Download or read book Multiscale Modeling of Degradation in Lithium ion Batteries written by Fridolin Röder and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive methodology for multiscale simulation of degradation in lithium-ion batteries. The work helps to understand battery degradation processes by revealing complex multiscale effects, which cannot be taken into account by single-scale models. A novel numerical method is presented, which dynamically couples molecular models based on kinetic Monte Carlo method with macroscopic models. Moreover, the work provides mathematical models of degradation on various length scales, e.g. heterogeneous side reactions on molecular scale and the restructuring of particle size distributions on electrode scale. Instead of describing processes separately, the multiscale methodology systematically analyzes interaction of degradation processes and cell operation. The presented methodology is certainly applicable to other electrochemical systems with considerable multi-scale nature.

Download or read book Physical Multiscale Modeling and Numerical Simulation of Electrochemical Devices for Energy Conversion and Storage written by Alejandro A. Franco and published by Springer. This book was released on 2015-11-12 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to review innovative physical multiscale modeling methods which numerically simulate the structure and properties of electrochemical devices for energy storage and conversion. Written by world-class experts in the field, it revisits concepts, methodologies and approaches connecting ab initio with micro-, meso- and macro-scale modeling of components and cells. It also discusses the major scientific challenges of this field, such as that of lithium-ion batteries. This book demonstrates how fuel cells and batteries can be brought together to take advantage of well-established multi-scale physical modeling methodologies to advance research in this area. This book also highlights promising capabilities of such approaches for inexpensive virtual experimentation. In recent years, electrochemical systems such as polymer electrolyte membrane fuel cells, solid oxide fuel cells, water electrolyzers, lithium-ion batteries and supercapacitors have attracted much attention due to their potential for clean energy conversion and as storage devices. This has resulted in tremendous technological progress, such as the development of new electrolytes and new engineering designs of electrode structures. However, these technologies do not yet possess all the necessary characteristics, especially in terms of cost and durability, to compete within the most attractive markets. Physical multiscale modeling approaches bridge the gap between materials’ atomistic and structural properties and the macroscopic behavior of a device. They play a crucial role in optimizing the materials and operation in real-life conditions, thereby enabling enhanced cell performance and durability at a reduced cost. This book provides a valuable resource for researchers, engineers and students interested in physical modelling, numerical simulation, electrochemistry and theoretical chemistry.

Download or read book Multiscale Modeling and Characterization for Performance and Safety of Lithium ion Batteries written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion batteries are highly complex electrochemical systems whose performance and safety are governed by coupled nonlinear electrochemical-electrical-thermal-mechanical processes over a range of spatiotemporal scales. In this paper we describe a new, open source computational framework for Lithium-ion battery simulations that is designed to support a variety of model types and formulations. This framework has been used to create three-dimensional cell and battery pack models that explicitly simulate all the battery components (current collectors, electrodes, and separator). The models are used to predict battery performance under normal operations and to study thermal and mechanical safety aspects under adverse conditions. The model development and validation are supported by experimental methods such as IR-imaging, X-ray tomography and micro-Raman mapping.

Download or read book Multiscale Modelling and Simulation written by Sabine Attinger and published by Springer Science & Business Media. This book was released on 2004-07-12 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: In August 2003, ETHZ Computational Laboratory (CoLab), together with the Swiss Center for Scientific Computing in Manno and the Università della Svizzera Italiana (USI), organized the Summer School in "Multiscale Modelling and Simulation" in Lugano, Switzerland. This summer school brought together experts in different disciplines to exchange ideas on how to link methodologies on different scales. Relevant examples of practical interest include: structural analysis of materials, flow through porous media, turbulent transport in high Reynolds number flows, large-scale molecular dynamic simulations, ab-initio physics and chemistry, and a multitude of others. Though multiple scale models are not new, the topic has recently taken on a new sense of urgency. A number of hybrid approaches are now created in which ideas coming from distinct disciplines or modelling approaches are unified to produce new and computationally efficient techniques.

Download or read book Multiscale Modeling Reformulation and Efficient Simulation of Lithium ion Batteries written by Paul Wesley Clairday Northrop and published by . This book was released on 2014 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion batteries are ubiquitous in modern society, ranging from relatively low-power applications, such as cell phones, to very high demand applications such as electric vehicles and grid storage. The higher power and energy density of lithium-ion batteries compared to other forms of electrochemical energy storage makes them very popular in such a wide range of applications. In order to engineer improved battery design and develop better control schemes, it is important to understand internal and external battery behavior under a variety of possible operating conditions. This can be achieved using physical experiments, but those can be costly and time consuming, especially for life-studies which can take years to perform. Here using mathematical models based on porous electrode theory to study the internal behavior of lithium-ion batteries is examined. As the physical phenomena which govern battery performance are described using several nonlinear partial differential equations, simulating battery models can quickly become computationally expensive. Thus, much of this work focuses on reformulating the battery model to improve simulation efficiency, allowing for use to solve problems which require many iterations to converge (e.g. optimization), or in applications which have limited computational resources (e.g. control). Computational time is improved while maintaining accuracy by using a coordinate transformation and orthogonal collocation to reduce the number of equations which must be solved using the method of lines. Orthogonal collocation is a spectral method which approximates all dependent variables as a series solution of trial functions. This approach discretizes the spatial derivatives with higher order accuracy than standard finite difference approach. The coefficients are determined by requiring the governing equation be satisfied at specified collocation points, resulting in a system of differential algebraic equations (DAEs) which must be solved with time as the only differential variable. The system of DAEs can be solved using standard time-adaptive integrating solvers. The error and simulation time of the battery model of orthogonal collocation is analyzed. The improved computational efficiency allows for more physical phenomena to be considered in the reformulated model. Lithium-ion batteries exposed to high temperatures can lead to internal damage and capacity fade. In extreme cases this can lead to thermal runaway, a dangerous scenario in which energy is rapidly released. In the other end of the temperature spectrum, low temperatures can significantly impede performance by increasing diffusion resistance. Although accounting for thermal effects increases the computational cost, the model reformulation allows for these important phenomena to be considered in single cell as well as 2D and multicell stack battery models. The growth of the solid electrolyte interface (SEI) layer contributes to capacity fade by means of a side reaction which removes lithium from the system irreversibly as well as increasing the resistance of the transfer lithium-ion from the electrolyte to the active material. As the reaction kinetics are not well understood, several proposed mechanisms are considered and implemented into the continuum reformulated model. The effects of SEI layer growth on a lithium-ion cell over 10,000 cycles is simulated and analyzed. Furthermore, a kinetic Monte Carlo model is developed and implemented to study the heterogeneous growth of the solid electrolyte layer. This is a stochastic approach which considers lithium-ion diffusion, intercalation, and side reactions. As millions of individual time steps may be performed for a single cycle, it is very computationally expensive, but allows for simulation of surface phenomena which are ignored in continuum models.

Download or read book Advances in Lithium Ion Batteries for Electric Vehicles written by Haifeng Dai and published by Elsevier. This book was released on 2024-02-15 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Lithium-Ion Batteries for Electric Vehicles: Degradation Mechanism, Health Estimation, and Lifetime Prediction examines the electrochemical nature of lithium-ion batteries, including battery degradation mechanisms and how to manage the battery state of health (SOH) to meet the demand for sustainable development of electric vehicles. With extensive case studies, methods and applications, the book provides practical, step-by-step guidance on battery tests, degradation mechanisms, and modeling and management strategies. The book begins with an overview of Li-ion battery aging and battery aging tests before discussing battery degradation mechanisms and methods for analysis. Further methods are then presented for battery state of health estimation and battery lifetime prediction, providing a range of case studies and techniques. The book concludes with a thorough examination of lifetime management strategies for electric vehicles, making it an essential resource for students, researchers, and engineers needing a range of approaches to tackle battery degradation in electric vehicles. - Evaluates the cause of battery degradation from the material level to the cell level - Explains key battery basic lifetime test methods and strategies - Presents advanced technologies of battery state of health estimation

Download or read book Polymer Electrolyte Fuel Cells written by Alejandro A. Franco and published by CRC Press. This book was released on 2013-07-09 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the recent research progress on the fundamental understanding of the materials degradation phenomena in PEFC, for automotive applications. On a multidisciplinary basis, through contributions of internationally recognized researchers in the field, this book provides a complete critical review on crucial scientific topics related to PEFC materials degradation, and ensures a strong balance between experimental and theoretical analysis and preparation techniques with several practical applications for both the research and the industrial communities.

Download or read book Nanoscale X ray Computed Tomography Based Modeling of Lithium ion Battery Electrodes written by Ali Ghorbani Kashkooli and published by . This book was released on 2018 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of their high energy/power density, long cycle life, and extremely low rate of self-discharge, lithium-ion batteries (LIBs) have dominated portable electronics, smart grid, and electric vehicles (EVs). Although they are the most developed and widely applied energy storage technology, there is still a strong desire to further enhance their energy/power density, cycle life, and safety. While all of these battery requirements are macroscopic and stated at cell/pack scale, they have to be addressed at particle or network of particles scale (mesoscale). At mesoscale, active material particles having different shape and morphologies are bound together with a carbon-doped polymer binder layer. This percolated network of particles serves as the electron conductive path from the reaction sites to the current collector. Even though significant research has been conducted to understand the physical and electrochemical behavior of material at the nanoscale, there have not been comprehensive studies to understand what is happening at the mesoscale. Mathematical models have emerged as a promising way to shed light on complex physical and electrochemical phenomena happening at this scale. The idea of using mathematical model to study multiphysics behavior of LIBs is not new. Traditional models involved homogeneous spherical particles or computer generated electrode structures as the model geometry to simulate electrode/cell performance. While these models are successful to predict the cell performance, heterogeneous electrode's structure at mesoscale questions the accuracy of their findings related to battery internal behavior and property distribution. The new advances in the field of 3D imaging including X-ray computed tomography (XCT) and Focused-ion beam/Scanning electron microscopy (FIB-SEM), have enabled the 3D visualization of the electrode's active particles and structures. In particular, XCT has offered nondestructive imaging and matter penetration capability in short period of time. Although it was commercialized in 70's, with the recent development of high resolution (down to 20 nm) laboratory and synchrotron radiation tomography has been revolutionized. 3D reconstructed electrodes based on XCT data can provide quantitative structural information such as particle and pore size distribution, porosity, solid/electrolyte interfacial surface area, and transport properties. In addition, XCT reconstructed geometry can be easily adopted as the model geometry for simulation purposes. For this, similar to traditional models, a modeling framework based on conservation of mass/charge and electrochemistry needs to be developed. The model links the electrode performance to the real electrode's structure geometry and allows for the detailed investigation of multiphysics phenomena. When combined with mechanical stress, such models can also be used for electrode's failure and degradation studies. The work presented in this dissertation aims to adopt 3D reconstructed structures from nano-XCT as the geometry to study multiphysics behaviour of the LIBs electrodes. In addition, 3D reconstructed structure provides more realistic electrode's morphological and transport properties. Such properties can benefit the homogeneous models by providing highly accurate input parameters. In the first study, a multiscale platform has been developed to model LIB electrodes based on the reconstructed morphology. This multiscale framework consists of a microscale level where the electrode microstructure architecture is modeled and a macroscale level where discharge/charge is simulated. The coupling between two scales is performed in real time unlike using common surrogate based models for microscale. For microscale geometry 3D microstructure is reconstructed based on the nano-XCT data replacing typical computer generated microstructure. It is shown that this model can predict the experimental performance of LiFePO4 (LFP) cathodes at different discharge rates more accurately than the traditional/homogenous models. The approach employed in this study provides valuable insight into the spatial distribution of lithium within the microstructure of LIB electrodes. In the second study, a new model that keeps all major advantages of the single-particle model of LIB and includes three-dimensional structure of the electrode was developed. Unlike the single spherical particle, this model considers a small volume element of an electrode, called the Representative Volume Element (RVE), which represent the real electrode structure. The advantages of using RVE as the model geometry was demonstrated for a typical LIB electrode consisting of nano-particle LFP active material. The model was employed to predict the voltage curve in a half-cell during galvanostatic operations and validated against experimental data. The simulation results showed that the distribution of lithium inside the electrode microstructure is very different from the results obtained based on the single-particle model. In the third study, synchrotron X-ray computed tomography has been utilized using two different imaging modes, absorption and Zernike phase contrast, to reconstruct the real 3D morphology of nanostructured Li4Ti5O12 (LTO) electrodes. The morphology of the high atomic number active material has been obtained using the absorption contrast mode, whereas the percolated solid network composed of active material and carbon-doped polymer binder domain (CBD) has been obtained using the Zernike phase contrast mode. The 3D absorption contrast image revealed that some LTO nano-particles tend to agglomerate and form secondary micro-sized particles with varying degrees of sphericity. The tortuosity of the pore and solid phases were found to have directional dependence, different from Bruggeman's tortuosity commonly used in homogeneous models. The electrode's heterogeneous structure behaviour was also investigated by developing a numerical model to simulate a galvanostatic discharge process using the Zernike phase contrast mode. In the last study, synchrotron X-ray nano-computed tomography has been employed to reconstruct real 3D active particle morphology of a LiMn2O4 (LMO) electrode. For the first time, CBD has been included in the electrode structure as a 108 nm thick uniform layer using image processing technique. With this unique model, stress generated inside four LMO particles with a uniform layer of CBD has been simulated, demonstrating its strong dependence on local morphology (surface concavity and convexity), and the mechanical properties of CBD such as Young's modulus. Specifically, high levels of stress have been found in vicinity of particle's center or near surface concave regions, however much lower than the material failure limits even after discharging rate as high as 5C. On the other hand, the stress inside CBD has reached its mechanical limits when discharged at 5C, suggesting that it can potentially lead to failure by plastic deformation. The findings in this study highlight the importance of modeling LIB active particles with CBD and its appropriate compositional design and development to prevent the loss of electrical connectivity of the active particles from the percolated solid network and power losses due to CBD failure. There are still plenty of opportunities to further develop the methods and models applied in this thesis work to better understand the multiscale multiphysics phenomena happening in the electrode of LIBs. For example, in the multiscale model, microscale solid phase charge transfer and electrolyte mass/charge transfer can be included. In this way, heterogeneous distribution of current density in microscale would be achieved. Also, in both multiscale and RVE models, the exact location of CBD can be incorporated in the electrode structure to specify lithium diffusional path inside the group of particles in the solid matrix. Finally, in the fourth study, the vehicle battery driving cycle can be applied instead of galvanostatic operating condition, to mimic the stress generated inside the electrodes in real practical condition. .

Download or read book Computational Electrochemistry written by S. Paddison and published by The Electrochemical Society. This book was released on 2015-12-28 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Techniques for Complex Transport Phenomena written by Wei Shyy and published by Cambridge University Press. This book was released on 2005-11-24 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes some newly developed computational techniques and modeling strategies for analyzing and predicting complex transport phenomena. It summarizes advances in the context of a pressure-based algorithm and discusses methods such as discretization schemes for treating convection and pressure, parallel computing, multigrid methods, and composite, multiblock techniques. The final chapter is devoted to practical applications that illustrate the advantages of various numerical and physical tools. The authors provide numerous examples throughout the text.

Download or read book Three dimensional Lithium ion Battery Model written by Gi-Heon Kim and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mathematical Modeling of Lithium Batteries written by Krishnan S. Hariharan and published by Springer. This book was released on 2017-12-28 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Numerical Mathematics and Advanced Applications ENUMATH 2015 written by Bülent Karasözen and published by Springer. This book was released on 2016-11-09 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: The European Conference on Numerical Mathematics and Advanced Applications (ENUMATH), held every 2 years, provides a forum for discussing recent advances in and aspects of numerical mathematics and scientific and industrial applications. The previous ENUMATH meetings took place in Paris (1995), Heidelberg (1997), Jyvaskyla (1999), Ischia (2001), Prague (2003), Santiago de Compostela (2005), Graz (2007), Uppsala (2009), Leicester (2011) and Lausanne (2013). This book presents a selection of invited and contributed lectures from the ENUMATH 2015 conference, which was organised by the Institute of Applied Mathematics (IAM), Middle East Technical University, Ankara, Turkey, from September 14 to 18, 2015. It offers an overview of central recent developments in numerical analysis, computational mathematics, and applications in the form of contributions by leading experts in the field.

Download or read book Mechanical Behavior of Materials written by William F. Hosford and published by Cambridge University Press. This book was released on 2010 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook on the mechanical behavior of materials for mechanical and materials engineering. It emphasizes quantitative problem solving. This new edition includes treatment of the effects of texture on properties and microstructure in Chapter 7, a new chapter (12) on discontinuous and inhomogeneous deformation, and treatment of foams in Chapter 21.

Download or read book Learning the Electrochemistry of Degradation and Safety in Graphite Porous Electrodes for Lithium ion Batteries written by Supratim Das and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lithium-ion batteries have become the centerpiece of portable technology and electric transportation, as well as for grid stabilization for intermittent renewable sources. The varied applications involve varying requirements for safety, lifetime, and energy/power density. To optimally design these systems for each application, researchers have a very large design space. This requires extensive and costly experimentation or computationally heavy modeling. Specifically for designing batteries with better lifetime and long-term capacity retention, relying on just experiments can take between weeks to months and thousands of cells to get any robust insights for process improvement. Data-driven and physics based modeling, when done rigorously, can help inform experimentation, reducing time and cost requirements. However, modeling battery degradation is challenging as it not only is hard to visualize in-operando, but also affects cell performance at multiple scales - from single particle to porous electrode to the battery pack. Insights obtained from experimentation on a given scale to inform modeling, often performs poorly when it comes to prediction at other scales, limiting applicability. This thesis is a small part of a collaboration between MIT, Stanford, Purdue and Toyota Research Institute to develop data-driven models for predicting battery performance and degradation, called the D3BATT: Data-Driven Design of Lithium-ion Batteries. We adopt a simultaneous 'bottom-up' (first principles) and 'top-down' (statistical analyses of experiments) approach to inform theory formulation at multiple scales. This thesis addresses the idea behind a multiscale 'bottom-up' approach to understanding battery degradation: First, we use experiments designed on simple systems to study the electrochemistry of key graphite degradation mechanisms such as solid-electrolyte interphase (SEI) growth and lithium plating at the single particle scale. This gives us robust kinetic and thermodynamic parameters that are invariant with scale. Second, we extend the single particle theory to the porous electrode scale to capture the effect of multi-particle interactions and macroscopic electrode and electrolyte properties. This is done using the Multiphase Porous Electrode Theory (MPET) software, developed in the Bazant Group at MIT. Third, by simulating various cycling protocols (such as slow and fast charging, full depth-of-discharge vs. shallow formation cycling and open-circuit storage), we can compare the predictions with that of data-driven models obtained from statistical analyses of cell data. This informs the porous electrode model of the key mechanisms relevant at the cell scale, and gives a reliable estimate of electrode-scale parameters that could not have been informed from single-particle models. As an example, we apply the informed porous electrode degradation model to battery formation cycling, and explain what makes a 'good' formation cycling protocol. Model improvement is an ongoing effort in the research group, as new experimental data come to light. This work can be applied to a multitude of cycling scenarios and battery chemistries to assist experimental design.

Download or read book Mathematical Modeling of Lithium Ion Batteries and Cells written by V. Subramanian and published by The Electrochemical Society. This book was released on 2012 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Experimental Characterization of Electrodes and Multi Scale Modeling of Swelling Induced Stresses in Lithium ion Batteries written by Priyank Gupta and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: