearly change in relation to the conductivity. The electrical properties of the YSZ electrolyte before and after the transformation are taken into account. The time constant is directly correlated with Y-diffusion with proper critical diffusion length (∼10 nm), while the Y-diffusion can be enhanced on the reduction of NiO; this gives rise to the oxygen potential dependence. The most important objective of simulating the conductivity degradation is to reproduce the oxygen potential profile shift on transformation. Detailed comparison between experimental and simulation results reveal that the shift of oxygen potential profile, therefore, the conductivity profile change inside the YSZ electrolyte can well account for the Raman spectra profile. This also reveals that with decreasing temperature, there appear other kinetic factors of weakening or diminishing enhancing effects by NiO reduction. This may be important in interpreting the ohmic losses in real stacks, because there are differences in time constant or in magnitude of degradation between the pellets and those industrial stacks in which transformation was confirmed by Raman spectroscopy.

Commentary by Dr. Valentin Fuster
J. Electrochem. En. Conv. Stor.. 2017;14(1):011005-011005-12. doi:10.1115/1.4036401.

To improve the industry benchmark of solid oxide fuel cell (SOFC) systems, we consider anode off-gas recirculation (AOR) using a small-scale fan. Evolutionary algorithms compare different system design alternatives with hot or cold recirculation. The system performance is evaluated through multi-objective optimization (MOO) criteria, i.e., maximization of electrical efficiency and cogeneration efficiency. The aerodynamic efficiency and rotordynamic stability of the high-speed recirculation fan is investigated in detail. The results obtained suggest that improvements to the best SOFC systems, in terms of net electrical efficiency, are achievable, including for small power scale (10 kWe).

Commentary by Dr. Valentin Fuster
J. Electrochem. En. Conv. Stor.. 2017;14(1):011006-011006-15. doi:10.1115/1.4036491.

Detailed physics-based computer models of fuel cells can be computationally prohibitive for applications such as optimization and uncertainty quantification. Such applications can require a very high number of runs in order to extract reliable results. Approximate models based on spatial homogeneity or data-driven techniques can serve as surrogates when scalar quantities such as the cell voltage are of interest. When more detailed information is required, e.g., the potential or temperature field, computationally inexpensive surrogate models are difficult to construct. In this paper, we use dimensionality reduction to develop a surrogate model approach for high-fidelity fuel cell codes in cases where the target is a field. A detailed 3D model of a high-temperature polymer electrolyte membrane (PEM) fuel cell is used to test the approach. We develop a framework for using such surrogate models to quantify the uncertainty in a scalar/functional output, using the field output results. We propose a number of alternative methods including a semi-analytical approach requiring only limited computational resources.

Commentary by Dr. Valentin Fuster

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