Modeling transport properties and electrochemical performance of hierarchically structured lithium-ion battery cathodes using resistor networks and mathematical half-cell models PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Modeling transport properties and electrochemical performance of hierarchically structured lithium-ion battery cathodes using resistor networks and mathematical half-cell models PDF full book. Access full book title Modeling transport properties and electrochemical performance of hierarchically structured lithium-ion battery cathodes using resistor networks and mathematical half-cell models by Birkholz, Oleg. Download full books in PDF and EPUB format.
Author: Birkholz, Oleg
Publisher: KIT Scientific Publishing
ISBN: 373151172X
Category : Science
Languages : en
Pages : 246
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
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
Get Book Here
Book Description
Author: Krishnan S. Hariharan
Publisher: Springer
ISBN: 3319035274
Category : Technology & Engineering
Languages : en
Pages : 213
Get Book Here
Book Description
This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals—often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. The authors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier. Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across—from detailed electrochemical models to algorithms used for real time estimation on a microchip—is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework—often invoking basic principles of thermodynamics or transport phenomena—and ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and health estimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well. The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models.
Author: Illig, Joerg
Publisher: KIT Scientific Publishing
ISBN: 3731502461
Category : Technology & Engineering
Languages : en
Pages : 231
Get Book Here
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.
