Modeling transport properties and electrochemical performance of hierarchically structured lithium-ion battery cathodes using resistor networks and mathematical half-cell models PDF Download
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Author: Birkholz, Oleg
Publisher: KIT Scientific Publishing
ISBN: 373151172X
Category : Science
Languages : en
Pages : 246
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Book Description
Hierarchically structured active materials in electrodes of lithium-ion cells are promising candidates for increasing gravimetric energy density and improving rate capability of the system. To investigate the influence of cathode structures on the performance of the whole cell, efficient tools for calculating effective transport properties of granular systems are developed and their influence on the electrochemical performance is investigated in specially adapted cell models.
Author: Birkholz, Oleg
Publisher: KIT Scientific Publishing
ISBN: 373151172X
Category : Science
Languages : en
Pages : 246
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Book Description
Hierarchically structured active materials in electrodes of lithium-ion cells are promising candidates for increasing gravimetric energy density and improving rate capability of the system. To investigate the influence of cathode structures on the performance of the whole cell, efficient tools for calculating effective transport properties of granular systems are developed and their influence on the electrochemical performance is investigated in specially adapted cell models.
Author: Röhe, Maximilian
Publisher: KIT Scientific Publishing
ISBN: 3731512343
Category :
Languages : en
Pages : 178
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Book Description
In this work, the first simulation model of oxygen depolarized cathodes (ODC), which are silver catalyst-based gas diffusion electrodes, is presented that considers the phase equilibrium of the gas-liquid interface and structure-related inhomogeneities in electrolyte distribution. By means of the model it has been identified that mass transport of water and ions in the liquid phase is a crucial factor for electrode performance and how it is influenced by the electrode structure.
Author: Schöller, Lukas
Publisher: KIT Scientific Publishing
ISBN: 3731513404
Category :
Languages : en
Pages : 230
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Book Description
During the production of fiber-reinforced thermosets, the resin material undergoes a reaction that can lead to damage. A two-stage polymerization reaction is modeled using molecular dynamics and evaluations of the system including a fiber surface are performed. In addition, a phase-field model for crack propagation in heterogeneous systems is derived. This model is able to predict crack growth where established models fail. Finally, the model is used to predict crack formation during curing.
Author: Lingelbach, Yannick
Publisher: KIT Scientific Publishing
ISBN: 3731513528
Category :
Languages : en
Pages : 278
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Book Description
This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework. - This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework.
Author: Mazzocchi, Francesco
Publisher: KIT Scientific Publishing
ISBN: 3731511819
Category : Technology & Engineering
Languages : en
Pages : 212
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Book Description
This work aimed at designing, studying and producing the first prototypes of KIDs tailored for fusion plasma polarimetric diagnostics. Diamond was considered for the first time as substrate material for low-temperature superconducting detectors given its unmatched optical, radiation hardness and thermal qualities, properties necessary for working environments potentially saturated with radiation. This work represents a first step toward the optimization and final application of this technology.
Author: David Eugene Stephenson
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 29131
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Book Description
In this work, a mathematical model is reported and validated, which describes the performance of porous electrodes under low and high rates of discharge. This porous battery model can be used to provide researchers a better physical understanding relative to prior models of how cell morphology and materials affect performance due to improved accounting of how effective resistance change with morphology and materials. The increased understanding of cell resistances will enable improved design of cells for high-power applications, such as hybrid and plug-in-hybrid electric vehicles. It was found electronic and liquid-phase ionic transport resistances are strongly coupled to particle conductivity, size, and distribution of particle sizes. The accuracy of determining effective resistances was increased by accounting for how particle's size, volume fraction, and electronic conductivity affect electronic resistances and by more accurately determining how cell morphology influences effective liquid-phase transport resistances. These model additions are used to better understand the cause for decreased utilization of active materials for relatively highly loaded lithium-ion cathodes at high discharge rates. Lithium cobalt and ruthenium oxides were tested and modeled individually and together in mixed-oxide cathodes to understand how the superior material properties relative to each other can work together to reduce cell resistances while maximizing energy storage. It was found for lithium cobalt oxide, a material with low electronic conductivity, its low rate (1C) performance is dominated by local electronic resistances between particles. At high rates (5C or higher) diffusional resistance in the liquid electrolyte had the greatest influence on cell performance. It was found in the mixed-oxide system that the performance of lithium cobalt oxide was improved by decreasing its local electronic losses due to the addition of lithium ruthenium oxide, a highly conductive active material, which improved the number of electron pathways to lithium cobalt oxide thereby decreasing local electronic losses.
Author: Mehrdad Mastali Majdabadi Kohneh
Publisher:
ISBN:
Category : Electric automobiles
Languages : en
Pages : 202
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Book Description
Incorporating lithium-ion (Li-ion) batteries as an energy storage system in electric devices including electric vehicles brings about new challenges. In fact, the design of Li-ion batteries has to be optimized depending on each application specifications to improve the performance and safety of battery operation under each application and at the same time prevent the batteries from quick degradation. As a result, accurate models capable of predicting the behavior of Li-ion batteries under various operating conditions are necessary. Therefore, the main objective of this research is to develop a battery model that includes thermal heating and is suitable for large-sized prismatic cells used in electric vehicles. This works starts with developing a dual-extended Kalman filter based on an equivalent circuit model for the battery. The dual-extended Kalman filter simultaneously estimates the dynamic internal resistance and state of the charge of the battery. However, the estimated parameters are only the fitted values to the experimental data and may be non-physical. In addition, this filter is only valid for the operating conditions that it is validated against via experimental data. To overcome these issues, physics-based electrochemical models for Li-ion batteries are subsequently considered. One drawback of physics-based models is their high computational cost. In this work, two simplified one-dimensional physics-based models capable of predicting the output voltage of coin cells with less than 2.5% maximum error compared to the full-order model are developed. These models reduce the simulation computational time more than one order of magnitude. In addition to computational time, the accuracy of the physico-chemical model parameter estimates is a concern for physics-based models. Therefore, commercial LiFePO4 (LFP) and graphite electrodes are precisely modelled and characterized by fitting experimental data at different charge/discharge rates (C/5 to 5C). The temperature dependency of the kinetic and transport properties of LFP and graphite electrodes is also estimated by fitting experimental data at various temperatures (10 °C, 23 °C, 35 °C, and 45 °C). Since the spatial current and temperature variations in the large-sized prismatic cells are significant, one-dimensional models cannot be used for the modeling of these prismatic cells. In this work, a resistor network methodology is utilized to combine the one-dimensional models into a three-dimensional multi-layer model. The developed model is verified by comparing the simulated temperatures at the surface of the prismatic cell (consist of LFP as the positive and graphite as the negative electrode) to experimental data at different charge/discharge rates (1C, 2C, 3C, and 5C). Using the developed model the effect of tab size and location, and the current collector thickness, on the electrochemical characteristics of large-sized batteries is evaluated. It is shown that transferring tabs from the edges and the same side (common commercial design) to the center and opposite sides of the cell, and extending them as much as possible in width, lowers the non-uniformity variation in electrochemical current generation.
Author: V. Subramanian
Publisher: The Electrochemical Society
ISBN: 1566779464
Category : Fuel cells
Languages : en
Pages : 37
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Book Description
Author: Illig, Joerg
Publisher: KIT Scientific Publishing
ISBN: 3731502461
Category : Technology & Engineering
Languages : en
Pages : 231
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Book Description
In this book, a new procedure to analyze lithium-ion cells is introduced. The cells are disassembled to analyze their components in experimental cell housings. Then, Electrochemical Impedance Spectroscopy, time domain measurements and the Distribution function of Relaxation Times are applied to obtain a deep understanding of the relevant loss processes. This procedure yields a notable surplus of information about the electrode contributions to the overall internal resistance of the cell.
Author: Bradley Louis Trembacki
Publisher:
ISBN:
Category :
Languages : en
Pages : 278
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Book Description
Lithium-ion batteries are commonly modeled using a volume-averaged formulation (porous electrode theory) in order to simulate battery behavior on a large scale. These methods utilize effective material properties and assume a simplified spherical geometry of the electrode particles. In contrast, a particle-scale (non-porous electrode) simulation applied to resolved electrode geometries predicts localized phenomena. Complete simulations of batteries require a coupling of the two scales to resolve the relevant physics. A central focus of this thesis is to develop a fully-coupled finite volume methodology for the simulation of the electrochemical equations in a lithium-ion battery cell at both the particle scale and using volume-averaged formulations. Due to highly complex electrode geometries at the particle scale, the formulation employs an unstructured computational mesh and is implemented within the MEMOSA software framework of Purdue’s PRISM (Prediction of Reliability, Integrity and Survivability of Microsystems) center. Stable and efficient algorithms are developed for full coupling of the nonlinear species transport equations, electrostatics, and Butler-Volmer kinetics. The model is applied to synthetic electrode particle beds for comparison with porous electrode theory simulations and to evaluate numerical performance capabilities. The model is also applied to a half-cell mesh created from a real cathode particle bed reconstruction to demonstrate the feasibility of such simulations. The second focus of the thesis is to investigate 3D battery electrode architectures that offer potential energy density and power density improvements over traditional particle bed battery geometries. A singular feature of these geometries is their interpenetrating nature, which significantly reduces diffusion distance. Advancement of micro-scale additive manufacturing techniques has made it possible to fabricate these electrode microarchitectures. A fully-coupled finite volume methodology for the transport equations coupled to the relevant electrochemistry is implemented in the PETSc (Portable, Extensible Toolkit for Scientific Computation) software framework which allows for a straightforward scalable simulation on orthogonal hexahedral meshes. Such scalability becomes important when performing simulations on fully resolved microstructures with many parameter sweeps across multiple variables. Using the computational model, a variety of 3D battery electrode geometries are simulated and compared across various battery discharge rates and length scales in order to quantify performance trends and investigate geometrical factors that improve battery performance. The energy density and power density of the 3D battery microstructures are compared in several ways, including a uniform surface area to volume ratio comparison as well as a comparison requiring a minimum manufacturable feature size. Significant performance improvements over traditional particle bed electrode designs are observed, and electrode microarchitectures derived from minimal surfaces are shown to be superior under a minimum feature size constraint. An average Thiele modulus formulation is presented to predict the performance trends of 3D microbattery electrode geometries. As a natural extension of the 3D battery particle-scale modeling, the third and final focus of the thesis is the development and evaluation of a volume-averaged porous electrode theory formulation for these unique 3D interpenetrating geometries. It is necessary to average all three material domains (anode, cathode, and electrolyte) together, in contrast to traditional two material volume-averaging formulations for particle bed geometries. This model is discretized and implemented in the PETSc software framework in a manner similar to the particle-scale implementation and enables battery-level simulations of interpenetrating 3D battery electrode architectures. Electrode concentration gradients are modeled using a characteristic diffusion length, and results for plate and cylinder electrode geometries are compared to particle-scale simulation results. Additionally, effective diffusion lengths that minimize error with respect to particle-scale results for gyroid and Schwarz P electrode microstructures are determined, since a theoretical single diffusion length is not easily calculated. Using these models, the porous electrode formulation for these 3D interpenetrating geometries is shown to match the results of particle-scale models very well.
