Lifetime prediction on lithium-ion battery cell and system level (Band 8)

Lifetime prediction on lithium-ion battery cell and system level (Band 8)
Author: Severin Lukas Hahn
Publisher: Cuvillier Verlag
Total Pages: 231
Release: 2022-08-23
Genre: Technology & Engineering
ISBN: 3736966296

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Lithium-Ionen Batteriesysteme leiden unter elektrochemischen Degradations- und Ausfallmechanismen, die nur mit hohem Testaufwand abzusichern sind. Daher verfolgt diese Arbeit das Ziel, Prädiktionen des kalendarischen Kapazitätsverlustes und der Druckentwicklung auf Zell- und Systemebene zu verbessern. Eine fundamentale Inkonsistenz semi-empirischer kalendarischer Alterungsmodelle konnte aufgrund theoretischer Überlegungen aufgelöst werden, indem der Einfluss der initialen Anodendeckschicht berücksichtigt wird. Ein neuartiges Validierungskonzept, welches durch maschinelles Lernen inspiriert wurde, konnte die dadurch verbessere Prognosefähigkeit gegenüber der Literatur aufzeigen. Das Verhalten von Einzelzellen in repräsentativer Modulverspannung konnte auf einer neuen aktiv geregelte Zellpresse untersucht werden und schuf grundlegendes Verständnis. Die Presse ermöglichte damit die Systemmodellierung der Druckentwicklung, deren detaillierte Parametrisierung und die Messung des Gasverdrängungsdruckes von laminierten Zellen. Durch die Messung der Druckentwicklung in Alterungsversuchen von Modulen konnte die Modellprädiktion auf Systemebene erfolgreich für Moduldesigns validiert werden.

Degradation Mechanisms and Lifetime Prediction for Lithium-Ion Batteries -- A Control Perspective: Preprint

Degradation Mechanisms and Lifetime Prediction for Lithium-Ion Batteries -- A Control Perspective: Preprint
Author:
Publisher:
Total Pages: 0
Release: 2015
Genre:
ISBN:

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Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under different levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries
Author:
Publisher:
Total Pages: 0
Release: 2023
Genre:
ISBN:

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Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

Applied Technologies

Applied Technologies
Author: Miguel Botto-Tobar
Publisher: Springer Nature
Total Pages: 496
Release: 2020-03-02
Genre: Computers
ISBN: 3030425312

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This thirs volume of the three-volume set (CCIS 1193, 1194, 1195) constitutes the refereed proceedings of the First International Conference on Applied Technologies, ICAT 2019, held in Quito, Ecuador, in December 2019. The 124 full papers were carefully reviewed and selected from 328 submissions. The papers are organized according to the following topics: technology trends; computing; intelligent systems; machine vision; security; communication; electronics; e-learning; e-government; e-participation.

Advances in Lithium-Ion Batteries for Electric Vehicles

Advances in Lithium-Ion Batteries for Electric Vehicles
Author: Haifeng Dai
Publisher: Elsevier
Total Pages: 326
Release: 2024-02-26
Genre: Technology & Engineering
ISBN: 0443155445

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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

Safety and Reliability: Methodology and Applications

Safety and Reliability: Methodology and Applications
Author: Tomasz Nowakowski
Publisher: CRC Press
Total Pages: 408
Release: 2014-09-01
Genre: Technology & Engineering
ISBN: 1315736977

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Within the last fifty years the performance requirements for technical objects and systems were supplemented with: customer expectations (quality), abilities to prevent the loss of the object properties in operation time (reliability and maintainability), protection against the effects of undesirable events (safety and security) and the ability to

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint

Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint
Author:
Publisher:
Total Pages: 0
Release: 2017
Genre:
ISBN:

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Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint Lithium-ion (Li-ion) batteries are being deployed on the electrical grid for a variety of purposes, such as to smooth fluctuations in solar renewable power generation. The lifetime of these batteries will vary depending on their thermal environment and how they are charged and discharged. To optimal utilization of a battery over its lifetime requires characterization of its performance degradation under different storage and cycling conditions. Aging tests were conducted on commercial graphite/nickel-manganese-cobalt (NMC) Li-ion cells. A general lifetime prognostic model framework is applied to model changes in capacity and resistance as the battery degrades. Across 9 aging test conditions from 0oC to 55oC, the model predicts capacity fade with 1.4 percent RMS error and resistance growth with 15 percent RMS error. The model, recast in state variable form with 8 states representing separate fade mechanisms, is used to extrapolate lifetime for example applications of the energy storage system integrated with renewable photovoltaic (PV) power generation.

Lifetime Prediction for Lithium-ion Batteries Undergoing Fast Charging Protocols

Lifetime Prediction for Lithium-ion Batteries Undergoing Fast Charging Protocols
Author: Michael Forsuelo
Publisher:
Total Pages: 115
Release: 2019
Genre:
ISBN:

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This thesis describes the application of Porous Electrode Theory and supervised machine learning to lifetime prediction for 18650 lithium iron phosphate (LiFePO4 LFP)/graphite cells subject to mixed galvanostatic and potentiostatic fast charging policies. Porous Electrode Theory is used to predict battery lifetime by parameteric reductions of effective solid-phase Fickian diffusivities, electrolytic Stefan-Maxwell diffusivity, and Butler-Volmer exchange currents. Parameter estimation and uncertainty quantification are formulated as least squares optimization over galvanostatic discharge curves with Bayesian estimation of uncertainties. A battery lifetime approach from the literature is extended with identifiability analysis to enhance fidelity of the inverse problem, the attribution of degradation modes, and the accuracy of parametric power-law lifetime predictions. Multiphase Porous Electrode Theory (MPET) is also explored in this thesis. In MPET, each particle of the porous electrode ensemble is described by generalized Allen-Cahn-Hilliard dynamics. Single-particle dynamics are governed by firstprinciples free energy landscapes as opposed to inductive fits to open-circuit battery voltages. Multiscale parameter estimation and central limit theorem analysis are implemented, enhancing the suitability of MPET for capacity fade predictions. Supervised machine learning algorithms utilizing feature-based correlations for battery lifetime are described. Electrochemical features that go beyond the discharge-only model provide improved lifetime predictions, generalized voltage analysis indiscrimant of (dis)charge protocol or data, and a clear connection between battery physics and machine learning, and suggest an optimal charging protocol.

Handbook on Battery Energy Storage System

Handbook on Battery Energy Storage System
Author: Asian Development Bank
Publisher: Asian Development Bank
Total Pages: 123
Release: 2018-12-01
Genre: Technology & Engineering
ISBN: 9292614711

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This handbook serves as a guide to deploying battery energy storage technologies, specifically for distributed energy resources and flexibility resources. Battery energy storage technology is the most promising, rapidly developed technology as it provides higher efficiency and ease of control. With energy transition through decarbonization and decentralization, energy storage plays a significant role to enhance grid efficiency by alleviating volatility from demand and supply. Energy storage also contributes to the grid integration of renewable energy and promotion of microgrid.

Battery Management Systems

Battery Management Systems
Author: Gregory L. Plett
Publisher: Artech House Publishers
Total Pages: 0
Release: 2015
Genre: Technology & Engineering
ISBN: 9781630810276

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State-Of-The-Art applications of equivalent-circuit methods as they pertain to solving problems in battery management and control.