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One of the bottlenecks hindering the usage of polymer electrolyte membrane fuel cell technology in automotive applications is the highly load-sensitive degradation of the cell components. The cell failure cases reported in the literature show localized cell component degradation, mainly caused by flow-field dependent non-uniform distribution of reactants. The existing methodologies for diagnostics of localized cell failure are either invasive or require sophisticated and expensive apparatus. In this study, with the help of a multiscale simulation framework, a single polymer electrolyte membrane fuel cell (PEMFC) model is exposed to a standardized drive cycle provided by a system model of a fuel cell car. A 2D multiphysics model of the PEMFC is used to investigate catalyst degradation due to spatio-temporal variations in the fuel cell state variables under the highly transient load cycles. A three-step (extraction, oxidation, and dissolution) model of platinum loss in the cathode catalyst layer is used to investigate the cell performance degradation due to the consequent reduction in the electro-chemical active surface area (ECSA). By using a time-upscaling methodology, we present a comparative prediction of cell end-of-life (EOL) under different driving behavior of New European Driving Cycle (NEDC) and Worldwide Harmonized Light Vehicles Test Cycle (WLTC).
The significant market growth of stationary electrical energy storage systems both for private and commercial applications has raised the question of battery lifetime under practical operation conditions. Here, we present a study of two 8 kWh lithium-ion battery (LIB) systems, each equipped with 14 lithium iron phosphate/graphite (LFP) single cells in different cell configurations. One system was based on a standard configuration with cells connected in series, including a cell-balancing system and a 48 V inverter. The other system featured a novel configuration of two stacks with a parallel connection of seven cells each, no cell-balancing system, and a 4 V inverter. The two systems were operated as part of a microgrid both in continuous cycling mode between 30% and 100% state of charge, and in solar-storage mode with day–night cycling. The aging characteristics in terms of capacity loss and internal resistance change in the cells were determined by disassembling the systems for regular checkups and characterizing the individual cells under well-defined laboratory conditions. As a main result, the two systems showed cell-averaged capacity losses of 18.6% and 21.4% for the serial and parallel configurations, respectively, after 2.5 years of operation with 810 (serial operation) and 881 (parallel operation) cumulated equivalent full cycles. This is significantly higher than the aging of a reference single cell cycled under laboratory conditions at 20 °C, which showed a capacity loss of only 10% after 1000 continuous full cycles.
Die Erfindung betrifft eine Photovoltaik-Stromversorgungsvorrichtung, insbesondere vom öffentlichen Stromnetz unabhängige Photovoltaik-Stromversorgungsvorrichtung, mit einem positiven (204) und einem negativen (206) Lastanschluss für den Anschluss einer elektrischen Last, mit einer Mehrzahl von photovoltaischen Zellen (104) und einer wiederaufladbaren Batterie (5), welche wenigstens zwei in Serie geschaltete Batteriezellen (112) umfasst. Nach der Erfindung sind die photovoltaischen Zellen (104) zu einer der Anzahl der Batteriezellen (112) entsprechenden Anzahl von seriell verbundenen Teilstrings (108) verschaltet und jeder Teilstring (108) ist mit einem positiven Teilstringanschluss mit einem Pluspol und mit einem negativen Teilstringanschluss mit einem Minuspol einer zugeordneten Batteriezelle (112) oder mehreren zugeordneten parallel geschalteten Batteriezellen (112) verbunden. Dabei kann jeder Teilstring (108) zwischen dem positiven und negativen Teilstringanschluss eine maximale Leerlaufspannung erzeugen, die kleiner oder gleich einer vorgegebenen Ladeschlussspannung der zugeordneten Batteriezelle (112) oder der zugeordneten parallel geschalteten Batteriezellen (112) ist. Weiterhin betrifft die Erfindung eine Schaltungsanordnung zum Laden einer wiederaufladbaren Batterie, die zur Realisierung einer derartigen Photovoltaik-Stromversorgungsvorrichtung geeignet ist.
Passive hybridization refers to a parallel connection of photovoltaic and battery cells on the direct current level without any active controllers or inverters. We present the first study of a lithium-ion battery cell connected in parallel to a string of four or five serially-connected photovoltaic cells. Experimental investigations were performed using a modified commercial photovoltaic module and a lithium titanate battery pouch cell, representing an overall 41.7 W-peak (photovoltaic)/36.8 W-hour (battery) passive hybrid system. Systematic and detailed monitoring of this system over periods of several days with different load scenarios was carried out. A scaled dynamic synthetic load representing a typical profile of a single-family house was successfully supplied with 100 % self-sufficiency over a period of two days. The system shows dynamic, fully passive self-regulation without maximum power point tracking and without battery management system. The feasibility of a photovoltaic/lithium-ion battery passive hybrid system could therefore be demonstrated.
Passive hybridization of battery cell and photovoltaic cell: modeling and experimental validation
(2017)
In this article the high-temperature behavior of a cylindrical lithium iron phosphate/graphite lithium-ion cell is investigated numerically and experimentally by means of differential scanning calorimetry (DSC), accelerating rate calorimetry (ARC), and external short circuit test (ESC). For the simulations a multi-physics multi-scale (1D+1D+1D) model is used. Assuming a two-step electro-/thermochemical SEI formation mechanism, the model is able to qualitatively reproduce experimental data at temperatures up to approx. 200 °C. Model assumptions and parameters could be evaluated via comparison to experimental results, where the three types of experiments (DSC, ARC, ESC) show complementary sensitivities towards model parameters. The results underline that elevated-temperature experiments can be used to identify parameters of the multi-physics model, which then can be used to understand and interpret high-temperature behavior. The resulting model is able to describe nominal charge/discharge operation behavior, long-term calendaric aging behavior, and short-term high-temperature behavior during extreme events, demonstrating the descriptive and predictive capabilities of physicochemical models.
Lithium-ion batteries exhibit a complex, nonlinear and dynamic voltage behaviour. Modelling their slow dynamics is a challenge due to the multiple potential causes involved. We present here a neural equivalent circuit model for lithium-ion batteries including slow voltage dynamics. The model uses an equivalent circuit with voltage source, series resistor, and diffusion element. The series resistance is parameterized using neural networks. The diffusion element is based on a discretized form of Fickian diffusion, parameterized using a neural network and learnable parameters. It is flexible to represent not only Warburg behaviour, but also resistor-capacitor-type dynamics. Mathematically, the resulting model is given by a differential–algebraic equation system combining ordinary and neural differential equations. Therefore, the model combines concepts of both physical theory (white-box model) and artificial intelligence (black-box model) to a combined framework (grey-box model). We apply this approach to a lithium iron phosphate based lithium-ion battery cell. The experimental voltage behaviour during constant-current cycles as well as the dynamics during pulse tests are well reproduced by the model. Only at very high and very low states of charge the simulation significantly deviates from experiments, which might result from insufficient training data in these regions.
The formation of secondary phases in the porous electrodes is a severe mechanism affecting the lifetime of solid oxide fuel cells (SOFC). It can occur via various chemical mechanisms and it has a significant influence on cell performance due to pore clogging and deactivation of active surfaces and triple-phase boundary (TPB). We present a modeling and simulation study of nickel oxide formation (reoxidation) and carbon formation (coking) within the SOFC anode. We use a 2D continuum model based on a multi-phase framework [Neidhardt et al., J. Electrochem. Soc., 159, 9 (2012)] that allows the introduction of arbitrary solid phases (here: Ni, YSZ, NiO, Carbon) plus gas phase. Reactions between the bulk phases are modeled via interface-adsorbed species and are described by an elementary kinetic approach. Published experimental data are used for parameterization and validation. Simulations allow the prediction of cell performance under critical operation conditions, like (i) a non-fuel operation test, where NiO formation is taking place (Figure 1a), or (ii) an open circuit voltage (OCV) stability test under hydrocarbon atmosphere, where solid carbon is formed (Figure 1b). Results are applied for enhanced interpretation of experimental data and for prediction of safe operation conditions.
The lifetime and performance of solid-oxide fuel cells (SOFC) and electrolyzer cells (SOEC) can be significantly degraded by oxidation of nickel within the electrode and support structures. This paper documents a detailed computational model describing nickel oxide (NiO) formation as a growing film layer on top of the nickel phase in Ni/YSZ composite electrodes. The model assumes that the oxidation rate is controlled by transport of ions across the film (Wagner's theory). The computational model, which is implemented in a two-dimensional continuum framework, facilitates the investigation of alternative chemical reaction and transport mechanisms. Model predictions agree well with a literature experimental measurement of oxidation-layer growth. In addition to providing insight in interpreting experimental observations, the model provides a quantitative predictive capability for improving electrode design and controlling operating conditions.